From 045d8338ca1f5009c4d3716e6c0a73fa67898492 Mon Sep 17 00:00:00 2001 From: MRDep Date: Thu, 17 Sep 2015 17:29:33 +0100 Subject: [PATCH] first commit --- Joint Fitting/Dynamics/dyn_0.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_0.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_1.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_1.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_10.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_10.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_11.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_11.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_12.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_12.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_13.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_13.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_14.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_14.img | Bin 0 -> 224400 bytes Joint Fitting/Dynamics/dyn_15.hdr | Bin 0 -> 348 bytes 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Fitting/Dynamics/dyn_95.hdr | Bin 0 -> 348 bytes Joint Fitting/Dynamics/dyn_95.img | Bin 0 -> 224400 bytes Joint Fitting/ROImask.hdr | Bin 0 -> 348 bytes Joint Fitting/ROImask.img | Bin 0 -> 56100 bytes Joint Fitting/VFA/fa_10.hdr | Bin 0 -> 348 bytes Joint Fitting/VFA/fa_10.img | Bin 0 -> 224400 bytes Joint Fitting/VFA/fa_35.hdr | Bin 0 -> 348 bytes Joint Fitting/VFA/fa_35.img | Bin 0 -> 224400 bytes Joint Fitting/VFA/fa_5.hdr | Bin 0 -> 348 bytes Joint Fitting/VFA/fa_5.img | Bin 0 -> 224400 bytes Joint Fitting/batch_run.pro | 32 + .../dcemriprocessor_frees0_define.pro | 1390 ++++++ Joint Fitting/expconvolution.pro | 27 + Joint Fitting/flash_func.pro | 12 + Joint Fitting/idlffanalyze__define.pro | 2458 +++++++++++ Joint Fitting/linecolors.pro | 326 ++ Joint Fitting/log.log | 63 + Joint Fitting/log1.log | 64 + Joint Fitting/log2.log | 63 + Joint Fitting/log3.log | 63 + Joint Fitting/log4.log | 63 + Joint Fitting/log5.log | 5 + Joint Fitting/mpcurvefit.pro | 616 +++ Joint Fitting/mpfit.pro | 3737 +++++++++++++++++ Joint Fitting/p0x123123batch.pro | 4 + Joint Fitting/p1x123123batch.pro | 4 + Joint Fitting/p2x123123batch.pro | 4 + Joint Fitting/p3x123123batch.pro | 4 + Joint Fitting/p4x123123batch.pro | 4 + Joint Fitting/p5x123123batch.pro | 4 + Joint Fitting/phantomAIF.dat | Bin 0 -> 1664 bytes Joint Fitting/randomgauss.pro | 14 + Joint Fitting/read_analyze.pro | 25 + Joint Fitting/run_2cxm_phantom.pro | 243 ++ Joint Fitting/sample_from_array.pro | 49 + Joint Fitting/split_for.pro | 283 ++ Joint Fitting/tofts_ost_expc.pro | 38 + Joint Fitting/twocxm_ifit_dc.pro | 111 + Joint Fitting/twocxm_vfa_jfit_dc.pro | 120 + 229 files changed, 9826 insertions(+) create mode 100644 Joint Fitting/Dynamics/dyn_0.hdr create mode 100644 Joint Fitting/Dynamics/dyn_0.img create mode 100644 Joint Fitting/Dynamics/dyn_1.hdr create mode 100644 Joint Fitting/Dynamics/dyn_1.img create mode 100644 Joint Fitting/Dynamics/dyn_10.hdr create mode 100644 Joint 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index 0000000..886679f --- /dev/null +++ b/Joint Fitting/batch_run.pro @@ -0,0 +1,32 @@ +pro batch_run + +;This file runs the script 'run_2cxm_phantom' in batch mode. It uses multithreading to access multiple cores to increase speed. + +!EXCEPT=0 + + mean_baseline = 163.0 + + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + COMMON sigma_info, fixed_sigma, equal_sigma, known_sigma + + ;parameters relating to how M0v and M0d are varied during fitting + equal_and_free = 1 + unequal_and_free = 0 + equal_by_baseline = 0 + + ;multithread indices. 6 jobs, sequential and joint estimation for 3 AIF conditions + index = [1,2,3,4,5,6] + + T1_dataType = 'vfa'; could adapt to fit to IR or SR T1 mapping data + model = 'XM'; could change to Tofts or E.Tofts + n_repeats = 100; number of Monte Carlo repeats + n_vox_fit = 504; number of voxels to sample + snr_dyn = 5.0; required SNR of dynamic images + snr_vfa = 11.2; required SNR of VFA images -> snr_dyn*sqrt(5) to account for 5 signal averages + +split_for,0,n_elements(index)-1,nsplit = 8,command = [$ +'tag = ""',$ +'a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit)'],$ +varnames=['snr_dyn','snr_vfa','T1_datatype','model','index','n_repeats','n_vox_fit'] + +end \ No newline at end of file diff --git a/Joint Fitting/dcemriprocessor_frees0_define.pro b/Joint Fitting/dcemriprocessor_frees0_define.pro new file mode 100644 index 0000000..fce897b --- /dev/null +++ b/Joint Fitting/dcemriprocessor_frees0_define.pro @@ -0,0 +1,1390 @@ +;DCEMRIprocessor is a tool to fit tracer kinetic models to dynamic contrast enhanced MRI data. + +function DCEMRIprocessor_freeS0::Generate_maps, $ + fit_type,$ ; string. sequential:'ifit', joint:'jfit' + data_type,$; string. 'phantom' or 'real' + sa = sa,$; 1D array. arterial signal + ca = ca,$; ID array. arterial contrast agent concentration + update = update,$; logical. update reference dynamics and ref vfa (used for registration) after each Monte Carlo iteration. + n_vox_fit = n_vox_fit,$; integer. Number of voxels to sample during Monte Carlo experiements + ostfORf = ostfORf,$; string. 'Free' or 'Fixed'. Should the ost be free or fixed during fitting. If free it is bound by +-5 seconds of the Tofts model estimate. + FAfORf = FAfORf,$; string. 'Free' or 'Fixed'. Should the flip angle error be estimated. Recommend to set as fixed. + aif_cap = aif_cap,$; integer. A user defined estimate of dynamic image in which enhancement occurs. At all timepoints before this ca is set to 0. + Hmt = Hmt,$; float. An estimate of the patient hematocrit. Used to convert sa to ca. + model = model,$; string. The tracer kinetic model to fit. The options are 'Tofts', 'ETofts' and 'XM' (two compartment exchange model) + known_T1 = known_T1,$; float. A user defined estimate of precontrast T1. Useful if T1 mapping data does not exist or if thought to be unreliable. + known_S0v = known_S0v,$;float. Ditto for S0v. + T1_dataType = T1_dataType,$; string. Type of T1 mapping data. At the moment only 'vfa'. + baseline_cap = baseline_cap; integer. Similar to aif_cap. defines the last dynamic image up to which calculate the precontrast dynamic signal. + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON TwoCXM_params,E,K_m,K_p + COMMON time, timepoints + COMMON indices, index, xyz_indices + COMMON signal_result, Res + COMMON ost, T10_ost + COMMON ve_vp_constraints, constrain + COMMON iteration, j + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + COMMON sigma_info, fixed_sigma, equal_sigma, known_sigma ; fixed sigma will fixed sigmas to inputs from 'known sigma' or scan for sigma. equal sigma sets sigma_vfa = sigma_dyn. + COMMON IRparams, little_tr, long_TR, rad_IR, ETL,n_centre + + ;defines how S0v and S0d should be fit + equal_and_free = 1 + unequal_and_free = 0 + equal_by_baseline = 0 + + COMPILE_OPT idl2 + + device, decompose = 0 ; for linecolors to work, color decomposition needs to be set to zero. + linecolors + + ;---------------------------------------- Data read-in from self. + ; read in dynamic data + ROI_timeseries = (*self.DCE_timeseries_p)*(*self.ROI_mask_p)/100.0 ; read in masked dce-time series + TR = self.scan_params.TR + alpha_dyn = self.scan_params.alpha_dyn + rad_dyn = alpha_dyn*!dtor + + row= self.scan_params.row + col= self.scan_params.column + n_slices = self.scan_params.n_slices + n_timepoints = self.scan_params.n_timepoints + timepoints = *self.scan_params.timepoints_p + + ; contrast agent and arterial blood properties + r = self.scan_params.relaxivity + ;T10_a = 1480.0/1000; See Zhang Mag Res Med 70:1082-1086 + T10_a = 1200.0/1000 + + ;read in variable flip angle data + if T1_datatype eq 'vfa' then begin + vfa_images = *self.vfa_images_p; read in vfa images + alpha_vfa = *self.scan_params.alpha_vfa_p + rad_vfa = alpha_vfa*!dtor + n_vfa = n_elements(rad_vfa) + ref_vfa_images_LS = fltarr(col,row,n_slices,n_vfa) + ref_vfa_images_ML = fltarr(col,row,n_slices,n_vfa) + ref_vfa = fltarr(col,row,n_slices,n_vfa) + endif + + noisefree_images = *self.noisefree_images_p + + ;----------------- Fitting parameters + + n_startpoints = 100 ; number of startpoints for fitting + + ;---------------------------------------- Defintion of reference storage arrays + + ref_timeseries_LS = fltarr(col,row,n_slices,n_timepoints); storage arrays for least squares fitting (assuming gaussian noise) + + ;---------------------------------------- ifit and jfit specific operations + ; for sequential estimation we generate T1 map prior to tracer kinetic parameters. + ; for joint estimation we also need to do this so that we can fit the Tofts model to estimate ost. + ;--------------------------------------- Get AIF + + IF n_elements(sa) GT 0 THEN AIF = self->Convert_s2c(t10_a,sa, Hmt = Hmt, aif_cap = aif_cap) + + IF n_elements(ca) GT 0 THEN AIF = ca + + if aif_cap gt 0 then begin ; cap aif if needed. This puts zeroes in the AID up to the point where injection is thought to occur. + AIF[0:aif_cap-1] = fltarr(aif_cap) + endif + + ;-------------------------------------- Defining arrays to aid processing + ;Here we convert our 4D arrays into 2D list type arrays by extracting the relevant information + + ROI_random_vox = fltarr(col,row,n_slices); an matrix to hold signal time series for randomly selected voxels. + + ;generating a mask which selects n_vox_fit random voxels from all voxels + if n_elements(n_vox_fit) gt 0 then begin ; add on if we don't want to fit to all roi voxels + + n_voxels = n_vox_fit + + ROI_timeseries = (*self.DCE_timeseries_p)*(*self.ROI_mask_p)/100.0 + + index_all = where(ROI_timeseries[*,*,*] gt 0.) + + seed_for_sample = 1.0 + + index = sample_from_array(index_all,n_vox_fit,seed_for_sample,/no_replacement) ; creating an index array to select n_vox_fit random voxels from the roi voxels. + + si = sort(index); indices are in random order. Need to be sorted + index = index[si] + ROI_random_vox[index] = 100.0 + + endif else begin + ;or if we want to fit to all voxels we skip the previous step + + index = where(ROI_timeseries[*,*,*] gt 0, n_voxels) ; Finding the linear indices and roi voxels + + endelse + + ; defining number of datapoints and dummy arrays for processing + + if T1_datatype eq 'vfa' then begin + if fit_type eq 'ifit' then n_x = n_timepoints + if fit_type eq 'jfit' then n_x = n_timepoints + n_vfa + noisefree_array = fltarr(n_timepoints + n_vfa, n_voxels) + vfa_array = fltarr(n_vfa,n_voxels) + endif + + sv_array = fltarr(n_timepoints,n_voxels); an array of the measured sig-time curves + sv_mod = fltarr(n_x,n_voxels,n_startpoints) + T1_array = fltarr(n_voxels) ; an array of T1 values. One element for each voxel in the roi. + xyz_indices = findgen(3,n_voxels); a 3 by n_voxels array of x,y,z indices to hold the location of roi voxels. + chisq_arr = fltarr(n_voxels,n_startpoints) ; an array to hold the chisq value for each voxel and startpoint. + ost_array = fltarr(n_voxels) ; an array to hold ost if we want to set it beforehand. i.e. for bootstrapping. + ;------------------------------------------------ Converting image arrays into 2D arrays where each row represent signal data for a voxel. + + z = 0 ; counter variable + + if n_elements(n_vox_fit) eq 0 then begin + ROI_filler = ROI_timeseries + endif else begin + ROI_filler = roi_random_vox + endelse + + FOR k = 0,n_slices-1 DO BEGIN + FOR j = 0, row-1 DO BEGIN + FOR i = 0, col-1 DO BEGIN + + IF ROI_filler[i,j,k] GT 0 THEN BEGIN + ; print,i,j,k + sv_array[*,z] = ROI_timeseries[i,j,k,*] ; filling the sig-time array with sig time curves from all ROI voxels + + if T1_datatype eq 'vfa' then vfa_array[*,z] = vfa_images[i,j,k,*] + + ;noisefree_array[*,z] = noisefree_images[i,j,k,*] + + xyz_indices[*,z] = [i,j,k] + + if n_elements(ost_map_old) gt 0 then ost_array[z] = ost_map_old[i,j,k] ; fills ost_array with passed values if needed + z++ ; increment z + + ENDIF + + ENDFOR + ENDFOR + ENDFOR + + ;------------------------------------------ Defining storage arrays to hold maps + + Fp_map_LS = fltarr(col,row,n_slices) + FE_map_LS = fltarr(col,row,n_slices) + ve_map_LS = fltarr(col,row,n_slices) + vp_map_LS = fltarr(col,row,n_slices) + T1_map_LS = fltarr(col,row,n_slices) + S0v_map_LS = fltarr(col,row,n_slices) + S0d_map_LS = fltarr(col,row,n_slices) + ost_map_LS = fltarr(col,row,n_slices) + Ktrans_map_LS = fltarr(col, row, n_slices) + FAerror_map_LS = fltarr(col,row,n_slices) + chisq_map_LS = fltarr(col,row,n_slices) + + + ;-------------------------------------------- Begin model fitting + + FOR i = 0, n_voxels-1 DO BEGIN ; fit the tracer kinetic (ifit) or tracer kinetic and SPGR models (jfit) to each voxel within the roi one at a time + print, '------------------------' + + sv = sv_array[*,i] ; pick out signal-time curve for voxel i + + if T1_datatype eq 'vfa' then sv_vfa = vfa_array[*,i]; pick out signal-flip angle curves for voxel i + + noisefree_sig = noisefree_array[*,i] + + ;-------------------Defining the precontrast mean and dynamic noise + + cutoff = baseline_cap + + baseline = mean(sv[0:cutoff]); fixed for synthetic data. Used in sequential estimation to calculate S0d. + noise = stddev(sv[0:cutoff]) + SNR = baseline/noise + + ;---------------if we have no T1 estimate for a patient we use an estimate of T1 and S0v calculated from average of other patients + + if n_elements(known_T1) gt 0 then begin ; section of code for patients with no T1 estimate + + if T1_dataType eq 'vfa' then begin + + output = {ref_vfa:ref_vfa_images_LS,T1:known_T1,S0v:known_S0v} + T10_ost = output.T1 + + endif + + endif else begin ; for all other patients do this. + + if T1_dataType eq 'vfa' then output = self->SPGR_Fit(sv_vfa) ; fit SPGR model to vfa curves. Outputs T1 and S0v estiamtes. T1 estimate is used by both sequential and joint (ost calc) + + T10_ost = output.T1 ; set this T10_v estimate to the variable used to calculate ost. + + endelse + + S0v = output.S0v ; for ifit this is not changed in the proceding code. For jfit it is changed. + + if fit_type eq 'ifit' then begin + + T1_map_LS[index[i]] = output.T1; for SE, assign Sov and T1 estimates to arrays and update common block + S0v_map_LS[index[i]] = output.S0v + T10_v = output.T1 + + if T1_dataType eq 'vfa' then begin + ref_vfa = output.ref_vfa + if n_elements(known_T1) gt 0 then LS_mod_vfa = fltarr(n_vfa) else LS_mod_vfa = ref_vfa + endif + + endif + + ;Defining the ost to be fed as an initial param + if n_elements(ost_map_old) gt 0 then ost = ost_array[i] else ost = self->Get_ost_by_model(timepoints,sv,AIF) ;if ost_map_old supplied then ost should be taken from there and be fixed later. + ;--------------------------------------------------- Fit model using least squares while varying vp + + if model eq 'Tofts' then n_startpoints = 1 + FOR j = 0, n_startpoints-1 DO BEGIN; ; fit 100 times while incrementing vp + + ; model dependent starting parameters + start_params = self->Set_startparamsLS(fit_type,ost) + + if T1_datatype eq 'vfa' then sv_T1 = sv_vfa + + LS_output = self->Run_LSfit(fit_type,data_type,start_params,timepoints,sv,sv_T1,ostfORf = ostfORf,FAfORf = FAfORf, model = model, T1_datatype = T1_datatype); output is in the form output = {modelled_sig:A, result:B, parinfo:C] + + sv_mod[*,i,j] = LS_output.modelled_signal ; this is just dyn for ifit and dyn + vfa for jfit + + LS_params = LS_output.parameters; LS_params is an array with all fitted parameters. + + + chisq = LS_output.chisquared + + n = n_elements(LS_params) + + ;----------------------------------------------------- Choosing the best fit and filling LS maps + + chisq_arr[i,j] = chisq; for each voxel (i) there is a chisq value for each vp increment (j). We want to choose the fit with the lowest chisq. + ;print, [LS_params,S0d,S0v,T10_v], chisq_arr[i,j] + + gt_zero_index = where(chisq_arr[i,*] gt 0) ; finding the indexes of the non-zero elements + + if gt_zero_index[0] gt -1 then chisq_no_zeroes = chisq_arr[i,gt_zero_index] else chisq_no_zeroes = -1 + + tester1 = (chisq_arr[i,j] le min(chisq_no_zeroes)) && (chisq_arr[i,j] gt 0); + + IF tester1 EQ 1 THEN BEGIN; if we are on the first startpoint and chisq gt 0 + + S0v_map_LS[index[i]] = LS_params[0] + T1_map_LS[index[i]] = LS_params[1] + Fp_map_LS[index[i]] = LS_params[2] + vp_map_LS[index[i]] = LS_params[3] + ve_map_LS[index[i]] = LS_params[4] + FE_map_LS[index[i]] = LS_params[5] + S0d_map_LS[index[i]] = LS_params[6] + ost_map_LS[index[i]] = LS_params[7] + Ktrans_map_LS[index[i]] = LS_params[8] + FAerror_map_LS[index[i]] = LS_params[9] + + ENDIF + + + ENDFOR ; end of loop over n_startpoints + + + gt_zero_index1 = where(chisq_arr[i,*] gt 0) ; extracting the modelled curve from the best fit. + min_chisq = min(chisq_arr[i,gt_zero_index1],index_min) + LS_mod_sig = sv_mod[*,i,index_min] + + ;calculate the normalised chisq for all timepoints. + chisq_map_LS[index[i]] = min_chisq/n_timepoints + + ref_timeseries_LS[xyz_indices[0,i],xyz_indices[1,i],xyz_indices[2,i],*] = LS_mod_sig[0:n_timepoints-1] ; filling the reference time series array for registration. + + ;------------------------------------------------- Plotting LS fits + + IF fit_type eq 'ifit' THEN BEGIN + + LS_mod_dyn = LS_mod_sig[0:n_timepoints-1] + + if T1_datatype eq 'vfa' then begin + ;ref_vfa_images_LS[xyz_indices[0,i],xyz_indices[1,i],xyz_indices[2,i],*] = LS_mod_vfa + plot, [rad_vfa, rad_vfa[2] + timepoints],[sv_vfa,sv],psym = 4, xtitle = 'Time (minutes)', ytitle = 'Signal intensity' + oplot, [rad_vfa, rad_vfa[2]+ timepoints], [LS_mod_vfa,LS_mod_dyn] ,color = 7 + wait, 0.00001 + endif + + xyouts, 400,220, 'S0v = ' + strtrim(string(S0v_map_LS[index[i]]),1) ,/Device,CHARSIZE = 2 + xyouts, 400,200, 'S0d = ' + strtrim(string(S0d_map_LS[index[i]]),1) ,/Device,CHARSIZE = 2 + xyouts, 400,180, 'T1 = ' + strtrim(string(T1_map_LS[index[i]]),1) + 's',/Device,CHARSIZE = 2 + if model eq 'XM' then xyouts, 400,160, 'Fp = ' + strtrim(string(Fp_map_LS[index[i]]),1) + ' ml/min/ml' ,/Device,CHARSIZE = 2 + if model eq 'ETofts' || model eq 'Tofts' then xyouts, 400,160, 'Ktrans = ' + strtrim(string(Ktrans_map_LS[index[i]]),1) + 'ml-1' ,/Device,CHARSIZE = 2 + xyouts, 400,140, 'vp = ' + strtrim(string(vp_map_LS[index[i]]),1) + ' ml/ml',/Device,CHARSIZE = 2 + xyouts, 400,120, 've = ' + strtrim(string(ve_map_LS[index[i]]),1) + ' ml/ml',/Device,CHARSIZE = 2 + if model eq 'XM' then xyouts, 400,100,'FE = ' + strtrim(string(FE_map_LS[index[i]]),1) + ' ml/min/ml',/Device,CHARSIZE = 2 + xyouts, 400,80,'ost = ' + strtrim(string(ost_map_LS[index[i]]),1) + ' min',/Device,CHARSIZE = 2 + + if model eq 'XM' then print, 'LS params',' S0v ',S0v_map_LS[index[i]],' T1 ',T1_map_LS[index[i]],' Fp ',Fp_map_LS[index[i]], ' vp ',vp_map_LS[index[i]],' ve ',ve_map_LS[index[i]],' FE ',FE_map_LS[index[i]],' S0d ',S0d_map_LS[index[i]],'ost',ost_map_LS[index[i]] + if model eq 'UM' then print, 'LS params',' S0v ',S0v_map_LS[index[i]],' T1 ',T1_map_LS[index[i]],' Fp ',Fp_map_LS[index[i]], ' vp ',vp_map_LS[index[i]],' FE ',FE_map_LS[index[i]],' S0d ',S0d_map_LS[index[i]],'ost',ost_map_LS[index[i]] + if model eq 'Tofts' || model eq 'ETofts' then print, 'LS params',' S0v ',S0v_map_LS[index[i]],' T1 ',T1_map_LS[index[i]],' vp ',vp_map_LS[index[i]],' ve ',ve_map_LS[index[i]],' Ktrans ',Ktrans_map_LS[index[i]],' S0d ',S0d_map_LS[index[i]],'ost',ost_map_LS[index[i]] + ENDIF + + IF fit_type eq 'jfit' THEN BEGIN + + LS_mod_dyn = LS_mod_sig[0:n_timepoints - 1] + + if T1_datatype eq 'vfa' then begin + LS_mod_vfa = LS_mod_sig[n_timepoints:*] + ref_vfa_images_LS[xyz_indices[0,i],xyz_indices[1,i],xyz_indices[2,i],*] = LS_mod_vfa + plot, [rad_vfa, timepoints],[sv_vfa,sv],psym = 4, xtitle = 'Time (minutes)', ytitle = 'Signal intensity' + oplot, [rad_vfa, timepoints], [LS_mod_sig[n_timepoints:*],LS_mod_sig[0:n_timepoints-1]],color = 7 + wait, 0.000001 + endif + + if T1_datatype eq 'SR' then begin + LS_mod_SR = LS_mod_sig[n_timepoints:*] + ref_SR_images_LS[xyz_indices[0,i],xyz_indices[1,i],xyz_indices[2,i],*] = LS_mod_SR + plot, [Inv_times/10., Inv_times[4]/10. + timepoints[0:80]],[sv_SR,sv[0:80]],psym = 4, xtitle = 'Time (minutes)', ytitle = 'Signal intensity' + oplot, [Inv_times/10., Inv_times[4]/10. + timepoints[0:80]], [LS_mod_SR,LS_mod_dyn[0:80]] ,color = 7 + wait, 0.000001 + endif + + xyouts, 400,220, 'S0v = ' + strtrim(string(S0v_map_LS[index[i]]),1) ,/Device,CHARSIZE = 2 + xyouts, 400,200, 'S0d = ' + strtrim(string(S0d_map_LS[index[i]]),1) ,/Device,CHARSIZE = 2 + xyouts, 400,180, 'T1 = ' + strtrim(string(T1_map_LS[index[i]]),1) + 's',/Device,CHARSIZE = 2 + if model eq 'XM' then xyouts, 400,160, 'Fp = ' + strtrim(string(Fp_map_LS[index[i]]),1) + ' ml/min/ml' ,/Device,CHARSIZE = 2 + if model eq 'Tofts' || model eq 'ETofts' then xyouts, 400,160, 'Ktrans = ' + strtrim(string(Ktrans_map_LS[index[i]]),1) + ' ml-1' ,/Device,CHARSIZE = 2 + xyouts, 400,140, 'vp = ' + strtrim(string(vp_map_LS[index[i]]),1) + ' ml/ml',/Device,CHARSIZE = 2 + xyouts, 400,120, 've = ' + strtrim(string(ve_map_LS[index[i]]),1) + ' ml/ml',/Device,CHARSIZE = 2 + if model eq 'XM' then xyouts, 400,100,'FE = ' + strtrim(string(FE_map_LS[index[i]]),1) + ' ml/min/ml',/Device,CHARSIZE = 2 + xyouts, 400,80,'ost = ' + strtrim(string(ost_map_LS[index[i]]),1) + ' min',/Device,CHARSIZE = 2 + + if model eq 'XM' then print, 'LS params',' S0v ',S0v_map_LS[index[i]],' T1 ',T1_map_LS[index[i]],' Fp ',Fp_map_LS[index[i]], ' vp ',vp_map_LS[index[i]],' ve ',ve_map_LS[index[i]],' FE ',FE_map_LS[index[i]],' S0d ',S0d_map_LS[index[i]],'ost',ost_map_LS[index[i]], 'FAerror ',FAerror_map_LS[index[i]] + if model eq 'Tofts' || model eq 'ETofts' then print, 'LS params',' S0v ',S0v_map_LS[index[i]],' T1 ',T1_map_LS[index[i]],' Ktrans ',Ktrans_map_LS[index[i]], ' vp ',vp_map_LS[index[i]],' ve ',ve_map_LS[index[i]],' S0d ',S0d_map_LS[index[i]],'ost',ost_map_LS[index[i]], 'FAerror ',FAerror_map_LS[index[i]] + + ENDIF + +endfor + +end + +function DCEMRIprocessor_freeS0::Set_startparamsLS,fit_type,ost + + COMMON iteration, j + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + ;start params for 2CXM + + Fp_int = 0.5 ; default 0.5 + vp_int = 0.0000001 + 0.01*j ; if this is set to zero then funny things happen + ve_int = 0.2 ;default 0.2 + FE_int = 0.2 ; be careful if using 2CUM as we get discontinuities in IRF when Fp ~ FE, default 0.2 + S0d_int = 5000.0; default ; 5000 + if fit_type eq 'ifit' then S0d_int = baseline*((1- cos(rad_dyn)*exp(-TR/T10_v))/(sin(rad_dyn)*(1-exp(-TR/T10_v)))) + S0v_int = 5000.0 + T10_v_int = 1.0 + ost_int = ost ; this will be the estimate from fitting to Tofts model or passed using ost_map_old + Ktrans = 0.2 + f = 1. + + start_params = [S0v_int,T10_v_int,Fp_int,vp_int,ve_int,FE_int,S0d_int,ost_int, Ktrans,f] + + return, start_params + +end +;---------------------------------------------------------------------------------------------------------------------------------------------- +function DCEMRIprocessor_freeS0::Set_LScontraints, model, fit_type, data_type, start_params, ostfORf = ostfORf, FAfORf = FAfORf + + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + + + result = start_params; S0v,T10,Fp,vp,ve,FE,S0d,ost, Ktrans, f + + parinfo = replicate({limited:[0,0],limits:[0.D,0],fixed:0, tied: ''},n_elements(result)) ; parinfo is an array of structures + + parinfo[0].limited[0] = 1 ;set lower limit for S0v + parinfo[0].limits[0] = 0.D + parinfo[0].limited[1] = 1 ;set upper limit for S0v + parinfo[0].limits[1] = 80000.D ; usually 20000 for simulated and cervix data + + if equal_by_baseline eq 1 then parinfo[0].fixed = 1 + + parinfo[1].limited[0] = 1 ;set lower limit for T10 + parinfo[1].limits[0] = 0.D + parinfo[1].limited[1] = 1 ;set lower limit for T10 + parinfo[1].limits[1] = 10.D + + parinfo[2].limited[0] = 1 ;set lower limit for Fp + parinfo[2].limits[0] = 0.D + if model eq 'ETofts' || model eq 'Tofts' then parinfo[2].fixed = 1. + + parinfo[3].limited[0] = 1 ;set lower limit for vp + parinfo[3].limits[0] = 0.D + parinfo[3].limited[1] = 1 ;set upper limit for vp + parinfo[3].limits[1] = 1.D + parinfo[3].fixed = 1 + + parinfo[4].limited[0] = 1 ;set lower limit for ve + parinfo[4].limits[0] = 0.D + parinfo[4].limited[1] = 1 ;set upper limit for ve + parinfo[4].limits[1] = 1.D + if model eq 'UM' then parinfo[4].fixed = 1. + + parinfo[5].limited[0] = 1 ;set lower limit for FE + parinfo[5].limits[0] = 0.D + + if model eq 'ETofts' || model eq 'Tofts' then parinfo[5].fixed = 1. + + parinfo[6].limited[0] = 1 ;set lower limit for S0d + parinfo[6].limits[0] = 0.D + parinfo[6].limited[1] = 1 ;set lower limit for S0d + parinfo[6].limits[1] = 80000.D + + parinfo[8].limited[0] = 1 ;set lower limit for Ktrans + parinfo[8].limits[0] = 0.D + parinfo[8].limited[1] = 1 ;set lower limit for Ktrans + parinfo[8].limits[1] = 10.D + + if equal_by_baseline eq 1 then parinfo[6].fixed = 1 + if equal_and_free eq 1 then parinfo[0].tied = 'p[6]' + + ;fix parameter to reduce searching unnessasarily. + if fit_type eq 'ifit' then parinfo[0].fixed = 1 ; this param is still passed in ifit. + if fit_type eq 'ifit' then parinfo[1].fixed = 1 ; this param is still passed in ifit. + if fit_type eq 'ifit' then parinfo[6].fixed = 1 ; this param is still passed in ifit. + + ;constraints for ost calculation. + + if ostfORf eq 'free' then begin + + temp_ost = start_params[7] + + parinfo[7].limited[0] = 1 ;set lower limit for ost + + ;temp_ost - 5.0/60 is the estimated ost - 5/60th of a minute. Is this a wide enough range? + if temp_ost - 5.0/60 lt 0 then parinfo[7].limits[0] = 0 else parinfo[7].limits[0] = temp_ost - 5.0/60 + + parinfo[7].limited[1] = 1;set upper limit for ost + parinfo[7].limits[1] = temp_ost + 5.0/60 + + endif else begin ;this will fix ost in fitting. The intial value will be set to tht calculated from fitting to Tofts or that passed by ost_old. + + parinfo[7].fixed = 1 + + endelse + + if model eq 'XM' || model eq 'UM' then parinfo[8].fixed = 1 + + ;flip angle correction + if FAfORf eq 'free' then begin + parinfo[9].limited[0] = 1 ;set lower limit for f + parinfo[9].limits[0] = 0.5D + parinfo[9].limited[1] = 1 ;set lower limit for f + parinfo[9].limits[1] = 1.5D + if fit_type eq 'ifit' then parinfo[9].fixed = 1 + endif else begin + parinfo[9].fixed = 1 + endelse + + return, {parinfo:parinfo, result:result} + +end + + + +;----------Run_LSfit +;PURPOSE: +;Method to fit the 2CXM to dynamic timeseries data using sequential/joint estimation +;INPUTS: +;fit_type -> string, sequential estimation ('ifit') or joint estimation ('ifit') +;data_type -> string, tells the program the type of data it is analysing ('phantom' or 'real'). Has implications regarding offset time estimation. +;start_params -> array, of intial parameter estimates for fitting. start_params = [Fp,vp,ve,FE,T10_v,S0,ost] +;timepoints -> array, timepoint vector for the dynamic time series. +;sv -> array, dce signal vector for the voxel. +;rad_vfa -> array flip angles used for T1 mapping. +;sv_vfa -> array, vfa signal vector for the voxel. +;ostfORf -> string array, tells us allow ost to be a free parameter or fixedduring fitting. +;model = model -> string, '2CXM' or '2CUM'. Can easily add more. + +function DCEMRIprocessor_freeS0::Run_LSfit,fit_type,data_type,start_params,timepoints,sv,sv_T1,ostfORf = ostfORf,FAfORf = FAfORf,model = model,T1_datatype = T1_datatype + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON sigma_info, fixed_sigma, equal_sigma, known_sigma ; fixed sigma will fixed sigmas to inputs from 'known sigma' or scan for sigma. equal sigma sets sigma_vfa = sigma_dyn. + + LS_constraints = self->Set_LScontraints(model, fit_type, data_type, start_params, ostfORf = ostfORf, FAfORf = FAfORf) + + param_estimates = LS_constraints.result + + parinfo = LS_constraints.parinfo + + if fit_type eq 'ifit' then begin + + x_meas = timepoints + y_meas = sv + weights = findgen(n_elements(x_meas)) + weights[*] = 1.0 + + if model eq 'UM' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='twoCUM_ifit_dc',parinfo=parinfo,/noderivative,/quiet) + if model eq 'XM' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='twoCXM_ifit_dc',parinfo=parinfo,/noderivative,/quiet) + if model eq 'Tofts' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='Tofts_ifit_dc',parinfo=parinfo,/noderivative,/quiet) + if model eq 'ETofts' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='ETofts_ifit_dc',parinfo=parinfo,/noderivative,/quiet) + + result = param_estimates ; may need to adjust for Tofts and ET + + endif + + if fit_type eq 'jfit' then begin + + if T1_datatype eq 'vfa' then begin + y_meas= [sv,sv_T1] + x_meas = [timepoints, rad_vfa] + endif + + if T1_datatype eq 'SR' then begin + y_meas= [sv,sv_T1] + x_meas = [timepoints, Inv_times] + endif + + if T1_datatype eq 'IR' then begin + y_meas= [sv,sv_T1] + x_meas = [timepoints, Inv_times] + endif + + weights = findgen(n_elements(x_meas)) + + if known_sigma.sigmaDYN eq known_sigma.sigmaVFA then begin ; logic + + weights[*] = 1.0 + ;weights[0:10] = 5.0 + + endif else begin + + weights[0:n_timepoints-1] = 1.0/(known_sigma.sigmaDYN^2) + weights[n_timepoints:*] = 1.0/(known_sigma.sigmaVFA^2) + + endelse + + if model eq 'XM' then begin + if T1_datatype eq 'vfa' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='twoCXM_vfa_jfit_dc',parinfo=parinfo, /noderivative, /quiet) + if T1_datatype eq 'SR' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='twoCXM_SR_jfit_dc',parinfo=parinfo, /noderivative, /quiet) + ; function to do IR jointly is not written yet. + ;if T1_datatype eq 'IR' then curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='twoCXM_IR_jfit_dc',parinfo=parinfo, /noderivative, /quiet) + endif + + if model eq 'Tofts' then begin + curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='Tofts_vfa_jfit_dc',parinfo=parinfo, /noderivative, /quiet) + endif + + if model eq 'ETofts' then begin + curve = mpcurvefit(x_meas,y_meas,weights,param_estimates,chisq=chisq, function_name='ETofts_vfa_jfit_dc',parinfo=parinfo, /noderivative, /quiet) + endif + + result = param_estimates + + ; we minimise the joint chisq, but select best vp using only the dynamic chisq? + ;chisq = total((curve[0:n_timepoints-1] - y_meas[0:n_timepoints-1])^2) + + endif + + output = {modelled_signal:curve,parameters:result,chisquared:chisq, parameter_info:parinfo} + + return, output + +end + +;------------------------------------------------------------------------------------------------------------------- +;Method to perform registration of the dynamic timeseries with a reference volume using translational registration. +;------------------------------------------------------------------------------------------------------------------- + +function DCEMRIprocessor_freeS0::RIGID_reg_dynamics, objective_function, optimiser,reg_params_k = reg_params_k, ref_timeseries = ref_timeseries + + compile_opt idl2 + + COMMON registration_params,ref_timepoint,dce_timepoint,reg_timepoint,roi,pre_vector, obj_fcn + COMMON stepper, step_size,boundary + + Obj_fcn = objective_function + + dce_timeseries = *self.dce_timeseries_p ; Get dce_timeseries from storage + ;----------------------------- import images and masks from storage + + if n_elements(ref_timeseries) eq 0 then begin ; if ref timeseries not supplied + ref_timeseries = *self.ref_timeseries_p + endif else begin + ref_timeseries = ref_timeseries + endelse + + s = size(ref_timeseries) + + roi_fourD = *self.roi_mask_p; get roi mask from storage + + roi = roi_fourD[*,*,*,0]/100.0 + + n_timepoints = s[4] + + reg_timeseries = fltarr(s[1],s[2],s[3],s[4]) ; generate an array for the registered timeseries + + ;-----------------Generate a "pre vector" for each voxel in roi ------------------------- + + roi_index = where(roi_fourD[*,*,*] gt 0, n_voxels) ; find the roi voxels + + pre_vector = fltarr(n_voxels,4) ; [xi,yi,zi,1] + + n_startpoints = 1 + + xf_i = fltarr(3,n_startpoints) + xf_f = fltarr(3,n_startpoints) + of_min_i = fltarr(n_startpoints) + of_min_f = fltarr(n_startpoints) + min_xf = fltarr(4,s[4]) + reg_params = fltarr(3,s[4]) + + n = 0 + for i = 0, s[1] -1 do begin + for j = 0, s[2] -1 do begin + for k = 0, s[3] -1 do begin + + if ref_timeseries[i,j,k] gt 0 then begin + + pre_vector[n,0] = i + pre_vector[n,1] = j + pre_vector[n,2] = k + pre_vector[n,3] = 1.0 + + n++ + + endif + + endfor + endfor + endfor + + ;exclude voxels that fail to fit properly (i.e. duds in ref timeseries) + index_nan = where(finite(ref_timeseries,/NAN)) + + ref_timeseries[index_nan] = 0.0 + + + for i = 0, n_timepoints - 1 do begin + + ref_timepoint = ref_timeseries[*,*,*,i] ;selects the ith timepoint of the reference vol (just roi voxels) + dce_timepoint = DCE_timeseries[*,*,*,i] ; selects the ith timepoint of the shifted image for reg (full vol) + for j = 0, n_startpoints -1 do begin + + reg_timepoint = fltarr(s[1],s[2],s[3]) + + CASE optimiser OF + + 'sa_then_powell': BEGIN + + ; start by finding an estimate of global minimum using simulated annealing + print, 'timepoint ', i + nstep = 1000 + step_size = 0.01 ; was 0.1 changed to 0.01 on 24/03/2014 + boundary = 5.0 + start_state = [0.0,0.0,0.0] + best_params = sa(nstep = nstep, start_state = start_state) + + xf_i[*,j] = best_params.best_state_tab ; best reg params after sa + of_min_i[j] = best_params.best_fitness_tab + + + ; refine estimate with POWELL + print, 'sa estimate', xf_i[*,j] + + dx = xf_i[0,j] + dy = xf_i[1,j] + dz = xf_i[2,j] + + X = [dx,dy,dz] + + ftol = 1.0e-15 + + xi = [[1.0,0.0,0.0],[0.0,1.0,0.0],[0.0,0.0,1.0]] ; intial direction vectors for search + + powell,X,xi,ftol,fmin,'register_fcn' + + xf_f[*,j] = X ; best reg params after sa and powell + + print, 'powell refinement', xf_f[*,j] + + of_min_f[j] = fmin + + END + + 'sa': BEGIN + + ; start by finding an estimate of global minimum using simulated annealing + print, 'timepoint ', i + nstep = 1000 + step_size = 0.01 + boundary = 5.0 + start_state = [0.0,0.0,0.0] + best_params = sa(nstep = nstep, start_state = start_state) + + xf_f[*,j] = best_params.best_state_tab ; best reg params after sa + of_min_f[j] = best_params.best_fitness_tab + print, 'sa estimates',xf_f + + + END + + 'powell': BEGIN + + ;------------just use powell + + dx = 0.0 + dy = 0.0 + dz = 0.0 + + X = [dx,dy,dz] + + ftol = 1.0e-15 + + xi = [[1.0,0.0,0.0],[0.0,1.0,0.0],[0.0,0.0,1.0]] ; intial direction vectors for search + + powell,X,xi,ftol,fmin,'register_fcn' + + xf_f[*,j] = X + of_min_f[j] = fmin + print, 'powell estimate', xf_f + END + + + ENDCASE + + endfor ; end of loop over n_startpoints + + ; ------------------- find the transformation parameters with the minimum SAD (from all startpoints) + + minimum_of = min(of_min_f,min_index) + + min_xf[*,i] = [minimum_of,xf_f[0,min_index],xf_f[1,min_index],xf_f[2,min_index]] + + print, 'objective function minimum', minimum_of + + ;--------------------Calculating the transformation vectors ------------------------------- + reg_params[*,i] = min_xf[1:3,i] + + trans = [[1,0,0, reg_params[0,i]],[0,1,0,reg_params[1,i]],[0,0,1,reg_params[2,i]],[0,0,0,1]] + + pre_vector_allvox = fltarr(s[1]*s[2]*s[3],4) ; performing the transformation on the volume. + + c = 0 + + for l = 0, s[1] -1 do begin + for m = 0, s[2] -1 do begin + for n = 0, s[3] -1 do begin + + pre_vector_allvox[c,0] = l + pre_vector_allvox[c,1] = m + pre_vector_allvox[c,2] = n + pre_vector_allvox[c,3] = 1.0 + + c++ + + endfor + endfor + endfor + + post_vector = trans##pre_vector_allvox + + ;--------------------------- Preparing arrays for interpolate function + + interp_x = 2*pre_vector_allvox[*,0] - post_vector[*,0] + interp_y = 2*pre_vector_allvox[*,1] - post_vector[*,1] + interp_z = 2*pre_vector_allvox[*,2] - post_vector[*,2] + + interp = interpolate(dce_timepoint[*,*,*],interp_x,interp_y,interp_z,missing = 0.0) + + num = n_elements(interp) + + for k = 0, num-1 do begin + + reg_timepoint[pre_vector_allvox[k,0],pre_vector_allvox[k,1],pre_vector_allvox[k,2]] = interp[k] + + endfor + + reg_timeseries[*,*,*,i] = reg_timepoint + + endfor; end of loop over n_timepoints + + ; display_series, image_array = [dce_timeseries, ref_timeseries, reg_timeseries], matrix = [s[1],s[2]], ns = s[3], nt = s[4], scale = 1500 + + *self.dce_timeseries_p = reg_timeseries ; set the new dce_timeseries to the registered timeseries + ; + reg_output = {reg_timeseries:reg_timeseries,ref_timeseries:ref_timeseries,reg_params:reg_params} + ; + return, reg_output + ; +end + +;------------------------------------------------------------------------------------------------ +;Method to performs translational registration of fa images to the average dce timeseries volume. +;------------------------------------------------------------------------------------------------ + +function DCEMRIprocessor_freeS0::RIGID_reg_fa2dyn, objective_function, optimiser + + compile_opt idl2 + + COMMON registration_params,ref_timepoint,dce_timepoint,reg_timepoint,roi,pre_vector, obj_fcn + COMMON stepper, step_size,boundary + + + Obj_fcn = objective_function + + ;----------------------------- import images and masks from storage + + dce_timeseries = *self.dce_timeseries_p ; Get dce_timeseries from storage + vfa_images = *self.O_vfa_images_p ; Get fa images from storage + + roi_fourD = *self.roi_mask_p; get roi mask from storage + roi = roi_fourD[*,*,*,0]; get roi mask from storage + roi_timeseries = dce_timeseries*roi_fourD/100.0 ; 100 accounts for the fact that roi mask is between 0 and 100 not 0 and 1 + + row = self.scan_params.row + col = self.scan_params.column + n_slices = self.scan_params.n_slices + n_timepoints = self.scan_params.n_timepoints + + ref_vol = fltarr(col,row, n_slices) + + ;generating the ref vol which is the mean to all dynamic timepoints + ; for i = 0, n_timepoints-1 do begin + ; + ; ref_vol[*,*,*] = roi_timeseries[*,*,*,i] + ref_vol[*,*,*] + ; + ; endfor + ; + ; ref_vol = ref_vol/n_timepoints + + ref_vol = (roi_timeseries[*,*,*,0]+roi_timeseries[*,*,*,1] + roi_timeseries[*,*,*,2] + roi_timeseries[*,*,*,3] + roi_timeseries[*,*,*,4]+ roi_timeseries[*,*,*,5]+ roi_timeseries[*,*,*,6]+ roi_timeseries[*,*,*,7])/8 + + s = size(ref_vol) + + ;----------------------------- make new image arrays + + n_vfa = 3 + + reg_params = fltarr(3,n_vfa) + + reg_fa = fltarr(s[1],s[2],s[3],n_vfa) ; generate an array for the registered timeseries + + ; -----------------Generate a "pre vector" for each voxel in roi ------------------------- + + roi_index = where(ref_vol gt 0, n_voxels) + + pre_vector = fltarr(n_voxels,4) ; [xi,yi,zi,1] + + n_startpoints = 1 + + xf_i = fltarr(3,n_startpoints) + xf_f = fltarr(3,n_startpoints) + of_min_i = fltarr(n_startpoints) + of_min_f = fltarr(n_startpoints) + min_xf = fltarr(4,n_vfa) + + + n = 0 + for i = 0,s[1] -1 do begin + for j = 0, s[2] -1 do begin + for k = 0, s[3] -1 do begin + + ; if ref_timeseries[i,j,k,0] gt 0 then begin + if ref_vol[i,j,k] gt 0 then begin + + pre_vector[n,0] = i + pre_vector[n,1] = j + pre_vector[n,2] = k + pre_vector[n,3] = 1.0 + + n++ + + endif + + endfor + endfor + endfor + + ; ;------------------------------ perform the optimisation + + print, 'number',n_elements(reg_params_k) + + + for i = 0, n_vfa - 1 do begin + + dce_timepoint = vfa_images[*,*,*,i]; selecting an fa image to register + + for j = 0, n_startpoints -1 do begin + + reg_fa1 = fltarr(s[1],s[2],s[3]) ; an array to store a single registered fa image + + + + ;-------------------------renaming of volumes to work with common block + + ref_timepoint = ref_vol + reg_timepoint = reg_fa1 + + ;------------------------------------------------------------------------ + + ; start by finding an estimate of global minimum using SIMULATED ANNEALING + + Case optimiser of + + 'sa_then_powell': begin + + nstep = 1000 + start_state = [0.0,0.0,0.0] + step_size = 0.1 + boundary = 10.0 + best_params = sa(nstep = nstep, start_state = start_state) + + + xf_i[*,j] = best_params.best_state_tab + of_min_i[j] = best_params.best_fitness_tab + + ;------------ refine estimate with POWELL and sinc integration + print, xf_i[*,j] + + dx = xf_i[0,j] + dy = xf_i[1,j] + dz = xf_i[2,j] + + X = [dx,dy,dz] + + ftol = 1.0e-15 + + xi = [[1.0,0.0,0.0],[0.0,1.0,0.0],[0.0,0.0,1.0]] ; intial direction vectors for search + + powell,X,xi,ftol,fmin,'register_fcn' + + xf_f[*,j] = X + of_min_f = fmin + + + End + + + 'sa': begin + + nstep = 1000 + start_state = [0.0,0.0,0.0] + step_size = 0.01 + boundary = 10.0 + best_params = sa(nstep = nstep, start_state = start_state) + + + xf_f[*,j] = best_params.best_state_tab + of_min_f[j] = best_params.best_fitness_tab + + + + + End + + 'powell': begin + + ;------------refine estimate with POWELL + dx = 0.0 + dy = 0.0 + dz = 0.0 + + X = [dx,dy,dz] + + ftol = 1.0e-15 + + xi = [[1.0,0.0,0.0],[0.0,1.0,0.0],[0.0,0.0,1.0]] ; intial direction vectors for search + + powell,X,xi,ftol,fmin,'register_fcn' + + xf_f[*,j] = X + of_min_f = fmin + + End + + + Endcase + + endfor ; end of loop over n_startpoints + ;display_series, image_array = [filtered_ref_timepoint,filtered_roi_timepoint], matrix = [size_image[1], size_image[2]], ns = size_image[3],nt = 1 + ; calculating the transformed timeseries + + ; ------------------- find the transformation parameters with the minimum SAD (from all startpoints) + + ; print output + minimum_of = min(of_min_f,min_index) + + min_xf[*,i] = [minimum_of,xf_f[0,min_index],xf_f[1,min_index],xf_f[2,min_index]] + + print, 'registration params', min_xf[1:3,i] + print, 'objective function minimum', minimum_of + ;--------------------Calculating the post transformation vectors ------------------------------- + reg_params[*,i] = min_xf[1:3,i] + + trans = [[1,0,0,reg_params[0,i]],[0,1,0,reg_params[1,i]],[0,0,1,reg_params[2,i]],[0,0,0,1]] + + post_vector = trans##pre_vector + + ;---------------------------Preparing arrays for interpolate function + + interp_x = 2*pre_vector[*,0] - post_vector[*,0] + interp_y = 2*pre_vector[*,1] - post_vector[*,1] + interp_z = 2*pre_vector[*,2] - post_vector[*,2] + + interp = interpolate(dce_timepoint[*,*,*],interp_x,interp_y,interp_z,missing = -1) + + num = n_elements(interp) + + for k = 0, num-1 do begin + + if interp[k] gt 0 then begin + + reg_timepoint[pre_vector[k,0],pre_vector[k,1],pre_vector[k,2]] = interp[k] + + endif + + endfor + + reg_fa[*,*,*,i] = reg_timepoint + + + endfor ; end of loop over n_timepoints + + ;set the newly created registered timeseries as fa_images + *self.vfa_images_p = reg_fa + + reg_output = {reg_fa:reg_fa,reg_params:reg_params} + + return, reg_output + ;display_series, image_array = [reg_fa3, vfa_images], matrix = [size_image[1], size_image[2]], ns = size_image[3],nt = 3, scale = 1500 + +end + + +;----------------------------------------------------------- +;Method to convert MR signal to contrast agent concentration +;----------------------------------------------------------- + +function DCEMRIprocessor_freeS0::Convert_s2c,t10,sy,Hmt = Hmt, aif_cap = aif_cap + + ; Method to convert a signal->concentration + + ; Checked for accuracy on 12/06/2013. passed. + + compile_opt idl2 + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + + E = exp(-TR/t10) + + Q = (sin(rad_dyn)*(1.0-E))/(1.0- cos(rad_dyn)*E) ; ; rad_dyn is the flip angle of the DCE-MRI time series not of the flip angle scans used for T1 mapping + + ;baseline = mean(sy[0:9]) ; take a mean of the precontrast datapoints. Maybe incorporate the BAT into this calc? + + S0_AIF = mean(sy[0:aif_cap-1])/Q; really dodgy. Need to vary from patient to patient + + ;A1 = alog((sy*cos(rad_dyn)/S0_AIF*sin(rad_dyn)) + 1.0) + + A2 = alog((sy*cos(rad_dyn) - S0_AIF*sin(rad_dyn))/((sy - S0_AIF*sin(rad_dyn)))) + + ;R1_1 = A1/TR + ;cy_1 = (R1_1-1.0/t10)/r ; a array of concentration values + + ;R1_2 = A2/TR + ;cy_2 = (R1_2-1.0/t10)/r ; a array of concentration values + +; cgplot,cy_1, color = 'red' +; cgoplot,cy_2 + + R1 = A2/TR + cy = (R1-1.0/t10)/r ; a array of concentration values + a = plot(cy) + if n_elements(Hmt) gt 0 then begin + + cp = cy/(1-Hmt) + + endif + a = plot(cp, /overplot) + print, 'Finished conversion of AIF signal to AIF concentration' + return, cp + +end + + +;-------------------------------------------------------------------------------------- +;Method to estimates the bolus arrival time by fitting the Tofts model to the concentration time curve +;and varying the arrival time as a free parameter +;------------------------------------------------------------------------------------------------------ + +function DCEMRIprocessor_freeS0::GET_ost_by_model,timepoints,sv,AIF + + ; computes the offset time between the AIF and tissue conc BATs by fitting the Tofts model with the offset time as a free param. + ;COMMON signal_result, Res + compile_opt idl2 + + n_timepoints_ost = n_elements(timepoints)/3. + sv_ost = sv[0:n_timepoints_ost-1] + timepoints_ost = timepoints[0:n_timepoints_ost-1] + + + Ktrans = 0.5 ; volume transfer constant + ve_k = 0.25 ; EES volume + ost = 5.0/60 ; offset time between the signal time curve and the AIF. In minutes. + + Result1 = [Ktrans,ve_k,ost] + + parinfo = replicate({limited:[0,0],limits:[0.D,0]},n_elements(Result1)) ; parinfo is an array of structures + + parinfo[0].limited[0] = 1 ;set lower limit for Ktrans + parinfo[0].limits[0] = 0.D + parinfo[1].limited[0] = 1 ;set lower limit for ve + parinfo[1].limits[0] = 0.D + parinfo[1].limited[1] = 1 ;set upper limit for ve + parinfo[1].limits[1] = 1.D + parinfo[2].limited[0] = 1 ;set lower limit for ost + parinfo[2].limits[0] = 0.D + parinfo[2].limited[1] = 1 ;set upper limit for ost + parinfo[2].limits[1] = 25.0/60 + + Result = Result1 + + weights = fltarr(n_timepoints_ost) + weights[*] = 1 + + Res = mpcurvefit(timepoints_ost,sv_ost,weights,Result,chisq=chisq,status=status,function_name='Tofts_ost_expC',parinfo=parinfo,/noderivative,/quiet); LS fitting using ExpConvolution + + ost = Result[2] + + return, ost + +end + +;----------------------------------------------------- +;Method to compute a T1 map given a set of VFA images +;---------------------------------------------------- + +function DCEMRIprocessor_freeS0::SPGR_Fit,sv_vfa + + compile_opt idl2 + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + + weights = [1.0,1.0,1.0] ; setting the uncertainty on each measurement of signal to be the same + Result1 = [5000.0,1.5] ; intialising the values [S0,T1] + n_vfa = n_elements(rad_vfa) + + parinfo = replicate({limited:[0,0],limits:[0.D,0],value:0.D, fixed:0}, n_elements(Result1)) ; defining the variable parinfo + + parinfo[0].limited[0] = 1 ;set lower limit for S0_vfa + parinfo[0].limits[0] = 0.D + parinfo[0].limited[1] = 1 ;set upper limit for S0_vfa + parinfo[0].limits[1] = 80000.D + + if equal_by_baseline eq 1 then begin + parinfo[0].fixed = 1 + endif + + parinfo[1].limited[0] = 1 ;set lower limit for T1 + parinfo[1].limits[0] = 0.D + parinfo[1].limited[1] = 1 ;set upper limit for T1 + parinfo[1].limits[1] = 10.D ; usually 4.0 for simulated data + + S = sv_vfa + + P = Result1 + + ref_vfa = MPCURVEFIT(rad_vfa,S,weights,P,Chisq = chisq, FUNCTION_NAME= 'FLASH_func',PARINFO = parinfo, /noderivative, /quiet) ; fit the function FLASH_func to the S vs alpha time datapoint + + S0v_temp = P[0] + + T1_temp = P[1] + + output = {T1:T1_temp, S0v:S0v_temp, ref_vfa:ref_vfa} + + return,output + +end + +pro DCEMRIprocessor_freeS0::Get_data, $ + TR=TR, $ + long_TR=long_TR, $ + little_TR=little_TR, $ + alpha_dyn = alpha_dyn, $ + alpha_vfa = alpha_vfa, $ + alpha_IR = alpha_IR, $ + alpha_SR = alpha_SR, $ + Inv_times = Inv_times, $ + row = row, $ + column = column, $ + n_timepoints = n_timepoints, $ + timepoints = timepoints, $ + n_slices = n_slices, $ + patient_filename = patient_filename, $ + DCE_timeseries = DCE_timeseries, $ + O_DCE_timeseries = O_DCE_timeseries, $ + reg_timeseries = reg_timeseries, $ + vfa_images = vfa_images, $ + IR_images = IR_images, $ + SR_images = SR_images, $ + noisefree_images = noisefree_images, $ + O_vfa_images = O_vfa_images, $ + O_SR_images = O_SR_images, $ + reg_vfa_images = reg_vfa_images, $ + ROI_mask = ROI_mask, $ + T1_map = T1_map, $ + temp_res = temp_res, $ + relaxivity = relaxivity, $ + GT_maps = GT_maps, $ + temporal_resolution = temporal_resolution + + compile_opt idl2 + + if arg_present(TR) then self.scan_params.TR = TR + if arg_present(long_TR) then self.scan_params.long_TR = long_TR + if arg_present(little_tr) then self.scan_params.little_tr = little_tr + if arg_present(Inv_times) then self.scan_params.Inv_times_p = ptr_new(Inv_times) ; flip angle values for flipa gnle images. + if arg_present(alpha_dyn) then self.scan_params.alpha_dyn = alpha_dyn ; flip angle values for dynamics + if arg_present(alpha_vfa) then self.scan_params.alpha_vfa_p = ptr_new(alpha_vfa) ; flip angle values for flipa gnle images. + if arg_present(alpha_IR) then self.scan_params.alpha_IR = alpha_IR ; flip angle values for IR t1 measurements + if arg_present(alpha_SR) then self.scan_params.alpha_SR = alpha_SR ; flip angle values for SR t1 measurements + if arg_present(row) then self.scan_params.row = row + if arg_present(column) then self.scan_params.column = column + if arg_present(n_slices) then self.scan_params.n_slices = n_slices + if arg_present(n_timepoints) then self.scan_params.n_timepoints = n_timepoints + if arg_present(relaxivity) then self.scan_params.relaxivity = relaxivity + if arg_present(patient_filename) then self.patient_filename = patient_filename + if arg_present(temporal_resolution) then self.scan_params.temporal_resolution = temporal_resolution + if arg_present(timepoints) then self.scan_params.timepoints_p = ptr_new(timepoints) + if arg_present(DCE_timeseries) then self.DCE_timeseries_p = ptr_new(DCE_timeseries) ; this assigns the pointer DCE_timeseries_p to point at DCEtimeseries + if arg_present(O_DCE_timeseries) then self.O_DCE_timeseries_p = ptr_new(O_DCE_timeseries) + if arg_present(reg_timeseries) then self.reg_timeseries_p = ptr_new(reg_timeseries) + if arg_present(vfa_images) then self.vfa_images_p = ptr_new(vfa_images) + if arg_present(IR_images) then self.IR_images_p = ptr_new(IR_images) + if arg_present(SR_images) then self.SR_images_p = ptr_new(SR_images) + if arg_present(O_vfa_images) then self.O_vfa_images_p = ptr_new(O_vfa_images) + if arg_present(O_SR_images) then self.O_SR_images_p = ptr_new(O_SR_images) + if arg_present(reg_vfa_images) then self.reg_vfa_images_p = ptr_new(reg_vfa_images) + if arg_present(reg_SR_images) then self.reg_SR_images_p = ptr_new(reg_SR_images) + if arg_present(ROI_mask) then self.ROI_mask_p = ptr_new(ROI_mask) + if arg_present(T1_map) then self.T1_map_p = ptr_new(T1_map) + if arg_present(noisefree_images) then self.noisefree_images_p = ptr_new(noisefree_images) + + + ref_vfa_images_p = ptr_new(/allocate) + ref_timeseries_p = ptr_new(/allocate) + + print, 'Finished data readin' +end + +;------------------------------------------------------------------------------------------------------------------------ +pro DCEMRIprocessor_freeS0::cleanup + compile_opt idl2 + + ;freeing memory used for pointers + ; memory used for objetct is freed manually after the user has finished using the class + + if ptr_valid(self.DCE_timeseries_p) then ptr_free, self.DCE_timeseries_p + if ptr_valid(self.O_DCE_timeseries_p) then ptr_free, self.O_DCE_timeseries_p + if ptr_valid(self.O_vfa_images_p) then ptr_free, self.O_vfa_images_p + if ptr_valid(self.O_SR_images_p) then ptr_free, self.O_SR_images_p + if ptr_valid(self.ref_timeseries_p) then ptr_free, self.ref_timeseries_p + if ptr_valid(self.reg_timeseries_p) then ptr_free, self.reg_timeseries_p + if ptr_valid(self.ref_vfa_images_p) then ptr_free, self.ref_vfa_images_p + if ptr_valid(self.ref_IR_images_p) then ptr_free, self.ref_IR_images_p + if ptr_valid(self.ref_SR_images_p) then ptr_free, self.ref_SR_images_p + if ptr_valid(self.reg_vfa_images_p) then ptr_free, self.reg_vfa_images_p + if ptr_valid(self.reg_SR_images_p) then ptr_free, self.reg_SR_images_p + if ptr_valid(self.roi_mask_p) then ptr_free, self.roi_mask_p + ;if ptr_valid(self.roi_random_vox_mask_p) then ptr_free, self.roi_random_vox_mask_p + if ptr_valid(self.T1_map_p) then ptr_free, self.T1_map_p + if ptr_valid(self.vfa_images_p) then ptr_free, self.vfa_images_p + if ptr_valid(self.IR_images_p) then ptr_free, self.IR_images_p + if ptr_valid(self.SR_images_p) then ptr_free, self.SR_images_p + if ptr_valid(self.scan_params.timepoints_p) then ptr_free, self.scan_params.timepoints_p + if ptr_valid(self.noisefree_images_p) then ptr_free, self.noisefree_images_p + + print,'cleanup complete' + +end + +function DCEMRIprocessor_freeS0::Init + + compile_opt idl2 + + self.ref_vfa_images_p = ptr_new(/allocate) + self.ref_IR_images_p = ptr_new(/allocate) + self.ref_SR_images_p = ptr_new(/allocate) + self.ref_timeseries_p = ptr_new(/allocate) + self.reg_timeseries_p = ptr_new(/allocate) + self.reg_vfa_images_p = ptr_new(/allocate) + self.reg_SR_images_p = ptr_new(/allocate) + ;self.ROI_random_vox_mask_p = ptr_new(/allocate) + self.Est_maps_p = ptr_new(/allocate) + self.scan_params.alpha_vfa_p = ptr_new(/allocate) + self.noisefree_images_p = ptr_new(/allocate) + print,'init complete' + return,1 + +end + +;------------------------------------------------------------------------------------------------------------------------- + +pro DCEMRIprocessor_freeS0_define + + compile_opt idl2 + + + ; DCEMRIprocessor scan params structure + ; + void = {Scan_parameters, $ ; scan parameters structure key { + TR : 0.0, $ ; int ; + long_TR : 0.0, $ ; int ; + little_tr : 0.0, $ ; int ; + Inv_times_p :ptr_new(), $ + TE : 0.0, $ ; float + alpha_dyn : 0, $ ; float + alpha_vfa_p:ptr_new(), $; float array + alpha_IR : 0, $ + alpha_SR : 0, $ + row : 0, $ ; int + column : 0 , $ ; int + relaxivity: 0.0, $; float + n_timepoints: 0, $ + timepoints_p: ptr_new(), $ + temporal_resolution: 0.0, $ + n_slices: 0}; may need to change for different datasets + + + ;DCEMRIprocessor class structure : + + class = {DCEMRIprocessor_freeS0, $ + fit_type : '', $ ; A string containing the specified fitting technique + fit_method : '', $ ; A string containing the specified fit method + fit_domain : '', $ ; A string containing the specified fit_domain + scan_params: {scan_parameters}, $ ; A stucture of scan parameters - filled by calling the IDL variables containing the image data + DCE_timeseries_p: ptr_new() , $ ; saves memory for a pointer to reference DCE-MRI timeseiress + O_DCE_timeseries_p: ptr_new(), $ ; an array to hold the original DCE-MRI timeseries before any registration is performed + O_SR_timeseries_p: ptr_new(), $ ; an array to hold the original DCE-MRI timeseries before any registration is performed + ref_timeseries_p: ptr_new(), $ ; A blank array to store the modelled (reference) timeseries (for registration + bootstrapping purposes) + reg_timeseries_p: ptr_new(), $ + vfa_images_p : ptr_new() , $ ; a ptr to the flip angle array [FA1, FA2, FA3] if T1 map has + IR_images_p : ptr_new() , $ ; a ptr to the IR array [IR1, IR2, IR3,IR4,IR5] + SR_images_p : ptr_new() , $ ; a ptr to the SR array [IR1, IR2, IR3,IR4,IR5] + O_vfa_images_p:ptr_new(), $ + O_SR_images_p:ptr_new(), $ + ref_vfa_images_p: ptr_new(), $; A blank array to store the modelled (reference) fa images (for bootstrapping purposes only) + ref_IR_images_p: ptr_new(), $; A blank array to store the modelled (reference) fa images (for bootstrapping purposes only) + ref_SR_images_p: ptr_new(), $; A blank array to store the modelled (reference) fa images (for bootstrapping purposes only) + reg_vfa_images_p:ptr_new(), $ + reg_SR_images_p:ptr_new(), $ + ROI_mask_p: ptr_new() , $ ; a ptr to the ROI mask + noisefree_images_p: ptr_new() , $ ; noisefree + ;ROI_random_vox_mask_p: ptr_new() , $ + T1_map_p: ptr_new(), $ ; a ptr to the T1 map if single estimation is used + Est_maps_p: ptr_new(), $ + patient_filename : ''} + ; + +end + +;-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- + diff --git a/Joint Fitting/expconvolution.pro b/Joint Fitting/expconvolution.pro new file mode 100644 index 0000000..f692904 --- /dev/null +++ b/Joint Fitting/expconvolution.pro @@ -0,0 +1,27 @@ +function ExpConvolution, l, X + + n = n_elements(X)/2 + + T = X[0:n-1] ; T is the first half go the X array, i.e. the time points + + A = X[n:*] ; A is the second half of the X array i.e. the concentration values at each time point ; units of mM + + + DT = T[1:n-1]-T[0:n-2] ; This is an array of dt between time points + DA = A[1:n-1]-A[0:n-2] ; this is an array of da between conc values + + Z = l*DT ;Z is an array of K*dt + + E = exp(-Z); E is an array of exponentials [exp-lDT0, exp-lDT1 etc + E0 = 1-E ; E0 is an array [(1-exp-lDT0), (1-exp-lDT1) + E1 = Z-E0 + + Il = (A[0:n-2]*E0 + DA*E1/Z)/l + + Y = fltarr(n) ; Y is a double precision array with every element set to 0.0 + + for i=0L,n-2 do Y[i+1] = E[i]*Y[i] + Il[i] + + return, Y + +end diff --git a/Joint Fitting/flash_func.pro b/Joint Fitting/flash_func.pro new file mode 100644 index 0000000..a87f0e1 --- /dev/null +++ b/Joint Fitting/flash_func.pro @@ -0,0 +1,12 @@ +pro Flash_func,FA2,p,data + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + + T1 = p[1] + E0 = exp(-TR/T1) + S0 = p[0] + + data = S0*((sin(FA2)*(1-E0))/(1- cos(FA2)*E0)); FLASH EQUATION + +end \ No newline at end of file diff --git a/Joint Fitting/idlffanalyze__define.pro b/Joint Fitting/idlffanalyze__define.pro new file mode 100644 index 0000000..f4e1ccb --- /dev/null +++ b/Joint Fitting/idlffanalyze__define.pro @@ -0,0 +1,2458 @@ +; +; File: IDLffAnalyze__define.pro +; +; Defines the IDLffAnalyze object which can be used to read/write +; ANALYZE 7.5 format files. +; +; RTK, 23-Nov-2004 +; Last update: 09-Dec-2004 +; +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; +; +; Interprets Analyze 7.5 files as defined in "ANALYZE 7.5 File Format" PDF +; with (some) extensions for SPM99 and SPM2. +; +;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; + + +; +; Private: +; + +;----------------------------------------------------------- +; IDLffAnalyze::isNum +;+ +; Assert that a value is a number of a specific type and +; within a specific range. +; +; @returns True (1) if all assertions pass, (0) otherwise. +; +; @param n {in}{type=any} +; The number (or array) which will be tested. If an +; array, each element of the array must pass the test. +; +; @keyword POSITIVE {in}{type=boolean}{optional} +; Number must be positive (and not zero unless /ZERO also set) +; +; @keyword NEGATIVE {in}{type=boolean}{optional} +; Number must be negative (and not zero unless /ZERO also set) +; +; @keyword ZERO {in}{type=boolean}{optional} +; Number must be exactly zero or adds zero to the allowed range +; if /POSITIVE or /NEGATIVE set. +; +; @keyword LIMITS {in}{type=2-element vector}{optional} +; If present, represents the lower and upper limits allowed for n. +; If set, other keywords except TYPE are ignored. +; +; @keyword INTEGER {in}{type=boolean}{optional} +; If set input must be an integer (IDL types 1,2,3,12,13,14, or 15). +; +; @keyowrd FLOATING {in}{type=boolean}{optional} +; If set input must be floating point real (IDL types 4 and 5). +; +; @keyword TYPE {in}{type=integer}{optional} +; If present, also asserts that n is of the given IDL type. Overrides +; /INTEGER or /FLOATING. +; +;@private +;- +function IDLffAnalyze::isNum, n, POSITIVE=pos, NEGATIVE=neg, ZERO=zero, $ + LIMITS=lim, TYPE=type, INTEGER=integer, $ + FLOATING=floating + compile_opt idl2, HIDDEN + + ; + ; Assert that n is a number and of the proper type + ; + t = size(n, /TYPE) + + if where(t eq [0,7,8,10,11]) ne -1 then $ + return, 0 + + if n_elements(type) ne 0 then begin + if t ne type[0] then return, 0 + endif else begin + z = keyword_set(integer) + 2*keyword_set(floating) + case z of + 0: ; no other type keywords, ignore + 1: if (where(t eq [1,2,3,12,13,14,15]) eq -1) then return, 0 ; INTEGER + 2: if (t ne 4) and (t ne 5) then return, 0 ; FLOATING + 3: message, 'Incompatible keywords: /INTEGER and /FLOATING.' + endcase + endelse + + ; + ; Use limits or other keywords + ; + if ~keyword_set(lim) then begin + ; + ; Assert that n is positive, negative, or zero, etc. + ; + z = keyword_set(pos) + 2*keyword_set(neg) + 4*keyword_set(zero) + + case z of + 0: ; no keywords set, ignored + 1: if (min(n) le 0.0) then return, 0 ; positive only + 2: if (max(n) ge 0.0) then return, 0 ; negative only + 3: if (where(n eq 0.0) ne -1) then return, 0 ; pos or neg, anything but zero + 4: if (where(n ne 0.0) ne -1) then return, 0 ; zero only + 5: if (min(n) lt 0.0) then return, 0 ; pos or zero + 6: if (max(n) gt 0.0) then return, 0 ; neg or zero + 7: ; any value, ignore these keywords + endcase + + endif else begin + ; + ; Assert that all elements are in [lim[0], lim[1]] + ; + if (n_elements(lim) ne 2) then $ + message, 'LIMITS must be a two-element numeric vector.' + if (where(size(lim,/TYPE) eq [0,7,8,10,11]) ne -1) then $ + message, 'LIMITS must be a numeric vector.' + + lo = lim[0] + hi = lim[1] + if (lo ge hi) then $ + message, 'LIMITS must be of the form [lo,hi] with lo > hi.' + + if (min(n) lt lo) or (max(n) gt hi) then $ + return, 0 + endelse + + ; All assertions pass + return, 1 +end + + +;----------------------------------------------------------- +; IDLffAnalyze::Swap +;+ +; @param n {in}{type=numeric} The value to be byte swapped. +; +;@private +;- +pro IDLffAnalyze::Swap, n + compile_opt idl2, HIDDEN + + case size(n,/TYPE) of + 2: byteorder, n, /SSWAP ; short + 3: byteorder, n, /LSWAP ; long + 4: byteorder, n, /LSWAP ; float + 5: byteorder, n, /L64SWAP ; double + 6: byteorder, n, /L64SWAP ; complex + ELSE: ; nothing, leave as is + endcase +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SwapHeader +;+ +; Byte swap a HEADER structure. +; +; @param h {in}{type=HEADER structure} +; The structure to byte swap. +; +;@private +;- +pro IDLffAnalyze::SwapHeader, h + compile_opt idl2, HIDDEN + + ; Must be a header structure + if (size(h,/TYPE) ne 8) then $ + message, 'Argument must be a HEADER structure.' + if (size(h,/SNAME) ne 'HEADER') then $ + message, 'Argument must be a HEADER structure.' + + ; + ; Only swap numeric values, type determines how it is swapped. + ; + q = h.sizeof_hdr & self->Swap,q & h.sizeof_hdr = q ; int sizeof_hdr; + q = h.extents & self->Swap,q & h.extents = q ; int extents; + q = h.session_error & self->Swap,q & h.session_error = q ; short int session_error; + q = h.dim & self->Swap,q & h.dim = q ; short int dim[8]; + q = h.unused1 & self->Swap,q & h.unused1 = q ; short int unused1; + q = h.datatype & self->Swap,q & h.datatype = q ; short int datatype; + q = h.bitpix & self->Swap,q & h.bitpix = q ; short int bitpix; + q = h.dim_un0 & self->Swap,q & h.dim_un0 = q ; short int dim_un0; + q = h.pixdim & self->Swap,q & h.pixdim = q ; float pixdim[8]; + q = h.vox_offset & self->Swap,q & h.vox_offset = q ; float vox_offset; + q = h.roi_scale & self->Swap,q & h.roi_scale = q ; float roi_scale; + q = h.funused1 & self->Swap,q & h.funused1 = q ; float funused1; // scalefactor in SPM + q = h.funused2 & self->Swap,q & h.funused2 = q ; float funused2; // dcoff in SPM2 + q = h.cal_max & self->Swap,q & h.cal_max = q ; float cal_max; + q = h.cal_min & self->Swap,q & h.cal_min = q ; float cal_min; + q = h.compressed & self->Swap,q & h.compressed = q ; int compressed; + q = h.verified & self->Swap,q & h.verified = q ; int verified; + q = h.glmax & self->Swap,q & h.glmax = q ; int glmax; + q = h.glmin & self->Swap,q & h.glmin = q ; int glmin; + q = h.orient & self->Swap,q & h.orient = q ; char orient; + q = h.views & self->Swap,q & h.views = q ; int views; + q = h.vols_added & self->Swap,q & h.vols_added = q ; int vols_added; + q = h.start_field & self->Swap,q & h.start_field = q ; int start_field; + q = h.field_skip & self->Swap,q & h.field_skip = q ; int field_skip; + q = h.omax & self->Swap,q & h.omax = q ; int omax; + q = h.omin & self->Swap,q & h.omin = q ; int omin; + q = h.smax & self->Swap,q & h.smax = q ; int smax; + q = h.smin & self->Swap,q & h.smin = q ; int smin; + + ; + ; Originator is a special case. Swap as if it were being used by + ; SPM since it appears that little else actually uses this field. + ; + ; char originator[10]; // image_origin in SPM + ; + w = h.originator + t = w[0] & w[0] = w[1] & w[1] = t + t = w[2] & w[2] = w[3] & w[3] = t + t = w[4] & w[4] = w[5] & w[5] = t + h.originator = w +end + + +;----------------------------------------------------------- +; IDLffAnalyze::IDLtoAnalyzeType +;+ +; @returns The Analyze type for a given IDL type, -1 if +; Analyze does not support the IDL type. +; +; @param itype {in}{type=integer} +; The IDL type code. +; +;@private +;- +function IDLffAnalyze::IDLtoAnalyzeType, itype + compile_opt idl2, HIDDEN + + idx = where(itype eq indgen(16)) + return, ([0,2,4,8,16,64,32,-1,-1,-1,-1,-1,-1,-1,-1,-1])[idx[0]] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::AnalyzetoIDLType +;+ +; @returns The IDL type for a given Analyze type. +; +; @param atype {in}{type=integer} +; The Analyze type code. +; +;@private +;- +function IDLffAnalyze::AnalyzetoIDLType, atype + compile_opt idl2, HIDDEN + + idx = (where(atype eq [0,1,2,4,8,16,64,32]))[0] + return, ([0,0,1,2,3,4,5,6])[idx] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::IDLtoAnalyzeBitPix +;+ +; @returns The Analyze bits per pixel for a given IDL type, -1 if +; Analyze does not support the IDL type. +; +; @param itype {in}{type=integer} +; The IDL type code. +; +;@private +;- +function IDLffAnalyze::IDLtoAnalyzeBitPix, itype + compile_opt idl2, HIDDEN + + idx = where(itype eq indgen(16)) + return, ([0,8,16,32,32,64,64,-1,-1,-1,-1,-1,-1,-1,-1,-1])[idx[0]] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SystemByteOrder +;+ +; @returns True (1) if the system is big-endian, false (0) +; if the system is little-endian. +; +;@private +;- +function IDLffAnalyze::SystemByteOrder + compile_opt HIDDEN + + b = (a=123) + byteorder, a, /SWAP_IF_LITTLE_ENDIAN + return, (b ne a) ? 0 : 1 +end + + +;----------------------------------------------------------- +; IDLffAnalyze::Destroy +;+ +; Free memory used by this object. +; +;@private +;- +pro IDLffAnalyze::Destroy + compile_opt idl2, HIDDEN + + ; remove any image data + if ptr_valid(self.imgdata) then ptr_free, self.imgdata +end + + +; +; These functions (superficially) validate property assignments: +; + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateAll +;+ +; This is a dangerous function. *No* checking whatsoever +; is performed for consistent values. +; +; @param all {in}{type=header struct} Structure containing +; the entire Analyze header. +; +;@private +;- +pro IDLffAnalyze::UpdateAll, all + compile_opt idl2, HIDDEN + + ; Must be a header structure + if (size(all,/SNAME) ne 'HEADER') then $ + message, 'ALL must be a header structure.' + + self.hdr = all +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateDim +;+ +; @param dim {in}{type=vector} Dimension vector. +; +;@private +;- +pro IDLffAnalyze::UpdateDim, dim + compile_opt idl2, HIDDEN + + ; Must be integer + if (~self->isNum(dim, /INTEGER)) then $ + message, 'DIM must be integer.' + if (n_elements(dim) ne 8) then $ + message, 'DIM must be an 8 element vector.' + + self.hdr.dim = dim +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateGlmin +;+ +; @param glmin {in}{type=int32} Minimum pixel value for entire file. +; +;@private +;- +pro IDLffAnalyze::UpdateGlmin, glmin + compile_opt idl2, HIDDEN + + ; Must be an integer + if (~self->isNum(glmin, /INTEGER)) then $ + message, 'GLMIN must be an integer.' + if (n_elements(glmin) ne 1) then $ + message, 'GLMIN must be a scalar.' + + self.hdr.glmin = glmin ; IDL converts to LONG if necessary + ; w/o warning if precision is lost. +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateGlmax +;+ +; @param glmax {in}{type=int32} Maximum pixel value for entire file. +; +;@private +;- +pro IDLffAnalyze::UpdateGlmax, glmax + compile_opt idl2, HIDDEN + + ; Must be an integer + if (~self->isNum(glmax, /INTEGER)) then $ + message, 'GLMAX must be an integer.' + if (n_elements(glmax) ne 1) then $ + message, 'GLMAX must be a scalar.' + + self.hdr.glmax = glmax +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdatePixdim +;+ +; @param pixdim {in}{type=vector} Pixel dimensions vector. +; +;@private +;- +pro IDLffAnalyze::UpdatePixdim, pixdim + compile_opt idl2, HIDDEN + + ; Must be floating point + if (~self->isNum(pixdim, /FLOATING)) then $ + message, 'PIXDIM must be a 32-bit float.' + if (n_elements(pixdim) ne 8) then $ + message, 'PIXDIM must be an 8 element vector.' + + ; Assign w/o regard for meaningfulness + self.hdr.pixdim = pixdim +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateVoxUnits +;+ +; @param vox_units {in}{type=character*4} Spatial voxel units of measure. +; +;@private +;- +pro IDLffAnalyze::UpdateVoxUnits, vox_units + compile_opt idl2, HIDDEN + + ; Must be a single string + if (size(vox_units,/TYPE) ne 7) then $ + message, 'VOX_UNITS must be a string.' + if (n_elements(vox_units) ne 1) then $ + message, 'VOX_UNITS must be a single string.' + + ; Chop if too long + if (strlen(vox_units) le 4) then begin + self.hdr.vox_units = byte(' ') + self.hdr.vox_units = byte(vox_units) + endif else begin + self.hdr.vox_units = byte(strmid(vox_units,0,4)) + endelse +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateCalUnits +;+ +; Mindlessly chops input that is too long and adds trailing +; spaces to input that is too short. +; +; @param cal_units {in}{type=character*8} Calibration units. +; +;@private +;- +pro IDLffAnalyze::UpdateCalUnits, cal_units + compile_opt idl2, HIDDEN + + ; Must be a single string + if (size(cal_units,/TYPE) ne 7) then $ + message, 'CAL_UNITS must be a string.' + if (n_elements(cal_units) ne 1) then $ + message, 'CAL_UNITS must be a single string.' + + ; Chop if too long + if (strlen(cal_units) le 8) then begin + self.hdr.cal_units = byte(' ') + self.hdr.cal_units = byte(cal_units) + endif else begin + self.hdr.cal_units = byte(strmid(cal_units,0,8)) + endelse +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateDatatype +;+ +; N.B. This function expects the Analyze datatype codes, not +; IDL datatype codes. See self->DT_XXX() functions. +; +; @param datatype {in}{type=int16} Data type code for image pixels. +; +;@private +;- +pro IDLffAnalyze::UpdateDatatype, datatype + compile_opt idl2, HIDDEN + + ; Must be numeric and scalar + if (~self->isNum(datatype, /POSITIVE)) then $ + message, 'DATATYPE must be numeric.' + if (n_elements(datatype) ne 1) then $ + message, 'DATATYPE must be a scalar.' + + ; Must also be a valid code + if (where(datatype eq [0,1,2,4,8,16,32,64,128,255]) eq -1) then $ + message, 'DATATYPE must be a valid Analyze 7.5 datatype code.' + + self.hdr.datatype = datatype +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateBitpix +;+ +; @param bitpix {in}{type=int16} Bits per pixel. +; +;@private +;- +pro IDLffAnalyze::UpdateBitpix, bitpix + compile_opt idl2, HIDDEN + + ; Must be numeric and scalar + if (~self->isNum(bitpix, /POSITIVE)) then $ + message, 'BITPIX must be numeric.' + if (n_elements(bitpix) ne 1) then $ + message, 'BITPIX must be a scalar.' + + ; Must also be 1, 8, 16, 32, or 64 + if (where(bitpix eq [1,8,16,32,64]) eq -1) then $ + message, 'BITPIX must be 1, 8, 16, 32, or 64.' + + self.hdr.bitpix = bitpix +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateVoxOffset +;+ +; @param vox_offset {in}{type=float32} Offset, in bytes, +; to the start of voxel data in the .img file. +; +;@private +;- +pro IDLffAnalyze::UpdateVoxOffset, vox_offset + compile_opt idl2, HIDDEN + + ; Must be a positive or zero integer scalar + if (~self->isNum(vox_offset, /POS, /ZERO)) then $ + message, 'VOX_OFFSET must be a number >= 0.' + if (n_elements(vox_offset) ne 1) then $ + message, 'VOX_OFFSET must be a scalar.' + + self.hdr.vox_offset = vox_offset +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateCalMin +;+ +; @param cal_min {in}{type=float32} Minimum calibration value. +; +;@private +;- +pro IDLffAnalyze::UpdateCalMin, cal_min + compile_opt idl2, HIDDEN + + ; Must be a scalar number + if (~self->isNum(cal_min)) then $ + message, 'CAL_MIN must be a number.' + if (n_elements(cal_min) ne 1) then $ + message, 'CAL_MIN must be a scalar.' + + self.hdr.cal_min = cal_min +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateCalMax +;+ +; @param cal_max {in}{type=float32} Maximum calibration value. +; +;@private +;- +pro IDLffAnalyze::UpdateCalMax, cal_max + compile_opt idl2, HIDDEN + + ; Must be a scalar number + if (~self->isNum(cal_max)) then $ + message, 'CAL_MAX must be a number.' + if (n_elements(cal_max) ne 1) then $ + message, 'CAL_MAX must be a scalar.' + + self.hdr.cal_max = cal_max +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateOrient +;+ +; +; N.B. This is the primitive approach to updating the +; orientation parameter. It simply checks for values +; in range and mindlessly sets the value given. +; +; Use IDLffAnalyze::SetOrientation instead unless one is very +; certain of what he is doing. +; +; @param orient {in}{type=byte} Slice orientation indicator. +; +;@private +;- +pro IDLffAnalyze::UpdateOrient, orient + compile_opt idl2, HIDDEN + + ; Must be an integer scalar + if (~self->isNum(orient, /INTEGER)) then $ + message, 'ORIENT must be an integer.' + if (n_elements(orient) ne 1) then $ + message, 'ORIENT must be a scalar.' + + self.hdr.orient = orient +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateScaleFactor +;+ +; @param scal {in}{type=float32} Pixel scale factor (SPM2, SPM99) +; +;@private +;- +pro IDLffAnalyze::UpdateScaleFactor, scal + compile_opt idl2, HIDDEN + + ; Must be a numeric scalar + if (~self->isNum(scal)) then $ + message, 'SCALEFACTOR must be numeric.' + if (n_elements(scal) ne 1) then $ + message, 'SCALEFACTOR must be a scalar.' + + self.hdr.funused1 = scal ; IDL will not change the type of funused1 +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateDCoff +;+ +; @param dcoff {in}{type=float32} Image intensity zero intercept. (SPM2) +; +;@private +;- +pro IDLffAnalyze::UpdateDCoff, dcoff + compile_opt idl2, HIDDEN + + ; Must be a numeric scalar + if (~self->isNum(dcoff)) then $ + message, 'DC offset must be numeric.' + if (n_elements(dcoff) ne 1) then $ + message, 'DC offset must be a scalar' + + self.hdr.funused2 = dcoff +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateImageOrigin +;+ +; @param im {in}{type=int16 vector} Image origin (SPM2, SPM99) +; +;@private +;- +pro IDLffAnalyze::UpdateImageOrigin, im + compile_opt idl2, HIDDEN + + ; Must be numeric and of three elements + if (~self->isNum(im, TYPE=2)) then $ + message, 'IMAGE_ORIGIN must be a short integer vector.' + if (n_elements(im) ne 3) then $ + message, 'IMAGE_ORIGIN must be a three element vector.' + + ; + ; Since image_origin is overlayed on originator (10 element, char) + ; the values have to be assigned manually according with the + ; proper endian-ness. + ; + w = self.hdr.originator + if (self.endian eq 1) then begin + w[0] = byte(im[0]/256) & w[1] = byte(im[0] mod 256) ; big-endian + w[2] = byte(im[1]/256) & w[3] = byte(im[1] mod 256) + w[4] = byte(im[2]/256) & w[5] = byte(im[2] mod 256) + endif else begin + w[1] = byte(im[0]/256) & w[0] = byte(im[0] mod 256) ; little-endian + w[3] = byte(im[1]/256) & w[2] = byte(im[1] mod 256) + w[5] = byte(im[2]/256) & w[4] = byte(im[2] mod 256) + endelse + self.hdr.originator = w +end + + +;----------------------------------------------------------- +; IDLffAnalyze::UpdateEndian +;+ +; @param endian {in}{type=integer} Endian, 1 (big), 0 (little). +; +;@private +;- +pro IDLffAnalyze::UpdateEndian, endian + compile_opt idl2, HIDDEN + + ; Must be 0 or 1 + if (~self->isNum(endian, /INTEGER, LIMITS=[0,1])) then $ + message, 'ENDIAN must be 0 (little) or 1 (big).' + + self.endian = endian +end + + +;---------------------------------------------------------- +; IDLffAnalyze::ReadTRSImageFile +;+ +; @returns The properly read and byte swapped image data +; for the given pathname. +; +; @param f {in}{type=string} +; Pathname for the image file (.img). +; +; @param h {in}{type=instance of HEADER structure} +; The header values for this file. +; +; @param endian {in}{type=boolean} +; File byte order, 1=big, 0=little. +; +; @keyword FLIP {in}{type=boolean}{optional} +; If set, flip the proper axis of the image data. +; +;@private +;- +function IDLffAnalyze::ReadTRSImageFile, f, h, endian, FLIP=flip + compile_opt idl2, HIDDEN + + ; Create the image data array of the proper type + ans = make_array(h.dim[1:4], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; Ready the file + openr, u, f, /GET_LUN + pix = make_array(h.dim[1], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; + ; Read the file + ; + if (~keyword_set(flip)) then begin + for v = 0, h.dim[4]-1 do begin ; normal + for z = 0, h.dim[3]-1 do begin + for y = 0, h.dim[2]-1 do begin + readu, u, pix + ans[*,y,z,v] = pix + endfor + endfor + endfor + endif else begin + for v = 0, h.dim[4]-1 do begin ; flipped + for z = 0, h.dim[3]-1 do begin + for y = h.dim[2]-1,0,-1 do begin + readu, u, pix + ans[*,y,z,v] = pix + endfor + endfor + endfor + endelse + + free_lun, u + + ; change endian if necessary + if (endian ne self->SystemByteOrder()) then $ + self->Swap, ans + + return, ans +end + + +;---------------------------------------------------------- +; IDLffAnalyze::ReadCORImageFile +;+ +; @returns The properly read and byte swapped image data +; for the given pathname. +; +; @param f {in}{type=string} +; Pathname for the image file (.img). +; +; @param h {in}{type=instance of HEADER structure} +; The header values for this file. +; +; @param endian {in}{type=boolean} +; File byte order, 1=big, 0=little. +; +; @keyword FLIP {in}{type=boolean}{optional} +; If set, flip the proper axis of the image data. +; +;@private +;- +function IDLffAnalyze::ReadCORImageFile, f, h, endian, FLIP=flip + compile_opt idl2, HIDDEN + + ; Create the image data array of the proper type + ans = make_array(h.dim[1], h.dim[3], h.dim[2], h.dim[4], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; Ready the file + openr, u, f, /GET_LUN + pix = make_array(h.dim[1], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; + ; Read the file + ; + if (~keyword_set(flip)) then begin + for v = 0, h.dim[4]-1 do begin ; normal + for y = 0, h.dim[3]-1 do begin + for z = 0, h.dim[2]-1 do begin + readu, u, pix + ans[*,y,z,v] = pix + endfor + endfor + endfor + endif else begin + for v = 0, h.dim[4]-1 do begin ; flipped + for y = 0, h.dim[3]-1 do begin + for z = h.dim[2]-1,0,-1 do begin + readu, u, pix + ans[*,y,z,v] = pix + endfor + endfor + endfor + endelse + + free_lun, u + + ; change endian if necessary + if (endian ne self->SystemByteOrder()) then $ + self->Swap, ans + + return, ans +end + + +;---------------------------------------------------------- +; IDLffAnalyze::ReadSAGImageFile +;+ +; @returns The properly read and byte swapped image data +; for the given pathname. +; +; @param f {in}{type=string} +; Pathname for the image file (.img). +; +; @param h {in}{type=instance of HEADER structure} +; The header values for this file. +; +; @param endian {in}{type=boolean} +; File byte order, 1=big, 0=little. +; +; @keyword FLIP {in}{type=boolean}{optional} +; If set, flip the proper axis of the image data. +; +;@private +;- +function IDLffAnalyze::ReadSAGImageFile, f, h, endian, FLIP=flip + compile_opt idl2, HIDDEN + + ; Create the image data array of the proper type + ans = make_array(h.dim[3], h.dim[1], h.dim[2], h.dim[4], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; Ready the file + openr, u, f, /GET_LUN + pix = make_array(h.dim[1], TYPE=self->AnalyzetoIDLType(h.datatype)) + + ; + ; Read the file + ; + if (~keyword_set(flip)) then begin + for v = 0, h.dim[4]-1 do begin ; normal + for x = 0, h.dim[3]-1 do begin + for z = 0, h.dim[2]-1 do begin + readu, u, pix + ans[x,*,z,v] = pix + endfor + endfor + endfor + endif else begin + for v = 0, h.dim[4]-1 do begin ; flipped + for x = 0, h.dim[3]-1 do begin + for z = h.dim[2]-1,0,-1 do begin + readu, u, pix + ans[x,*,z,v] = pix + endfor + endfor + endfor + endelse + + free_lun, u + + ; change endian if necessary + if (endian ne self->SystemByteOrder()) then $ + self->Swap, ans + + return, ans +end + + +;---------------------------------------------------------- +; IDLffAnalyze::ReadImageFile +;+ +; @returns The image data for the given file. +; +; @param f {in}{type=string} +; The pathname of the image file. +; +; @param h {in}{type=HEADER structure} +; The header file structure associated with this image data. +; +; @param orient {in}{type=integer} +; Orientation to use when reading the file. +; +; @keyword ENDIAN {in}{type=integer} +; Byte order of the image data. +; +;@private +;- +function IDLffAnalyze::ReadImageFile, f, h, orient, ENDIAN=endian + compile_opt idl2, HIDDEN + + ; + ; Add a .img extension if not already present. + ; + if (strmatch(f,'*.IMG',/FOLD_CASE) eq 1) then begin + fname = f ; already ends in .img + endif else begin + if (strmatch(f,'*.HDR',/FOLD_CASE) eq 1) then begin + fname = strmid(f,0,strlen(f)-4) + '.img' + endif else begin + fname = f + '.img' + endelse + endelse + + ; Verify that there is a data file to read. + if (~file_test(fname,/READ)) then $ + message, 'Unable to read file ['+fname+']' + + ; Check for invalid dimension values + if (h.dim[0] ne 4) then h.dim[0] = 4 ; always 4D + if (h.dim[3] eq 0) then h.dim[3] = 1 ; with one slice + if (h.dim[4] eq 0) then h.dim[4] = 1 ; and one volume + if (h.dim[1] eq 0) then message, 'Invalid header file used, cols == 0.' + if (h.dim[2] eq 0) then message, 'Invalid header file used, rows == 0.' + + ; Load according to given orientation + q = h.dim[1:3] + case orient of + 0: ans = self->ReadTRSImageFile(fname, h, endian) + 1: BEGIN + ans = self->ReadCORImageFile(fname, h, endian) + h.dim[2:3] = [q[2],q[1]] + END + 2: BEGIN + ans = self->ReadSAGImageFile(fname, h, endian) + h.dim[1:3] = [q[2],q[0],q[1]] + END + ; + ; Rare formats: + ; + 3: ans = self->ReadTRSImageFile(fname, h, endian, /FLIP) + 4: ans = self->ReadCORImageFile(fname, h, endian, /FLIP) + 5: ans = self->ReadSAGImageFile(fname, h, endian, /FLIP) + ELSE: message, 'ORIENT has an illegal value.' + endcase + + ; Return image data + return, ans +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteSagittalFlipFile +;+ +; Write the data to a single file in sagittal flipped order. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteSagittalFlipFile, f + compile_opt idl2, HIDDEN + + ; + ; Need this before bytes get swapped + ; + xmax = self.hdr.dim[1] + nvol = self.hdr.dim[4] + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata ; and data itself + swapped = 1 + endif + + ; + ; XYZ for dim and pixdim reflect how the data is + ; stored, therefore, these need to be adjusted as well: + ; XYZ -> YZX + ; + orig = self.hdr.dim[1:3] + porig= self.hdr.pixdim[1:3] + self.hdr.dim[1:3] = self.hdr.dim[[2,3,1]] + self.hdr.pixdim[1:3] = self.hdr.pixdim[[2,3,1]] + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + + for v=0, nvol-1 do begin + for x = 0, xmax-1 do begin + w = reverse(reform((*self.imgdata)[x,*,*,v]),2) + writeu, u, w + endfor + endfor + + free_lun, u + + ; + ; Re-arrange the dim and pixdim vectors + ; + self.hdr.dim[1:3] = orig + self.hdr.pixdim[1:3] = porig + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteCoronalFlipFile +;+ +; Write the data to a single file in coronal flipped order. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteCoronalFlipFile, f + compile_opt idl2, HIDDEN + + ; + ; Need this before bytes get swapped + ; + ymax = self.hdr.dim[2] + nvol = self.hdr.dim[4] + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + swapped = 1 + endif + + ; + ; XYZ for dim and pixdim reflect how the data is + ; stored, therefore, these need to be adjusted as well: + ; XYZ -> XZY + ; + self.hdr.dim[2:3] = self.hdr.dim[[3,2]] + self.hdr.pixdim[2:3] = self.hdr.pixdim[[3,2]] + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + + for v=0, nvol-1 do begin + for y = 0, ymax-1 do begin + w = reverse(reform((*self.imgdata)[*,y,*,v]),2) + writeu, u, w + endfor + endfor + + free_lun, u + + ; + ; Re-arrange the dim and pixdim vectors + ; + self.hdr.dim[2:3] = self.hdr.dim[[3,2]] + self.hdr.pixdim[2:3] = self.hdr.pixdim[[3,2]] + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteTransverseFlipFile +;+ +; Write the data to a single file in transverse flipped order. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteTransverseFlipFile, f + compile_opt idl2, HIDDEN + + ; + ; Get limit prior to any byte swap + ; + zmax = self.hdr.dim[3] + nvol = self.hdr.dim[4] + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + swapped = 1 + endif + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + + ; Output images with Y (rows) flipped + for v=0, nvol-1 do begin + for z = 0, zmax-1 do begin + w = reverse(reform((*self.imgdata)[*,*,z,v]),2) + writeu, u, w + endfor + endfor + + free_lun, u + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteSagittalFile +;+ +; Write the data to a single file in sagittal order. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteSagittalFile, f + compile_opt idl2, HIDDEN + + ; + ; Need this before bytes get swapped + ; + xmax = self.hdr.dim[1] + nvol = self.hdr.dim[4] + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + swapped = 1 + endif + + ; + ; XYZ for dim and pixdim reflect how the data is + ; stored, therefore, these need to be adjusted as well: + ; XYZ -> YZX + ; + orig = self.hdr.dim[1:3] + porig= self.hdr.pixdim[1:3] + self.hdr.dim[1:3] = self.hdr.dim[[2,3,1]] + self.hdr.pixdim[1:3] = self.hdr.pixdim[[2,3,1]] + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + + for v=0, nvol-1 do begin + for x = 0, xmax-1 do begin + w = reform((*self.imgdata)[x,*,*,v]) + writeu, u, w + endfor + endfor + + free_lun, u + + ; + ; Re-arrange the dim and pixdim vectors + ; + self.hdr.dim[1:3] = orig + self.hdr.pixdim[1:3] = porig + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteCoronalFile +;+ +; Write the data to a single file in coronal order. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteCoronalFile, f + compile_opt idl2, HIDDEN + + ; + ; Need this before bytes get swapped + ; + ymax = self.hdr.dim[2] + nvol = self.hdr.dim[4] + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + swapped = 1 + endif + + ; + ; XYZ for dim and pixdim reflect how the data is + ; stored, therefore, these need to be adjusted as well: + ; XYZ -> XZY + ; + self.hdr.dim[2:3] = self.hdr.dim[[3,2]] + self.hdr.pixdim[2:3] = self.hdr.pixdim[[3,2]] + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + + for v = 0, nvol-1 do begin + for y = 0, ymax-1 do begin + w = reform((*self.imgdata)[*,y,*,v]) + writeu, u, w + endfor + endfor + + free_lun, u + + ; + ; Re-arrange the dim and pixdim vectors + ; + self.hdr.dim[2:3] = self.hdr.dim[[3,2]] + self.hdr.pixdim[2:3] = self.hdr.pixdim[[3,2]] + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteTransverseFile +;+ +; Write the data to a single file in transverse order. +; This is the fastest since the data is already stored +; this way. +; +; @param f {in}{type=string} Output base name. +; +;@private +;- +pro IDLffAnalyze::WriteTransverseFile, f + compile_opt idl2, HIDDEN + + ; + ; Swap bytes if necessary + ; + swapped = 0 + if (self.endian ne self->SystemByteOrder()) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + swapped = 1 + endif + + ; Header + openw, u, f+'.hdr', /GET_LUN + writeu, u, self.hdr + free_lun, u + + ; Image data + openw, u, f+'.img', /GET_LUN + writeu, u, *self.imgdata + free_lun, u + + ; + ; Swap back, if necessary + ; + if (swapped eq 1) then begin + h = self.hdr + self->SwapHeader, h + self.hdr = h + self->Swap, *self.imgdata + endif +end + + +;---------------------------------------------------------- +; IDLffAnalyze::WriteSingleFile +;+ +; Output the current data as a single Analyze file using +; orient to properly orient the data. +; +; @param f {in}{type=string} Output pathname. +; +;@private +;- +pro IDLffAnalyze::WriteSingleFile, f + compile_opt idl2, HIDDEN + + ; + ; Respond to the orient field + ; + case self.hdr.orient of + 0: self->WriteTransverseFile, f + 1: self->WriteCoronalFile, f + 2: self->WriteSagittalFile, f + ; + ; These are rare, probably shouldn't be supported: + ; + 3: self->WriteTransverseFlipFile, f + 4: self->WriteCoronalFlipFile, f + 5: self->WriteSagittalFlipFile, f + ELSE: message, 'ORIENT has an invalid value.' + endcase +end + + +;----------------------------------------------------------- +; IDLffAnalyze::WriteMultipleFiles +;+ +; Output the current data as a series of individual image +; files. This is always done in transverse order (ie, as +; a set of transverse images) regardless of the value of +; orient in the header. +; +; @param f {in}{type=string} Output base file name. +; +;@private +;- +pro IDLffAnalyze::WriteMultipleFiles, f + compile_opt idl2, HIDDEN + + ; Set up for byte swapping + swap = 0 + if (self.endian ne self->SystemByteOrder()) then $ + swap = 1 + + ; + ; Loop through all axial slices outputing + ; each to a new pair of files (.hdr, .img) + ; with a header that reflects the updated + ; dimensions and proper byte swapping applied. + ; + nvol = self.hdr.dim[4] + for vol=0, nvol-1 do begin + for slice=0, self.hdr.dim[3]-1 do begin + ; + ; Get the image data and construct an appropriate header + ; + img = reform((*self.imgdata)[*,*,slice,vol]) + h = {header} + h.sizeof_hdr = long(348) + h.extents = long(16384) + h.regular = byte('r') + h.dim = self.hdr.dim + h.dim[3:4] = [1,1] ; one slice, one volume + h.pixdim[3:4] = [0.,0.] + h.orient = 0 + h.glmin = min(img) + h.glmax = max(img) + h.bitpix= self.hdr.bitpix + h.datatype = self.hdr.datatype$ + bname = (nvol eq 1) ? f+strtrim(string(slice, format='(I04)'),2) $ + : f+strtrim(string(vol),2)+'_'+strtrim(string(slice, format='(I04)'),2) + hname = bname+'.hdr' + iname = bname+'.img' + + ; + ; Swap if necessary + ; + if (swap eq 1) then begin + self->SwapHeader, h + self->Swap, img + endif + + ; + ; Write the header and image data + ; + openw, u, hname, /GET_LUN + writeu, u, h + free_lun, u + + openw, u, iname, /GET_LUN + writeu, u, img + free_lun, u + endfor + endfor +end + + + +; +; Public: +; + +;----------------------------------------------------------- +; IDLffAnalyze::GetProperty +;+ +; +;- +pro IDLffAnalyze::GetProperty, $ + ALL=all, DIM=dim, GLMIN=glmin, GLMAX=glmax, PIXDIM=pixdim, $ + VOX_UNITS=vox_units, CAL_UNITS=cal_units, DATATYPE=datatype, $ + BITPIX=bitpix, VOX_OFFSET=vox_offset, CAL_MIN=cal_min, $ + CAL_MAX=cal_max, ORIENT=orient, SCALEFACTOR=scalefactor, $ + IMAGE_ORIGIN=image_origin, ENDIAN=endian, DCOFF=dcoff + compile_opt idl2 + + if arg_present(endian) then endian= self.endian + if arg_present(all) then all= self.hdr + if arg_present(dim) then dim= self.hdr.dim + if arg_present(glmin) then glmin= self.hdr.glmin + if arg_present(glmax) then glmax= self.hdr.glmax + if arg_present(pixdim) then pixdim= self.hdr.pixdim + if arg_present(vox_units) then vox_units= self.hdr.vox_units + if arg_present(cal_units) then cal_units= self.hdr.cal_units + if arg_present(datatype) then datatype= self.hdr.datatype + if arg_present(bitpix) then bitpix= self.hdr.bitpix + if arg_present(vox_offset) then vox_offset= self.hdr.vox_offset + if arg_present(cal_min) then cal_min= self.hdr.cal_min + if arg_present(cal_max) then cal_max= self.hdr.cal_max + if arg_present(orient) then orient= self.hdr.orient + if arg_present(scalefactor) then scalefactor= self.hdr.funused1 + if arg_present(dcoff) then dcoff= self.hdr.funused2 + if arg_present(image_origin) then begin + w = self.hdr.originator + if (endian eq 1) then begin + image_origin = [fix(256*w[0]+w[1]), $ ; big-endian + fix(256*w[2]+w[3]), $ + fix(256*w[4]+w[5])] + endif else begin + image_origin = [fix(256*w[1]+w[0]), $ ; little-endian + fix(256*w[3]+w[2]), $ + fix(256*w[5]+w[4])] + endelse + endif +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetNCols +;+ +; @returns The number of pixel columns. +;- +function IDLffAnalyze::GetNCols + compile_opt idl2 + return, self.hdr.dim[1] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetNRows +;+ +; @returns The number of pixel rows. +;- +function IDLffAnalyze::GetNRows + compile_opt idl2 + return, self.hdr.dim[2] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetNSlices +;+ +; @returns The number of slices. +;- +function IDLffAnalyze::GetNSlices + compile_opt idl2 + return, self.hdr.dim[3] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetNVolumes +;+ +; @returns The number of volumes or time-points. +;- +function IDLffAnalyze::GetNVolumes + compile_opt idl2 + return, self.hdr.dim[4] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetOrientation +;+ +; Return the orientation field value as a string and/or +; a number. The orientation string maps XYZ axes, which are +; always in radiological, left-handed order (ala Analyze) to +; the final direction of the axis. For example, normal axial +; (TRS) images, in radiological order, follow this pattern: +; +; XYZ -> R-L, P-A, I-S, "LAS" which means that X runs from +; (patient) right to left, posterior to anterior (back to front) +; and inferior to superior (feet to head) if the patient is in +; a supine position (on his back, face up). +; +; Orient is used to properly place the data read from the file into +; memory or when the file is written to disk. +; +; A "-" in front of the returned order string means "flipped". +; These are rare in the wild and not recommended for use. +; +; @keyword TEXT {in}{type=boolean}{optional} +; If set, return the orientation as a string, not a number. +;- +function IDLffAnalyze::GetOrientation, TEXT=text + compile_opt idl2 + + if ~keyword_set(text) then begin + return, self.hdr.orient + endif else begin + return, (["TRS","COR","SAG","-TRS","-COR","-SAG"])[self.hdr.orient] + endelse +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetVoxelDims +;+ +; Get the pixdim dimensions. These are the actual physical +; dimensions in mm or ms (assumed units). Provides a +; shortcut to GetProperty, PIXDIM=p and removes the need to +; remember which elements go with which label. +; +; @keyword VOXEL_WIDTH {out}{type=double}{optional} +; If present, the voxel width (along readout, for example). +; +; @keyword VOXEL_HEIGHT {out}{type=double}{optional} +; The voxel height (eg, along phase axis) in mm (assumed). +; +; @keyword SLICE_THICKNESS {out}{type=double}{optional} +; Slice thickness (as opposed to slice spacing) in mm (assumed). +; +; @keyword TIME_POINTS {out}{type=double}{optional} +; Time points at which volumes were acquired. Really number +; of volumes (corresponding to dim[4]) which would make this +; perhaps the interval between acquisitions, in ms (assumed). +;- +pro IDLffAnalyze::GetVoxelDims, VOXEL_WIDTH=width, VOXEL_HEIGHT=height, $ + SLICE_THICKNESS=thick, TIME_POINTS=timep + compile_opt idl2 + + if arg_present(width) then width = self.hdr.pixdim[1] + if arg_present(height) then height= self.hdr.pixdim[2] + if arg_present(thick) then thick = self.hdr.pixdim[3] + if arg_present(timep) then timep = self.hdr.pixdim[4] +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetProperty +;+ +; Allows direct setting of header properties. The most important +; of these properties are set by SetPixelData, SetVoxelDimensions +; or SetBitPix. With this function it is possible to create +; an invalid header file that does not reflect the actual data in +; the .img file. Caveat emptor! +;- +pro IDLffAnalyze::SetProperty, $ + ALL=all, DIM=dim, GLMIN=glmin, GLMAX=glmax, PIXDIM=pixdim, $ + VOX_UNITS=vox_units, CAL_UNITS=cal_units, DATATYPE=datatype, $ + BITPIX=bitpix, VOX_OFFSET=vox_offset, CAL_MIN=cal_min, $ + CAL_MAX=cal_max, ORIENT=orient, SCALEFACTOR=scalefactor, $ + IMAGE_ORIGIN=image_origin, DCOFF =dcoff, ENDIAN=endian + compile_opt idl2 + + ; + ; Update elements using Analyze names + ; + if (n_elements(all) ne 0) then self->UpdateAll, all + if (n_elements(dim) ne 0) then self->UpdateDim, dim + if (n_elements(glmin) ne 0) then self->UpdateGlmin, glmin + if (n_elements(glmax) ne 0) then self->UpdateGlmax, glmax + if (n_elements(pixdim) ne 0) then self->UpdatePixdim, pixdim + if (n_elements(vox_units) ne 0) then self->UpdateVoxUnits, vox_units + if (n_elements(cal_units) ne 0) then self->UpdateCalUnits, cal_units + if (n_elements(datatype) ne 0) then self->UpdateDatatype, datatype + if (n_elements(bitpix) ne 0) then self->UpdateBitpix, bitpix + if (n_elements(vox_offset) ne 0) then self->UpdateVoxOffset, vox_offset + if (n_elements(cal_min) ne 0) then self->UpdateCalMin, cal_min + if (n_elements(cal_max) ne 0) then self->UpdateCalMax, cal_max + if (n_elements(orient) ne 0) then self->UpdateOrient, orient + if (n_elements(scalefactor) ne 0) then self->UpdateScaleFactor, scalefactor + if (n_elements(dcoff) ne 0) then self->UpdateDcoff, dcoff + if (n_elements(image_origin) ne 0) then self->UpdateImageOrigin, image_origin + if (n_elements(endian) ne 0) then self->UpdateEndian, endian +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetVoxelDims +;+ +; Set the pixdim dimensions. These are the actual physical +; dimensions in mm or ms (assumed units). +; +; @keyword VOXEL_WIDTH {in}{type=double}{optional} +; The voxel width (eg, along read axis) in mm (assumed). +; +; @keyword VOXEL_HEIGHT {in}{type=double}{optional} +; The voxel height (eg, along phase axis) in mm (assumed). +; +; @keyword SLICE_THICKNESS {in}{type=double}{optional} +; Slice thickness (as opposed to slice spacing) in mm (assumed). +; +; @keyword TIME_POINTS {in}{type=double}{optional} +; Time points at which volumes were acquired. Really number +; of volumes (corresponding to dim[4]) which would make this +; perhaps the interval between acquisitions, in ms (assumed). +;- +pro IDLffAnalyze::SetVoxelDims, VOXEL_WIDTH=width, VOXEL_HEIGHT=height, $ + SLICE_THICKNESS=thick, TIME_POINTS=timep + compile_opt idl2 + + p = self.hdr.pixdim + + if (n_elements(width) ne 0) then begin + if (~self->isNum(width, /POS)) then $ + message, 'VOXEL_WIDTH must be positive.' + p[1] = width + endif + + if (n_elements(height) ne 0) then begin + if (~self->isNum(height, /POS)) then $ + message, 'VOXEL_HEIGHT must be positive.' + p[2] = height + endif + + if (n_elements(thick) ne 0) then begin + if (~self->isNum(thick, /POS)) then $ + message, 'SLICE_THICK must be positive.' + p[3] = thick + endif + + if (n_elements(timep) ne 0) then begin + if (~self->isNum(timep, /POS)) then $ + message, 'TIME_POINTS must be positive.' + p[4] = timep + endif + + self.hdr.pixdim = p +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetBitPix +;+ +; Set the bits per pixel field. +; +; @param bitpix {in}{type=integer} +; Number of bits per pixel of data. +;- +pro IDLffAnalyze::SetBitPix, bitpix + compile_opt idl2 + + ; Assert that bitpix is a positive number + if ~self->isNum(bitpix, /POS) then $ + message, 'Bits per pixel must be a positive integer.' + + ; Must be one of the following + if where(bitpix eq [1,8,16,32,64]) eq -1 then $ + message, 'Bits per pixel must be 1, 8, 16, 32, or 64.' + + ; Assign a valid number + self.hdr.bitpix = bitpix +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetOrientation +;+ +; Set the output orientation. Internally, data is stored and +; accessed in transverse, LAS order. +; +; Value String +; 0 TRS +; 1 COR +; 2 SAG +; 3 -TRS +; 4 -COR +; 5 -SAG +; +; The orientation string maps XYZ axes, which are +; always in radiological, left-handed order (ala Analyze) to +; the final direction of the axis. For example, normal axial +; (TRS) images, in radiological order, follow this pattern: +; +; XYZ -> R-L, P-A, I-S, "LAS" which means that X runs from +; (patient) right to left, posterior to anterior (back to front) +; and inferior to superior (feet to head) if the patient is in +; a supine position (on his back, face up). +; +; Orient is used to properly place the data read from the file into +; memory or when the file is written to disk. +; +; A "-" in front of the order string means "flipped". +; These are rare in the wild and not recommended for use. +;- +pro IDLffAnalyze::SetOrientation, ord + compile_opt idl2 + + ; Must be a scalar + if (n_elements(ord) ne 1) then $ + message, 'ORIENT must be a scalar or single string.' + + ; Can be a string + if (size(ord,/TYPE) eq 7) then begin + ans = where(strupcase(ord) eq ['TRS','COR','SAG','-TRS','-COR','-SAG']) + if (ans eq -1) then message, 'Illegal string given for ORIENT.' + self.hdr.orient = ans + endif else begin + if (~self->isNum(ord, LIMITS=[0,5])) then $ + message, 'ORIENT must be between 0 and 5, inclusive.' + self.hdr.orient = ord + endelse +end + + +; +; Get/Set pixel data methods: +; + +;----------------------------------------------------------- +; IDLffAnalyze::QueryPixelData +;+ +; @returns True (1) if there is valid image data, false (0) +; otherwise. +;- +function IDLffAnalyze::QueryPixelData + return, ptr_valid(self.imgdata) +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetPixelData +;+ +; @returns The pixel data, or query image data status. +; +; @keyword POINTER {in}{type=boolean}{optional} +; If set, return a pointer to the image data. This +; is against "good" object-oriented design but these +; files might be very large and direct access through a +; pointer will not result in copying megabytes of data. +;- +function IDLffAnalyze::GetPixelData, POINTER=pointer + compile_opt idl2 + + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + if ~keyword_set(pointer) then begin + return, *self.imgdata ; this might require a lot of memory + endif else begin + return, self.imgdata ; memory friendly, but dangerous + endelse +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetVolume +;+ +; @returns A copy of the desired volume. +; +; @param v {in}{type=integer} Volume (time point) number. +;- +function IDLffAnalyze::GetVolume, v + compile_opt idl2 + + ; There must be some data + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + ; Validate the volume number + if ~self->isNum(v, /POS, /ZERO, /INTEGER) then $ + message, 'Volume (time point) number must be an integer >=0.' + if (v ge self.hdr.dim[4]) then $ + message, 'Volume (time point) index out of bounds.' + + return, reform((*self.imgdata)[*,*,*,v]) +end + + +;----------------------------------------------------------- +; IDLffAnalyze::GetImage +;+ +; @returns The selected image, from the given volume and +; orientation. +; +; @param i {in}{type=integer} +; The image number, zero-based. +; +; @param v0 {in}{type=integer}{optional} +; The source volume (time point), zero-based. Defaults +; to 0 if not given. +; +; @keyword AXIAL {in}{type=boolean}{optional} +; Select an axial image, default. +; +; @keyword TRS {in}{type=boolean}{optional} +; Synonym for AXIAL. +; +; @keyword TRANSVERSE {in}{type=boolean}{optional} +; Synonym for AXIAL. +; +; @keyword CORONAL {in}{type=boolean}{optional} +; Select a coronal image. +; +; @keyword SAGITTAL {in}{type=boolean}{optional} +; Select a sagittal image. +;- +function IDLffAnalyze::GetImage, i, v0, AXIAL=axial, TRS=trs, $ + TRANSVERSE=transverse, CORONAL=coronal, SAGITTAL=sagittal + compile_opt idl2 + + ; There must be some image data + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + ; Keywords are mutually exclusive + z = keyword_set(axial) + 2*keyword_set(trs) + 4*keyword_set(transverse) + $ + 8*keyword_set(coronal) + 16*keyword_set(sagittal) + + if (where(z eq [0,1,2,4,8,16]) eq -1) then $ + message, 'Incompatible keywords specified.' + + ; Volume (time point) number must exist + v = (n_params() eq 2) ? v0 : 0 + if (v ge self.hdr.dim[4]) then $ + message, 'Volume (time point) out of range.' + + ; Get the desired image + msg = 'Image number out of range.' + + case z of + 16: BEGIN + if (i ge self.hdr.dim[1]) then message, msg ; sagittal + img = reform((*self.imgdata)[i,*,*,v]) + END + 8: BEGIN + if (i ge self.hdr.dim[2]) then message, msg ; coronal + img = reform((*self.imgdata)[*,i,*,v]) + END + ELSE: BEGIN + if (i ge self.hdr.dim[3]) then message, msg ; transverse + img = (*self.imgdata)[*,*,i,v] + END + endcase + + return, img +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetPixelData +;+ +; Set the pixel data and associated header elements using +; the input array. Will set glmin, glmax, datatype, bitpix, +; and dim but does not set orient. +; +; @param d {in}{type=numeric array, 2, 3, or 4D} +; The data to store. +; +; @keyword NO_COPY {in}{type=boolean}{optional} +; If set the original array input will be destroyed +; once the data has been assigned to the heap. Ie, +; the NO_COPY keyword to ptr_new(). +;- +pro IDLffAnalyze::SetPixelData, d, NO_COPY=no_copy0 + compile_opt idl2 + + no_copy = keyword_set(no_copy0) ? no_copy0 : 0 + + ; + ; Must be a numeric array that is supported by the + ; Analyze 7.5 "standard". + ; + if (where(size(d,/TYPE) eq [1,2,3,4,5,6]) eq -1) then $ + message, 'Input array not of a type supported by Analyze 7.5.' + + ; Must be 2, 3, or 4 dimensional + dims = size(d,/DIM) + ndims = n_elements(dims) + if (ndims lt 2) or (ndims gt 4) then $ + message, 'Input array must be of 2, 3 or 4 dimensions.' + + ; Remove any existing data + if ptr_valid(self.imgdata) then $ + ptr_free, self.imgdata + + ; + ; Reset the header structure to default values, including orient + ; (all data set this way is "transverse") + ; + self.hdr = self.default + + ; Set the dimensions + self.hdr.dim[0] = 4 ; always say it is 4-dimensional + self.hdr.dim[1] = dims[0] ; X direction (columns) + self.hdr.dim[2] = dims[1] ; Y direction (rows) + self.hdr.dim[3] = (ndims ge 3) ? dims[2] : 1 ; Z direction (slices), 2D is one slice + self.hdr.dim[4] = (ndims eq 4) ? dims[3] : 1 ; volumes (time points), 3D is one time point + + ; Set the datatype + self.hdr.datatype = self->IDLtoAnalyzeType(size(d,/TYPE)) + + ; Set bits per pixel + self.hdr.bitpix = self->IDLtoAnalyzeBitPix(size(d,/TYPE)) + + ; Set the glmin and glmax + self.hdr.glmin = min(d) + self.hdr.glmax = max(d) + + ; Set endian to the order this system uses + self.endian = self->SystemByteOrder() + + ; Set the data itself + self.imgdata = ptr_new(d, NO_COPY=no_copy) +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetVolume +;+ +; Update an existing volume (time point). Datatype and +; dimensions must match the existing volume. +; +; @param v {in}{type=integer} +; The volume (time point) number. +; +; @param vol {in}{type=3D array} +; The new volume data. +;- +pro IDLffAnalyze::SetVolume, v, vol + compile_opt idl2 + + ; Is there any data? + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + ; Validate v, volume number + if ~self->isNum(v, /POS, /ZERO, /INTEGER) then $ + message, 'Volume (time point) number must be an integer >=0.' + if (v ge self.hdr.dim[4]) then $ + message, 'Volume (time point) index out of bounds.' + + ; Validate vol, the new volume data + if n_elements(size(vol,/DIM)) ne 3 then $ + message, 'Input volume must be 3 dimensions.' + + ; What about the datatype? + if (self->IDLtoAnalyzeType(size(vol,/TYPE)) ne self.hdr.datatype) then $ + message, 'Data type of input must be the same as existing image data.' + + ; Now for the dimensions + if ~array_equal(size(vol,/DIM),self.hdr.dim[1:3]) then $ + message, 'Input volume must match the dimensions of the existing image data.' + + ; Assign the new image data + (*self.imgdata)[*,*,*,v] = vol +end + + +;----------------------------------------------------------- +; IDLffAnalyze::SetImage +;+ +; Update an existing image in a particular volume with a +; particular orientation. Dimensions and datatype must +; match (exactly, no behind-the-scenes promotion of types). +; +; @param i {in}{type=integer} +; Image number to update. +; +; @param v {in}{type=integer} +; Volume which holds the image. +; +; @param img {in}{type=matrix} +; The new image data. +; +; @keyword AXIAL {in}{type=boolean}{optional} +; Select an axial image, default. +; +; @keyword TRS {in}{type=boolean}{optional} +; Synonym for AXIAL. +; +; @keyword TRANSVERSE {in}{type=boolean}{optional} +; Synonym for AXIAL. +; +; @keyword CORONAL {in}{type=boolean}{optional} +; Select a coronal image. +; +; @keyword SAGITTAL {in}{type=boolean}{optional} +; Select a sagittal image. +;- +pro IDLffAnalyze::SetImage, i, v, img, AXIAL=axial, TRS=trs, $ + TRANSVERSE=transverse, CORONAL=coronal, SAGITTAL=sagittal + compile_opt idl2 + + ; There must be some image data + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + ; Keywords are mutually exclusive + z = keyword_set(axial) + 2*keyword_set(trs) + 4*keyword_set(transverse) + $ + 8*keyword_set(coronal) + 16*keyword_set(sagittal) + + if (where(z eq [0,1,2,4,8,16]) eq -1) then $ + message, 'Incompatible keywords specified.' + + ; Volume (time point) number must exist + if ~self->isNum(v, /POS, /ZERO, /INTEGER) then $ + message, 'Volume (time point) number must be an integer >=0.' + if (v ge self.hdr.dim[4]) then $ + message, 'Volume (time point) out of range.' + + ; Check the datatype + if (self->IDLtoAnalyzeType(size(img,/TYPE)) ne self.hdr.datatype) then $ + message, 'Data type of input must be the same as existing image data.' + + ; Assign the desired image + msg = 'Image number out of range.' + msg2 = 'Input image dimensions do not match existing data.' + d = size(img,/DIM) + + case z of + 16: BEGIN + if (i ge self.hdr.dim[1]) then message, msg ; sagittal + if (d[0] ne self.hdr.dim[2]) and $ + (d[1] ne self.hdr.dim[3]) then message, msg2 + (*self.imgdata)[i,*,*,v] = img + END + 8: BEGIN + if (i ge self.hdr.dim[2]) then message, msg ; coronal + if (d[0] ne self.hdr.dim[1]) and $ + (d[1] ne self.hdr.dim[3]) then message, msg2 + (*self.imgdata)[*,i,*,v] = img + END + ELSE: BEGIN + if (i ge self.hdr.dim[3]) then message, msg ; transverse + if (d[0] ne self.hdr.dim[1]) and $ + (d[1] ne self.hdr.dim[2]) then message, msg2 + (*self.imgdata)[*,*,i,v] = img + END + endcase +end + + +; +; File I/O methods: +; + +;---------------------------------------------------------- +; IDLffAnalyze::ReadHeaderFile +;+ +; @returns An instance of {header} for the given .hdr file. +; +; @param f {in}{type=string} +; Pathname to the header file. +; +; @keyword ENDIAN {out}{type=integer} +; Set to the byte order of the header (1=big, 0=little). +;- +function IDLffAnalyze::ReadHeaderFile, f, ENDIAN=endian + compile_opt idl2 + + ; Filename must really exist with read permission + if (~file_test(f,/READ)) then $ + message, 'Unable to read file ['+f+']' + + ; File must be 384 bytes long, no extended headers + info = file_info(f) + if (info.size ne 348) then $ + message, 'Non-standard header files not supported, length > 384 bytes.' + + ; Read the structure. + ans = {header} + openr, u, f, /GET_LUN + readu, u, ans + free_lun, u + + ; + ; Determine file byte order and set local ENDIAN property. + ; Used by ReadImageFile() to swap bytes properly. + ; + if (ans.sizeof_hdr eq 348) then begin + ; system and header using same byte order + endian = self->SystemByteOrder() + endif else begin + ; system and header using opposite byte order + endian = ~self->SystemByteOrder() ; store true order + self->SwapHeader, ans ; swap to get to local system order + endelse + + ; Return the structure + return, ans +end + + +;----------------------------------------------------------- +; IDLffAnalyze::ReadFile +;+ +; Reads an Analyze 7.5 file. +; +; @param f {in}{type=string vector}{optional} +; Name or names of the files to load. If not given +; an open dialog box is used. +; +; @keyword ORIENTATION {in}{type=string or integer}{optional} +; Orientation to use when reading the file, overrides any +; specified in the header. If not given use the value in +; the header. Integer 0..5 or 'TRS','COR','SAG' with '-' +; in front for flipped (values 3..5). +; +; @keyword _EXTRA {in}{type=any}{optional} +; Extra keywords for dialog_pickfile. +;- +pro IDLffAnalyze::ReadFile, f, ORIENTATION=orient0, _EXTRA=extra + compile_opt idl2 + + ; + ; Set up the orientation, 0..5 or -1 for header + ; + orient = -1 + if (n_elements(orient0) ne 0) then begin + if (n_elements(orient0) ne 1) then $ + message, 'Orientation must be a string or integer scalar.' + if (size(orient0,/TYPE) eq 7) then begin + idx = where(strupcase(orient0) eq ['TRS','COR','SAG','-TRS','-COR','-SAG']) + if (idx eq -1) then $ + message, 'Orientation must be a valid string.' + orient = idx[0] + endif else begin + if (~self->isNum(orient0, /INTEGER, LIMITS=[0,5])) then $ + message, 'Orientation must be an integer, [0,5] inclusive.' + orient = fix(orient0) + endelse + endif + + ; If f given? + if (n_params() eq 0) then begin + f = dialog_pickfile(/MUST_EXIST, FILTER='*.hdr', _EXTRA=extra) + if f[0] eq '' then return ; user cancel + f = f[0] + endif else begin + ; Validate f + if (size(f,/TYPE) ne 7) then $ + message, 'Argument must be a string.' + if (n_elements(f) ne 1) then $ + message, 'Argument must be a single string.' + endelse + + ; Read the header file + h = self->ReadHeaderFile(f, ENDIAN=endian) + + ; Set orientation properly + if (orient eq -1) then orient = h.orient + + ; Now read the image file + img = self->ReadImageFile(f, h, orient, ENDIAN=endian) + + ; All read successfully, update necessary fields + if ptr_valid(self.imgdata) then ptr_free, self.imgdata + self.imgdata = ptr_new(img,/NO_COPY) + self.hdr = h + self.hdr.orient = orient ; orientation actually used + self.endian = endian +end + + +;----------------------------------------------------------- +; IDLffAnalyze::WriteFile +;+ +; Output the image data to a file or set of files. +; +; @param f {in}{type=string}{optional} +; The output file name. Base name only, no extensions. +; +; @keyword MULTIPLE_FILES {in}{type=boolean}{optional} +; If set will create multiple .hdr/.img pairs for each +; image in the data set using axial ordering (ie, axial +; images, ignores the orient field). +; +; @keyword _EXTRA {in}{type=any}{optional} +; Extra keywords for dialog_pickfile. +;- +pro IDLffAnalyze::WriteFile, f, MULTIPLE_FILES=mult, _EXTRA=extra + compile_opt idl2 + + ; Must have something to write + if ~ptr_valid(self.imgdata) then $ + message, 'No image data available.' + + ; + ; Get a filename + ; + if (n_params() eq 1) then begin + if (size(f,/TYPE) ne 7) then $ ; f given, validate it + message, 'Output filename must be a string.' + if (n_elements(f) ne 1) then $ + message, 'Output filename must be a single string.' + endif else begin + ; f not present, use a dialog box + if n_elements(dp) ne 0 then begin + f = dialog_pickfile(_EXTRA=extra) + endif else begin + f = dialog_pickfile(_EXTRA=extra) + endelse + if f[0] eq '' then return + f = f[0] ; dialog_pickfile returns a vector + endelse + + ; + ; Decide whether or not to output a single file or + ; multiple files. + ; + if ~keyword_set(mult) then begin + self->WriteSingleFile, f + endif else begin + self->WriteMultipleFiles, f + endelse +end + + + +; +; Lifecycle methods: +; + +;----------------------------------------------------------- +; IDLffAnalyze::Init +;+ +; Create an instance of this class. +; +; @returns True (1) if the class successfully created. +; +; @param f {in}{type=string}{optional} +; If present, must be a string giving the name of a +; header file. This file (and its associated .img +; file which must be in the same directory) are loaded. +; +; @keyword ORIENTATION {in}{type=integer or string}{optional} +; Orientation to use when reading the data, if f is given. +; +; @keyword DATA {in}{type=array}{optional} +; If present, the data from this array is used to +; set up the object. This overrides any given argument. +;- +function IDLffAnalyze::Init, f, DATA=data, ORIENTATION=orient + compile_opt idl2 + + ; + ; Catch any errors so memory isn't wasted + ; + CATCH, err + if (err ne 0) then begin + catch, /CANCEL + self->Destroy ; release any allocated memory + return, 0 ; object creation failed + endif + + ; + ; Set certain constant values, save as default + ; + self.hdr.sizeof_hdr = long(348) + self.hdr.extents = long(16384) + self.hdr.regular = byte('r') + + self.default = self.hdr + + ; Use the system byte order by default + self.endian = self->SystemByteOrder() + + if keyword_set(data) then begin + self->SetPixelData, data + endif else begin + if (n_elements(f) eq 0) then begin + ; no arguments at all... + endif else begin + self->ReadFile, f, ORIENTATION=orient + end + endelse + + ; have a valid object + return, 1 +end + + +;----------------------------------------------------------- +; IDLffAnalyze::Cleanup +;+ +; Destory the object. +;- +pro IDLffAnalyze::Cleanup + compile_opt idl2 + + self->Destroy ; separate destroy method so it can be + ; called from Init if necessary +end + + +;----------------------------------------------------------- +; IDLffAnalyze__define +;+ +; Define the class and other structures. +;- +pro idlffanalyze__define + compile_opt idl2 ; N.B. matters here! + + ; + ; These structures define the contents of the .hdr file: + ; + + ; + ; Analyze 7.5 header structure - incorporates the + ; header_key, image_dimension, and data_history structures. + ; + void = {header, $ ; struct header_key { + sizeof_hdr : 348, $ ; int sizeof_hdr; + data_type : bytarr(10), $ ; char data_type[10]; + db_name : bytarr(18), $ ; char db_name[18]; + extents : 16384, $ ; int extents; + session_error : 0s, $ ; short int session_error; + regular : byte('r'), $ ; char regular; + hkey_un0 : 0b, $ ; char hkey_un0; } + $ ; + $ ; Analyze 7.5 image_dimension structure: + $ ; ; struct image_dimension { + dim : fix(intarr(8),TYPE=2), $ ; short int dim[8]; + vox_units : bytarr(4), $ ; char vox_units[4]; + cal_units : bytarr(8), $ ; char cal_units[4]; + unused1 : 0s, $ ; short int unused1; + datatype : 0s, $ ; short int datatype; + bitpix : 0s, $ ; short int bitpix; + dim_un0 : 0s, $ ; short int dim_un0; + pixdim : fltarr(8), $ ; float pixdim[8]; + vox_offset: FLOAT(0.0), $ ; float vox_offset; + roi_scale : FLOAT(0.0), $ ; float roi_scale; + funused1 : FLOAT(0.0), $ ; float funused1; // scalefactor in SPM + funused2 : FLOAT(0.0), $ ; float funused2; // dcoff in SPM2 + cal_max : FLOAT(0.0), $ ; float cal_max; + cal_min : FLOAT(0.0), $ ; float cal_min; + compressed: 0, $ ; int compressed; + verified : 0, $ ; int verified; + glmax : 0, $ ; int glmax; + glmin : 0, $ ; int glmin; } + $ ; + $ ; Analyze 7.5 data_history structure: + $ ; ; struct data_history { + descrip : bytarr(80), $ ; char descrip[80]; + aux_file : bytarr(24), $ ; char aux_file[24]; + orient : 0b, $ ; char orient; + originator : bytarr(10), $ ; char originator[10]; // image_origin in SPM + generated : bytarr(10), $ ; char generated[10]; + scannum : bytarr(10), $ ; char scannum[10]; + patient_id : bytarr(10), $ ; char patient_id[10]; + exp_date : bytarr(10), $ ; char exp_date[10]; + exp_time : bytarr(10), $ ; char exp_time[10]; + hist_un0 : bytarr(3), $ ; char hist_un0[3]; + views : 0, $ ; int views; + vols_added : 0, $ ; int vols_added; + start_field: 0, $ ; int start_field; + field_skip : 0, $ ; int field_skip; + omax : 0, $ ; int omax; + omin : 0, $ ; int omin; + smax : 0, $ ; int smax; + smin : 0 $ ; int smin; + } ; } + + ; + ; Class instance vars: + ; + class = { IDLffAnalyze, $ + endian : 0, $ ; 1=big-endian, 0=little-endian (read/write) + hdr : {header}, $ ; header data + default: {header}, $ ; default header values + imgdata: ptr_new() $ ; actual image data + } +end + + +; +; End idlffanalyze__define.pro +; diff --git a/Joint Fitting/linecolors.pro b/Joint Fitting/linecolors.pro new file mode 100644 index 0000000..25cd41d --- /dev/null +++ b/Joint Fitting/linecolors.pro @@ -0,0 +1,326 @@ +;Viewing contents of file '../idllib/ssw/allpro/linecolors.pro' +;+ +; +; file LINECOLORS.PRO +; +; Create a color table with "n" distinct color indices at the low end of +; the table and the index at !D.TABLE_SIZE-1 with the colors defined below. +; +; Where: the first color index will be black +; 'n' is the number of distinct colors hard coded below +; and, the last color index is white +; +; INDEX NUMBER COLOR PRODUCED (if use default colors) +; 0 black +; 1 maroon +; 2 red +; 3 pink +; 4 orange +; 5 yellow +; 6 olive +; 7 green +; 8 dark green +; 9 cyan +; 10 blue +; 11 dark blue +; 12 magenta +; 13 purple +; +; General color table stuff: +; Each color available is made up of the values found in three arrays. +; These array represent how much RED, GREEN, and BLUE color to use. +; A value of zero means don't use any of that color. +; A value of 255 means use the maximum amount of that color. +; These arrays are considered your 'color guns'. +; +; How large your 'color gun' arrays can be is determined by your system. +; !D.N_COLORS system variable hold the max number of colors you can have. +; !D.TABLE_SIZE is the maximum number of indices you may use. +; You may not have all 255 colors. +; So for each 'color index' you must decide how much RED, GREEN and +; BLUE you want. +; The combination of these three 'color gun' arrays will be the color +; that appears in the individual 'color index'. +; +; +; CALLING SEQUENCE: +; LINECOLORS is the simplest form. It produces a color table with +; the colors listed above and loads it. All you do is +; call it and use the plot keyword COLOR=x. +; Where x is the index number from above. +; +; LINECOLORS [,MYCOL_R=mycol_g, MYCOL_G=mycol_g, MYCOL_B=mycol_b, +; LINE_R=line_g, LINE_G=line_g, LINE_B=line_b, +; table=table, /NOLOAD, /NOTOP, /NOSQUEEZE, USED=used, +; error=error] +; +; INPUT: +; MYCOL_R : If present, an array (convert to byte) containing the +; red gun values (0-255) to overwrite the common array COLORS +; This array is expanded or compressed to fit. Will override +; the TABLE keyword value. +; MYCOL_G : Same as above for green. +; MYCOL_B : Same as above for blue. +; TABLE : The number of an IDL User Library Color Table, to be loaded. +; It will be this table that is compressed into the indices +; remaining after MYCOL_R,_G,_B or the defaults arrays. +; NOLOAD : If set, don't do a TVLCT in this program. +; This new color table will not be active until doing a TVLCT +; NOTOP : If set, don't put white in the index at !D.TABLE_SIZE-1 +; Not all original color tables will have white at the top. +; NOSQUEEZE: If set, don't squeeze the current color table into +; the indices not taken by the distinct colors. The bottom +; colors of the original table will be overwritten the +; rest will remain as they were. Ignored if the keywords +; MYCOL_R, MYCOL_G, MYCOL_B are set. +; HELP: If set and device='x', display a colorbar with indices +; (!d.window is reset to original window number) +; +; OUTPUT: +; LINE_R : If present, returns the red color gun values for this new +; color table. This array is the same as found in the IDL +; common array R_CURR, upon returning. +; LINE_G : Same as above for green. +; LINE_B : Same as above for blue. +; +; USED : If present, returns the number of indices used by the +; distinct colors at the low end of the color table. +; Doesn't include the overwritting of the top index to white, +; or any value of MYCOL_R, MYCOL_G, MYCOL_B. +; +; also see the explaination of x_CURR below. +; ERROR : 0/1 means no error / error +; +; +; COMMON: +; COMMON COLORS, R_ORIG, G_ORIG, B_ORIG, R_CURR, G_CURR, B_CURR +; This IDL common contains the current color table. +; +; SIDE EFFECTS: +; The color table side will be determined by the current device +; If the device is not 'X', an informational message will be printed. +; + +; RESTRICTIONS: +; The output graphic device must accept the LOADCT calls, if +; /TABLE is set or if no previous table has been loaded. +; The output graphic device must accept the TVLCT call, unless +; the /NOLOAD keyword is set. +; +; PROCEDURE: +; Some time before you do your plot command, call this routine. +; +; LINECOLOR +; +; If you use the /NOLOAD keyword, then upon returning you will need +; to load the new created color table with TVLCT, ,, +; +; LINECOLORS, LINE_R=LINE_R, LINE_G=LINE_G, LINE_B=LINE_B, /NOLOAD +; TVLCT, LINE_R, LINE_G, LINE_B +; +; +; To postscript printer : +; SET_PLOT,'PS',/copy ; prints plot the postscript file +; +; DEVICE, [FILENAME=filename] ; black and white print +; or +; DEVICE, [FILENAME=filename], /color ; color print +; +; To plot, use the desired color index, by using the plotting +; keyword COLOR=index. +; You may want to first plot the axises in white then over plot the +; data in a distinct color. +; +; plot, x, y, /nodata ... ; titles and axes +; ; color defaults to the +; ; largest index. In our +; ; color table this is white +; ; Black for prints. +; +; oplot, x, y, color=n ... ; Plot the data. 'n' is +; ; the color index of choice +; +; If you were printing then you'll need to close the output file, +; and print. +; +; DEVICE,/CLOSE +; PSPLOT, FILENAME=filename ; for black and white +; PSPLOT, FILENAME=filename, /color ; for color print +; +; An example: +; pro brian, color=color ; color is 0 for b/w +; ; 1 for color +; +; linecolors +; set_plot,'ps',/copy +; if not(color) then device,file='brain.ps' $ +; else device,file='brain.ps', color=color +; +; plot, indgen(100), /nodata +; oplot, (indgen(100)-10)>0, color=1 +; oplot, (indgen(100)-20)>0, color=3 +; oplot, (indgen(100)-30)>0, color=5 +; oplot, (indgen(100)-40)>0, color=7 +; oplot, (indgen(100)-50)>0, color=9 +; +; device,/close +; if not(color) then psplot,filename='brain.ps' $ +; else psplot,filename='brain.ps',/color +; +; return & end +; +; MODIFICATION HISTORY: +; Elaine Einfalt (HSTX) +; MAY 93 - If mycol_r,g,b arrays are passes they are added +; after the distinct colors, not instead. +; 23-sep-94 (SLF) - added HELP keyword (display color bar with indices) +;- + +pro linecolors, mycol_r=mycol_r, mycol_g=mycol_g, mycol_b=mycol_b, $ + line_r=line_r, line_g=line_g, line_b=line_b, table=table, $ + noload=noload, notop=notop, squeeze=squeeze, used=used, $ + error=error, help=help + + common colors, r_orig, g_orig, b_orig, r_curr, g_curr, b_curr + + error = 0 + + ; + ; First, does user want an IDL User Library Color Table loaded. + ; If not, and no table has been loaded this session or table size is wrong, + ; then load one now. Loading a table assigns the real !D.TABLE_SIZE value. + ; + if n_elements(table) ne 0 then loadct, table, /silent ; User's table choice + + if ((!d.name eq 'X') and (!d.window eq -1)) or $ ; need a window, or + (n_elements(r_orig) ne !d.table_size) $ ; changed device + then loadct, 0, /silent ; black and white linear + + + ; + ; Second, define the distinct colors that will be used for plot lines + ; These color may be expanded or changed simply by adding to or altering + ; the 'color gun' arrays values. + ; + + distinct_r = [0,128,255,255,255,255,128, 0, 0, 0, 0, 0,255,128] + distinct_g = [0, 0, 0, 0,128,255,128,255,128,255, 0, 0, 0, 0] + distinct_b = [0, 0, 0,128, 0, 0, 0, 0, 0,255,255,128,255,128] + + ; + ; Will that many colors fit into the available indices? + ; + + used = n_elements(distinct_r) > n_elements(distinct_g) > $ + n_elements(distinct_b) + must_have = used + (1-keyword_set(notop)) ; remember about the + ; possible top white + + if !d.table_size lt must_have then begin + message, 'Error - color table NOT loaded. Only ' + $ + strtrim(!d.table_size,2) + ' indices where available.', /info + error = 1 + return + endif + + + ; + ; Third, overwrite current color table with new colors. + ; + + r_temp = r_curr + g_temp = g_curr + b_temp = b_curr + + ; + ; The distinct colors are placed at the bottom of the table + ; + + r_temp(0) = distinct_r & g_temp(0) = distinct_g & b_temp(0) = distinct_b + + + ; + ; Does the user have a set of color gun arrays that they want loaded? + ; + + remain = !d.table_size - used ; space left after distinct colors + n_orig = n_elements(r_orig) ; Common arrays are same size + + ; + ; If user did not pass a color gun array and NOSQUEEZE was not set, then + ; then squeeze original color table into remaining indices. + ; If use passed a color gun array, then expand or squeeze their array to + ; fit in remaining indices (NOSQUEEZE is ignored). + ; + + if (size(mycol_r))(0) eq 0 then begin ; no colors passed by user + if not keyword_set(nosqueeze) then $ ; if allowed to squeeze + r_temp(used) = congrid(reform(r_orig, n_orig, 1), remain, 1) + endif else $ ; fit in user's colors + r_temp(used) = congrid(reform(mycol_r, (size(mycol_r))(1), 1), remain, 1) + + if (size(mycol_g))(0) eq 0 then begin ; no colors passed by user + if not keyword_set(nosqueeze) then $ ; if allowed to squeeze + g_temp(used) = congrid(reform(g_orig, n_orig, 1), remain, 1) + endif else $ ; fit in user's colors + g_temp(used) = congrid(reform(mycol_g, (size(mycol_g))(1), 1), remain, 1) + + if (size(mycol_b))(0) eq 0 then begin ; no colors passed by user + if not keyword_set(nosqueeze) then $ ; if allowed to squeeze + b_temp(used) = congrid(reform(b_orig, n_orig, 1), remain, 1) + endif else $ ; fit in user's colors + b_temp(used) = congrid(reform(mycol_b, (size(mycol_b))(1), 1), remain, 1) + + ; + ; Overwrite common's color table in favor of this new matrix. + ; + + r_curr = r_temp & g_curr = g_temp & b_curr = b_temp + + + if not keyword_set(notop) then begin + ; + ; Unless the user specifically said not to, make last color index white. + ; + r_curr(!d.table_size - 1) = 255 + g_curr(!d.table_size - 1) = 255 + b_curr(!d.table_size - 1) = 255 + endif + + ; + ; Now load this new color table, if the user wants it. + ; If /NOLOAD was set, then the user will load the color table later. + ; + + if not keyword_set(noload) then begin + + tvlct, r_curr, g_curr, b_curr + r_orig = r_curr & g_orig = g_curr & b_orig = b_curr + + endif + + ; + ; Allow user access to arrays without requiring the common block. + ; + line_r = r_curr & line_g = g_curr & line_b = b_curr + + + ; + ; If not 'X' then tell the user what they have just done. + ; + + if !d.name ne 'X' then message, /info, strtrim(!d.table_size,2) + $ + ' color table indices set for ' + !d.name + ' device.' + + ; slf - added HELP keyword and function + if keyword_set(help) and !d.name eq 'X' then begin + bar=rebin(indgen(used),32*used,used*4,/sample) + wtemp=!d.window + wdef,zz,/ur,image=bar + tv,bar + xyouts,indgen(used)*32+8, 32,strtrim(sindgen(used),2),/device,size=1.5,charthick=2. + if wtemp ne -1 then wset,wtemp + endif + + return +end \ No newline at end of file diff --git a/Joint Fitting/log.log b/Joint Fitting/log.log new file mode 100644 index 0000000..7338045 --- /dev/null +++ b/Joint Fitting/log.log @@ -0,0 +1,63 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Compiled module: READ_ANALYZE. +% Compiled module: IDLFFANALYZE__DEFINE. +% Compiled module: RANDOMGAUSS. +% Compiled module: DCEMRIPROCESSOR_FREES0_DEFINE. +init complete +Finished data readin +% Compiled module: LINECOLORS. +% LINECOLORS: 256 color table indices set for WIN device. +% Compiled module: SAMPLE_FROM_ARRAY. +------------------------ +% Compiled module: MPCURVEFIT. +% Compiled module: MPFIT. +% Compiled module: FLASH_FUNC. +% Compiled module: TOFTS_OST_EXPC. +% Compiled module: INTERPOL. +% Compiled module: EXPCONVOLUTION. +% Compiled module: TWOCXM_IFIT_DC. +LS params S0v 10163.5 T1 0.784172 Fp 0.401764 + vp 0.160000 ve 0.329679 FE 0.0916042 S0d + 9950.87ost 0.0746818 +------------------------ +LS params S0v 11025.1 T1 0.954619 Fp 0.366345 + vp 0.0500001 ve 0.140439 FE 0.0903419 S0d + 12687.3ost 0.117938 +------------------------ +LS params S0v 10430.7 T1 0.856579 Fp 0.473820 + vp 0.130000 ve 0.860136 FE 0.0514047 S0d + 10623.5ost 0.0929632 +------------------------ +LS params S0v 9569.78 T1 0.920049 Fp 0.555557 + vp 0.0100001 ve 0.402301 FE 0.106294 S0d + 8393.02ost 0.0565013 +------------------------ +LS params S0v 9765.57 T1 0.924756 Fp 0.420543 + vp 0.0800001 ve 0.311119 FE 0.115405 S0d + 7759.48ost 0.111268 +------------------------ +LS params S0v 13693.3 T1 1.44850 Fp 0.190022 + vp 0.0300001 ve 0.236972 FE 0.0326398 S0d + 14725.4ost 0.132223 +------------------------ +LS params S0v 11366.0 T1 1.16562 Fp 0.102646 + vp 0.0100001 ve 0.204750 FE 0.0518423 S0d + 12907.1ost 0.166588 +------------------------ +LS params S0v 9891.00 T1 0.750984 Fp 0.665451 + vp 0.100000 ve 0.247190 FE 0.105224 S0d + 9519.46ost 0.0886912 +------------------------ +LS params S0v 11564.8 T1 0.960096 Fp 0.487909 + vp 0.0400001 ve 0.241381 FE 0.100283 S0d + 11686.3ost 0.0731898 +------------------------ +LS params S0v 12096.7 T1 1.00453 Fp 0.263786 + vp 0.0900001 ve 0.185964 FE 0.0983001 S0d + 14046.5ost 0.103259 +% Expression must be a structure in this context: OUTPUT_STRUCT. +% Execution halted at: RUN_2CXM_PHANTOM 194 C:\Users\ben dickie\Desktop\JE + Software\run_2cxm_phantom.pro +% $MAIN$ +cleanup complete + diff --git a/Joint Fitting/log1.log b/Joint Fitting/log1.log new file mode 100644 index 0000000..e410382 --- /dev/null +++ b/Joint Fitting/log1.log @@ -0,0 +1,64 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Compiled module: READ_ANALYZE. +% Compiled module: IDLFFANALYZE__DEFINE. +% Compiled module: RANDOMGAUSS. +% Compiled module: DCEMRIPROCESSOR_FREES0_DEFINE. +init complete +Finished data readin +% Compiled module: LINECOLORS. +% LINECOLORS: 256 color table indices set for WIN device. +% Compiled module: SAMPLE_FROM_ARRAY. +------------------------ +% Compiled module: MPCURVEFIT. +% Compiled module: MPFIT. +% Compiled module: FLASH_FUNC. +% Compiled module: TOFTS_OST_EXPC. +% Compiled module: INTERPOL. +% Compiled module: EXPCONVOLUTION. +% Compiled module: TWOCXM_VFA_JFIT_DC. +LS params S0v 10324.1 T1 0.801352 Fp 0.384082 + vp 0.150000 ve 0.296795 FE 0.0902612 S0d + 10324.1ost 0.0769943FAerror 1.00000 +------------------------ +LS params S0v 10017.5 T1 0.801422 Fp 0.507308 + vp 0.0700001 ve 0.193448 FE 0.120786 S0d + 10017.5ost 0.111976FAerror 1.00000 +------------------------ +LS params S0v 10069.3 T1 0.808741 Fp 0.496339 + vp 0.140000 ve 0.768167 FE 0.0547581 S0d + 10069.3ost 0.0926146FAerror 1.00000 +------------------------ +LS params S0v 10175.8 T1 1.02556 Fp 0.292046 + vp 0.0100001 ve 0.323831 FE 0.0882079 S0d + 10175.8ost 0.0420646FAerror 1.00000 +------------------------ +LS params S0v 11110.2 T1 1.15339 Fp 0.387634 + vp 0.0300001 ve 0.195640 FE 0.0765671 S0d + 11110.2ost 0.154352FAerror 1.00000 +------------------------ +LS params S0v 13130.4 T1 1.35264 Fp 0.202806 + vp 0.0400001 ve 0.402481 FE 0.0345829 S0d + 13130.4ost 0.104176FAerror 1.00000 +------------------------ +LS params S0v 10223.9 T1 0.979660 Fp 0.248608 + vp 0.0100001 ve 0.269219 FE 0.0581497 S0d + 10223.9ost 0.166678FAerror 1.00000 +------------------------ +LS params S0v 9983.42 T1 0.768932 Fp 0.639985 + vp 0.0900001 ve 0.228146 FE 0.101137 S0d + 9983.42ost 0.0918422FAerror 1.00000 +------------------------ +LS params S0v 11779.2 T1 0.988303 Fp 0.496314 + vp 0.0400001 ve 0.237930 FE 0.101926 S0d + 11779.2ost 0.0731045FAerror 1.00000 +------------------------ +LS params S0v 10844.5 T1 0.832777 Fp 0.370245 + vp 0.130000 ve 0.253939 FE 0.134547 S0d + 10844.5ost 0.0952425FAerror 1.00000 +% Expression must be a structure in this context: OUTPUT_STRUCT. +% Execution halted at: RUN_2CXM_PHANTOM 194 C:\Users\ben dickie\Desktop\JE + Software\run_2cxm_phantom.pro +% $MAIN$ +cleanup complete + +% Interrupted at: $MAIN$ diff --git a/Joint Fitting/log2.log b/Joint Fitting/log2.log new file mode 100644 index 0000000..08816c6 --- /dev/null +++ b/Joint Fitting/log2.log @@ -0,0 +1,63 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Compiled module: READ_ANALYZE. +% Compiled module: IDLFFANALYZE__DEFINE. +% Compiled module: RANDOMGAUSS. +% Compiled module: DCEMRIPROCESSOR_FREES0_DEFINE. +init complete +Finished data readin +% Compiled module: LINECOLORS. +% LINECOLORS: 256 color table indices set for WIN device. +% Compiled module: SAMPLE_FROM_ARRAY. +------------------------ +% Compiled module: MPCURVEFIT. +% Compiled module: MPFIT. +% Compiled module: FLASH_FUNC. +% Compiled module: TOFTS_OST_EXPC. +% Compiled module: INTERPOL. +% Compiled module: EXPCONVOLUTION. +% Compiled module: TWOCXM_IFIT_DC. +LS params S0v 10163.5 T1 0.784172 Fp 0.263868 + vp 0.110000 ve 0.239640 FE 0.0568476 S0d + 9950.87ost 0.0727053 +------------------------ +LS params S0v 11025.1 T1 0.954619 Fp 0.261131 + vp 0.0300001 ve 0.0957841 FE 0.0631015 S0d + 12687.3ost 0.121338 +------------------------ +LS params S0v 10430.7 T1 0.856579 Fp 0.305239 + vp 0.0900001 ve 0.898712 FE 0.0322515 S0d + 10623.5ost 0.0907810 +------------------------ +LS params S0v 9569.78 T1 0.920049 Fp 0.178812 + vp 0.0200001 ve 0.251965 FE 0.0880880 S0d + 8393.02ost 0.0124738 +------------------------ +LS params S0v 9765.57 T1 0.924756 Fp 0.256483 + vp 0.0600001 ve 0.208758 FE 0.0731331 S0d + 7759.48ost 0.105367 +------------------------ +LS params S0v 13693.3 T1 1.44850 Fp 0.116121 + vp 0.0200001 ve 0.142946 FE 0.0228193 S0d + 14725.4ost 0.111986 +------------------------ +LS params S0v 11366.0 T1 1.16562 Fp 0.0655781 + vp 0.0100001 ve 0.143583 FE 0.0319775 S0d + 12907.1ost 0.166618 +------------------------ +LS params S0v 9891.00 T1 0.750984 Fp 0.427580 + vp 0.0700001 ve 0.166773 FE 0.0667531 S0d + 9519.46ost 0.0861280 +------------------------ +LS params S0v 11564.8 T1 0.960096 Fp 0.305224 + vp 0.0300001 ve 0.164830 FE 0.0637748 S0d + 11686.3ost 0.0710521 +------------------------ +LS params S0v 12096.7 T1 1.00453 Fp 0.175722 + vp 0.0600001 ve 0.123092 FE 0.0658284 S0d + 14046.5ost 0.102991 +% Expression must be a structure in this context: OUTPUT_STRUCT. +% Execution halted at: RUN_2CXM_PHANTOM 194 C:\Users\ben dickie\Desktop\JE + Software\run_2cxm_phantom.pro +% $MAIN$ +cleanup complete + diff --git a/Joint Fitting/log3.log b/Joint Fitting/log3.log new file mode 100644 index 0000000..7dc2892 --- /dev/null +++ b/Joint Fitting/log3.log @@ -0,0 +1,63 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Compiled module: READ_ANALYZE. +% Compiled module: IDLFFANALYZE__DEFINE. +% Compiled module: RANDOMGAUSS. +% Compiled module: DCEMRIPROCESSOR_FREES0_DEFINE. +init complete +Finished data readin +% Compiled module: LINECOLORS. +% LINECOLORS: 256 color table indices set for WIN device. +% Compiled module: SAMPLE_FROM_ARRAY. +------------------------ +% Compiled module: MPCURVEFIT. +% Compiled module: MPFIT. +% Compiled module: FLASH_FUNC. +% Compiled module: TOFTS_OST_EXPC. +% Compiled module: INTERPOL. +% Compiled module: EXPCONVOLUTION. +% Compiled module: TWOCXM_VFA_JFIT_DC. +LS params S0v 10313.7 T1 0.800129 Fp 0.255977 + vp 0.100000 ve 0.205742 FE 0.0594433 S0d + 10313.7ost 0.0771807FAerror 1.00000 +------------------------ +LS params S0v 10020.2 T1 0.805717 Fp 0.326715 + vp 0.0500001 ve 0.127166 FE 0.0783145 S0d + 10020.2ost 0.110219FAerror 1.00000 +------------------------ +LS params S0v 10449.9 T1 0.848387 Fp 0.320612 + vp 0.0900001 ve 0.904325 FE 0.0336438 S0d + 10449.9ost 0.0920955FAerror 1.00000 +------------------------ +LS params S0v 10410.8 T1 1.05967 Fp 0.0967878 + vp 0.0200001 ve 0.191890 FE 0.0785263 S0d + 10410.8ost 0.0125952FAerror 1.00000 +------------------------ +LS params S0v 11315.3 T1 1.18395 Fp 0.251416 + vp 0.0200001 ve 0.125688 FE 0.0508440 S0d + 11315.3ost 0.154195FAerror 1.00000 +------------------------ +LS params S0v 12763.6 T1 1.30751 Fp 0.123997 + vp 0.0300001 ve 0.305022 FE 0.0234727 S0d + 12763.6ost 0.101482FAerror 1.00000 +------------------------ +LS params S0v 10367.6 T1 1.00093 Fp 0.0717640 + vp 0.0200001 ve 0.155369 FE 0.0521980 S0d + 10367.6ost 0.130721FAerror 1.00000 +------------------------ +LS params S0v 10038.1 T1 0.775033 Fp 0.424450 + vp 0.0600001 ve 0.151433 FE 0.0666704 S0d + 10038.1ost 0.0923889FAerror 1.00000 +------------------------ +LS params S0v 11625.3 T1 0.972101 Fp 0.315133 + vp 0.0300001 ve 0.164573 FE 0.0659051 S0d + 11625.3ost 0.0700846FAerror 1.00000 +------------------------ +LS params S0v 10825.0 T1 0.830890 Fp 0.241824 + vp 0.0900001 ve 0.169133 FE 0.0868804 S0d + 10825.0ost 0.0941253FAerror 1.00000 +% Expression must be a structure in this context: OUTPUT_STRUCT. +% Execution halted at: RUN_2CXM_PHANTOM 194 C:\Users\ben dickie\Desktop\JE + Software\run_2cxm_phantom.pro +% $MAIN$ +cleanup complete + diff --git a/Joint Fitting/log4.log b/Joint Fitting/log4.log new file mode 100644 index 0000000..a43fd04 --- /dev/null +++ b/Joint Fitting/log4.log @@ -0,0 +1,63 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Compiled module: READ_ANALYZE. +% Compiled module: IDLFFANALYZE__DEFINE. +% Compiled module: RANDOMGAUSS. +% Compiled module: DCEMRIPROCESSOR_FREES0_DEFINE. +init complete +Finished data readin +% Compiled module: LINECOLORS. +% LINECOLORS: 256 color table indices set for WIN device. +% Compiled module: SAMPLE_FROM_ARRAY. +------------------------ +% Compiled module: MPCURVEFIT. +% Compiled module: MPFIT. +% Compiled module: FLASH_FUNC. +% Compiled module: TOFTS_OST_EXPC. +% Compiled module: INTERPOL. +% Compiled module: EXPCONVOLUTION. +% Compiled module: TWOCXM_IFIT_DC. +LS params S0v 10163.5 T1 0.784172 Fp 0.786775 + vp 0.330000 ve 0.641260 FE 0.178495 S0d + 9950.87ost 0.0731435 +------------------------ +LS params S0v 11025.1 T1 0.954619 Fp 0.786455 + vp 0.0900001 ve 0.287075 FE 0.189240 S0d + 12687.3ost 0.121798 +------------------------ +LS params S0v 10430.7 T1 0.856579 Fp 0.965293 + vp 0.250000 ve 0.749903 FE 0.119813 S0d + 10623.5ost 0.0945162 +------------------------ +LS params S0v 9569.78 T1 0.920049 Fp 1.17494 + vp 0.0200001 ve 0.811459 FE 0.207563 S0d + 8393.02ost 0.0607935 +------------------------ +LS params S0v 9765.57 T1 0.924756 Fp 0.804356 + vp 0.170000 ve 0.629215 FE 0.223877 S0d + 7759.48ost 0.108708 +------------------------ +LS params S0v 13693.3 T1 1.44850 Fp 0.312332 + vp 0.0700001 ve 0.591658 FE 0.0618491 S0d + 14725.4ost 0.106996 +------------------------ +LS params S0v 11366.0 T1 1.16562 Fp 0.251359 + vp 0.0100001 ve 0.350413 FE 0.105084 S0d + 12907.1ost 0.166645 +------------------------ +LS params S0v 9891.00 T1 0.750984 Fp 1.25956 + vp 0.210000 ve 0.494860 FE 0.203568 S0d + 9519.46ost 0.0833333 +------------------------ +LS params S0v 11564.8 T1 0.960096 Fp 0.962586 + vp 0.0800001 ve 0.480929 FE 0.201867 S0d + 11686.3ost 0.0723013 +------------------------ +LS params S0v 12096.7 T1 1.00453 Fp 0.531659 + vp 0.180000 ve 0.371190 FE 0.195159 S0d + 14046.5ost 0.104539 +% Expression must be a structure in this context: OUTPUT_STRUCT. +% Execution halted at: RUN_2CXM_PHANTOM 194 C:\Users\ben dickie\Desktop\JE + Software\run_2cxm_phantom.pro +% $MAIN$ +cleanup complete + diff --git a/Joint Fitting/log5.log b/Joint Fitting/log5.log new file mode 100644 index 0000000..68b03c5 --- /dev/null +++ b/Joint Fitting/log5.log @@ -0,0 +1,5 @@ +% Compiled module: RUN_2CXM_PHANTOM. +% Keyword TAG not allowed in call to: RUN_2CXM_PHANTOM +% Execution halted at: $MAIN$ + +% Interrupted at: $MAIN$ diff --git a/Joint Fitting/mpcurvefit.pro b/Joint Fitting/mpcurvefit.pro new file mode 100644 index 0000000..9e2fcc2 --- /dev/null +++ b/Joint Fitting/mpcurvefit.pro @@ -0,0 +1,616 @@ +;+ +; NAME: +; MPCURVEFIT +; +; AUTHOR: +; Craig B. Markwardt, NASA/GSFC Code 662, Greenbelt, MD 20770 +; craigm@lheamail.gsfc.nasa.gov +; UPDATED VERSIONs can be found on my WEB PAGE: +; http://cow.physics.wisc.edu/~craigm/idl/idl.html +; +; PURPOSE: +; Perform Levenberg-Marquardt least-squares fit (replaces CURVEFIT) +; +; MAJOR TOPICS: +; Curve and Surface Fitting +; +; CALLING SEQUENCE: +; YFIT = MPCURVEFIT(X, Y, WEIGHTS, P, [SIGMA,] FUNCTION_NAME=FUNC, +; ITER=iter, ITMAX=itmax, +; CHISQ=chisq, NFREE=nfree, DOF=dof, +; NFEV=nfev, COVAR=covar, [/NOCOVAR, ] [/NODERIVATIVE, ] +; FUNCTARGS=functargs, PARINFO=parinfo, +; FTOL=ftol, XTOL=xtol, GTOL=gtol, TOL=tol, +; ITERPROC=iterproc, ITERARGS=iterargs, +; NPRINT=nprint, QUIET=quiet, +; ERRMSG=errmsg, STATUS=status) +; +; DESCRIPTION: +; +; MPCURVEFIT fits a user-supplied model -- in the form of an IDL +; function -- to a set of user-supplied data. MPCURVEFIT calls +; MPFIT, the MINPACK-1 least-squares minimizer, to do the main +; work. +; +; Given the data and their uncertainties, MPCURVEFIT finds the best +; set of model parameters which match the data (in a least-squares +; sense) and returns them in the parameter P. +; +; MPCURVEFIT returns the best fit function. +; +; The user must supply the following items: +; - An array of independent variable values ("X"). +; - An array of "measured" *dependent* variable values ("Y"). +; - An array of weighting values ("WEIGHTS"). +; - The name of an IDL function which computes Y given X ("FUNC"). +; - Starting guesses for all of the parameters ("P"). +; +; There are very few restrictions placed on X, Y or FUNCT. Simply +; put, FUNCT must map the "X" values into "Y" values given the +; model parameters. The "X" values may represent any independent +; variable (not just Cartesian X), and indeed may be multidimensional +; themselves. For example, in the application of image fitting, X +; may be a 2xN array of image positions. +; +; MPCURVEFIT carefully avoids passing large arrays where possible to +; improve performance. +; +; See below for an example of usage. +; +; USER FUNCTION +; +; The user must define a function which returns the model value. For +; applications which use finite-difference derivatives -- the default +; -- the user function should be declared in the following way: +; +; ; MYFUNCT - example user function +; ; X - input independent variable (vector same size as data) +; ; P - input parameter values (N-element array) +; ; YMOD - upon return, user function values +; ; DP - upon return, the user function must return +; ; an ARRAY(M,N) of derivatives in this parameter +; ; +; PRO MYFUNCT, x, p, ymod, dp +; ymod = F(x, p) ;; Model function +; +; if n_params() GE 4 then begin +; ; Create derivative and compute derivative array +; dp = make_array(n_elements(x), n_elements(p), value=x[0]*0) +; +; ; Compute derivative if requested by caller +; for i = 0, n_elements(p)-1 do dp(*,i) = FGRAD(x, p, i) +; endif +; END +; +; where FGRAD(x, p, i) is a model function which computes the +; derivative of the model F(x,p) with respect to parameter P(i) at X. +; The returned array YMOD must have the same dimensions and type as +; the "measured" Y values. The returned array DP[i,j] is the +; derivative of the ith function value with respect to the jth +; parameter. +; +; User functions may also indicate a fatal error condition +; using the ERROR_CODE common block variable, as described +; below under the MPFIT_ERROR common block definition. +; +; If NODERIVATIVE=1, then MPCURVEFIT will never request explicit +; derivatives from the user function, and instead will user numerical +; estimates (i.e. by calling the user function multiple times). +; +; CONSTRAINING PARAMETER VALUES WITH THE PARINFO KEYWORD +; +; The behavior of MPFIT can be modified with respect to each +; parameter to be fitted. A parameter value can be fixed; simple +; boundary constraints can be imposed; limitations on the parameter +; changes can be imposed; properties of the automatic derivative can +; be modified; and parameters can be tied to one another. +; +; These properties are governed by the PARINFO structure, which is +; passed as a keyword parameter to MPFIT. +; +; PARINFO should be an array of structures, one for each parameter. +; Each parameter is associated with one element of the array, in +; numerical order. The structure can have the following entries +; (none are required): +; +; .VALUE - the starting parameter value (but see the START_PARAMS +; parameter for more information). +; +; .FIXED - a boolean value, whether the parameter is to be held +; fixed or not. Fixed parameters are not varied by +; MPFIT, but are passed on to MYFUNCT for evaluation. +; +; .LIMITED - a two-element boolean array. If the first/second +; element is set, then the parameter is bounded on the +; lower/upper side. A parameter can be bounded on both +; sides. Both LIMITED and LIMITS must be given +; together. +; +; .LIMITS - a two-element float or double array. Gives the +; parameter limits on the lower and upper sides, +; respectively. Zero, one or two of these values can be +; set, depending on the values of LIMITED. Both LIMITED +; and LIMITS must be given together. +; +; .PARNAME - a string, giving the name of the parameter. The +; fitting code of MPFIT does not use this tag in any +; way. However, the default ITERPROC will print the +; parameter name if available. +; +; .STEP - the step size to be used in calculating the numerical +; derivatives. If set to zero, then the step size is +; computed automatically. Ignored when AUTODERIVATIVE=0. +; This value is superceded by the RELSTEP value. +; +; .RELSTEP - the *relative* step size to be used in calculating +; the numerical derivatives. This number is the +; fractional size of the step, compared to the +; parameter value. This value supercedes the STEP +; setting. If the parameter is zero, then a default +; step size is chosen. +; +; .MPSIDE - the sidedness of the finite difference when computing +; numerical derivatives. This field can take four +; values: +; +; 0 - one-sided derivative computed automatically +; 1 - one-sided derivative (f(x+h) - f(x) )/h +; -1 - one-sided derivative (f(x) - f(x-h))/h +; 2 - two-sided derivative (f(x+h) - f(x-h))/(2*h) +; +; Where H is the STEP parameter described above. The +; "automatic" one-sided derivative method will chose a +; direction for the finite difference which does not +; violate any constraints. The other methods do not +; perform this check. The two-sided method is in +; principle more precise, but requires twice as many +; function evaluations. Default: 0. +; +; .MPMAXSTEP - the maximum change to be made in the parameter +; value. During the fitting process, the parameter +; will never be changed by more than this value in +; one iteration. +; +; A value of 0 indicates no maximum. Default: 0. +; +; .TIED - a string expression which "ties" the parameter to other +; free or fixed parameters. Any expression involving +; constants and the parameter array P are permitted. +; Example: if parameter 2 is always to be twice parameter +; 1 then use the following: parinfo(2).tied = '2 * P(1)'. +; Since they are totally constrained, tied parameters are +; considered to be fixed; no errors are computed for them. +; [ NOTE: the PARNAME can't be used in expressions. ] +; +; .MPPRINT - if set to 1, then the default ITERPROC will print the +; parameter value. If set to 0, the parameter value +; will not be printed. This tag can be used to +; selectively print only a few parameter values out of +; many. Default: 1 (all parameters printed) +; +; +; Future modifications to the PARINFO structure, if any, will involve +; adding structure tags beginning with the two letters "MP". +; Therefore programmers are urged to avoid using tags starting with +; the same letters; otherwise they are free to include their own +; fields within the PARINFO structure, and they will be ignored. +; +; PARINFO Example: +; parinfo = replicate({value:0.D, fixed:0, limited:[0,0], $ +; limits:[0.D,0]}, 5) +; parinfo(0).fixed = 1 +; parinfo(4).limited(0) = 1 +; parinfo(4).limits(0) = 50.D +; parinfo(*).value = [5.7D, 2.2, 500., 1.5, 2000.] +; +; A total of 5 parameters, with starting values of 5.7, +; 2.2, 500, 1.5, and 2000 are given. The first parameter +; is fixed at a value of 5.7, and the last parameter is +; constrained to be above 50. +; +; INPUTS: +; X - Array of independent variable values. +; +; Y - Array of "measured" dependent variable values. Y should have +; the same data type as X. The function FUNCT should map +; X->Y. +; +; WEIGHTS - Array of weights to be used in calculating the +; chi-squared value. If WEIGHTS is specified then the ERR +; parameter is ignored. The chi-squared value is computed +; as follows: +; +; CHISQ = TOTAL( (Y-FUNCT(X,P))^2 * ABS(WEIGHTS) ) +; +; Here are common values of WEIGHTS: +; +; 1D/ERR^2 - Normal weighting (ERR is the measurement error) +; 1D/Y - Poisson weighting (counting statistics) +; 1D - Unweighted +; +; P - An array of starting values for each of the parameters of the +; model. The number of parameters should be fewer than the +; number of measurements. Also, the parameters should have the +; same data type as the measurements (double is preferred). +; +; Upon successful completion the new parameter values are +; returned in P. +; +; If both START_PARAMS and PARINFO are passed, then the starting +; *value* is taken from START_PARAMS, but the *constraints* are +; taken from PARINFO. +; +; SIGMA - The formal 1-sigma errors in each parameter, computed from +; the covariance matrix. If a parameter is held fixed, or +; if it touches a boundary, then the error is reported as +; zero. +; +; If the fit is unweighted (i.e. no errors were given, or +; the weights were uniformly set to unity), then SIGMA will +; probably not represent the true parameter uncertainties. +; +; *If* you can assume that the true reduced chi-squared +; value is unity -- meaning that the fit is implicitly +; assumed to be of good quality -- then the estimated +; parameter uncertainties can be computed by scaling SIGMA +; by the measured chi-squared value. +; +; DOF = N_ELEMENTS(X) - N_ELEMENTS(P) ; deg of freedom +; CSIGMA = SIGMA * SQRT(CHISQ / DOF) ; scaled uncertainties +; +; RETURNS: +; +; Returns the array containing the best-fitting function. +; +; KEYWORD PARAMETERS: +; +; CHISQ - the value of the summed, squared, weighted residuals for +; the returned parameter values, i.e. the chi-square value. +; +; COVAR - the covariance matrix for the set of parameters returned +; by MPFIT. The matrix is NxN where N is the number of +; parameters. The square root of the diagonal elements +; gives the formal 1-sigma statistical errors on the +; parameters IF errors were treated "properly" in MYFUNC. +; Parameter errors are also returned in PERROR. +; +; To compute the correlation matrix, PCOR, use this: +; IDL> PCOR = COV * 0 +; IDL> FOR i = 0, n-1 DO FOR j = 0, n-1 DO $ +; PCOR(i,j) = COV(i,j)/sqrt(COV(i,i)*COV(j,j)) +; +; If NOCOVAR is set or MPFIT terminated abnormally, then +; COVAR is set to a scalar with value !VALUES.D_NAN. +; +; DOF - number of degrees of freedom, computed as +; DOF = N_ELEMENTS(DEVIATES) - NFREE +; Note that this doesn't account for pegged parameters (see +; NPEGGED). +; +; ERRMSG - a string error or warning message is returned. +; +; FTOL - a nonnegative input variable. Termination occurs when both +; the actual and predicted relative reductions in the sum of +; squares are at most FTOL (and STATUS is accordingly set to +; 1 or 3). Therefore, FTOL measures the relative error +; desired in the sum of squares. Default: 1D-10 +; +; FUNCTION_NAME - a scalar string containing the name of an IDL +; procedure to compute the user model values, as +; described above in the "USER MODEL" section. +; +; FUNCTARGS - A structure which contains the parameters to be passed +; to the user-supplied function specified by FUNCT via +; the _EXTRA mechanism. This is the way you can pass +; additional data to your user-supplied function without +; using common blocks. +; +; By default, no extra parameters are passed to the +; user-supplied function. +; +; GTOL - a nonnegative input variable. Termination occurs when the +; cosine of the angle between fvec and any column of the +; jacobian is at most GTOL in absolute value (and STATUS is +; accordingly set to 4). Therefore, GTOL measures the +; orthogonality desired between the function vector and the +; columns of the jacobian. Default: 1D-10 +; +; ITER - the number of iterations completed. +; +; ITERARGS - The keyword arguments to be passed to ITERPROC via the +; _EXTRA mechanism. This should be a structure, and is +; similar in operation to FUNCTARGS. +; Default: no arguments are passed. +; +; ITERPROC - The name of a procedure to be called upon each NPRINT +; iteration of the MPFIT routine. It should be declared +; in the following way: +; +; PRO ITERPROC, FUNCT, p, iter, fnorm, FUNCTARGS=fcnargs, $ +; PARINFO=parinfo, QUIET=quiet, ... +; ; perform custom iteration update +; END +; +; ITERPROC must either accept all three keyword +; parameters (FUNCTARGS, PARINFO and QUIET), or at least +; accept them via the _EXTRA keyword. +; +; FUNCT is the user-supplied function to be minimized, +; P is the current set of model parameters, ITER is the +; iteration number, and FUNCTARGS are the arguments to be +; passed to FUNCT. FNORM should be the +; chi-squared value. QUIET is set when no textual output +; should be printed. See below for documentation of +; PARINFO. +; +; In implementation, ITERPROC can perform updates to the +; terminal or graphical user interface, to provide +; feedback while the fit proceeds. If the fit is to be +; stopped for any reason, then ITERPROC should set the +; common block variable ERROR_CODE to negative value (see +; MPFIT_ERROR common block below). In principle, +; ITERPROC should probably not modify the parameter +; values, because it may interfere with the algorithm's +; stability. In practice it is allowed. +; +; Default: an internal routine is used to print the +; parameter values. +; +; ITMAX - The maximum number of iterations to perform. If the +; number is exceeded, then the STATUS value is set to 5 +; and MPFIT returns. +; Default: 200 iterations +; +; NFEV - the number of FUNCT function evaluations performed. +; +; NFREE - the number of free parameters in the fit. This includes +; parameters which are not FIXED and not TIED, but it does +; include parameters which are pegged at LIMITS. +; +; NOCOVAR - set this keyword to prevent the calculation of the +; covariance matrix before returning (see COVAR) +; +; NODERIVATIVE - if set, then the user function will not be queried +; for analytical derivatives, and instead the +; derivatives will be computed by finite differences +; (and according to the PARINFO derivative settings; +; see above for a description). +; +; NPRINT - The frequency with which ITERPROC is called. A value of +; 1 indicates that ITERPROC is called with every iteration, +; while 2 indicates every other iteration, etc. Note that +; several Levenberg-Marquardt attempts can be made in a +; single iteration. +; Default value: 1 +; +; PARINFO - Provides a mechanism for more sophisticated constraints +; to be placed on parameter values. When PARINFO is not +; passed, then it is assumed that all parameters are free +; and unconstrained. Values in PARINFO are never +; modified during a call to MPFIT. +; +; See description above for the structure of PARINFO. +; +; Default value: all parameters are free and unconstrained. +; +; QUIET - set this keyword when no textual output should be printed +; by MPFIT +; +; STATUS - an integer status code is returned. All values other +; than zero can represent success. It can have one of the +; following values: +; +; 0 improper input parameters. +; +; 1 both actual and predicted relative reductions +; in the sum of squares are at most FTOL. +; +; 2 relative error between two consecutive iterates +; is at most XTOL +; +; 3 conditions for STATUS = 1 and STATUS = 2 both hold. +; +; 4 the cosine of the angle between fvec and any +; column of the jacobian is at most GTOL in +; absolute value. +; +; 5 the maximum number of iterations has been reached +; +; 6 FTOL is too small. no further reduction in +; the sum of squares is possible. +; +; 7 XTOL is too small. no further improvement in +; the approximate solution x is possible. +; +; 8 GTOL is too small. fvec is orthogonal to the +; columns of the jacobian to machine precision. +; +; TOL - synonym for FTOL. Use FTOL instead. +; +; XTOL - a nonnegative input variable. Termination occurs when the +; relative error between two consecutive iterates is at most +; XTOL (and STATUS is accordingly set to 2 or 3). Therefore, +; XTOL measures the relative error desired in the approximate +; solution. Default: 1D-10 +; +; YERROR - upon return, the root-mean-square variance of the +; residuals. +; +; +; EXAMPLE: +; +; ; First, generate some synthetic data +; npts = 200 +; x = dindgen(npts) * 0.1 - 10. ; Independent variable +; yi = gauss1(x, [2.2D, 1.4, 3000.]) ; "Ideal" Y variable +; y = yi + randomn(seed, npts) * sqrt(1000. + yi); Measured, w/ noise +; sy = sqrt(1000.D + y) ; Poisson errors +; +; ; Now fit a Gaussian to see how well we can recover +; p0 = [1.D, 1., 1000.] ; Initial guess +; yfit = mpcurvefit(x, y, 1/sy^2, p0, $ ; Fit a function +; FUNCTION_NAME='GAUSS1P',/autoderivative) +; print, p +; +; Generates a synthetic data set with a Gaussian peak, and Poisson +; statistical uncertainty. Then the same function is fitted to the +; data to see how close we can get. GAUSS1 and GAUSS1P are +; available from the same web page. +; +; +; COMMON BLOCKS: +; +; COMMON MPFIT_ERROR, ERROR_CODE +; +; User routines may stop the fitting process at any time by +; setting an error condition. This condition may be set in either +; the user's model computation routine (MYFUNCT), or in the +; iteration procedure (ITERPROC). +; +; To stop the fitting, the above common block must be declared, +; and ERROR_CODE must be set to a negative number. After the user +; procedure or function returns, MPFIT checks the value of this +; common block variable and exits immediately if the error +; condition has been set. By default the value of ERROR_CODE is +; zero, indicating a successful function/procedure call. +; +; REFERENCES: +; +; MINPACK-1, Jorge More', available from netlib (www.netlib.org). +; "Optimization Software Guide," Jorge More' and Stephen Wright, +; SIAM, *Frontiers in Applied Mathematics*, Number 14. +; +; MODIFICATION HISTORY: +; Translated from MPFITFUN, 25 Sep 1999, CM +; Alphabetized documented keywords, 02 Oct 1999, CM +; Added QUERY keyword and query checking of MPFIT, 29 Oct 1999, CM +; Check to be sure that X and Y are present, 02 Nov 1999, CM +; Documented SIGMA for unweighted fits, 03 Nov 1999, CM +; Changed to ERROR_CODE for error condition, 28 Jan 2000, CM +; Copying permission terms have been liberalized, 26 Mar 2000, CM +; Propagated improvements from MPFIT, 17 Dec 2000, CM +; Corrected behavior of NODERIVATIVE, 13 May 2002, CM +; Documented RELSTEP field of PARINFO (!!), CM, 25 Oct 2002 +; Make more consistent with comparable IDL routines, 30 Jun 2003, CM +; Minor documentation adjustment, 03 Feb 2004, CM +; Fix error in documentation, 26 Aug 2005, CM +; Convert to IDL 5 array syntax (!), 16 Jul 2006, CM +; Move STRICTARR compile option inside each function/procedure, 9 Oct 2006 +; Fix bug in handling of explicit derivatives with errors/weights +; (the weights were not being applied), CM, 2012-07-22 +; Add more documentation on calling interface for user function and +; parameter derivatives, CM, 2012-07-22 +; +; $Id: mpcurvefit.pro,v 1.11 2012/07/22 21:08:58 cmarkwar Exp $ +;- +; Copyright (C) 1997-2000, 2002, 2003, 2004, 2005, 2012, Craig Markwardt +; This software is provided as is without any warranty whatsoever. +; Permission to use, copy, modify, and distribute modified or +; unmodified copies is granted, provided this copyright and disclaimer +; are included unchanged. +;- + +FORWARD_FUNCTION mpcurvefit_eval, mpcurvefit, mpfit + +; This is the call-back function for MPFIT. It evaluates the +; function, subtracts the data, and returns the residuals. +function mpcurvefit_eval, p, dp, _EXTRA=extra + + COMPILE_OPT strictarr + common mpcurvefit_common, fcn, x, y, wts, f, fcnargs + + ;; The function is evaluated here. There are four choices, + ;; depending on whether (a) FUNCTARGS was passed to MPCURVEFIT, which + ;; is passed to this function as "hf"; or (b) the derivative + ;; parameter "dp" is passed, meaning that derivatives should be + ;; calculated analytically by the function itself. + if n_elements(fcnargs) GT 0 then begin + if n_params() GT 1 then call_procedure, fcn, x, p, f, dp,_EXTRA=fcnargs $ + else call_procedure, fcn, x, p, f, _EXTRA=fcnargs + endif else begin + if n_params() GT 1 then call_procedure, fcn, x, p, f, dp $ + else call_procedure, fcn, x, p, f + endelse + + ;; Compute the deviates, applying the weights + result = (y-f)*wts + + ;; Apply weights to derivative quantities + if n_params() GT 1 then begin + np = n_elements(p) + nf = n_elements(f) + for j = 0L, np-1 do dp[j*nf] = dp[j*nf:j*nf+nf-1] * wts + endif + + ;; Make sure the returned result is one-dimensional. + result = reform(result, n_elements(result), /overwrite) + return, result + +end + +function mpcurvefit, x, y, wts, p, perror, function_name=fcn, $ + iter=iter, itmax=maxiter, $ + chisq=bestnorm, nfree=nfree, dof=dof, $ + nfev=nfev, covar=covar, nocovar=nocovar, yerror=yerror, $ + noderivative=noderivative, tol=tol, ftol=ftol, $ + FUNCTARGS=fa, parinfo=parinfo, $ + errmsg=errmsg, STATUS=status, QUIET=quiet, $ + query=query, _EXTRA=extra + + COMPILE_OPT strictarr + status = 0L + errmsg = '' + + ;; Detect MPFIT and crash if it was not found + catch, catcherror + if catcherror NE 0 then begin + MPFIT_NOTFOUND: + catch, /cancel + message, 'ERROR: the required function MPFIT must be in your IDL path', /info + return, !values.d_nan + endif + if mpfit(/query) NE 1 then goto, MPFIT_NOTFOUND + catch, /cancel + if keyword_set(query) then return, 1 + + if n_params() EQ 0 then begin + message, "USAGE: YFIT = MPCURVEFIT(X, Y, WTS, P, DP)", /info + return, !values.d_nan + endif + if n_elements(x) EQ 0 OR n_elements(y) EQ 0 then begin + message, 'ERROR: X and Y must be defined', /info + return, !values.d_nan + endif + if n_elements(fcn) EQ 0 then fcn = 'funct' + if n_elements(noderivative) EQ 0 then noderivative = 0 + + common mpcurvefit_common, fc, xc, yc, wc, mc, ac + fc = fcn & xc = x & yc = y & wc = sqrt(abs(wts)) & mc = 0L + ac = 0 & dummy = size(temporary(ac)) + if n_elements(fa) GT 0 then ac = fa + + if n_elements(tol) GT 0 then ftol = tol + + result = mpfit('mpcurvefit_eval', p, maxiter=maxiter, $ + autoderivative=noderivative, ftol=ftol, $ + parinfo=parinfo, STATUS=status, nfev=nfev, BESTNORM=bestnorm,$ + covar=covar, perror=perror, niter=iter, nfree=nfree, dof=dof,$ + ERRMSG=errmsg, quiet=quiet, _EXTRA=extra) + + ;; Retrieve the fit value + yfit = temporary(mc) + ;; Now do some clean-up + xc = 0 & yc = 0 & wc = 0 & mc = 0 & ac = 0 + + if NOT keyword_set(quiet) AND errmsg NE '' then $ + message, errmsg, /info $ + else $ + p = result + + yerror = p[0]*0 + if n_elements(dof) GT 0 AND dof[0] GT 0 then begin + yerror[0] = sqrt( total( (y-yfit)^2 ) / dof[0] ) + endif + + return, yfit +end \ No newline at end of file diff --git a/Joint Fitting/mpfit.pro b/Joint Fitting/mpfit.pro new file mode 100644 index 0000000..b30cffd --- /dev/null +++ b/Joint Fitting/mpfit.pro @@ -0,0 +1,3737 @@ +;+ +; NAME: +; MPFIT +; +; AUTHOR: +; Craig B. Markwardt, NASA/GSFC Code 662, Greenbelt, MD 20770 +; craigm@lheamail.gsfc.nasa.gov +; UPDATED VERSIONs can be found on my WEB PAGE: +; http://cow.physics.wisc.edu/~craigm/idl/idl.html +; +; PURPOSE: +; Perform Levenberg-Marquardt least-squares minimization (MINPACK-1) +; +; MAJOR TOPICS: +; Curve and Surface Fitting +; +; CALLING SEQUENCE: +; parms = MPFIT(MYFUNCT, start_parms, FUNCTARGS=fcnargs, NFEV=nfev, +; MAXITER=maxiter, ERRMSG=errmsg, NPRINT=nprint, QUIET=quiet, +; FTOL=ftol, XTOL=xtol, GTOL=gtol, NITER=niter, +; STATUS=status, ITERPROC=iterproc, ITERARGS=iterargs, +; COVAR=covar, PERROR=perror, BESTNORM=bestnorm, +; PARINFO=parinfo) +; +; DESCRIPTION: +; +; MPFIT uses the Levenberg-Marquardt technique to solve the +; least-squares problem. In its typical use, MPFIT will be used to +; fit a user-supplied function (the "model") to user-supplied data +; points (the "data") by adjusting a set of parameters. MPFIT is +; based upon MINPACK-1 (LMDIF.F) by More' and collaborators. +; +; For example, a researcher may think that a set of observed data +; points is best modelled with a Gaussian curve. A Gaussian curve is +; parameterized by its mean, standard deviation and normalization. +; MPFIT will, within certain constraints, find the set of parameters +; which best fits the data. The fit is "best" in the least-squares +; sense; that is, the sum of the weighted squared differences between +; the model and data is minimized. +; +; The Levenberg-Marquardt technique is a particular strategy for +; iteratively searching for the best fit. This particular +; implementation is drawn from MINPACK-1 (see NETLIB), and seems to +; be more robust than routines provided with IDL. This version +; allows upper and lower bounding constraints to be placed on each +; parameter, or the parameter can be held fixed. +; +; The IDL user-supplied function should return an array of weighted +; deviations between model and data. In a typical scientific problem +; the residuals should be weighted so that each deviate has a +; gaussian sigma of 1.0. If X represents values of the independent +; variable, Y represents a measurement for each value of X, and ERR +; represents the error in the measurements, then the deviates could +; be calculated as follows: +; +; DEVIATES = (Y - F(X)) / ERR +; +; where F is the function representing the model. You are +; recommended to use the convenience functions MPFITFUN and +; MPFITEXPR, which are driver functions that calculate the deviates +; for you. If ERR are the 1-sigma uncertainties in Y, then +; +; TOTAL( DEVIATES^2 ) +; +; will be the total chi-squared value. MPFIT will minimize the +; chi-square value. The values of X, Y and ERR are passed through +; MPFIT to the user-supplied function via the FUNCTARGS keyword. +; +; Simple constraints can be placed on parameter values by using the +; PARINFO keyword to MPFIT. See below for a description of this +; keyword. +; +; MPFIT does not perform more general optimization tasks. See TNMIN +; instead. MPFIT is customized, based on MINPACK-1, to the +; least-squares minimization problem. +; +; USER FUNCTION +; +; The user must define a function which returns the appropriate +; values as specified above. The function should return the weighted +; deviations between the model and the data. For applications which +; use finite-difference derivatives -- the default -- the user +; function should be declared in the following way: +; +; FUNCTION MYFUNCT, p, X=x, Y=y, ERR=err +; ; Parameter values are passed in "p" +; model = F(x, p) +; return, (y-model)/err +; END +; +; See below for applications with explicit derivatives. +; +; The keyword parameters X, Y, and ERR in the example above are +; suggestive but not required. Any parameters can be passed to +; MYFUNCT by using the FUNCTARGS keyword to MPFIT. Use MPFITFUN and +; MPFITEXPR if you need ideas on how to do that. The function *must* +; accept a parameter list, P. +; +; In general there are no restrictions on the number of dimensions in +; X, Y or ERR. However the deviates *must* be returned in a +; one-dimensional array, and must have the same type (float or +; double) as the input arrays. +; +; See below for error reporting mechanisms. +; +; +; CHECKING STATUS AND HANNDLING ERRORS +; +; Upon return, MPFIT will report the status of the fitting operation +; in the STATUS and ERRMSG keywords. The STATUS keyword will contain +; a numerical code which indicates the success or failure status. +; Generally speaking, any value 1 or greater indicates success, while +; a value of 0 or less indicates a possible failure. The ERRMSG +; keyword will contain a text string which should describe the error +; condition more fully. +; +; By default, MPFIT will trap fatal errors and report them to the +; caller gracefully. However, during the debugging process, it is +; often useful to halt execution where the error occurred. When you +; set the NOCATCH keyword, MPFIT will not do any special error +; trapping, and execution will stop whereever the error occurred. +; +; MPFIT does not explicitly change the !ERROR_STATE variable +; (although it may be changed implicitly if MPFIT calls MESSAGE). It +; is the caller's responsibility to call MESSAGE, /RESET to ensure +; that the error state is initialized before calling MPFIT. +; +; User functions may also indicate non-fatal error conditions using +; the ERROR_CODE common block variable, as described below under the +; MPFIT_ERROR common block definition (by setting ERROR_CODE to a +; number between -15 and -1). When the user function sets an error +; condition via ERROR_CODE, MPFIT will gracefully exit immediately +; and report this condition to the caller. The ERROR_CODE is +; returned in the STATUS keyword in that case. +; +; +; EXPLICIT DERIVATIVES +; +; In the search for the best-fit solution, MPFIT by default +; calculates derivatives numerically via a finite difference +; approximation. The user-supplied function need not calculate the +; derivatives explicitly. However, the user function *may* calculate +; the derivatives if desired, but only if the model function is +; declared with an additional position parameter, DP, as described +; below. If the user function does not accept this additional +; parameter, MPFIT will report an error. As a practical matter, it +; is often sufficient and even faster to allow MPFIT to calculate the +; derivatives numerically, but this option is available for users who +; wish more control over the fitting process. +; +; There are two ways to enable explicit derivatives. First, the user +; can set the keyword AUTODERIVATIVE=0, which is a global switch for +; all parameters. In this case, MPFIT will request explicit +; derivatives for every free parameter. +; +; Second, the user may request explicit derivatives for specifically +; selected parameters using the PARINFO.MPSIDE=3 (see "CONSTRAINING +; PARAMETER VALUES WITH THE PARINFO KEYWORD" below). In this +; strategy, the user picks and chooses which parameter derivatives +; are computed explicitly versus numerically. When PARINFO[i].MPSIDE +; EQ 3, then the ith parameter derivative is computed explicitly. +; +; The keyword setting AUTODERIVATIVE=0 always globally overrides the +; individual values of PARINFO.MPSIDE. Setting AUTODERIVATIVE=0 is +; equivalent to resetting PARINFO.MPSIDE=3 for all parameters. +; +; Even if the user requests explicit derivatives for some or all +; parameters, MPFIT will not always request explicit derivatives on +; every user function call. +; +; EXPLICIT DERIVATIVES - CALLING INTERFACE +; +; When AUTODERIVATIVE=0, the user function is responsible for +; calculating the derivatives of the *residuals* with respect to each +; parameter. The user function should be declared as follows: +; +; ; +; ; MYFUNCT - example user function +; ; P - input parameter values (N-element array) +; ; DP - upon input, an N-vector indicating which parameters +; ; to compute derivatives for; +; ; upon output, the user function must return +; ; an ARRAY(M,N) of derivatives in this keyword +; ; (keywords) - any other keywords specified by FUNCTARGS +; ; RETURNS - residual values +; ; +; FUNCTION MYFUNCT, p, dp, X=x, Y=y, ERR=err +; model = F(x, p) ;; Model function +; resid = (y - model)/err ;; Residual calculation (for example) +; +; if n_params() GT 1 then begin +; ; Create derivative and compute derivative array +; requested = dp ; Save original value of DP +; dp = make_array(n_elements(x), n_elements(p), value=x[0]*0) +; +; ; Compute derivative if requested by caller +; for i = 0, n_elements(p)-1 do if requested(i) NE 0 then $ +; dp(*,i) = FGRAD(x, p, i) / err +; endif +; +; return, resid +; END +; +; where FGRAD(x, p, i) is a model function which computes the +; derivative of the model F(x,p) with respect to parameter P(i) at X. +; +; A quirk in the implementation leaves a stray negative sign in the +; definition of DP. The derivative of the *residual* should be +; "-FGRAD(x,p,i) / err" because of how the residual is defined +; ("resid = (data - model) / err"). **HOWEVER** because of the +; implementation quirk, MPFIT expects FGRAD(x,p,i)/err instead, +; i.e. the opposite sign of the gradient of RESID. +; +; Derivatives should be returned in the DP array. DP should be an +; ARRAY(m,n) array, where m is the number of data points and n is the +; number of parameters. -DP[i,j] is the derivative of the ith +; residual with respect to the jth parameter (note the minus sign +; due to the quirk described above). +; +; As noted above, MPFIT may not always request derivatives from the +; user function. In those cases, the parameter DP is not passed. +; Therefore functions can use N_PARAMS() to indicate whether they +; must compute the derivatives or not. +; +; The derivatives with respect to fixed parameters are ignored; zero +; is an appropriate value to insert for those derivatives. Upon +; input to the user function, DP is set to a vector with the same +; length as P, with a value of 1 for a parameter which is free, and a +; value of zero for a parameter which is fixed (and hence no +; derivative needs to be calculated). This input vector may be +; overwritten as needed. In the example above, the original DP +; vector is saved to a variable called REQUESTED, and used as a mask +; to calculate only those derivatives that are required. +; +; If the data is higher than one dimensional, then the *last* +; dimension should be the parameter dimension. Example: fitting a +; 50x50 image, "dp" should be 50x50xNPAR. +; +; EXPLICIT DERIVATIVES - TESTING and DEBUGGING +; +; For reasonably complicated user functions, the calculation of +; explicit derivatives of the correct sign and magnitude can be +; difficult to get right. A simple sign error can cause MPFIT to be +; confused. MPFIT has a derivative debugging mode which will compute +; the derivatives *both* numerically and explicitly, and compare the +; results. +; +; It is expected that during production usage, derivative debugging +; should be disabled for all parameters. +; +; In order to enable derivative debugging mode, set the following +; PARINFO members for the ith parameter. +; PARINFO[i].MPSIDE = 3 ; Enable explicit derivatives +; PARINFO[i].MPDERIV_DEBUG = 1 ; Enable derivative debugging mode +; PARINFO[i].MPDERIV_RELTOL = ?? ; Relative tolerance for comparison +; PARINFO[i].MPDERIV_ABSTOL = ?? ; Absolute tolerance for comparison +; Note that these settings are maintained on a parameter-by-parameter +; basis using PARINFO, so the user can choose which parameters +; derivatives will be tested. +; +; When .MPDERIV_DEBUG is set, then MPFIT first computes the +; derivative explicitly by requesting them from the user function. +; Then, it computes the derivatives numerically via finite +; differencing, and compares the two values. If the difference +; exceeds a tolerance threshold, then the values are printed out to +; alert the user. The tolerance level threshold contains both a +; relative and an absolute component, and is expressed as, +; +; ABS(DERIV_U - DERIV_N) GE (ABSTOL + RELTOL*ABS(DERIV_U)) +; +; where DERIV_U and DERIV_N are the derivatives computed explicitly +; and numerically, respectively. Appropriate values +; for most users will be: +; +; PARINFO[i].MPDERIV_RELTOL = 1d-3 ;; Suggested relative tolerance +; PARINFO[i].MPDERIV_ABSTOL = 1d-7 ;; Suggested absolute tolerance +; +; although these thresholds may have to be adjusted for a particular +; problem. When the threshold is exceeded, users can expect to see a +; tabular report like this one: +; +; FJAC DEBUG BEGIN +; # IPNT FUNC DERIV_U DERIV_N DIFF_ABS DIFF_REL +; FJAC PARM 2 +; 80 -0.7308 0.04233 0.04233 -5.543E-07 -1.309E-05 +; 99 1.370 0.01417 0.01417 -5.518E-07 -3.895E-05 +; 118 0.07187 -0.01400 -0.01400 -5.566E-07 3.977E-05 +; 137 1.844 -0.04216 -0.04216 -5.589E-07 1.326E-05 +; FJAC DEBUG END +; +; The report will be bracketed by FJAC DEBUG BEGIN/END statements. +; Each parameter will be delimited by the statement FJAC PARM n, +; where n is the parameter number. The columns are, +; +; IPNT - data point number (0 ... M-1) +; FUNC - function value at that point +; DERIV_U - explicit derivative value at that point +; DERIV_N - numerical derivative estimate at that point +; DIFF_ABS - absolute difference = (DERIV_U - DERIV_N) +; DIFF_REL - relative difference = (DIFF_ABS)/(DERIV_U) +; +; When prints appear in this report, it is most important to check +; that the derivatives computed in two different ways have the same +; numerical sign and the same order of magnitude, since these are the +; most common programming mistakes. +; +; A line of this form may also appear +; +; # FJAC_MASK = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 +; +; This line indicates for which parameters explicit derivatives are +; expected. A list of all-1s indicates all explicit derivatives for +; all parameters are requested from the user function. +; +; +; CONSTRAINING PARAMETER VALUES WITH THE PARINFO KEYWORD +; +; The behavior of MPFIT can be modified with respect to each +; parameter to be fitted. A parameter value can be fixed; simple +; boundary constraints can be imposed; limitations on the parameter +; changes can be imposed; properties of the automatic derivative can +; be modified; and parameters can be tied to one another. +; +; These properties are governed by the PARINFO structure, which is +; passed as a keyword parameter to MPFIT. +; +; PARINFO should be an array of structures, one for each parameter. +; Each parameter is associated with one element of the array, in +; numerical order. The structure can have the following entries +; (none are required): +; +; .VALUE - the starting parameter value (but see the START_PARAMS +; parameter for more information). +; +; .FIXED - a boolean value, whether the parameter is to be held +; fixed or not. Fixed parameters are not varied by +; MPFIT, but are passed on to MYFUNCT for evaluation. +; +; .LIMITED - a two-element boolean array. If the first/second +; element is set, then the parameter is bounded on the +; lower/upper side. A parameter can be bounded on both +; sides. Both LIMITED and LIMITS must be given +; together. +; +; .LIMITS - a two-element float or double array. Gives the +; parameter limits on the lower and upper sides, +; respectively. Zero, one or two of these values can be +; set, depending on the values of LIMITED. Both LIMITED +; and LIMITS must be given together. +; +; .PARNAME - a string, giving the name of the parameter. The +; fitting code of MPFIT does not use this tag in any +; way. However, the default ITERPROC will print the +; parameter name if available. +; +; .STEP - the step size to be used in calculating the numerical +; derivatives. If set to zero, then the step size is +; computed automatically. Ignored when AUTODERIVATIVE=0. +; This value is superceded by the RELSTEP value. +; +; .RELSTEP - the *relative* step size to be used in calculating +; the numerical derivatives. This number is the +; fractional size of the step, compared to the +; parameter value. This value supercedes the STEP +; setting. If the parameter is zero, then a default +; step size is chosen. +; +; .MPSIDE - selector for type of derivative calculation. This +; field can take one of five possible values: +; +; 0 - one-sided derivative computed automatically +; 1 - one-sided derivative (f(x+h) - f(x) )/h +; -1 - one-sided derivative (f(x) - f(x-h))/h +; 2 - two-sided derivative (f(x+h) - f(x-h))/(2*h) +; 3 - explicit derivative used for this parameter +; +; In the first four cases, the derivative is approximated +; numerically by finite difference, with step size +; H=STEP, where the STEP parameter is defined above. The +; last case, MPSIDE=3, indicates to allow the user +; function to compute the derivative explicitly (see +; section on "EXPLICIT DERIVATIVES"). AUTODERIVATIVE=0 +; overrides this setting for all parameters, and is +; equivalent to MPSIDE=3 for all parameters. For +; MPSIDE=0, the "automatic" one-sided derivative method +; will chose a direction for the finite difference which +; does not violate any constraints. The other methods +; (MPSIDE=-1 or MPSIDE=1) do not perform this check. The +; two-sided method is in principle more precise, but +; requires twice as many function evaluations. Default: +; 0. +; +; .MPDERIV_DEBUG - set this value to 1 to enable debugging of +; user-supplied explicit derivatives (see "TESTING and +; DEBUGGING" section above). In addition, the +; user must enable calculation of explicit derivatives by +; either setting AUTODERIVATIVE=0, or MPSIDE=3 for the +; desired parameters. When this option is enabled, a +; report may be printed to the console, depending on the +; MPDERIV_ABSTOL and MPDERIV_RELTOL settings. +; Default: 0 (no debugging) +; +; +; .MPDERIV_ABSTOL, .MPDERIV_RELTOL - tolerance settings for +; print-out of debugging information, for each parameter +; where debugging is enabled. See "TESTING and +; DEBUGGING" section above for the meanings of these two +; fields. +; +; +; .MPMAXSTEP - the maximum change to be made in the parameter +; value. During the fitting process, the parameter +; will never be changed by more than this value in +; one iteration. +; +; A value of 0 indicates no maximum. Default: 0. +; +; .TIED - a string expression which "ties" the parameter to other +; free or fixed parameters as an equality constraint. Any +; expression involving constants and the parameter array P +; are permitted. +; Example: if parameter 2 is always to be twice parameter +; 1 then use the following: parinfo[2].tied = '2 * P[1]'. +; Since they are totally constrained, tied parameters are +; considered to be fixed; no errors are computed for them, +; and any LIMITS are not obeyed. +; [ NOTE: the PARNAME can't be used in a TIED expression. ] +; +; .MPPRINT - if set to 1, then the default ITERPROC will print the +; parameter value. If set to 0, the parameter value +; will not be printed. This tag can be used to +; selectively print only a few parameter values out of +; many. Default: 1 (all parameters printed) +; +; .MPFORMAT - IDL format string to print the parameter within +; ITERPROC. Default: '(G20.6)' (An empty string will +; also use the default.) +; +; Future modifications to the PARINFO structure, if any, will involve +; adding structure tags beginning with the two letters "MP". +; Therefore programmers are urged to avoid using tags starting with +; "MP", but otherwise they are free to include their own fields +; within the PARINFO structure, which will be ignored by MPFIT. +; +; PARINFO Example: +; parinfo = replicate({value:0.D, fixed:0, limited:[0,0], $ +; limits:[0.D,0]}, 5) +; parinfo[0].fixed = 1 +; parinfo[4].limited[0] = 1 +; parinfo[4].limits[0] = 50.D +; parinfo[*].value = [5.7D, 2.2, 500., 1.5, 2000.] +; +; A total of 5 parameters, with starting values of 5.7, +; 2.2, 500, 1.5, and 2000 are given. The first parameter +; is fixed at a value of 5.7, and the last parameter is +; constrained to be above 50. +; +; +; RECURSION +; +; Generally, recursion is not allowed. As of version 1.77, MPFIT has +; recursion protection which does not allow a model function to +; itself call MPFIT. Users who wish to perform multi-level +; optimization should investigate the 'EXTERNAL' function evaluation +; methods described below for hard-to-evaluate functions. That +; method places more control in the user's hands. The user can +; design a "recursive" application by taking care. +; +; In most cases the recursion protection should be well-behaved. +; However, if the user is doing debugging, it is possible for the +; protection system to get "stuck." In order to reset it, run the +; procedure: +; MPFIT_RESET_RECURSION +; and the protection system should get "unstuck." It is save to call +; this procedure at any time. +; +; +; COMPATIBILITY +; +; This function is designed to work with IDL 5.0 or greater. +; +; Because TIED parameters and the "(EXTERNAL)" user-model feature use +; the EXECUTE() function, they cannot be used with the free version +; of the IDL Virtual Machine. +; +; +; DETERMINING THE VERSION OF MPFIT +; +; MPFIT is a changing library. Users of MPFIT may also depend on a +; specific version of the library being present. As of version 1.70 +; of MPFIT, a VERSION keyword has been added which allows the user to +; query which version is present. The keyword works like this: +; +; RESULT = MPFIT(/query, VERSION=version) +; +; This call uses the /QUERY keyword to query the version number +; without performing any computations. Users of MPFIT can call this +; method to determine which version is in the IDL path before +; actually using MPFIT to do any numerical work. Upon return, the +; VERSION keyword contains the version number of MPFIT, expressed as +; a string of the form 'X.Y' where X and Y are integers. +; +; Users can perform their own version checking, or use the built-in +; error checking of MPFIT. The MIN_VERSION keyword enforces the +; requested minimum version number. For example, +; +; RESULT = MPFIT(/query, VERSION=version, MIN_VERSION='1.70') +; +; will check whether the accessed version is 1.70 or greater, without +; performing any numerical processing. +; +; The VERSION and MIN_VERSION keywords were added in MPFIT +; version 1.70 and later. If the caller attempts to use the VERSION +; or MIN_VERSION keywords, and an *older* version of the code is +; present in the caller's path, then IDL will throw an 'unknown +; keyword' error. Therefore, in order to be robust, the caller, must +; use exception handling. Here is an example demanding at least +; version 1.70. +; +; MPFIT_OK = 0 & VERSION = '' +; CATCH, CATCHERR +; IF CATCHERR EQ 0 THEN MPFIT_OK = MPFIT(/query, VERSION=version, $ +; MIN_VERSION='1.70') +; CATCH, /CANCEL +; +; IF NOT MPFIT_OK THEN $ +; MESSAGE, 'ERROR: you must have MPFIT version 1.70 or higher in '+$ +; 'your path (found version '+version+')' +; +; Of course, the caller can also do its own version number +; requirements checking. +; +; +; HARD-TO-COMPUTE FUNCTIONS: "EXTERNAL" EVALUATION +; +; The normal mode of operation for MPFIT is for the user to pass a +; function name, and MPFIT will call the user function multiple times +; as it iterates toward a solution. +; +; Some user functions are particularly hard to compute using the +; standard model of MPFIT. Usually these are functions that depend +; on a large amount of external data, and so it is not feasible, or +; at least highly impractical, to have MPFIT call it. In those cases +; it may be possible to use the "(EXTERNAL)" evaluation option. +; +; In this case the user is responsible for making all function *and +; derivative* evaluations. The function and Jacobian data are passed +; in through the EXTERNAL_FVEC and EXTERNAL_FJAC keywords, +; respectively. The user indicates the selection of this option by +; specifying a function name (MYFUNCT) of "(EXTERNAL)". No +; user-function calls are made when EXTERNAL evaluation is being +; used. +; +; ** SPECIAL NOTE ** For the "(EXTERNAL)" case, the quirk noted above +; does not apply. The gradient matrix, EXTERNAL_FJAC, should be +; comparable to "-FGRAD(x,p)/err", which is the *opposite* sign of +; the DP matrix described above. In other words, EXTERNAL_FJAC +; has the same sign as the derivative of EXTERNAL_FVEC, and the +; opposite sign of FGRAD. +; +; At the end of each iteration, control returns to the user, who must +; reevaluate the function at its new parameter values. Users should +; check the return value of the STATUS keyword, where a value of 9 +; indicates the user should supply more data for the next iteration, +; and re-call MPFIT. The user may refrain from calling MPFIT +; further; as usual, STATUS will indicate when the solution has +; converged and no more iterations are required. +; +; Because MPFIT must maintain its own data structures between calls, +; the user must also pass a named variable to the EXTERNAL_STATE +; keyword. This variable must be maintained by the user, but not +; changed, throughout the fitting process. When no more iterations +; are desired, the named variable may be discarded. +; +; +; INPUTS: +; MYFUNCT - a string variable containing the name of the function to +; be minimized. The function should return the weighted +; deviations between the model and the data, as described +; above. +; +; For EXTERNAL evaluation of functions, this parameter +; should be set to a value of "(EXTERNAL)". +; +; START_PARAMS - An one-dimensional array of starting values for each of the +; parameters of the model. The number of parameters +; should be fewer than the number of measurements. +; Also, the parameters should have the same data type +; as the measurements (double is preferred). +; +; This parameter is optional if the PARINFO keyword +; is used (but see PARINFO). The PARINFO keyword +; provides a mechanism to fix or constrain individual +; parameters. If both START_PARAMS and PARINFO are +; passed, then the starting *value* is taken from +; START_PARAMS, but the *constraints* are taken from +; PARINFO. +; +; RETURNS: +; +; Returns the array of best-fit parameters. +; Exceptions: +; * if /QUERY is set (see QUERY). +; +; +; KEYWORD PARAMETERS: +; +; AUTODERIVATIVE - If this is set, derivatives of the function will +; be computed automatically via a finite +; differencing procedure. If not set, then MYFUNCT +; must provide the explicit derivatives. +; Default: set (=1) +; NOTE: to supply your own explicit derivatives, +; explicitly pass AUTODERIVATIVE=0 +; +; BESTNORM - upon return, the value of the summed squared weighted +; residuals for the returned parameter values, +; i.e. TOTAL(DEVIATES^2). +; +; BEST_FJAC - upon return, BEST_FJAC contains the Jacobian, or +; partial derivative, matrix for the best-fit model. +; The values are an array, +; ARRAY(N_ELEMENTS(DEVIATES),NFREE) where NFREE is the +; number of free parameters. This array is only +; computed if /CALC_FJAC is set, otherwise BEST_FJAC is +; undefined. +; +; The returned array is such that BEST_FJAC[I,J] is the +; partial derivative of DEVIATES[I] with respect to +; parameter PARMS[PFREE_INDEX[J]]. Note that since +; deviates are (data-model)*weight, the Jacobian of the +; *deviates* will have the opposite sign from the +; Jacobian of the *model*, and may be scaled by a +; factor. +; +; BEST_RESID - upon return, an array of best-fit deviates. +; +; CALC_FJAC - if set, then calculate the Jacobian and return it in +; BEST_FJAC. If not set, then the return value of +; BEST_FJAC is undefined. +; +; COVAR - the covariance matrix for the set of parameters returned +; by MPFIT. The matrix is NxN where N is the number of +; parameters. The square root of the diagonal elements +; gives the formal 1-sigma statistical errors on the +; parameters IF errors were treated "properly" in MYFUNC. +; Parameter errors are also returned in PERROR. +; +; To compute the correlation matrix, PCOR, use this example: +; PCOR = COV * 0 +; FOR i = 0, n-1 DO FOR j = 0, n-1 DO $ +; PCOR[i,j] = COV[i,j]/sqrt(COV[i,i]*COV[j,j]) +; or equivalently, in vector notation, +; PCOR = COV / (PERROR # PERROR) +; +; If NOCOVAR is set or MPFIT terminated abnormally, then +; COVAR is set to a scalar with value !VALUES.D_NAN. +; +; DOF - number of degrees of freedom, computed as +; DOF = N_ELEMENTS(DEVIATES) - NFREE +; Note that this doesn't account for pegged parameters (see +; NPEGGED). It also does not account for data points which +; are assigned zero weight by the user function. +; +; ERRMSG - a string error or warning message is returned. +; +; EXTERNAL_FVEC - upon input, the function values, evaluated at +; START_PARAMS. This should be an M-vector, where M +; is the number of data points. +; +; EXTERNAL_FJAC - upon input, the Jacobian array of partial +; derivative values. This should be a M x N array, +; where M is the number of data points and N is the +; number of parameters. NOTE: that all FIXED or +; TIED parameters must *not* be included in this +; array. +; +; EXTERNAL_STATE - a named variable to store MPFIT-related state +; information between iterations (used in input and +; output to MPFIT). The user must not manipulate +; or discard this data until the final iteration is +; performed. +; +; FASTNORM - set this keyword to select a faster algorithm to +; compute sum-of-square values internally. For systems +; with large numbers of data points, the standard +; algorithm can become prohibitively slow because it +; cannot be vectorized well. By setting this keyword, +; MPFIT will run faster, but it will be more prone to +; floating point overflows and underflows. Thus, setting +; this keyword may sacrifice some stability in the +; fitting process. +; +; FTOL - a nonnegative input variable. Termination occurs when both +; the actual and predicted relative reductions in the sum of +; squares are at most FTOL (and STATUS is accordingly set to +; 1 or 3). Therefore, FTOL measures the relative error +; desired in the sum of squares. Default: 1D-10 +; +; FUNCTARGS - A structure which contains the parameters to be passed +; to the user-supplied function specified by MYFUNCT via +; the _EXTRA mechanism. This is the way you can pass +; additional data to your user-supplied function without +; using common blocks. +; +; Consider the following example: +; if FUNCTARGS = { XVAL:[1.D,2,3], YVAL:[1.D,4,9], +; ERRVAL:[1.D,1,1] } +; then the user supplied function should be declared +; like this: +; FUNCTION MYFUNCT, P, XVAL=x, YVAL=y, ERRVAL=err +; +; By default, no extra parameters are passed to the +; user-supplied function, but your function should +; accept *at least* one keyword parameter. [ This is to +; accomodate a limitation in IDL's _EXTRA +; parameter-passing mechanism. ] +; +; GTOL - a nonnegative input variable. Termination occurs when the +; cosine of the angle between fvec and any column of the +; jacobian is at most GTOL in absolute value (and STATUS is +; accordingly set to 4). Therefore, GTOL measures the +; orthogonality desired between the function vector and the +; columns of the jacobian. Default: 1D-10 +; +; ITERARGS - The keyword arguments to be passed to ITERPROC via the +; _EXTRA mechanism. This should be a structure, and is +; similar in operation to FUNCTARGS. +; Default: no arguments are passed. +; +; ITERPRINT - The name of an IDL procedure, equivalent to PRINT, +; that ITERPROC will use to render output. ITERPRINT +; should be able to accept at least four positional +; arguments. In addition, it should be able to accept +; the standard FORMAT keyword for output formatting; and +; the UNIT keyword, to redirect output to a logical file +; unit (default should be UNIT=1, standard output). +; These keywords are passed using the ITERARGS keyword +; above. The ITERPRINT procedure must accept the _EXTRA +; keyword. +; NOTE: that much formatting can be handled with the +; MPPRINT and MPFORMAT tags. +; Default: 'MPFIT_DEFPRINT' (default internal formatter) +; +; ITERPROC - The name of a procedure to be called upon each NPRINT +; iteration of the MPFIT routine. ITERPROC is always +; called in the final iteration. It should be declared +; in the following way: +; +; PRO ITERPROC, MYFUNCT, p, iter, fnorm, FUNCTARGS=fcnargs, $ +; PARINFO=parinfo, QUIET=quiet, DOF=dof, PFORMAT=pformat, $ +; UNIT=unit, ... +; ; perform custom iteration update +; END +; +; ITERPROC must either accept all three keyword +; parameters (FUNCTARGS, PARINFO and QUIET), or at least +; accept them via the _EXTRA keyword. +; +; MYFUNCT is the user-supplied function to be minimized, +; P is the current set of model parameters, ITER is the +; iteration number, and FUNCTARGS are the arguments to be +; passed to MYFUNCT. FNORM should be the chi-squared +; value. QUIET is set when no textual output should be +; printed. DOF is the number of degrees of freedom, +; normally the number of points less the number of free +; parameters. See below for documentation of PARINFO. +; PFORMAT is the default parameter value format. UNIT is +; passed on to the ITERPRINT procedure, and should +; indicate the file unit where log output will be sent +; (default: standard output). +; +; In implementation, ITERPROC can perform updates to the +; terminal or graphical user interface, to provide +; feedback while the fit proceeds. If the fit is to be +; stopped for any reason, then ITERPROC should set the +; common block variable ERROR_CODE to negative value +; between -15 and -1 (see MPFIT_ERROR common block +; below). In principle, ITERPROC should probably not +; modify the parameter values, because it may interfere +; with the algorithm's stability. In practice it is +; allowed. +; +; Default: an internal routine is used to print the +; parameter values. +; +; ITERSTOP - Set this keyword if you wish to be able to stop the +; fitting by hitting the predefined ITERKEYSTOP key on +; the keyboard. This only works if you use the default +; ITERPROC. +; +; ITERKEYSTOP - A keyboard key which will halt the fit (and if +; ITERSTOP is set and the default ITERPROC is used). +; ITERSTOPKEY may either be a one-character string +; with the desired key, or a scalar integer giving the +; ASCII code of the desired key. +; Default: 7b (control-g) +; +; NOTE: the default value of ASCI 7 (control-G) cannot +; be read in some windowing environments, so you must +; change to a printable character like 'q'. +; +; MAXITER - The maximum number of iterations to perform. If the +; number of calculation iterations exceeds MAXITER, then +; the STATUS value is set to 5 and MPFIT returns. +; +; If MAXITER EQ 0, then MPFIT does not iterate to adjust +; parameter values; however, the user function is evaluated +; and parameter errors/covariance/Jacobian are estimated +; before returning. +; Default: 200 iterations +; +; MIN_VERSION - The minimum requested version number. This must be +; a scalar string of the form returned by the VERSION +; keyword. If the current version of MPFIT does not +; satisfy the minimum requested version number, then, +; MPFIT(/query, min_version='...') returns 0 +; MPFIT(...) returns NAN +; Default: no version number check +; NOTE: MIN_VERSION was added in MPFIT version 1.70 +; +; NFEV - the number of MYFUNCT function evaluations performed. +; +; NFREE - the number of free parameters in the fit. This includes +; parameters which are not FIXED and not TIED, but it does +; include parameters which are pegged at LIMITS. +; +; NITER - the number of iterations completed. +; +; NOCATCH - if set, then MPFIT will not perform any error trapping. +; By default (not set), MPFIT will trap errors and report +; them to the caller. This keyword will typically be used +; for debugging. +; +; NOCOVAR - set this keyword to prevent the calculation of the +; covariance matrix before returning (see COVAR) +; +; NPEGGED - the number of free parameters which are pegged at a +; LIMIT. +; +; NPRINT - The frequency with which ITERPROC is called. A value of +; 1 indicates that ITERPROC is called with every iteration, +; while 2 indicates every other iteration, etc. Be aware +; that several Levenberg-Marquardt attempts can be made in +; a single iteration. Also, the ITERPROC is *always* +; called for the final iteration, regardless of the +; iteration number. +; Default value: 1 +; +; PARINFO - A one-dimensional array of structures. +; Provides a mechanism for more sophisticated constraints +; to be placed on parameter values. When PARINFO is not +; passed, then it is assumed that all parameters are free +; and unconstrained. Values in PARINFO are never +; modified during a call to MPFIT. +; +; See description above for the structure of PARINFO. +; +; Default value: all parameters are free and unconstrained. +; +; PERROR - The formal 1-sigma errors in each parameter, computed +; from the covariance matrix. If a parameter is held +; fixed, or if it touches a boundary, then the error is +; reported as zero. +; +; If the fit is unweighted (i.e. no errors were given, or +; the weights were uniformly set to unity), then PERROR +; will probably not represent the true parameter +; uncertainties. +; +; *If* you can assume that the true reduced chi-squared +; value is unity -- meaning that the fit is implicitly +; assumed to be of good quality -- then the estimated +; parameter uncertainties can be computed by scaling PERROR +; by the measured chi-squared value. +; +; DOF = N_ELEMENTS(X) - N_ELEMENTS(PARMS) ; deg of freedom +; PCERROR = PERROR * SQRT(BESTNORM / DOF) ; scaled uncertainties +; +; PFREE_INDEX - upon return, PFREE_INDEX contains an index array +; which indicates which parameter were allowed to +; vary. I.e. of all the parameters PARMS, only +; PARMS[PFREE_INDEX] were varied. +; +; QUERY - if set, then MPFIT() will return immediately with one of +; the following values: +; 1 - if MIN_VERSION is not set +; 1 - if MIN_VERSION is set and MPFIT satisfies the minimum +; 0 - if MIN_VERSION is set and MPFIT does not satisfy it +; The VERSION output keyword is always set upon return. +; Default: not set. +; +; QUIET - set this keyword when no textual output should be printed +; by MPFIT +; +; RESDAMP - a scalar number, indicating the cut-off value of +; residuals where "damping" will occur. Residuals with +; magnitudes greater than this number will be replaced by +; their logarithm. This partially mitigates the so-called +; large residual problem inherent in least-squares solvers +; (as for the test problem CURVI, http://www.maxthis.com/- +; curviex.htm). A value of 0 indicates no damping. +; Default: 0 +; +; Note: RESDAMP doesn't work with AUTODERIV=0 +; +; STATUS - an integer status code is returned. All values greater +; than zero can represent success (however STATUS EQ 5 may +; indicate failure to converge). It can have one of the +; following values: +; +; -18 a fatal execution error has occurred. More information +; may be available in the ERRMSG string. +; +; -16 a parameter or function value has become infinite or an +; undefined number. This is usually a consequence of +; numerical overflow in the user's model function, which +; must be avoided. +; +; -15 to -1 +; these are error codes that either MYFUNCT or ITERPROC +; may return to terminate the fitting process (see +; description of MPFIT_ERROR common below). If either +; MYFUNCT or ITERPROC set ERROR_CODE to a negative number, +; then that number is returned in STATUS. Values from -15 +; to -1 are reserved for the user functions and will not +; clash with MPFIT. +; +; 0 improper input parameters. +; +; 1 both actual and predicted relative reductions +; in the sum of squares are at most FTOL. +; +; 2 relative error between two consecutive iterates +; is at most XTOL +; +; 3 conditions for STATUS = 1 and STATUS = 2 both hold. +; +; 4 the cosine of the angle between fvec and any +; column of the jacobian is at most GTOL in +; absolute value. +; +; 5 the maximum number of iterations has been reached +; +; 6 FTOL is too small. no further reduction in +; the sum of squares is possible. +; +; 7 XTOL is too small. no further improvement in +; the approximate solution x is possible. +; +; 8 GTOL is too small. fvec is orthogonal to the +; columns of the jacobian to machine precision. +; +; 9 A successful single iteration has been completed, and +; the user must supply another "EXTERNAL" evaluation of +; the function and its derivatives. This status indicator +; is neither an error nor a convergence indicator. +; +; VERSION - upon return, VERSION will be set to the MPFIT internal +; version number. The version number will be a string of +; the form "X.Y" where X is a major revision number and Y +; is a minor revision number. +; NOTE: the VERSION keyword was not present before +; MPFIT version number 1.70, therefore, callers must +; use exception handling when using this keyword. +; +; XTOL - a nonnegative input variable. Termination occurs when the +; relative error between two consecutive iterates is at most +; XTOL (and STATUS is accordingly set to 2 or 3). Therefore, +; XTOL measures the relative error desired in the approximate +; solution. Default: 1D-10 +; +; +; EXAMPLE: +; +; p0 = [5.7D, 2.2, 500., 1.5, 2000.] +; fa = {X:x, Y:y, ERR:err} +; p = mpfit('MYFUNCT', p0, functargs=fa) +; +; Minimizes sum of squares of MYFUNCT. MYFUNCT is called with the X, +; Y, and ERR keyword parameters that are given by FUNCTARGS. The +; resulting parameter values are returned in p. +; +; +; COMMON BLOCKS: +; +; COMMON MPFIT_ERROR, ERROR_CODE +; +; User routines may stop the fitting process at any time by +; setting an error condition. This condition may be set in either +; the user's model computation routine (MYFUNCT), or in the +; iteration procedure (ITERPROC). +; +; To stop the fitting, the above common block must be declared, +; and ERROR_CODE must be set to a negative number. After the user +; procedure or function returns, MPFIT checks the value of this +; common block variable and exits immediately if the error +; condition has been set. This value is also returned in the +; STATUS keyword: values of -1 through -15 are reserved error +; codes for the user routines. By default the value of ERROR_CODE +; is zero, indicating a successful function/procedure call. +; +; COMMON MPFIT_PROFILE +; COMMON MPFIT_MACHAR +; COMMON MPFIT_CONFIG +; +; These are undocumented common blocks are used internally by +; MPFIT and may change in future implementations. +; +; THEORY OF OPERATION: +; +; There are many specific strategies for function minimization. One +; very popular technique is to use function gradient information to +; realize the local structure of the function. Near a local minimum +; the function value can be taylor expanded about x0 as follows: +; +; f(x) = f(x0) + f'(x0) . (x-x0) + (1/2) (x-x0) . f''(x0) . (x-x0) +; ----- --------------- ------------------------------- (1) +; Order 0th 1st 2nd +; +; Here f'(x) is the gradient vector of f at x, and f''(x) is the +; Hessian matrix of second derivatives of f at x. The vector x is +; the set of function parameters, not the measured data vector. One +; can find the minimum of f, f(xm) using Newton's method, and +; arrives at the following linear equation: +; +; f''(x0) . (xm-x0) = - f'(x0) (2) +; +; If an inverse can be found for f''(x0) then one can solve for +; (xm-x0), the step vector from the current position x0 to the new +; projected minimum. Here the problem has been linearized (ie, the +; gradient information is known to first order). f''(x0) is +; symmetric n x n matrix, and should be positive definite. +; +; The Levenberg - Marquardt technique is a variation on this theme. +; It adds an additional diagonal term to the equation which may aid the +; convergence properties: +; +; (f''(x0) + nu I) . (xm-x0) = -f'(x0) (2a) +; +; where I is the identity matrix. When nu is large, the overall +; matrix is diagonally dominant, and the iterations follow steepest +; descent. When nu is small, the iterations are quadratically +; convergent. +; +; In principle, if f''(x0) and f'(x0) are known then xm-x0 can be +; determined. However the Hessian matrix is often difficult or +; impossible to compute. The gradient f'(x0) may be easier to +; compute, if even by finite difference techniques. So-called +; quasi-Newton techniques attempt to successively estimate f''(x0) +; by building up gradient information as the iterations proceed. +; +; In the least squares problem there are further simplifications +; which assist in solving eqn (2). The function to be minimized is +; a sum of squares: +; +; f = Sum(hi^2) (3) +; +; where hi is the ith residual out of m residuals as described +; above. This can be substituted back into eqn (2) after computing +; the derivatives: +; +; f' = 2 Sum(hi hi') +; f'' = 2 Sum(hi' hj') + 2 Sum(hi hi'') (4) +; +; If one assumes that the parameters are already close enough to a +; minimum, then one typically finds that the second term in f'' is +; negligible [or, in any case, is too difficult to compute]. Thus, +; equation (2) can be solved, at least approximately, using only +; gradient information. +; +; In matrix notation, the combination of eqns (2) and (4) becomes: +; +; hT' . h' . dx = - hT' . h (5) +; +; Where h is the residual vector (length m), hT is its transpose, h' +; is the Jacobian matrix (dimensions n x m), and dx is (xm-x0). The +; user function supplies the residual vector h, and in some cases h' +; when it is not found by finite differences (see MPFIT_FDJAC2, +; which finds h and hT'). Even if dx is not the best absolute step +; to take, it does provide a good estimate of the best *direction*, +; so often a line minimization will occur along the dx vector +; direction. +; +; The method of solution employed by MINPACK is to form the Q . R +; factorization of h', where Q is an orthogonal matrix such that QT . +; Q = I, and R is upper right triangular. Using h' = Q . R and the +; ortogonality of Q, eqn (5) becomes +; +; (RT . QT) . (Q . R) . dx = - (RT . QT) . h +; RT . R . dx = - RT . QT . h (6) +; R . dx = - QT . h +; +; where the last statement follows because R is upper triangular. +; Here, R, QT and h are known so this is a matter of solving for dx. +; The routine MPFIT_QRFAC provides the QR factorization of h, with +; pivoting, and MPFIT_QRSOL;V provides the solution for dx. +; +; REFERENCES: +; +; Markwardt, C. B. 2008, "Non-Linear Least Squares Fitting in IDL +; with MPFIT," in proc. Astronomical Data Analysis Software and +; Systems XVIII, Quebec, Canada, ASP Conference Series, Vol. XXX, eds. +; D. Bohlender, P. Dowler & D. Durand (Astronomical Society of the +; Pacific: San Francisco), p. 251-254 (ISBN: 978-1-58381-702-5) +; http://arxiv.org/abs/0902.2850 +; Link to NASA ADS: http://adsabs.harvard.edu/abs/2009ASPC..411..251M +; Link to ASP: http://aspbooks.org/a/volumes/table_of_contents/411 +; +; Refer to the MPFIT website as: +; http://purl.com/net/mpfit +; +; MINPACK-1 software, by Jorge More' et al, available from netlib. +; http://www.netlib.org/ +; +; "Optimization Software Guide," Jorge More' and Stephen Wright, +; SIAM, *Frontiers in Applied Mathematics*, Number 14. +; (ISBN: 978-0-898713-22-0) +; +; More', J. 1978, "The Levenberg-Marquardt Algorithm: Implementation +; and Theory," in Numerical Analysis, vol. 630, ed. G. A. Watson +; (Springer-Verlag: Berlin), p. 105 (DOI: 10.1007/BFb0067690 ) +; +; MODIFICATION HISTORY: +; Translated from MINPACK-1 in FORTRAN, Apr-Jul 1998, CM +; Fixed bug in parameter limits (x vs xnew), 04 Aug 1998, CM +; Added PERROR keyword, 04 Aug 1998, CM +; Added COVAR keyword, 20 Aug 1998, CM +; Added NITER output keyword, 05 Oct 1998 +; D.L Windt, Bell Labs, windt@bell-labs.com; +; Made each PARINFO component optional, 05 Oct 1998 CM +; Analytical derivatives allowed via AUTODERIVATIVE keyword, 09 Nov 1998 +; Parameter values can be tied to others, 09 Nov 1998 +; Fixed small bugs (Wayne Landsman), 24 Nov 1998 +; Added better exception error reporting, 24 Nov 1998 CM +; Cosmetic documentation changes, 02 Jan 1999 CM +; Changed definition of ITERPROC to be consistent with TNMIN, 19 Jan 1999 CM +; Fixed bug when AUTDERIVATIVE=0. Incorrect sign, 02 Feb 1999 CM +; Added keyboard stop to MPFIT_DEFITER, 28 Feb 1999 CM +; Cosmetic documentation changes, 14 May 1999 CM +; IDL optimizations for speed & FASTNORM keyword, 15 May 1999 CM +; Tried a faster version of mpfit_enorm, 30 May 1999 CM +; Changed web address to cow.physics.wisc.edu, 14 Jun 1999 CM +; Found malformation of FDJAC in MPFIT for 1 parm, 03 Aug 1999 CM +; Factored out user-function call into MPFIT_CALL. It is possible, +; but currently disabled, to call procedures. The calling format +; is similar to CURVEFIT, 25 Sep 1999, CM +; Slightly changed mpfit_tie to be less intrusive, 25 Sep 1999, CM +; Fixed some bugs associated with tied parameters in mpfit_fdjac, 25 +; Sep 1999, CM +; Reordered documentation; now alphabetical, 02 Oct 1999, CM +; Added QUERY keyword for more robust error detection in drivers, 29 +; Oct 1999, CM +; Documented PERROR for unweighted fits, 03 Nov 1999, CM +; Split out MPFIT_RESETPROF to aid in profiling, 03 Nov 1999, CM +; Some profiling and speed optimization, 03 Nov 1999, CM +; Worst offenders, in order: fdjac2, qrfac, qrsolv, enorm. +; fdjac2 depends on user function, qrfac and enorm seem to be +; fully optimized. qrsolv probably could be tweaked a little, but +; is still <10% of total compute time. +; Made sure that !err was set to 0 in MPFIT_DEFITER, 10 Jan 2000, CM +; Fixed small inconsistency in setting of QANYLIM, 28 Jan 2000, CM +; Added PARINFO field RELSTEP, 28 Jan 2000, CM +; Converted to MPFIT_ERROR common block for indicating error +; conditions, 28 Jan 2000, CM +; Corrected scope of MPFIT_ERROR common block, CM, 07 Mar 2000 +; Minor speed improvement in MPFIT_ENORM, CM 26 Mar 2000 +; Corrected case where ITERPROC changed parameter values and +; parameter values were TIED, CM 26 Mar 2000 +; Changed MPFIT_CALL to modify NFEV automatically, and to support +; user procedures more, CM 26 Mar 2000 +; Copying permission terms have been liberalized, 26 Mar 2000, CM +; Catch zero value of zero a(j,lj) in MPFIT_QRFAC, 20 Jul 2000, CM +; (thanks to David Schlegel ) +; MPFIT_SETMACHAR is called only once at init; only one common block +; is created (MPFIT_MACHAR); it is now a structure; removed almost +; all CHECK_MATH calls for compatibility with IDL5 and !EXCEPT; +; profiling data is now in a structure too; noted some +; mathematical discrepancies in Linux IDL5.0, 17 Nov 2000, CM +; Some significant changes. New PARINFO fields: MPSIDE, MPMINSTEP, +; MPMAXSTEP. Improved documentation. Now PTIED constraints are +; maintained in the MPCONFIG common block. A new procedure to +; parse PARINFO fields. FDJAC2 now computes a larger variety of +; one-sided and two-sided finite difference derivatives. NFEV is +; stored in the MPCONFIG common now. 17 Dec 2000, CM +; Added check that PARINFO and XALL have same size, 29 Dec 2000 CM +; Don't call function in TERMINATE when there is an error, 05 Jan +; 2000 +; Check for float vs. double discrepancies; corrected implementation +; of MIN/MAXSTEP, which I still am not sure of, but now at least +; the correct behavior occurs *without* it, CM 08 Jan 2001 +; Added SCALE_FCN keyword, to allow for scaling, as for the CASH +; statistic; added documentation about the theory of operation, +; and under the QR factorization; slowly I'm beginning to +; understand the bowels of this algorithm, CM 10 Jan 2001 +; Remove MPMINSTEP field of PARINFO, for now at least, CM 11 Jan +; 2001 +; Added RESDAMP keyword, CM, 14 Jan 2001 +; Tried to improve the DAMP handling a little, CM, 13 Mar 2001 +; Corrected .PARNAME behavior in _DEFITER, CM, 19 Mar 2001 +; Added checks for parameter and function overflow; a new STATUS +; value to reflect this; STATUS values of -15 to -1 are reserved +; for user function errors, CM, 03 Apr 2001 +; DAMP keyword is now a TANH, CM, 03 Apr 2001 +; Added more error checking of float vs. double, CM, 07 Apr 2001 +; Fixed bug in handling of parameter lower limits; moved overflow +; checking to end of loop, CM, 20 Apr 2001 +; Failure using GOTO, TERMINATE more graceful if FNORM1 not defined, +; CM, 13 Aug 2001 +; Add MPPRINT tag to PARINFO, CM, 19 Nov 2001 +; Add DOF keyword to DEFITER procedure, and print degrees of +; freedom, CM, 28 Nov 2001 +; Add check to be sure MYFUNCT is a scalar string, CM, 14 Jan 2002 +; Addition of EXTERNAL_FJAC, EXTERNAL_FVEC keywords; ability to save +; fitter's state from one call to the next; allow '(EXTERNAL)' +; function name, which implies that user will supply function and +; Jacobian at each iteration, CM, 10 Mar 2002 +; Documented EXTERNAL evaluation code, CM, 10 Mar 2002 +; Corrected signficant bug in the way that the STEP parameter, and +; FIXED parameters interacted (Thanks Andrew Steffl), CM, 02 Apr +; 2002 +; Allow COVAR and PERROR keywords to be computed, even in case of +; '(EXTERNAL)' function, 26 May 2002 +; Add NFREE and NPEGGED keywords; compute NPEGGED; compute DOF using +; NFREE instead of n_elements(X), thanks to Kristian Kjaer, CM 11 +; Sep 2002 +; Hopefully PERROR is all positive now, CM 13 Sep 2002 +; Documented RELSTEP field of PARINFO (!!), CM, 25 Oct 2002 +; Error checking to detect missing start pars, CM 12 Apr 2003 +; Add DOF keyword to return degrees of freedom, CM, 30 June 2003 +; Always call ITERPROC in the final iteration; add ITERKEYSTOP +; keyword, CM, 30 June 2003 +; Correct bug in MPFIT_LMPAR of singularity handling, which might +; likely be fatal for one-parameter fits, CM, 21 Nov 2003 +; (with thanks to Peter Tuthill for the proper test case) +; Minor documentation adjustment, 03 Feb 2004, CM +; Correct small error in QR factorization when pivoting; document +; the return values of QRFAC when pivoting, 21 May 2004, CM +; Add MPFORMAT field to PARINFO, and correct behavior of interaction +; between MPPRINT and PARNAME in MPFIT_DEFITERPROC (thanks to Tim +; Robishaw), 23 May 2004, CM +; Add the ITERPRINT keyword to allow redirecting output, 26 Sep +; 2004, CM +; Correct MAXSTEP behavior in case of a negative parameter, 26 Sep +; 2004, CM +; Fix bug in the parsing of MINSTEP/MAXSTEP, 10 Apr 2005, CM +; Fix bug in the handling of upper/lower limits when the limit was +; negative (the fitting code would never "stick" to the lower +; limit), 29 Jun 2005, CM +; Small documentation update for the TIED field, 05 Sep 2005, CM +; Convert to IDL 5 array syntax (!), 16 Jul 2006, CM +; If MAXITER equals zero, then do the basic parameter checking and +; uncertainty analysis, but do not adjust the parameters, 15 Aug +; 2006, CM +; Added documentation, 18 Sep 2006, CM +; A few more IDL 5 array syntax changes, 25 Sep 2006, CM +; Move STRICTARR compile option inside each function/procedure, 9 Oct 2006 +; Bug fix for case of MPMAXSTEP and fixed parameters, thanks +; to Huib Intema (who found it from the Python translation!), 05 Feb 2007 +; Similar fix for MPFIT_FDJAC2 and the MPSIDE sidedness of +; derivatives, also thanks to Huib Intema, 07 Feb 2007 +; Clarify documentation on user-function, derivatives, and PARINFO, +; 27 May 2007 +; Change the wording of "Analytic Derivatives" to "Explicit +; Derivatives" in the documentation, CM, 03 Sep 2007 +; Further documentation tweaks, CM, 13 Dec 2007 +; Add COMPATIBILITY section and add credits to copyright, CM, 13 Dec +; 2007 +; Document and enforce that START_PARMS and PARINFO are 1-d arrays, +; CM, 29 Mar 2008 +; Previous change for 1-D arrays wasn't correct for +; PARINFO.LIMITED/.LIMITS; now fixed, CM, 03 May 2008 +; Documentation adjustments, CM, 20 Aug 2008 +; Change some minor FOR-loop variables to type-long, CM, 03 Sep 2008 +; Change error handling slightly, document NOCATCH keyword, +; document error handling in general, CM, 01 Oct 2008 +; Special case: when either LIMITS is zero, and a parameter pushes +; against that limit, the coded that 'pegged' it there would not +; work since it was a relative condition; now zero is handled +; properly, CM, 08 Nov 2008 +; Documentation of how TIED interacts with LIMITS, CM, 21 Dec 2008 +; Better documentation of references, CM, 27 Feb 2009 +; If MAXITER=0, then be sure to set STATUS=5, which permits the +; the covariance matrix to be computed, CM, 14 Apr 2009 +; Avoid numerical underflow while solving for the LM parameter, +; (thanks to Sergey Koposov) CM, 14 Apr 2009 +; Use individual functions for all possible MPFIT_CALL permutations, +; (and make sure the syntax is right) CM, 01 Sep 2009 +; Correct behavior of MPMAXSTEP when some parameters are frozen, +; thanks to Josh Destree, CM, 22 Nov 2009 +; Update the references section, CM, 22 Nov 2009 +; 1.70 - Add the VERSION and MIN_VERSION keywords, CM, 22 Nov 2009 +; 1.71 - Store pre-calculated revision in common, CM, 23 Nov 2009 +; 1.72-1.74 - Documented alternate method to compute correlation matrix, +; CM, 05 Feb 2010 +; 1.75 - Enforce TIED constraints when preparing to terminate the +; routine, CM, 2010-06-22 +; 1.76 - Documented input keywords now are not modified upon output, +; CM, 2010-07-13 +; 1.77 - Upon user request (/CALC_FJAC), compute Jacobian matrix and +; return in BEST_FJAC; also return best residuals in +; BEST_RESID; also return an index list of free parameters as +; PFREE_INDEX; add a fencepost to prevent recursion +; CM, 2010-10-27 +; 1.79 - Documentation corrections. CM, 2011-08-26 +; 1.81 - Fix bug in interaction of AUTODERIVATIVE=0 and .MPSIDE=3; +; Document FJAC_MASK. CM, 2012-05-08 +; +; $Id: mpfit.pro,v 1.82 2012/09/27 23:59:44 cmarkwar Exp $ +;- +; Original MINPACK by More' Garbow and Hillstrom, translated with permission +; Modifications and enhancements are: +; Copyright (C) 1997-2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012 Craig Markwardt +; This software is provided as is without any warranty whatsoever. +; Permission to use, copy, modify, and distribute modified or +; unmodified copies is granted, provided this copyright and disclaimer +; are included unchanged. +;- + +pro mpfit_dummy + ;; Enclose in a procedure so these are not defined in the main level + COMPILE_OPT strictarr + FORWARD_FUNCTION mpfit_fdjac2, mpfit_enorm, mpfit_lmpar, mpfit_covar, $ + mpfit, mpfit_call + + COMMON mpfit_error, error_code ;; For error passing to user function + COMMON mpfit_config, mpconfig ;; For internal error configrations +end + +;; Reset profiling registers for another run. By default, and when +;; uncommented, the profiling registers simply accumulate. + +pro mpfit_resetprof + COMPILE_OPT strictarr + common mpfit_profile, mpfit_profile_vals + + mpfit_profile_vals = { status: 1L, fdjac2: 0D, lmpar: 0D, mpfit: 0D, $ + qrfac: 0D, qrsolv: 0D, enorm: 0D} + return +end + +;; Following are machine constants that can be loaded once. I have +;; found that bizarre underflow messages can be produced in each call +;; to MACHAR(), so this structure minimizes the number of calls to +;; one. + +pro mpfit_setmachar, double=isdouble + COMPILE_OPT strictarr + common mpfit_profile, profvals + if n_elements(profvals) EQ 0 then mpfit_resetprof + + common mpfit_machar, mpfit_machar_vals + + ;; In earlier versions of IDL, MACHAR itself could produce a load of + ;; error messages. We try to mask some of that out here. + if (!version.release) LT 5 then dummy = check_math(1, 1) + + mch = 0. + mch = machar(double=keyword_set(isdouble)) + dmachep = mch.eps + dmaxnum = mch.xmax + dminnum = mch.xmin + dmaxlog = alog(mch.xmax) + dminlog = alog(mch.xmin) + if keyword_set(isdouble) then $ + dmaxgam = 171.624376956302725D $ + else $ + dmaxgam = 171.624376956302725 + drdwarf = sqrt(dminnum*1.5) * 10 + drgiant = sqrt(dmaxnum) * 0.1 + + mpfit_machar_vals = {machep: dmachep, maxnum: dmaxnum, minnum: dminnum, $ + maxlog: dmaxlog, minlog: dminlog, maxgam: dmaxgam, $ + rdwarf: drdwarf, rgiant: drgiant} + + if (!version.release) LT 5 then dummy = check_math(0, 0) + + return +end + + +; Call user function with no _EXTRA parameters +function mpfit_call_func_noextra, fcn, x, fjac, _EXTRA=extra + if n_params() EQ 2 then begin + return, call_function(fcn, x) + endif else begin + return, call_function(fcn, x, fjac) + endelse +end + +; Call user function with _EXTRA parameters +function mpfit_call_func_extra, fcn, x, fjac, _EXTRA=extra + if n_params() EQ 2 then begin + return, call_function(fcn, x, _EXTRA=extra) + endif else begin + return, call_function(fcn, x, fjac, _EXTRA=extra) + endelse +end + +; Call user procedure with no _EXTRA parameters +function mpfit_call_pro_noextra, fcn, x, fjac, _EXTRA=extra + if n_params() EQ 2 then begin + call_procedure, fcn, x, f + endif else begin + call_procedure, fcn, x, f, fjac + endelse + return, f +end + +; Call user procedure with _EXTRA parameters +function mpfit_call_pro_extra, fcn, x, fjac, _EXTRA=extra + if n_params() EQ 2 then begin + call_procedure, fcn, x, f, _EXTRA=extra + endif else begin + call_procedure, fcn, x, f, fjac, _EXTRA=extra + endelse + return, f +end + + +;; Call user function or procedure, with _EXTRA or not, with +;; derivatives or not. +function mpfit_call, fcn, x, fjac, _EXTRA=extra + + COMPILE_OPT strictarr + common mpfit_config, mpconfig + + if keyword_set(mpconfig.qanytied) then mpfit_tie, x, mpconfig.ptied + + ;; Decide whether we are calling a procedure or function, and + ;; with/without FUNCTARGS + proname = 'MPFIT_CALL' + proname = proname + ((mpconfig.proc) ? '_PRO' : '_FUNC') + proname = proname + ((n_elements(extra) GT 0) ? '_EXTRA' : '_NOEXTRA') + + if n_params() EQ 2 then begin + f = call_function(proname, fcn, x, _EXTRA=extra) + endif else begin + f = call_function(proname, fcn, x, fjac, _EXTRA=extra) + endelse + mpconfig.nfev = mpconfig.nfev + 1 + + if n_params() EQ 2 AND mpconfig.damp GT 0 then begin + damp = mpconfig.damp[0] + + ;; Apply the damping if requested. This replaces the residuals + ;; with their hyperbolic tangent. Thus residuals larger than + ;; DAMP are essentially clipped. + f = tanh(f/damp) + endif + + return, f +end + +function mpfit_fdjac2, fcn, x, fvec, step, ulimited, ulimit, dside, $ + iflag=iflag, epsfcn=epsfcn, autoderiv=autoderiv, $ + FUNCTARGS=fcnargs, xall=xall, ifree=ifree, dstep=dstep, $ + deriv_debug=ddebug, deriv_reltol=ddrtol, deriv_abstol=ddatol + + COMPILE_OPT strictarr + common mpfit_machar, machvals + common mpfit_profile, profvals + common mpfit_error, mperr + + ; prof_start = systime(1) + MACHEP0 = machvals.machep + DWARF = machvals.minnum + + if n_elements(epsfcn) EQ 0 then epsfcn = MACHEP0 + if n_elements(xall) EQ 0 then xall = x + if n_elements(ifree) EQ 0 then ifree = lindgen(n_elements(xall)) + if n_elements(step) EQ 0 then step = x * 0. + if n_elements(ddebug) EQ 0 then ddebug = intarr(n_elements(xall)) + if n_elements(ddrtol) EQ 0 then ddrtol = x * 0. + if n_elements(ddatol) EQ 0 then ddatol = x * 0. + has_debug_deriv = max(ddebug) + + if keyword_set(has_debug_deriv) then begin + ;; Header for debugging + print, 'FJAC DEBUG BEGIN' + print, "IPNT", "FUNC", "DERIV_U", "DERIV_N", "DIFF_ABS", "DIFF_REL", $ + format='("# ",A10," ",A10," ",A10," ",A10," ",A10," ",A10)' + endif + + nall = n_elements(xall) + + eps = sqrt(max([epsfcn, MACHEP0])); + m = n_elements(fvec) + n = n_elements(x) + + ;; Compute analytical derivative if requested + ;; Two ways to enable computation of explicit derivatives: + ;; 1. AUTODERIVATIVE=0 + ;; 2. AUTODERIVATIVE=1, but P[i].MPSIDE EQ 3 + + if keyword_set(autoderiv) EQ 0 OR max(dside[ifree] EQ 3) EQ 1 then begin + fjac_mask = intarr(nall) + ;; Specify which parameters need derivatives + ;; ---- Case 2 ------ ----- Case 1 ----- + fjac_mask[ifree] = (dside[ifree] EQ 3) OR (keyword_set(autoderiv) EQ 0) + if has_debug_deriv then $ + print, fjac_mask, format='("# FJAC_MASK = ",100000(I0," ",:))' + + fjac = fjac_mask ;; Pass the mask to the calling function as FJAC + mperr = 0 + fp = mpfit_call(fcn, xall, fjac, _EXTRA=fcnargs) + iflag = mperr + + if n_elements(fjac) NE m*nall then begin + message, /cont, 'ERROR: Derivative matrix was not computed properly.' + iflag = 1 + ; profvals.fdjac2 = profvals.fdjac2 + (systime(1) - prof_start) + return, 0 + endif + + ;; This definition is consistent with CURVEFIT (WRONG, see below) + ;; Sign error found (thanks Jesus Fernandez ) + + ;; ... and now I regret doing this sign flip since it's not + ;; strictly correct. The definition should be RESID = + ;; (Y-F)/SIGMA, so d(RESID)/dP should be -dF/dP. My response to + ;; Fernandez was unfounded because he was trying to supply + ;; dF/dP. Sigh. (CM 31 Aug 2007) + + fjac = reform(-temporary(fjac), m, nall, /overwrite) + + ;; Select only the free parameters + if n_elements(ifree) LT nall then $ + fjac = reform(fjac[*,ifree], m, n, /overwrite) + + ;; Are we done computing derivatives? The answer is, YES, if we + ;; computed explicit derivatives for all free parameters, EXCEPT + ;; when we are going on to compute debugging derivatives. + if min(fjac_mask[ifree]) EQ 1 AND NOT has_debug_deriv then begin + return, fjac + endif + endif + + ;; Final output array, if it was not already created above + if n_elements(fjac) EQ 0 then begin + fjac = make_array(m, n, value=fvec[0]*0.) + fjac = reform(fjac, m, n, /overwrite) + endif + + h = eps * abs(x) + + ;; if STEP is given, use that + ;; STEP includes the fixed parameters + if n_elements(step) GT 0 then begin + stepi = step[ifree] + wh = where(stepi GT 0, ct) + if ct GT 0 then h[wh] = stepi[wh] + endif + + ;; if relative step is given, use that + ;; DSTEP includes the fixed parameters + if n_elements(dstep) GT 0 then begin + dstepi = dstep[ifree] + wh = where(dstepi GT 0, ct) + if ct GT 0 then h[wh] = abs(dstepi[wh]*x[wh]) + endif + + ;; In case any of the step values are zero + wh = where(h EQ 0, ct) + if ct GT 0 then h[wh] = eps + + ;; Reverse the sign of the step if we are up against the parameter + ;; limit, or if the user requested it. + ;; DSIDE includes the fixed parameters (ULIMITED/ULIMIT have only + ;; varying ones) + mask = dside[ifree] EQ -1 + if n_elements(ulimited) GT 0 AND n_elements(ulimit) GT 0 then $ + mask = mask OR (ulimited AND (x GT ulimit-h)) + wh = where(mask, ct) + if ct GT 0 then h[wh] = -h[wh] + + ;; Loop through parameters, computing the derivative for each + for j=0L, n-1 do begin + dsidej = dside[ifree[j]] + ddebugj = ddebug[ifree[j]] + + ;; Skip this parameter if we already computed its derivative + ;; explicitly, and we are not debugging. + if (dsidej EQ 3) AND (ddebugj EQ 0) then continue + if (dsidej EQ 3) AND (ddebugj EQ 1) then $ + print, ifree[j], format='("FJAC PARM ",I0)' + + xp = xall + xp[ifree[j]] = xp[ifree[j]] + h[j] + + mperr = 0 + fp = mpfit_call(fcn, xp, _EXTRA=fcnargs) + + iflag = mperr + if iflag LT 0 then return, !values.d_nan + + if ((dsidej GE -1) AND (dsidej LE 1)) OR (dsidej EQ 3) then begin + ;; COMPUTE THE ONE-SIDED DERIVATIVE + ;; Note optimization fjac(0:*,j) + fjacj = (fp-fvec)/h[j] + + endif else begin + ;; COMPUTE THE TWO-SIDED DERIVATIVE + xp[ifree[j]] = xall[ifree[j]] - h[j] + + mperr = 0 + fm = mpfit_call(fcn, xp, _EXTRA=fcnargs) + + iflag = mperr + if iflag LT 0 then return, !values.d_nan + + ;; Note optimization fjac(0:*,j) + fjacj = (fp-fm)/(2*h[j]) + endelse + + ;; Debugging of explicit derivatives + if (dsidej EQ 3) AND (ddebugj EQ 1) then begin + ;; Relative and absolute tolerances + dr = ddrtol[ifree[j]] & da = ddatol[ifree[j]] + + ;; Explicitly calculated + fjaco = fjac[*,j] + + ;; If tolerances are zero, then any value for deriv triggers print... + if (da EQ 0 AND dr EQ 0) then $ + diffj = (fjaco NE 0 OR fjacj NE 0) + ;; ... otherwise the difference must be a greater than tolerance + if (da NE 0 OR dr NE 0) then $ + diffj = (abs(fjaco-fjacj) GT (da+abs(fjaco)*dr)) + + for k = 0L, m-1 do if diffj[k] then begin + print, k, fvec[k], fjaco[k], fjacj[k], fjaco[k]-fjacj[k], $ + (fjaco[k] EQ 0)?(0):((fjaco[k]-fjacj[k])/fjaco[k]), $ + format='(" ",I10," ",G10.4," ",G10.4," ",G10.4," ",G10.4," ",G10.4)' + endif + endif + + ;; Store final results in output array + fjac[0,j] = fjacj + + endfor + + if has_debug_deriv then print, 'FJAC DEBUG END' + + ; profvals.fdjac2 = profvals.fdjac2 + (systime(1) - prof_start) + return, fjac +end + +function mpfit_enorm, vec + + COMPILE_OPT strictarr + ;; NOTE: it turns out that, for systems that have a lot of data + ;; points, this routine is a big computing bottleneck. The extended + ;; computations that need to be done cannot be effectively + ;; vectorized. The introduction of the FASTNORM configuration + ;; parameter allows the user to select a faster routine, which is + ;; based on TOTAL() alone. + common mpfit_profile, profvals + ; prof_start = systime(1) + + common mpfit_config, mpconfig + ; Very simple-minded sum-of-squares + if n_elements(mpconfig) GT 0 then if mpconfig.fastnorm then begin + ans = sqrt(total(vec^2)) + goto, TERMINATE + endif + + common mpfit_machar, machvals + + agiant = machvals.rgiant / n_elements(vec) + adwarf = machvals.rdwarf * n_elements(vec) + + ;; This is hopefully a compromise between speed and robustness. + ;; Need to do this because of the possibility of over- or underflow. + mx = max(vec, min=mn) + mx = max(abs([mx,mn])) + if mx EQ 0 then return, vec[0]*0. + + if mx GT agiant OR mx LT adwarf then ans = mx * sqrt(total((vec/mx)^2))$ + else ans = sqrt( total(vec^2) ) + + TERMINATE: + ; profvals.enorm = profvals.enorm + (systime(1) - prof_start) + return, ans +end + +; ********** +; +; subroutine qrfac +; +; this subroutine uses householder transformations with column +; pivoting (optional) to compute a qr factorization of the +; m by n matrix a. that is, qrfac determines an orthogonal +; matrix q, a permutation matrix p, and an upper trapezoidal +; matrix r with diagonal elements of nonincreasing magnitude, +; such that a*p = q*r. the householder transformation for +; column k, k = 1,2,...,min(m,n), is of the form +; +; t +; i - (1/u(k))*u*u +; +; where u has zeros in the first k-1 positions. the form of +; this transformation and the method of pivoting first +; appeared in the corresponding linpack subroutine. +; +; the subroutine statement is +; +; subroutine qrfac(m,n,a,lda,pivot,ipvt,lipvt,rdiag,acnorm,wa) +; +; where +; +; m is a positive integer input variable set to the number +; of rows of a. +; +; n is a positive integer input variable set to the number +; of columns of a. +; +; a is an m by n array. on input a contains the matrix for +; which the qr factorization is to be computed. on output +; the strict upper trapezoidal part of a contains the strict +; upper trapezoidal part of r, and the lower trapezoidal +; part of a contains a factored form of q (the non-trivial +; elements of the u vectors described above). +; +; lda is a positive integer input variable not less than m +; which specifies the leading dimension of the array a. +; +; pivot is a logical input variable. if pivot is set true, +; then column pivoting is enforced. if pivot is set false, +; then no column pivoting is done. +; +; ipvt is an integer output array of length lipvt. ipvt +; defines the permutation matrix p such that a*p = q*r. +; column j of p is column ipvt(j) of the identity matrix. +; if pivot is false, ipvt is not referenced. +; +; lipvt is a positive integer input variable. if pivot is false, +; then lipvt may be as small as 1. if pivot is true, then +; lipvt must be at least n. +; +; rdiag is an output array of length n which contains the +; diagonal elements of r. +; +; acnorm is an output array of length n which contains the +; norms of the corresponding columns of the input matrix a. +; if this information is not needed, then acnorm can coincide +; with rdiag. +; +; wa is a work array of length n. if pivot is false, then wa +; can coincide with rdiag. +; +; subprograms called +; +; minpack-supplied ... dpmpar,enorm +; +; fortran-supplied ... dmax1,dsqrt,min0 +; +; argonne national laboratory. minpack project. march 1980. +; burton s. garbow, kenneth e. hillstrom, jorge j. more +; +; ********** +; +; PIVOTING / PERMUTING: +; +; Upon return, A(*,*) is in standard parameter order, A(*,IPVT) is in +; permuted order. +; +; RDIAG is in permuted order. +; +; ACNORM is in standard parameter order. +; +; NOTE: in IDL the factors appear slightly differently than described +; above. The matrix A is still m x n where m >= n. +; +; The "upper" triangular matrix R is actually stored in the strict +; lower left triangle of A under the standard notation of IDL. +; +; The reflectors that generate Q are in the upper trapezoid of A upon +; output. +; +; EXAMPLE: decompose the matrix [[9.,2.,6.],[4.,8.,7.]] +; aa = [[9.,2.,6.],[4.,8.,7.]] +; mpfit_qrfac, aa, aapvt, rdiag, aanorm +; IDL> print, aa +; 1.81818* 0.181818* 0.545455* +; -8.54545+ 1.90160* 0.432573* +; IDL> print, rdiag +; -11.0000+ -7.48166+ +; +; The components marked with a * are the components of the +; reflectors, and those marked with a + are components of R. +; +; To reconstruct Q and R we proceed as follows. First R. +; r = fltarr(m, n) +; for i = 0, n-1 do r(0:i,i) = aa(0:i,i) ; fill in lower diag +; r(lindgen(n)*(m+1)) = rdiag +; +; Next, Q, which are composed from the reflectors. Each reflector v +; is taken from the upper trapezoid of aa, and converted to a matrix +; via (I - 2 vT . v / (v . vT)). +; +; hh = ident ;; identity matrix +; for i = 0, n-1 do begin +; v = aa(*,i) & if i GT 0 then v(0:i-1) = 0 ;; extract reflector +; hh = hh ## (ident - 2*(v # v)/total(v * v)) ;; generate matrix +; endfor +; +; Test the result: +; IDL> print, hh ## transpose(r) +; 9.00000 4.00000 +; 2.00000 8.00000 +; 6.00000 7.00000 +; +; Note that it is usually never necessary to form the Q matrix +; explicitly, and MPFIT does not. + +pro mpfit_qrfac, a, ipvt, rdiag, acnorm, pivot=pivot + + COMPILE_OPT strictarr + sz = size(a) + m = sz[1] + n = sz[2] + + common mpfit_machar, machvals + common mpfit_profile, profvals + ; prof_start = systime(1) + + MACHEP0 = machvals.machep + DWARF = machvals.minnum + + ;; Compute the initial column norms and initialize arrays + acnorm = make_array(n, value=a[0]*0.) + for j = 0L, n-1 do $ + acnorm[j] = mpfit_enorm(a[*,j]) + rdiag = acnorm + wa = rdiag + ipvt = lindgen(n) + + ;; Reduce a to r with householder transformations + minmn = min([m,n]) + for j = 0L, minmn-1 do begin + if NOT keyword_set(pivot) then goto, HOUSE1 + + ;; Bring the column of largest norm into the pivot position + rmax = max(rdiag[j:*]) + kmax = where(rdiag[j:*] EQ rmax, ct) + j + if ct LE 0 then goto, HOUSE1 + kmax = kmax[0] + + ;; Exchange rows via the pivot only. Avoid actually exchanging + ;; the rows, in case there is lots of memory transfer. The + ;; exchange occurs later, within the body of MPFIT, after the + ;; extraneous columns of the matrix have been shed. + if kmax NE j then begin + temp = ipvt[j] & ipvt[j] = ipvt[kmax] & ipvt[kmax] = temp + rdiag[kmax] = rdiag[j] + wa[kmax] = wa[j] + endif + + HOUSE1: + + ;; Compute the householder transformation to reduce the jth + ;; column of A to a multiple of the jth unit vector + lj = ipvt[j] + ajj = a[j:*,lj] + ajnorm = mpfit_enorm(ajj) + if ajnorm EQ 0 then goto, NEXT_ROW + if a[j,lj] LT 0 then ajnorm = -ajnorm + + ajj = ajj / ajnorm + ajj[0] = ajj[0] + 1 + ;; *** Note optimization a(j:*,j) + a[j,lj] = ajj + + ;; Apply the transformation to the remaining columns + ;; and update the norms + + ;; NOTE to SELF: tried to optimize this by removing the loop, + ;; but it actually got slower. Reverted to "for" loop to keep + ;; it simple. + if j+1 LT n then begin + for k=j+1, n-1 do begin + lk = ipvt[k] + ajk = a[j:*,lk] + ;; *** Note optimization a(j:*,lk) + ;; (corrected 20 Jul 2000) + if a[j,lj] NE 0 then $ + a[j,lk] = ajk - ajj * total(ajk*ajj)/a[j,lj] + + if keyword_set(pivot) AND rdiag[k] NE 0 then begin + temp = a[j,lk]/rdiag[k] + rdiag[k] = rdiag[k] * sqrt((1.-temp^2) > 0) + temp = rdiag[k]/wa[k] + if 0.05D*temp*temp LE MACHEP0 then begin + rdiag[k] = mpfit_enorm(a[j+1:*,lk]) + wa[k] = rdiag[k] + endif + endif + endfor + endif + + NEXT_ROW: + rdiag[j] = -ajnorm + endfor + + ; profvals.qrfac = profvals.qrfac + (systime(1) - prof_start) + return +end + +; ********** +; +; subroutine qrsolv +; +; given an m by n matrix a, an n by n diagonal matrix d, +; and an m-vector b, the problem is to determine an x which +; solves the system +; +; a*x = b , d*x = 0 , +; +; in the least squares sense. +; +; this subroutine completes the solution of the problem +; if it is provided with the necessary information from the +; qr factorization, with column pivoting, of a. that is, if +; a*p = q*r, where p is a permutation matrix, q has orthogonal +; columns, and r is an upper triangular matrix with diagonal +; elements of nonincreasing magnitude, then qrsolv expects +; the full upper triangle of r, the permutation matrix p, +; and the first n components of (q transpose)*b. the system +; a*x = b, d*x = 0, is then equivalent to +; +; t t +; r*z = q *b , p *d*p*z = 0 , +; +; where x = p*z. if this system does not have full rank, +; then a least squares solution is obtained. on output qrsolv +; also provides an upper triangular matrix s such that +; +; t t t +; p *(a *a + d*d)*p = s *s . +; +; s is computed within qrsolv and may be of separate interest. +; +; the subroutine statement is +; +; subroutine qrsolv(n,r,ldr,ipvt,diag,qtb,x,sdiag,wa) +; +; where +; +; n is a positive integer input variable set to the order of r. +; +; r is an n by n array. on input the full upper triangle +; must contain the full upper triangle of the matrix r. +; on output the full upper triangle is unaltered, and the +; strict lower triangle contains the strict upper triangle +; (transposed) of the upper triangular matrix s. +; +; ldr is a positive integer input variable not less than n +; which specifies the leading dimension of the array r. +; +; ipvt is an integer input array of length n which defines the +; permutation matrix p such that a*p = q*r. column j of p +; is column ipvt(j) of the identity matrix. +; +; diag is an input array of length n which must contain the +; diagonal elements of the matrix d. +; +; qtb is an input array of length n which must contain the first +; n elements of the vector (q transpose)*b. +; +; x is an output array of length n which contains the least +; squares solution of the system a*x = b, d*x = 0. +; +; sdiag is an output array of length n which contains the +; diagonal elements of the upper triangular matrix s. +; +; wa is a work array of length n. +; +; subprograms called +; +; fortran-supplied ... dabs,dsqrt +; +; argonne national laboratory. minpack project. march 1980. +; burton s. garbow, kenneth e. hillstrom, jorge j. more +; +pro mpfit_qrsolv, r, ipvt, diag, qtb, x, sdiag + + COMPILE_OPT strictarr + sz = size(r) + m = sz[1] + n = sz[2] + delm = lindgen(n) * (m+1) ;; Diagonal elements of r + + common mpfit_profile, profvals + ; prof_start = systime(1) + + ;; copy r and (q transpose)*b to preserve input and initialize s. + ;; in particular, save the diagonal elements of r in x. + + for j = 0L, n-1 do $ + r[j:n-1,j] = r[j,j:n-1] + x = r[delm] + wa = qtb + ;; Below may look strange, but it's so we can keep the right precision + zero = qtb[0]*0. + half = zero + 0.5 + quart = zero + 0.25 + + ;; Eliminate the diagonal matrix d using a givens rotation + for j = 0L, n-1 do begin + l = ipvt[j] + if diag[l] EQ 0 then goto, STORE_RESTORE + sdiag[j:*] = 0 + sdiag[j] = diag[l] + + ;; The transformations to eliminate the row of d modify only a + ;; single element of (q transpose)*b beyond the first n, which + ;; is initially zero. + + qtbpj = zero + for k = j, n-1 do begin + if sdiag[k] EQ 0 then goto, ELIM_NEXT_LOOP + if abs(r[k,k]) LT abs(sdiag[k]) then begin + cotan = r[k,k]/sdiag[k] + sine = half/sqrt(quart + quart*cotan*cotan) + cosine = sine*cotan + endif else begin + tang = sdiag[k]/r[k,k] + cosine = half/sqrt(quart + quart*tang*tang) + sine = cosine*tang + endelse + + ;; Compute the modified diagonal element of r and the + ;; modified element of ((q transpose)*b,0). + r[k,k] = cosine*r[k,k] + sine*sdiag[k] + temp = cosine*wa[k] + sine*qtbpj + qtbpj = -sine*wa[k] + cosine*qtbpj + wa[k] = temp + + ;; Accumulate the transformation in the row of s + if n GT k+1 then begin + temp = cosine*r[k+1:n-1,k] + sine*sdiag[k+1:n-1] + sdiag[k+1:n-1] = -sine*r[k+1:n-1,k] + cosine*sdiag[k+1:n-1] + r[k+1:n-1,k] = temp + endif + ELIM_NEXT_LOOP: + endfor + + STORE_RESTORE: + sdiag[j] = r[j,j] + r[j,j] = x[j] + endfor + + ;; Solve the triangular system for z. If the system is singular + ;; then obtain a least squares solution + nsing = n + wh = where(sdiag EQ 0, ct) + if ct GT 0 then begin + nsing = wh[0] + wa[nsing:*] = 0 + endif + + if nsing GE 1 then begin + wa[nsing-1] = wa[nsing-1]/sdiag[nsing-1] ;; Degenerate case + ;; *** Reverse loop *** + for j=nsing-2,0,-1 do begin + sum = total(r[j+1:nsing-1,j]*wa[j+1:nsing-1]) + wa[j] = (wa[j]-sum)/sdiag[j] + endfor + endif + + ;; Permute the components of z back to components of x + x[ipvt] = wa + + ; profvals.qrsolv = profvals.qrsolv + (systime(1) - prof_start) + return +end + + +; +; subroutine lmpar +; +; given an m by n matrix a, an n by n nonsingular diagonal +; matrix d, an m-vector b, and a positive number delta, +; the problem is to determine a value for the parameter +; par such that if x solves the system +; +; a*x = b , sqrt(par)*d*x = 0 , +; +; in the least squares sense, and dxnorm is the euclidean +; norm of d*x, then either par is zero and +; +; (dxnorm-delta) .le. 0.1*delta , +; +; or par is positive and +; +; abs(dxnorm-delta) .le. 0.1*delta . +; +; this subroutine completes the solution of the problem +; if it is provided with the necessary information from the +; qr factorization, with column pivoting, of a. that is, if +; a*p = q*r, where p is a permutation matrix, q has orthogonal +; columns, and r is an upper triangular matrix with diagonal +; elements of nonincreasing magnitude, then lmpar expects +; the full upper triangle of r, the permutation matrix p, +; and the first n components of (q transpose)*b. on output +; lmpar also provides an upper triangular matrix s such that +; +; t t t +; p *(a *a + par*d*d)*p = s *s . +; +; s is employed within lmpar and may be of separate interest. +; +; only a few iterations are generally needed for convergence +; of the algorithm. if, however, the limit of 10 iterations +; is reached, then the output par will contain the best +; value obtained so far. +; +; the subroutine statement is +; +; subroutine lmpar(n,r,ldr,ipvt,diag,qtb,delta,par,x,sdiag, +; wa1,wa2) +; +; where +; +; n is a positive integer input variable set to the order of r. +; +; r is an n by n array. on input the full upper triangle +; must contain the full upper triangle of the matrix r. +; on output the full upper triangle is unaltered, and the +; strict lower triangle contains the strict upper triangle +; (transposed) of the upper triangular matrix s. +; +; ldr is a positive integer input variable not less than n +; which specifies the leading dimension of the array r. +; +; ipvt is an integer input array of length n which defines the +; permutation matrix p such that a*p = q*r. column j of p +; is column ipvt(j) of the identity matrix. +; +; diag is an input array of length n which must contain the +; diagonal elements of the matrix d. +; +; qtb is an input array of length n which must contain the first +; n elements of the vector (q transpose)*b. +; +; delta is a positive input variable which specifies an upper +; bound on the euclidean norm of d*x. +; +; par is a nonnegative variable. on input par contains an +; initial estimate of the levenberg-marquardt parameter. +; on output par contains the final estimate. +; +; x is an output array of length n which contains the least +; squares solution of the system a*x = b, sqrt(par)*d*x = 0, +; for the output par. +; +; sdiag is an output array of length n which contains the +; diagonal elements of the upper triangular matrix s. +; +; wa1 and wa2 are work arrays of length n. +; +; subprograms called +; +; minpack-supplied ... dpmpar,enorm,qrsolv +; +; fortran-supplied ... dabs,dmax1,dmin1,dsqrt +; +; argonne national laboratory. minpack project. march 1980. +; burton s. garbow, kenneth e. hillstrom, jorge j. more +; +function mpfit_lmpar, r, ipvt, diag, qtb, delta, x, sdiag, par=par + + COMPILE_OPT strictarr + common mpfit_machar, machvals + common mpfit_profile, profvals + ; prof_start = systime(1) + + MACHEP0 = machvals.machep + DWARF = machvals.minnum + + sz = size(r) + m = sz[1] + n = sz[2] + delm = lindgen(n) * (m+1) ;; Diagonal elements of r + + ;; Compute and store in x the gauss-newton direction. If the + ;; jacobian is rank-deficient, obtain a least-squares solution + nsing = n + wa1 = qtb + rthresh = max(abs(r[delm]))*MACHEP0 + wh = where(abs(r[delm]) LT rthresh, ct) + if ct GT 0 then begin + nsing = wh[0] + wa1[wh[0]:*] = 0 + endif + + if nsing GE 1 then begin + ;; *** Reverse loop *** + for j=nsing-1,0,-1 do begin + wa1[j] = wa1[j]/r[j,j] + if (j-1 GE 0) then $ + wa1[0:(j-1)] = wa1[0:(j-1)] - r[0:(j-1),j]*wa1[j] + endfor + endif + + ;; Note: ipvt here is a permutation array + x[ipvt] = wa1 + + ;; Initialize the iteration counter. Evaluate the function at the + ;; origin, and test for acceptance of the gauss-newton direction + iter = 0L + wa2 = diag * x + dxnorm = mpfit_enorm(wa2) + fp = dxnorm - delta + if fp LE 0.1*delta then goto, TERMINATE + + ;; If the jacobian is not rank deficient, the newton step provides a + ;; lower bound, parl, for the zero of the function. Otherwise set + ;; this bound to zero. + + zero = wa2[0]*0. + parl = zero + if nsing GE n then begin + wa1 = diag[ipvt]*wa2[ipvt]/dxnorm + + wa1[0] = wa1[0] / r[0,0] ;; Degenerate case + for j=1L, n-1 do begin ;; Note "1" here, not zero + sum = total(r[0:(j-1),j]*wa1[0:(j-1)]) + wa1[j] = (wa1[j] - sum)/r[j,j] + endfor + + temp = mpfit_enorm(wa1) + parl = ((fp/delta)/temp)/temp + endif + + ;; Calculate an upper bound, paru, for the zero of the function + for j=0L, n-1 do begin + sum = total(r[0:j,j]*qtb[0:j]) + wa1[j] = sum/diag[ipvt[j]] + endfor + gnorm = mpfit_enorm(wa1) + paru = gnorm/delta + if paru EQ 0 then paru = DWARF/min([delta,0.1]) + + ;; If the input par lies outside of the interval (parl,paru), set + ;; par to the closer endpoint + + par = max([par,parl]) + par = min([par,paru]) + if par EQ 0 then par = gnorm/dxnorm + + ;; Beginning of an interation + ITERATION: + iter = iter + 1 + + ;; Evaluate the function at the current value of par + if par EQ 0 then par = max([DWARF, paru*0.001]) + temp = sqrt(par) + wa1 = temp * diag + mpfit_qrsolv, r, ipvt, wa1, qtb, x, sdiag + wa2 = diag*x + dxnorm = mpfit_enorm(wa2) + temp = fp + fp = dxnorm - delta + + if (abs(fp) LE 0.1D*delta) $ + OR ((parl EQ 0) AND (fp LE temp) AND (temp LT 0)) $ + OR (iter EQ 10) then goto, TERMINATE + + ;; Compute the newton correction + wa1 = diag[ipvt]*wa2[ipvt]/dxnorm + + for j=0L,n-2 do begin + wa1[j] = wa1[j]/sdiag[j] + wa1[j+1:n-1] = wa1[j+1:n-1] - r[j+1:n-1,j]*wa1[j] + endfor + wa1[n-1] = wa1[n-1]/sdiag[n-1] ;; Degenerate case + + temp = mpfit_enorm(wa1) + parc = ((fp/delta)/temp)/temp + + ;; Depending on the sign of the function, update parl or paru + if fp GT 0 then parl = max([parl,par]) + if fp LT 0 then paru = min([paru,par]) + + ;; Compute an improved estimate for par + par = max([parl, par+parc]) + + ;; End of an iteration + goto, ITERATION + + TERMINATE: + ;; Termination + ; profvals.lmpar = profvals.lmpar + (systime(1) - prof_start) + if iter EQ 0 then return, par[0]*0. + return, par +end + +;; Procedure to tie one parameter to another. +pro mpfit_tie, p, _ptied + COMPILE_OPT strictarr + if n_elements(_ptied) EQ 0 then return + if n_elements(_ptied) EQ 1 then if _ptied[0] EQ '' then return + for _i = 0L, n_elements(_ptied)-1 do begin + if _ptied[_i] EQ '' then goto, NEXT_TIE + _cmd = 'p['+strtrim(_i,2)+'] = '+_ptied[_i] + _err = execute(_cmd) + if _err EQ 0 then begin + message, 'ERROR: Tied expression "'+_cmd+'" failed.' + return + endif + NEXT_TIE: + endfor +end + +;; Default print procedure +pro mpfit_defprint, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, $ + p11, p12, p13, p14, p15, p16, p17, p18, $ + format=format, unit=unit0, _EXTRA=extra + + COMPILE_OPT strictarr + if n_elements(unit0) EQ 0 then unit = -1 else unit = round(unit0[0]) + if n_params() EQ 0 then printf, unit, '' $ + else if n_params() EQ 1 then printf, unit, p1, format=format $ + else if n_params() EQ 2 then printf, unit, p1, p2, format=format $ + else if n_params() EQ 3 then printf, unit, p1, p2, p3, format=format $ + else if n_params() EQ 4 then printf, unit, p1, p2, p4, format=format + + return +end + + +;; Default procedure to be called every iteration. It simply prints +;; the parameter values. +pro mpfit_defiter, fcn, x, iter, fnorm, FUNCTARGS=fcnargs, $ + quiet=quiet, iterstop=iterstop, iterkeybyte=iterkeybyte, $ + parinfo=parinfo, iterprint=iterprint0, $ + format=fmt, pformat=pformat, dof=dof0, _EXTRA=iterargs + + COMPILE_OPT strictarr + common mpfit_error, mperr + mperr = 0 + + if keyword_set(quiet) then goto, DO_ITERSTOP + if n_params() EQ 3 then begin + fvec = mpfit_call(fcn, x, _EXTRA=fcnargs) + fnorm = mpfit_enorm(fvec)^2 + endif + + ;; Determine which parameters to print + nprint = n_elements(x) + iprint = lindgen(nprint) + + if n_elements(iterprint0) EQ 0 then iterprint = 'MPFIT_DEFPRINT' $ + else iterprint = strtrim(iterprint0[0],2) + + if n_elements(dof0) EQ 0 then dof = 1L else dof = floor(dof0[0]) + call_procedure, iterprint, iter, fnorm, dof, $ + format='("Iter ",I6," CHI-SQUARE = ",G15.8," DOF = ",I0)', $ + _EXTRA=iterargs + if n_elements(fmt) GT 0 then begin + call_procedure, iterprint, x, format=fmt, _EXTRA=iterargs + endif else begin + if n_elements(pformat) EQ 0 then pformat = '(G20.6)' + parname = 'P('+strtrim(iprint,2)+')' + pformats = strarr(nprint) + pformat + + if n_elements(parinfo) GT 0 then begin + parinfo_tags = tag_names(parinfo) + wh = where(parinfo_tags EQ 'PARNAME', ct) + if ct EQ 1 then begin + wh = where(parinfo.parname NE '', ct) + if ct GT 0 then $ + parname[wh] = strmid(parinfo[wh].parname,0,25) + endif + wh = where(parinfo_tags EQ 'MPPRINT', ct) + if ct EQ 1 then begin + iprint = where(parinfo.mpprint EQ 1, nprint) + if nprint EQ 0 then goto, DO_ITERSTOP + endif + wh = where(parinfo_tags EQ 'MPFORMAT', ct) + if ct EQ 1 then begin + wh = where(parinfo.mpformat NE '', ct) + if ct GT 0 then pformats[wh] = parinfo[wh].mpformat + endif + endif + + for i = 0L, nprint-1 do begin + call_procedure, iterprint, parname[iprint[i]], x[iprint[i]], $ + format='(" ",A0," = ",'+pformats[iprint[i]]+')', $ + _EXTRA=iterargs + endfor + endelse + + DO_ITERSTOP: + if n_elements(iterkeybyte) EQ 0 then iterkeybyte = 7b + if keyword_set(iterstop) then begin + k = get_kbrd(0) + if k EQ string(iterkeybyte[0]) then begin + message, 'WARNING: minimization not complete', /info + print, 'Do you want to terminate this procedure? (y/n)', $ + format='(A,$)' + k = '' + read, k + if strupcase(strmid(k,0,1)) EQ 'Y' then begin + message, 'WARNING: Procedure is terminating.', /info + mperr = -1 + endif + endif + endif + + return +end + +;; Procedure to parse the parameter values in PARINFO +pro mpfit_parinfo, parinfo, tnames, tag, values, default=def, status=status, $ + n_param=n + + COMPILE_OPT strictarr + status = 0 + if n_elements(n) EQ 0 then n = n_elements(parinfo) + + if n EQ 0 then begin + if n_elements(def) EQ 0 then return + values = def + status = 1 + return + endif + + if n_elements(parinfo) EQ 0 then goto, DO_DEFAULT + if n_elements(tnames) EQ 0 then tnames = tag_names(parinfo) + wh = where(tnames EQ tag, ct) + + if ct EQ 0 then begin + DO_DEFAULT: + if n_elements(def) EQ 0 then return + values = make_array(n, value=def[0]) + values[0] = def + endif else begin + values = parinfo.(wh[0]) + np = n_elements(parinfo) + nv = n_elements(values) + values = reform(values[*], nv/np, np) + endelse + + status = 1 + return +end + + +; ********** +; +; subroutine covar +; +; given an m by n matrix a, the problem is to determine +; the covariance matrix corresponding to a, defined as +; +; t +; inverse(a *a) . +; +; this subroutine completes the solution of the problem +; if it is provided with the necessary information from the +; qr factorization, with column pivoting, of a. that is, if +; a*p = q*r, where p is a permutation matrix, q has orthogonal +; columns, and r is an upper triangular matrix with diagonal +; elements of nonincreasing magnitude, then covar expects +; the full upper triangle of r and the permutation matrix p. +; the covariance matrix is then computed as +; +; t t +; p*inverse(r *r)*p . +; +; if a is nearly rank deficient, it may be desirable to compute +; the covariance matrix corresponding to the linearly independent +; columns of a. to define the numerical rank of a, covar uses +; the tolerance tol. if l is the largest integer such that +; +; abs(r(l,l)) .gt. tol*abs(r(1,1)) , +; +; then covar computes the covariance matrix corresponding to +; the first l columns of r. for k greater than l, column +; and row ipvt(k) of the covariance matrix are set to zero. +; +; the subroutine statement is +; +; subroutine covar(n,r,ldr,ipvt,tol,wa) +; +; where +; +; n is a positive integer input variable set to the order of r. +; +; r is an n by n array. on input the full upper triangle must +; contain the full upper triangle of the matrix r. on output +; r contains the square symmetric covariance matrix. +; +; ldr is a positive integer input variable not less than n +; which specifies the leading dimension of the array r. +; +; ipvt is an integer input array of length n which defines the +; permutation matrix p such that a*p = q*r. column j of p +; is column ipvt(j) of the identity matrix. +; +; tol is a nonnegative input variable used to define the +; numerical rank of a in the manner described above. +; +; wa is a work array of length n. +; +; subprograms called +; +; fortran-supplied ... dabs +; +; argonne national laboratory. minpack project. august 1980. +; burton s. garbow, kenneth e. hillstrom, jorge j. more +; +; ********** +function mpfit_covar, rr, ipvt, tol=tol + + COMPILE_OPT strictarr + sz = size(rr) + if sz[0] NE 2 then begin + message, 'ERROR: r must be a two-dimensional matrix' + return, -1L + endif + n = sz[1] + if n NE sz[2] then begin + message, 'ERROR: r must be a square matrix' + return, -1L + endif + + zero = rr[0] * 0. + one = zero + 1. + if n_elements(ipvt) EQ 0 then ipvt = lindgen(n) + r = rr + r = reform(rr, n, n, /overwrite) + + ;; Form the inverse of r in the full upper triangle of r + l = -1L + if n_elements(tol) EQ 0 then tol = one*1.E-14 + tolr = tol * abs(r[0,0]) + for k = 0L, n-1 do begin + if abs(r[k,k]) LE tolr then goto, INV_END_LOOP + r[k,k] = one/r[k,k] + for j = 0L, k-1 do begin + temp = r[k,k] * r[j,k] + r[j,k] = zero + r[0,k] = r[0:j,k] - temp*r[0:j,j] + endfor + l = k + endfor + INV_END_LOOP: + + ;; Form the full upper triangle of the inverse of (r transpose)*r + ;; in the full upper triangle of r + if l GE 0 then $ + for k = 0L, l do begin + for j = 0L, k-1 do begin + temp = r[j,k] + r[0,j] = r[0:j,j] + temp*r[0:j,k] + endfor + temp = r[k,k] + r[0,k] = temp * r[0:k,k] + endfor + + ;; Form the full lower triangle of the covariance matrix + ;; in the strict lower triangle of r and in wa + wa = replicate(r[0,0], n) + for j = 0L, n-1 do begin + jj = ipvt[j] + sing = j GT l + for i = 0L, j do begin + if sing then r[i,j] = zero + ii = ipvt[i] + if ii GT jj then r[ii,jj] = r[i,j] + if ii LT jj then r[jj,ii] = r[i,j] + endfor + wa[jj] = r[j,j] + endfor + + ;; Symmetrize the covariance matrix in r + for j = 0L, n-1 do begin + r[0:j,j] = r[j,0:j] + r[j,j] = wa[j] + endfor + + return, r +end + +;; Parse the RCSID revision number +function mpfit_revision + ;; NOTE: this string is changed every time an RCS check-in occurs + revision = '$Revision: 1.82 $' + + ;; Parse just the version number portion + revision = stregex(revision,'\$'+'Revision: *([0-9.]+) *'+'\$',/extract,/sub) + revision = revision[1] + return, revision +end + +;; Parse version numbers of the form 'X.Y' +function mpfit_parse_version, version + sz = size(version) + if sz[sz[0]+1] NE 7 then return, 0 + + s = stregex(version[0], '^([0-9]+)\.([0-9]+)$', /extract,/sub) + if s[0] NE version[0] then return, 0 + return, long(s[1:2]) +end + +;; Enforce a minimum version number +function mpfit_min_version, version, min_version + mv = mpfit_parse_version(min_version) + if mv[0] EQ 0 then return, 0 + v = mpfit_parse_version(version) + + ;; Compare version components + if v[0] LT mv[0] then return, 0 + if v[1] LT mv[1] then return, 0 + return, 1 +end + +; Manually reset recursion fencepost if the user gets in trouble +pro mpfit_reset_recursion + common mpfit_fencepost, mpfit_fencepost_active + mpfit_fencepost_active = 0 +end + +; ********** +; +; subroutine lmdif +; +; the purpose of lmdif is to minimize the sum of the squares of +; m nonlinear functions in n variables by a modification of +; the levenberg-marquardt algorithm. the user must provide a +; subroutine which calculates the functions. the jacobian is +; then calculated by a forward-difference approximation. +; +; the subroutine statement is +; +; subroutine lmdif(fcn,m,n,x,fvec,ftol,xtol,gtol,maxfev,epsfcn, +; diag,mode,factor,nprint,info,nfev,fjac, +; ldfjac,ipvt,qtf,wa1,wa2,wa3,wa4) +; +; where +; +; fcn is the name of the user-supplied subroutine which +; calculates the functions. fcn must be declared +; in an external statement in the user calling +; program, and should be written as follows. +; +; subroutine fcn(m,n,x,fvec,iflag) +; integer m,n,iflag +; double precision x(n),fvec(m) +; ---------- +; calculate the functions at x and +; return this vector in fvec. +; ---------- +; return +; end +; +; the value of iflag should not be changed by fcn unless +; the user wants to terminate execution of lmdif. +; in this case set iflag to a negative integer. +; +; m is a positive integer input variable set to the number +; of functions. +; +; n is a positive integer input variable set to the number +; of variables. n must not exceed m. +; +; x is an array of length n. on input x must contain +; an initial estimate of the solution vector. on output x +; contains the final estimate of the solution vector. +; +; fvec is an output array of length m which contains +; the functions evaluated at the output x. +; +; ftol is a nonnegative input variable. termination +; occurs when both the actual and predicted relative +; reductions in the sum of squares are at most ftol. +; therefore, ftol measures the relative error desired +; in the sum of squares. +; +; xtol is a nonnegative input variable. termination +; occurs when the relative error between two consecutive +; iterates is at most xtol. therefore, xtol measures the +; relative error desired in the approximate solution. +; +; gtol is a nonnegative input variable. termination +; occurs when the cosine of the angle between fvec and +; any column of the jacobian is at most gtol in absolute +; value. therefore, gtol measures the orthogonality +; desired between the function vector and the columns +; of the jacobian. +; +; maxfev is a positive integer input variable. termination +; occurs when the number of calls to fcn is at least +; maxfev by the end of an iteration. +; +; epsfcn is an input variable used in determining a suitable +; step length for the forward-difference approximation. this +; approximation assumes that the relative errors in the +; functions are of the order of epsfcn. if epsfcn is less +; than the machine precision, it is assumed that the relative +; errors in the functions are of the order of the machine +; precision. +; +; diag is an array of length n. if mode = 1 (see +; below), diag is internally set. if mode = 2, diag +; must contain positive entries that serve as +; multiplicative scale factors for the variables. +; +; mode is an integer input variable. if mode = 1, the +; variables will be scaled internally. if mode = 2, +; the scaling is specified by the input diag. other +; values of mode are equivalent to mode = 1. +; +; factor is a positive input variable used in determining the +; initial step bound. this bound is set to the product of +; factor and the euclidean norm of diag*x if nonzero, or else +; to factor itself. in most cases factor should lie in the +; interval (.1,100.). 100. is a generally recommended value. +; +; nprint is an integer input variable that enables controlled +; printing of iterates if it is positive. in this case, +; fcn is called with iflag = 0 at the beginning of the first +; iteration and every nprint iterations thereafter and +; immediately prior to return, with x and fvec available +; for printing. if nprint is not positive, no special calls +; of fcn with iflag = 0 are made. +; +; info is an integer output variable. if the user has +; terminated execution, info is set to the (negative) +; value of iflag. see description of fcn. otherwise, +; info is set as follows. +; +; info = 0 improper input parameters. +; +; info = 1 both actual and predicted relative reductions +; in the sum of squares are at most ftol. +; +; info = 2 relative error between two consecutive iterates +; is at most xtol. +; +; info = 3 conditions for info = 1 and info = 2 both hold. +; +; info = 4 the cosine of the angle between fvec and any +; column of the jacobian is at most gtol in +; absolute value. +; +; info = 5 number of calls to fcn has reached or +; exceeded maxfev. +; +; info = 6 ftol is too small. no further reduction in +; the sum of squares is possible. +; +; info = 7 xtol is too small. no further improvement in +; the approximate solution x is possible. +; +; info = 8 gtol is too small. fvec is orthogonal to the +; columns of the jacobian to machine precision. +; +; nfev is an integer output variable set to the number of +; calls to fcn. +; +; fjac is an output m by n array. the upper n by n submatrix +; of fjac contains an upper triangular matrix r with +; diagonal elements of nonincreasing magnitude such that +; +; t t t +; p *(jac *jac)*p = r *r, +; +; where p is a permutation matrix and jac is the final +; calculated jacobian. column j of p is column ipvt(j) +; (see below) of the identity matrix. the lower trapezoidal +; part of fjac contains information generated during +; the computation of r. +; +; ldfjac is a positive integer input variable not less than m +; which specifies the leading dimension of the array fjac. +; +; ipvt is an integer output array of length n. ipvt +; defines a permutation matrix p such that jac*p = q*r, +; where jac is the final calculated jacobian, q is +; orthogonal (not stored), and r is upper triangular +; with diagonal elements of nonincreasing magnitude. +; column j of p is column ipvt(j) of the identity matrix. +; +; qtf is an output array of length n which contains +; the first n elements of the vector (q transpose)*fvec. +; +; wa1, wa2, and wa3 are work arrays of length n. +; +; wa4 is a work array of length m. +; +; subprograms called +; +; user-supplied ...... fcn +; +; minpack-supplied ... dpmpar,enorm,fdjac2,lmpar,qrfac +; +; fortran-supplied ... dabs,dmax1,dmin1,dsqrt,mod +; +; argonne national laboratory. minpack project. march 1980. +; burton s. garbow, kenneth e. hillstrom, jorge j. more +; +; ********** +function mpfit, fcn, xall, FUNCTARGS=fcnargs, SCALE_FCN=scalfcn, $ + ftol=ftol0, xtol=xtol0, gtol=gtol0, epsfcn=epsfcn, $ + resdamp=damp0, $ + nfev=nfev, maxiter=maxiter, errmsg=errmsg, $ + factor=factor0, nprint=nprint0, STATUS=info, $ + iterproc=iterproc0, iterargs=iterargs, iterstop=ss,$ + iterkeystop=iterkeystop, $ + niter=iter, nfree=nfree, npegged=npegged, dof=dof, $ + diag=diag, rescale=rescale, autoderivative=autoderiv0, $ + pfree_index=ifree, $ + perror=perror, covar=covar, nocovar=nocovar, $ + bestnorm=fnorm, best_resid=fvec, $ + best_fjac=output_fjac, calc_fjac=calc_fjac, $ + parinfo=parinfo, quiet=quiet, nocatch=nocatch, $ + fastnorm=fastnorm0, proc=proc, query=query, $ + external_state=state, external_init=extinit, $ + external_fvec=efvec, external_fjac=efjac, $ + version=version, min_version=min_version0 + + COMPILE_OPT strictarr + info = 0L + errmsg = '' + + ;; Compute the revision number, to be returned in the VERSION and + ;; QUERY keywords. + common mpfit_revision_common, mpfit_revision_str + if n_elements(mpfit_revision_str) EQ 0 then $ + mpfit_revision_str = mpfit_revision() + version = mpfit_revision_str + + if keyword_set(query) then begin + if n_elements(min_version0) GT 0 then $ + if mpfit_min_version(version, min_version0[0]) EQ 0 then $ + return, 0 + return, 1 + endif + + if n_elements(min_version0) GT 0 then $ + if mpfit_min_version(version, min_version0[0]) EQ 0 then begin + message, 'ERROR: minimum required version '+min_version0[0]+' not satisfied', /info + return, !values.d_nan + endif + + if n_params() EQ 0 then begin + message, "USAGE: PARMS = MPFIT('MYFUNCT', START_PARAMS, ... )", /info + return, !values.d_nan + endif + + ;; Use of double here not a problem since f/x/gtol are all only used + ;; in comparisons + if n_elements(ftol0) EQ 0 then ftol = 1.D-10 else ftol = ftol0[0] + if n_elements(xtol0) EQ 0 then xtol = 1.D-10 else xtol = xtol0[0] + if n_elements(gtol0) EQ 0 then gtol = 1.D-10 else gtol = gtol0[0] + if n_elements(factor0) EQ 0 then factor = 100. else factor = factor0[0] + if n_elements(nprint0) EQ 0 then nprint = 1 else nprint = nprint0[0] + if n_elements(iterproc0) EQ 0 then iterproc = 'MPFIT_DEFITER' else iterproc = iterproc0[0] + if n_elements(autoderiv0) EQ 0 then autoderiv = 1 else autoderiv = autoderiv0[0] + if n_elements(fastnorm0) EQ 0 then fastnorm = 0 else fastnorm = fastnorm0[0] + if n_elements(damp0) EQ 0 then damp = 0 else damp = damp0[0] + + ;; These are special configuration parameters that can't be easily + ;; passed by MPFIT directly. + ;; FASTNORM - decide on which sum-of-squares technique to use (1) + ;; is fast, (0) is slower + ;; PROC - user routine is a procedure (1) or function (0) + ;; QANYTIED - set to 1 if any parameters are TIED, zero if none + ;; PTIED - array of strings, one for each parameter + common mpfit_config, mpconfig + mpconfig = {fastnorm: keyword_set(fastnorm), proc: 0, nfev: 0L, damp: damp} + common mpfit_machar, machvals + + iflag = 0L + catch_msg = 'in MPFIT' + nfree = 0L + npegged = 0L + dof = 0L + output_fjac = 0L + + ;; Set up a persistent fencepost that prevents recursive calls + common mpfit_fencepost, mpfit_fencepost_active + if n_elements(mpfit_fencepost_active) EQ 0 then mpfit_fencepost_active = 0 + if mpfit_fencepost_active then begin + errmsg = 'ERROR: recursion detected; you cannot run MPFIT recursively' + goto, TERMINATE + endif + ;; Only activate the fencepost if we are not in debugging mode + if NOT keyword_set(nocatch) then mpfit_fencepost_active = 1 + + + ;; Parameter damping doesn't work when user is providing their own + ;; gradients. + if damp NE 0 AND NOT keyword_set(autoderiv) then begin + errmsg = 'ERROR: keywords DAMP and AUTODERIV are mutually exclusive' + goto, TERMINATE + endif + + ;; Process the ITERSTOP and ITERKEYSTOP keywords, and turn this into + ;; a set of keywords to pass to MPFIT_DEFITER. + if strupcase(iterproc) EQ 'MPFIT_DEFITER' AND n_elements(iterargs) EQ 0 $ + AND keyword_set(ss) then begin + if n_elements(iterkeystop) GT 0 then begin + sz = size(iterkeystop) + tp = sz[sz[0]+1] + if tp EQ 7 then begin + ;; String - convert first char to byte + iterkeybyte = (byte(iterkeystop[0]))[0] + endif + if (tp GE 1 AND tp LE 3) OR (tp GE 12 AND tp LE 15) then begin + ;; Integer - convert to byte + iterkeybyte = byte(iterkeystop[0]) + endif + if n_elements(iterkeybyte) EQ 0 then begin + errmsg = 'ERROR: ITERKEYSTOP must be either a BYTE or STRING' + goto, TERMINATE + endif + + iterargs = {iterstop: 1, iterkeybyte: iterkeybyte} + endif else begin + iterargs = {iterstop: 1, iterkeybyte: 7b} + endelse + endif + + + ;; Handle error conditions gracefully + if NOT keyword_set(nocatch) then begin + catch, catcherror + if catcherror NE 0 then begin ;; An error occurred!!! + catch, /cancel + mpfit_fencepost_active = 0 + err_string = ''+!error_state.msg + message, /cont, 'Error detected while '+catch_msg+':' + message, /cont, err_string + message, /cont, 'Error condition detected. Returning to MAIN level.' + if errmsg EQ '' then $ + errmsg = 'Error detected while '+catch_msg+': '+err_string + if info EQ 0 then info = -18 + return, !values.d_nan + endif + endif + mpconfig = create_struct(mpconfig, 'NOCATCH', keyword_set(nocatch)) + + ;; Parse FCN function name - be sure it is a scalar string + sz = size(fcn) + if sz[0] NE 0 then begin + FCN_NAME: + errmsg = 'ERROR: MYFUNCT must be a scalar string' + goto, TERMINATE + endif + if sz[sz[0]+1] NE 7 then goto, FCN_NAME + + isext = 0 + if fcn EQ '(EXTERNAL)' then begin + if n_elements(efvec) EQ 0 OR n_elements(efjac) EQ 0 then begin + errmsg = 'ERROR: when using EXTERNAL function, EXTERNAL_FVEC '+$ + 'and EXTERNAL_FJAC must be defined' + goto, TERMINATE + endif + nv = n_elements(efvec) + nj = n_elements(efjac) + if (nj MOD nv) NE 0 then begin + errmsg = 'ERROR: the number of values in EXTERNAL_FJAC must be '+ $ + 'a multiple of the number of values in EXTERNAL_FVEC' + goto, TERMINATE + endif + isext = 1 + endif + + ;; Parinfo: + ;; --------------- STARTING/CONFIG INFO (passed in to routine, not changed) + ;; .value - starting value for parameter + ;; .fixed - parameter is fixed + ;; .limited - a two-element array, if parameter is bounded on + ;; lower/upper side + ;; .limits - a two-element array, lower/upper parameter bounds, if + ;; limited vale is set + ;; .step - step size in Jacobian calc, if greater than zero + + catch_msg = 'parsing input parameters' + ;; Parameters can either be stored in parinfo, or x. Parinfo takes + ;; precedence if it exists. + if n_elements(xall) EQ 0 AND n_elements(parinfo) EQ 0 then begin + errmsg = 'ERROR: must pass parameters in P or PARINFO' + goto, TERMINATE + endif + + ;; Be sure that PARINFO is of the right type + if n_elements(parinfo) GT 0 then begin + ;; Make sure the array is 1-D + parinfo = parinfo[*] + parinfo_size = size(parinfo) + if parinfo_size[parinfo_size[0]+1] NE 8 then begin + errmsg = 'ERROR: PARINFO must be a structure.' + goto, TERMINATE + endif + if n_elements(xall) GT 0 AND n_elements(xall) NE n_elements(parinfo) $ + then begin + errmsg = 'ERROR: number of elements in PARINFO and P must agree' + goto, TERMINATE + endif + endif + + ;; If the parameters were not specified at the command line, then + ;; extract them from PARINFO + if n_elements(xall) EQ 0 then begin + mpfit_parinfo, parinfo, tagnames, 'VALUE', xall, status=status + if status EQ 0 then begin + errmsg = 'ERROR: either P or PARINFO[*].VALUE must be supplied.' + goto, TERMINATE + endif + + sz = size(xall) + ;; Convert to double if parameters are not float or double + if sz[sz[0]+1] NE 4 AND sz[sz[0]+1] NE 5 then $ + xall = double(xall) + endif + xall = xall[*] ;; Make sure the array is 1-D + npar = n_elements(xall) + zero = xall[0] * 0. + one = zero + 1. + fnorm = -one + fnorm1 = -one + + ;; TIED parameters? + mpfit_parinfo, parinfo, tagnames, 'TIED', ptied, default='', n=npar + ptied = strtrim(ptied, 2) + wh = where(ptied NE '', qanytied) + qanytied = qanytied GT 0 + mpconfig = create_struct(mpconfig, 'QANYTIED', qanytied, 'PTIED', ptied) + + ;; FIXED parameters ? + mpfit_parinfo, parinfo, tagnames, 'FIXED', pfixed, default=0, n=npar + pfixed = pfixed EQ 1 + pfixed = pfixed OR (ptied NE '');; Tied parameters are also effectively fixed + + ;; Finite differencing step, absolute and relative, and sidedness of deriv. + mpfit_parinfo, parinfo, tagnames, 'STEP', step, default=zero, n=npar + mpfit_parinfo, parinfo, tagnames, 'RELSTEP', dstep, default=zero, n=npar + mpfit_parinfo, parinfo, tagnames, 'MPSIDE', dside, default=0, n=npar + ;; Debugging parameters + mpfit_parinfo, parinfo, tagnames, 'MPDERIV_DEBUG', ddebug, default=0, n=npar + mpfit_parinfo, parinfo, tagnames, 'MPDERIV_RELTOL', ddrtol, default=zero, n=npar + mpfit_parinfo, parinfo, tagnames, 'MPDERIV_ABSTOL', ddatol, default=zero, n=npar + + ;; Maximum and minimum steps allowed to be taken in one iteration + mpfit_parinfo, parinfo, tagnames, 'MPMAXSTEP', maxstep, default=zero, n=npar + mpfit_parinfo, parinfo, tagnames, 'MPMINSTEP', minstep, default=zero, n=npar + qmin = minstep * 0 ;; Remove minstep for now!! + qmax = maxstep NE 0 + wh = where(qmin AND qmax AND maxstep LT minstep, ct) + if ct GT 0 then begin + errmsg = 'ERROR: MPMINSTEP is greater than MPMAXSTEP' + goto, TERMINATE + endif + + ;; Finish up the free parameters + ifree = where(pfixed NE 1, nfree) + if nfree EQ 0 then begin + errmsg = 'ERROR: no free parameters' + goto, TERMINATE + endif + + ;; An external Jacobian must be checked against the number of + ;; parameters + if isext then begin + if (nj/nv) NE nfree then begin + errmsg = string(nv, nfree, nfree, $ + format=('("ERROR: EXTERNAL_FJAC must be a ",I0," x ",I0,' + $ + '" array, where ",I0," is the number of free parameters")')) + goto, TERMINATE + endif + endif + + ;; Compose only VARYING parameters + xnew = xall ;; xnew is the set of parameters to be returned + x = xnew[ifree] ;; x is the set of free parameters + ; Same for min/max step diagnostics + qmin = qmin[ifree] & minstep = minstep[ifree] + qmax = qmax[ifree] & maxstep = maxstep[ifree] + wh = where(qmin OR qmax, ct) + qminmax = ct GT 0 + + + ;; LIMITED parameters ? + mpfit_parinfo, parinfo, tagnames, 'LIMITED', limited, status=st1 + mpfit_parinfo, parinfo, tagnames, 'LIMITS', limits, status=st2 + if st1 EQ 1 AND st2 EQ 1 then begin + + ;; Error checking on limits in parinfo + wh = where((limited[0,*] AND xall LT limits[0,*]) OR $ + (limited[1,*] AND xall GT limits[1,*]), ct) + if ct GT 0 then begin + errmsg = 'ERROR: parameters are not within PARINFO limits' + goto, TERMINATE + endif + wh = where(limited[0,*] AND limited[1,*] AND $ + limits[0,*] GE limits[1,*] AND $ + pfixed EQ 0, ct) + if ct GT 0 then begin + errmsg = 'ERROR: PARINFO parameter limits are not consistent' + goto, TERMINATE + endif + + + ;; Transfer structure values to local variables + qulim = limited[1, ifree] + ulim = limits [1, ifree] + qllim = limited[0, ifree] + llim = limits [0, ifree] + + wh = where(qulim OR qllim, ct) + if ct GT 0 then qanylim = 1 else qanylim = 0 + + endif else begin + + ;; Fill in local variables with dummy values + qulim = lonarr(nfree) + ulim = x * 0. + qllim = qulim + llim = x * 0. + qanylim = 0 + + endelse + + ;; Initialize the number of parameters pegged at a hard limit value + wh = where((qulim AND (x EQ ulim)) OR (qllim AND (x EQ llim)), npegged) + + n = n_elements(x) + if n_elements(maxiter) EQ 0 then maxiter = 200L + + ;; Check input parameters for errors + if (n LE 0) OR (ftol LE 0) OR (xtol LE 0) OR (gtol LE 0) $ + OR (maxiter LT 0) OR (factor LE 0) then begin + errmsg = 'ERROR: input keywords are inconsistent' + goto, TERMINATE + endif + + if keyword_set(rescale) then begin + errmsg = 'ERROR: DIAG parameter scales are inconsistent' + if n_elements(diag) LT n then goto, TERMINATE + wh = where(diag LE 0, ct) + if ct GT 0 then goto, TERMINATE + errmsg = '' + endif + + if n_elements(state) NE 0 AND NOT keyword_set(extinit) then begin + szst = size(state) + if szst[szst[0]+1] NE 8 then begin + errmsg = 'EXTERNAL_STATE keyword was not preserved' + status = 0 + goto, TERMINATE + endif + if nfree NE n_elements(state.ifree) then begin + BAD_IFREE: + errmsg = 'Number of free parameters must not change from one '+$ + 'external iteration to the next' + status = 0 + goto, TERMINATE + endif + wh = where(ifree NE state.ifree, ct) + if ct GT 0 then goto, BAD_IFREE + + tnames = tag_names(state) + for i = 0L, n_elements(tnames)-1 do begin + dummy = execute(tnames[i]+' = state.'+tnames[i]) + endfor + wa4 = reform(efvec, n_elements(efvec)) + + goto, RESUME_FIT + endif + + common mpfit_error, mperr + + if NOT isext then begin + mperr = 0 + catch_msg = 'calling '+fcn + fvec = mpfit_call(fcn, xnew, _EXTRA=fcnargs) + iflag = mperr + if iflag LT 0 then begin + errmsg = 'ERROR: first call to "'+fcn+'" failed' + goto, TERMINATE + endif + endif else begin + fvec = reform(efvec, n_elements(efvec)) + endelse + + catch_msg = 'calling MPFIT_SETMACHAR' + sz = size(fvec[0]) + isdouble = (sz[sz[0]+1] EQ 5) + + mpfit_setmachar, double=isdouble + + common mpfit_profile, profvals + ; prof_start = systime(1) + + MACHEP0 = machvals.machep + DWARF = machvals.minnum + + szx = size(x) + ;; The parameters and the squared deviations should have the same + ;; type. Otherwise the MACHAR-based evaluation will fail. + catch_msg = 'checking parameter data' + tp = szx[szx[0]+1] + if tp NE 4 AND tp NE 5 then begin + if NOT keyword_set(quiet) then begin + message, 'WARNING: input parameters must be at least FLOAT', /info + message, ' (converting parameters to FLOAT)', /info + endif + x = float(x) + xnew = float(x) + szx = size(x) + endif + if isdouble AND tp NE 5 then begin + if NOT keyword_set(quiet) then begin + message, 'WARNING: data is DOUBLE but parameters are FLOAT', /info + message, ' (converting parameters to DOUBLE)', /info + endif + x = double(x) + xnew = double(xnew) + endif + + m = n_elements(fvec) + if (m LT n) then begin + errmsg = 'ERROR: number of parameters must not exceed data' + goto, TERMINATE + endif + + fnorm = mpfit_enorm(fvec) + + ;; Initialize Levelberg-Marquardt parameter and iteration counter + + par = zero + iter = 1L + qtf = x * 0. + + ;; Beginning of the outer loop + + OUTER_LOOP: + + ;; If requested, call fcn to enable printing of iterates + xnew[ifree] = x + if qanytied then mpfit_tie, xnew, ptied + dof = (n_elements(fvec) - nfree) > 1L + + if nprint GT 0 AND iterproc NE '' then begin + catch_msg = 'calling '+iterproc + iflag = 0L + if (iter-1) MOD nprint EQ 0 then begin + mperr = 0 + xnew0 = xnew + + call_procedure, iterproc, fcn, xnew, iter, fnorm^2, $ + FUNCTARGS=fcnargs, parinfo=parinfo, quiet=quiet, $ + dof=dof, _EXTRA=iterargs + iflag = mperr + + ;; Check for user termination + if iflag LT 0 then begin + errmsg = 'WARNING: premature termination by "'+iterproc+'"' + goto, TERMINATE + endif + + ;; If parameters were changed (grrr..) then re-tie + if max(abs(xnew0-xnew)) GT 0 then begin + if qanytied then mpfit_tie, xnew, ptied + x = xnew[ifree] + endif + + endif + endif + + ;; Calculate the jacobian matrix + iflag = 2 + if NOT isext then begin + catch_msg = 'calling MPFIT_FDJAC2' + ;; NOTE! If you change this call then change the one during + ;; clean-up as well! + fjac = mpfit_fdjac2(fcn, x, fvec, step, qulim, ulim, dside, $ + iflag=iflag, epsfcn=epsfcn, $ + autoderiv=autoderiv, dstep=dstep, $ + FUNCTARGS=fcnargs, ifree=ifree, xall=xnew, $ + deriv_debug=ddebug, deriv_reltol=ddrtol, deriv_abstol=ddatol) + if iflag LT 0 then begin + errmsg = 'WARNING: premature termination by FDJAC2' + goto, TERMINATE + endif + endif else begin + fjac = reform(efjac,n_elements(fvec),npar, /overwrite) + endelse + + ;; Rescale the residuals and gradient, for use with "alternative" + ;; statistics such as the Cash statistic. + catch_msg = 'prescaling residuals and gradient' + if n_elements(scalfcn) GT 0 then begin + call_procedure, strtrim(scalfcn[0],2), fvec, fjac + endif + + ;; Determine if any of the parameters are pegged at the limits + npegged = 0L + if qanylim then begin + catch_msg = 'zeroing derivatives of pegged parameters' + whlpeg = where(qllim AND (x EQ llim), nlpeg) + whupeg = where(qulim AND (x EQ ulim), nupeg) + npegged = nlpeg + nupeg + + ;; See if any "pegged" values should keep their derivatives + if (nlpeg GT 0) then begin + ;; Total derivative of sum wrt lower pegged parameters + ;; Note: total(fvec*fjac[*,i]) is d(CHI^2)/dX[i] + for i = 0L, nlpeg-1 do begin + sum = total(fvec * fjac[*,whlpeg[i]]) + if sum GT 0 then fjac[*,whlpeg[i]] = 0 + endfor + endif + if (nupeg GT 0) then begin + ;; Total derivative of sum wrt upper pegged parameters + for i = 0L, nupeg-1 do begin + sum = total(fvec * fjac[*,whupeg[i]]) + if sum LT 0 then fjac[*,whupeg[i]] = 0 + endfor + endif + endif + + ;; Save a copy of the Jacobian if the user requests it... + if keyword_set(calc_fjac) then output_fjac = fjac + + ;; ===================== + ;; Compute the QR factorization of the jacobian + catch_msg = 'calling MPFIT_QRFAC' + ;; IN: Jacobian + ;; OUT: Hh Vects Permutation RDIAG ACNORM + mpfit_qrfac, fjac, ipvt, wa1, wa2, /pivot + ;; Jacobian - jacobian matrix computed by mpfit_fdjac2 + ;; Hh vects - house holder vectors from QR factorization & R matrix + ;; Permutation - permutation vector for pivoting + ;; RDIAG - diagonal elements of R matrix + ;; ACNORM - norms of input Jacobian matrix before factoring + + ;; ===================== + ;; On the first iteration if "diag" is unspecified, scale + ;; according to the norms of the columns of the initial jacobian + catch_msg = 'rescaling diagonal elements' + if (iter EQ 1) then begin + ;; Input: WA2 = root sum of squares of original Jacobian matrix + ;; DIAG = user-requested diagonal (not documented!) + ;; FACTOR = user-requested norm factor (not documented!) + ;; Output: DIAG = Diagonal scaling values + ;; XNORM = sum of squared scaled residuals + ;; DELTA = rescaled XNORM + + if NOT keyword_set(rescale) OR (n_elements(diag) LT n) then begin + diag = wa2 ;; Calculated from original Jacobian + wh = where (diag EQ 0, ct) ;; Handle zero values + if ct GT 0 then diag[wh] = one + endif + + ;; On the first iteration, calculate the norm of the scaled x + ;; and initialize the step bound delta + wa3 = diag * x ;; WA3 is temp variable + xnorm = mpfit_enorm(wa3) + delta = factor*xnorm + if delta EQ zero then delta = zero + factor + endif + + ;; Form (q transpose)*fvec and store the first n components in qtf + catch_msg = 'forming (q transpose)*fvec' + wa4 = fvec + for j=0L, n-1 do begin + lj = ipvt[j] + temp3 = fjac[j,lj] + if temp3 NE 0 then begin + fj = fjac[j:*,lj] + wj = wa4[j:*] + ;; *** optimization wa4(j:*) + wa4[j] = wj - fj * total(fj*wj) / temp3 + endif + fjac[j,lj] = wa1[j] + qtf[j] = wa4[j] + endfor + ;; From this point on, only the square matrix, consisting of the + ;; triangle of R, is needed. + fjac = fjac[0:n-1, 0:n-1] + fjac = reform(fjac, n, n, /overwrite) + fjac = fjac[*, ipvt] ;; Convert to permuted order + fjac = reform(fjac, n, n, /overwrite) + + ;; Check for overflow. This should be a cheap test here since FJAC + ;; has been reduced to a (small) square matrix, and the test is + ;; O(N^2). + wh = where(finite(fjac) EQ 0, ct) + if ct GT 0 then goto, FAIL_OVERFLOW + + ;; Compute the norm of the scaled gradient + catch_msg = 'computing the scaled gradient' + gnorm = zero + if fnorm NE 0 then begin + for j=0L, n-1 do begin + l = ipvt[j] + if wa2[l] NE 0 then begin + sum = total(fjac[0:j,j]*qtf[0:j])/fnorm + gnorm = max([gnorm,abs(sum/wa2[l])]) + endif + endfor + endif + + ;; Test for convergence of the gradient norm + if gnorm LE gtol then info = 4 + if info NE 0 then goto, TERMINATE + if maxiter EQ 0 then begin + info = 5 + goto, TERMINATE + endif + + ;; Rescale if necessary + if NOT keyword_set(rescale) then $ + diag = diag > wa2 + + ;; Beginning of the inner loop + INNER_LOOP: + + ;; Determine the levenberg-marquardt parameter + catch_msg = 'calculating LM parameter (MPFIT_LMPAR)' + par = mpfit_lmpar(fjac, ipvt, diag, qtf, delta, wa1, wa2, par=par) + + ;; Store the direction p and x+p. Calculate the norm of p + wa1 = -wa1 + + if qanylim EQ 0 AND qminmax EQ 0 then begin + ;; No parameter limits, so just move to new position WA2 + alpha = one + wa2 = x + wa1 + + endif else begin + + ;; Respect the limits. If a step were to go out of bounds, then + ;; we should take a step in the same direction but shorter distance. + ;; The step should take us right to the limit in that case. + alpha = one + + if qanylim EQ 1 then begin + ;; Do not allow any steps out of bounds + catch_msg = 'checking for a step out of bounds' + if nlpeg GT 0 then wa1[whlpeg] = wa1[whlpeg] > 0 + if nupeg GT 0 then wa1[whupeg] = wa1[whupeg] < 0 + + dwa1 = abs(wa1) GT MACHEP0 + whl = where(dwa1 AND qllim AND (x + wa1 LT llim), lct) + if lct GT 0 then $ + alpha = min([alpha, (llim[whl]-x[whl])/wa1[whl]]) + whu = where(dwa1 AND qulim AND (x + wa1 GT ulim), uct) + if uct GT 0 then $ + alpha = min([alpha, (ulim[whu]-x[whu])/wa1[whu]]) + endif + + ;; Obey any max step values. + + if qminmax EQ 1 then begin + nwa1 = wa1 * alpha + whmax = where(qmax AND maxstep GT 0, ct) + if ct GT 0 then begin + mrat = max(abs(nwa1[whmax])/abs(maxstep[whmax])) + if mrat GT 1 then alpha = alpha / mrat + endif + endif + + ;; Scale the resulting vector + wa1 = wa1 * alpha + wa2 = x + wa1 + + ;; Adjust the final output values. If the step put us exactly + ;; on a boundary, make sure we peg it there. + sgnu = (ulim GE 0)*2d - 1d + sgnl = (llim GE 0)*2d - 1d + + ;; Handles case of + ;; ... nonzero *LIM ... ... zero *LIM ... + ulim1 = ulim*(1-sgnu*MACHEP0) - (ulim EQ 0)*MACHEP0 + llim1 = llim*(1+sgnl*MACHEP0) + (llim EQ 0)*MACHEP0 + + wh = where(qulim AND (wa2 GE ulim1), ct) + if ct GT 0 then wa2[wh] = ulim[wh] + + wh = where(qllim AND (wa2 LE llim1), ct) + if ct GT 0 then wa2[wh] = llim[wh] + endelse + + wa3 = diag * wa1 + pnorm = mpfit_enorm(wa3) + + ;; On the first iteration, adjust the initial step bound + if iter EQ 1 then delta = min([delta,pnorm]) + + xnew[ifree] = wa2 + if isext then goto, SAVE_STATE + + ;; Evaluate the function at x+p and calculate its norm + mperr = 0 + catch_msg = 'calling '+fcn + wa4 = mpfit_call(fcn, xnew, _EXTRA=fcnargs) + iflag = mperr + if iflag LT 0 then begin + errmsg = 'WARNING: premature termination by "'+fcn+'"' + goto, TERMINATE + endif + RESUME_FIT: + fnorm1 = mpfit_enorm(wa4) + + ;; Compute the scaled actual reduction + catch_msg = 'computing convergence criteria' + actred = -one + if 0.1D * fnorm1 LT fnorm then actred = - (fnorm1/fnorm)^2 + 1. + + ;; Compute the scaled predicted reduction and the scaled directional + ;; derivative + for j = 0L, n-1 do begin + wa3[j] = 0 + wa3[0:j] = wa3[0:j] + fjac[0:j,j]*wa1[ipvt[j]] + endfor + + ;; Remember, alpha is the fraction of the full LM step actually + ;; taken + temp1 = mpfit_enorm(alpha*wa3)/fnorm + temp2 = (sqrt(alpha*par)*pnorm)/fnorm + half = zero + 0.5 + prered = temp1*temp1 + (temp2*temp2)/half + dirder = -(temp1*temp1 + temp2*temp2) + + ;; Compute the ratio of the actual to the predicted reduction. + ratio = zero + tenth = zero + 0.1 + if prered NE 0 then ratio = actred/prered + + ;; Update the step bound + if ratio LE 0.25D then begin + if actred GE 0 then temp = half $ + else temp = half*dirder/(dirder + half*actred) + if ((0.1D*fnorm1) GE fnorm) OR (temp LT 0.1D) then temp = tenth + delta = temp*min([delta,pnorm/tenth]) + par = par/temp + endif else begin + if (par EQ 0) OR (ratio GE 0.75) then begin + delta = pnorm/half + par = half*par + endif + endelse + + ;; Test for successful iteration + if ratio GE 0.0001 then begin + ;; Successful iteration. Update x, fvec, and their norms + x = wa2 + wa2 = diag * x + + fvec = wa4 + xnorm = mpfit_enorm(wa2) + fnorm = fnorm1 + iter = iter + 1 + endif + + ;; Tests for convergence + if (abs(actred) LE ftol) AND (prered LE ftol) $ + AND (0.5D * ratio LE 1) then info = 1 + if delta LE xtol*xnorm then info = 2 + if (abs(actred) LE ftol) AND (prered LE ftol) $ + AND (0.5D * ratio LE 1) AND (info EQ 2) then info = 3 + if info NE 0 then goto, TERMINATE + + ;; Tests for termination and stringent tolerances + if iter GE maxiter then info = 5 + if (abs(actred) LE MACHEP0) AND (prered LE MACHEP0) $ + AND (0.5*ratio LE 1) then info = 6 + if delta LE MACHEP0*xnorm then info = 7 + if gnorm LE MACHEP0 then info = 8 + if info NE 0 then goto, TERMINATE + + ;; End of inner loop. Repeat if iteration unsuccessful + if ratio LT 0.0001 then begin + goto, INNER_LOOP + endif + + ;; Check for over/underflow + wh = where(finite(wa1) EQ 0 OR finite(wa2) EQ 0 OR finite(x) EQ 0, ct) + if ct GT 0 OR finite(ratio) EQ 0 then begin + FAIL_OVERFLOW: + errmsg = ('ERROR: parameter or function value(s) have become '+$ + 'infinite; check model function for over- '+$ + 'and underflow') + info = -16 + goto, TERMINATE + endif + + ;; End of outer loop. + goto, OUTER_LOOP + + TERMINATE: + catch_msg = 'in the termination phase' + ;; Termination, either normal or user imposed. + if iflag LT 0 then info = iflag + iflag = 0 + if n_elements(xnew) EQ 0 then goto, FINAL_RETURN + if nfree EQ 0 then xnew = xall else xnew[ifree] = x + if n_elements(qanytied) GT 0 then if qanytied then mpfit_tie, xnew, ptied + dof = n_elements(fvec) - nfree + + + ;; Call the ITERPROC at the end of the fit, if the fit status is + ;; okay. Don't call it if the fit failed for some reason. + if info GT 0 then begin + + mperr = 0 + xnew0 = xnew + + call_procedure, iterproc, fcn, xnew, iter, fnorm^2, $ + FUNCTARGS=fcnargs, parinfo=parinfo, quiet=quiet, $ + dof=dof, _EXTRA=iterargs + iflag = mperr + + if iflag LT 0 then begin + errmsg = 'WARNING: premature termination by "'+iterproc+'"' + endif else begin + ;; If parameters were changed (grrr..) then re-tie + if max(abs(xnew0-xnew)) GT 0 then begin + if qanytied then mpfit_tie, xnew, ptied + x = xnew[ifree] + endif + endelse + + endif + + ;; Initialize the number of parameters pegged at a hard limit value + npegged = 0L + if n_elements(qanylim) GT 0 then if qanylim then begin + wh = where((qulim AND (x EQ ulim)) OR $ + (qllim AND (x EQ llim)), npegged) + endif + + ;; Calculate final function value (FNORM) and residuals (FVEC) + if isext EQ 0 AND nprint GT 0 AND info GT 0 then begin + catch_msg = 'calling '+fcn + fvec = mpfit_call(fcn, xnew, _EXTRA=fcnargs) + catch_msg = 'in the termination phase' + fnorm = mpfit_enorm(fvec) + endif + + if n_elements(fnorm) GT 0 AND n_elements(fnorm1) GT 0 then begin + fnorm = max([fnorm, fnorm1]) + fnorm = fnorm^2. + endif + + covar = !values.d_nan + ;; (very carefully) set the covariance matrix COVAR + if info GT 0 AND NOT keyword_set(nocovar) $ + AND n_elements(n) GT 0 $ + AND n_elements(fjac) GT 0 AND n_elements(ipvt) GT 0 then begin + sz = size(fjac) + if n GT 0 AND sz[0] GT 1 AND sz[1] GE n AND sz[2] GE n $ + AND n_elements(ipvt) GE n then begin + catch_msg = 'computing the covariance matrix' + if n EQ 1 then $ + cv = mpfit_covar(reform([fjac[0,0]],1,1), ipvt[0]) $ + else $ + cv = mpfit_covar(fjac[0:n-1,0:n-1], ipvt[0:n-1]) + cv = reform(cv, n, n, /overwrite) + nn = n_elements(xall) + + ;; Fill in actual covariance matrix, accounting for fixed + ;; parameters. + covar = replicate(zero, nn, nn) + for i = 0L, n-1 do begin + covar[ifree, ifree[i]] = cv[*,i] + end + + ;; Compute errors in parameters + catch_msg = 'computing parameter errors' + i = lindgen(nn) + perror = replicate(abs(covar[0])*0., nn) + wh = where(covar[i,i] GE 0, ct) + if ct GT 0 then $ + perror[wh] = sqrt(covar[wh, wh]) + endif + endif + + ; catch_msg = 'returning the result' + ; profvals.mpfit = profvals.mpfit + (systime(1) - prof_start) + + FINAL_RETURN: + mpfit_fencepost_active = 0 + nfev = mpconfig.nfev + if n_elements(xnew) EQ 0 then return, !values.d_nan + return, xnew + + + ;; ------------------------------------------------------------------ + ;; Alternate ending if the user supplies the function and gradients + ;; externally + ;; ------------------------------------------------------------------ + + SAVE_STATE: + + catch_msg = 'saving MPFIT state' + + ;; Names of variables to save + varlist = ['alpha', 'delta', 'diag', 'dwarf', 'factor', 'fnorm', $ + 'fjac', 'gnorm', 'nfree', 'ifree', 'ipvt', 'iter', $ + 'm', 'n', 'machvals', 'machep0', 'npegged', $ + 'whlpeg', 'whupeg', 'nlpeg', 'nupeg', $ + 'mpconfig', 'par', 'pnorm', 'qtf', $ + 'wa1', 'wa2', 'wa3', 'xnorm', 'x', 'xnew'] + cmd = '' + + ;; Construct an expression that will save them + for i = 0L, n_elements(varlist)-1 do begin + ival = 0 + dummy = execute('ival = n_elements('+varlist[i]+')') + if ival GT 0 then begin + cmd = cmd + ',' + varlist[i]+':'+varlist[i] + endif + endfor + cmd = 'state = create_struct({'+strmid(cmd,1)+'})' + state = 0 + + if execute(cmd) NE 1 then $ + message, 'ERROR: could not save MPFIT state' + + ;; Set STATUS keyword to prepare for next iteration, and reset init + ;; so we do not init the next time + info = 9 + extinit = 0 + + return, xnew + +end diff --git a/Joint Fitting/p0x123123batch.pro b/Joint Fitting/p0x123123batch.pro new file mode 100644 index 0000000..315dfc3 --- /dev/null +++ b/Joint Fitting/p0x123123batch.pro @@ -0,0 +1,4 @@ +for i=0,0 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/p1x123123batch.pro b/Joint Fitting/p1x123123batch.pro new file mode 100644 index 0000000..267e27b --- /dev/null +++ b/Joint Fitting/p1x123123batch.pro @@ -0,0 +1,4 @@ +for i=1,1 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/p2x123123batch.pro b/Joint Fitting/p2x123123batch.pro new file mode 100644 index 0000000..3215bab --- /dev/null +++ b/Joint Fitting/p2x123123batch.pro @@ -0,0 +1,4 @@ +for i=2,2 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/p3x123123batch.pro b/Joint Fitting/p3x123123batch.pro new file mode 100644 index 0000000..33a65d7 --- /dev/null +++ b/Joint Fitting/p3x123123batch.pro @@ -0,0 +1,4 @@ +for i=3,3 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/p4x123123batch.pro b/Joint Fitting/p4x123123batch.pro new file mode 100644 index 0000000..ec459bd --- /dev/null +++ b/Joint Fitting/p4x123123batch.pro @@ -0,0 +1,4 @@ +for i=4,5 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/p5x123123batch.pro b/Joint Fitting/p5x123123batch.pro new file mode 100644 index 0000000..316ecc9 --- /dev/null +++ b/Joint Fitting/p5x123123batch.pro @@ -0,0 +1,4 @@ +for i=5,5 do begin &$ +tag = "" &$ +a = run_2CXM_phantom(snr_dyn = snr_dyn, snr_vfa = snr_vfa, T1_dataType = T1_dataType,model = model,multithreadindex = index[i],tag = tag,n_repeats = n_repeats,n_vox_fit = n_vox_fit) &$ +endfor diff --git a/Joint Fitting/phantomAIF.dat b/Joint Fitting/phantomAIF.dat new file mode 100644 index 0000000000000000000000000000000000000000..8cb0b282f911d3450cd57df453bcb21ef53b23e3 GIT binary patch literal 1664 zcmWFzVqjrlVBlh4Ub_PkX!-~ zgT!!Qc8v)UB|6r|@%r=1!j0BT&NHoTlc3fpW;8?x<|pMGdR{i3(S z!X;@A=VniJIBRI(Ft0eqA#(2o2bHrA9fUt!bP!yVh*Z$t$fA)8etJvR}_}l(=T%-Lhoh|k^{!FmHeooZ>+Cm5Wt7W|Q zSA1&hFROIhU;Jlcf8l1O{rPR7_UERYus>UJ*8WUbs{LupUi(vW4)!Nm>g|ueakoEq zb*lZ*0~z*5*6g)EJZqBuq0VRa2dlQ)AISM{zdzxi{l3s2_IrJn+V62W2#gyxAcg|~ DS)R~2 literal 0 HcmV?d00001 diff --git a/Joint Fitting/randomgauss.pro b/Joint Fitting/randomgauss.pro new file mode 100644 index 0000000..75a1d3d --- /dev/null +++ b/Joint Fitting/randomgauss.pro @@ -0,0 +1,14 @@ +function randomgauss,seed_temp,sigma,input + +; Function to generate random deviate/s drawn from a gaussian distribution with parameter sigma. +; sigma is the standard deviation of X and Y where R = sqrt(x^2 + Y^2), and R~R(M,s) +; +; If we want to add noise to a previously noisefree signal such that the resulting signal is a sample from a rice distribution then: +; new = randomrice(old,s) + +s = size(input) + +X = abs(sigma*randomn(seed_temp,s[1],s[2],s[3],s[4]) + input) ; adding gaussian noise to original data + +return, X +end \ No newline at end of file diff --git a/Joint Fitting/read_analyze.pro b/Joint Fitting/read_analyze.pro new file mode 100644 index 0000000..6aa8e12 --- /dev/null +++ b/Joint Fitting/read_analyze.pro @@ -0,0 +1,25 @@ +function read_analyze, directory, n_timepoints = n_timepoints + +;Reads in a phantom dynamic timeseries. + + image_obj = OBJ_NEW('IDLffanalyze') ; read in info and pixels for the whole tumour mask + + image_obj->READFILE, directory + '\dyn_0.hdr' + img = image_obj->GETPIXELDATA() + + size_img = size(img) + img_4D = fltarr(size_img[1],size_img[2],size_img[3],n_timepoints) + dir = directory + + for i = 0, n_timepoints -1 do begin + + filename_hdr = dir + '\dyn_' + strtrim(strcompress(string(i)),1) + '.hdr' + image_obj->READFILE,filename_hdr + img_4D[*,*,*,i] = image_obj->GETPIXELDATA() + + endfor + + obj_destroy, image_obj + return, img_4D + +end diff --git a/Joint Fitting/run_2cxm_phantom.pro b/Joint Fitting/run_2cxm_phantom.pro new file mode 100644 index 0000000..66c2680 --- /dev/null +++ b/Joint Fitting/run_2cxm_phantom.pro @@ -0,0 +1,243 @@ +function run_2CXM_phantom,$ + snr_dyn = snr_dyn,$ + snr_vfa = snr_vfa,$ + T1_datatype = T1_datatype,$ + model = model, $ + MultiThreadIndex= MultiThreadIndex,$ + n_repeats = n_repeats,$ + n_vox_fit = n_vox_fit + + !EXCEPT=0 + + ;PURPOSE: wrapper for dcemriProcessor enabling Monte Carlo simulations. + + COMMON ve_vp_constraints, constrain + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + COMMON sigma_info, fixed_sigma, equal_sigma, known_sigma + + if MultiThreadIndex eq 1 then begin + fit_type = 'ifit' + aif_type = '1' + endif + + if MultiThreadIndex eq 2 then begin + fit_type = 'jfit' + aif_type = '1' + endif + + if MultiThreadIndex eq 3 then begin + fit_type = 'ifit' + aif_type = '2' + endif + + if MultiThreadIndex eq 4 then begin + fit_type = 'jfit' + aif_type = '2' + endif + + if MultiThreadIndex eq 5 then begin + fit_type = 'ifit' + aif_type = '3' + endif + + if MultiThreadIndex eq 6 then begin + fit_type = 'jfit' + aif_type = '3' + endif + + constrain = 'yes' + ostfORf = 'free';ostfORf is a setting that allows ost to vary in the actual model fit as a free parameter + FAfORf = 'fixed';if free then fits for flip angle error + mean_baseline = 163.0 + sigma_struct = {fixed_sigma:1,equal_sigma:0,known_sigma:{sigmaDYN:mean_baseline/5.,sigmaVFA:mean_baseline/11.2}} + + fixed_sigma = sigma_struct.fixed_sigma + equal_sigma = sigma_struct.equal_sigma + known_sigma = sigma_struct.known_sigma + + ; define imaging parameters + TR = 3.2/1000 + TE = 1.2/1000 + alpha_dyn = 25. + alpha_fa = [5.,10.,35.] + temporal_resolution = 2.5 + r = 4.5 + + ;------------------------------ Read in phantom data + ;dynamics + dyn_array = read_analyze('Dynamics/', n_timepoints = 96); reads in the synthetic dynamic time series + s = size(dyn_array) + column = s[1] + row = s[2] + n_slices = s[3] + n_timepoints = s[4] + + ;vfa images + nfa = 3; number of unique flip angles + + Fa_array = fltarr(s[1],s[2],s[3],nfa); define a 4D array to hold flip angle images + + filename_hdr5_0 = 'VFA\fa_5.hdr' + filename_hdr10_0 = 'VFA\fa_10.hdr' + filename_hdr35_0 = 'VFA\fa_35.hdr' + + image_obj = Obj_New('IDLffanalyze'); define an analyze object to read in analyze format files + + image_obj->READFILE,filename_hdr5_0 + Fa_array[*,*,*,0] = image_obj->GETPIXELDATA() + + image_obj->READFILE,filename_hdr10_0 + Fa_array[*,*,*,1] = image_obj->GETPIXELDATA() + + image_obj->READFILE,filename_hdr35_0 + Fa_array[*,*,*,2] = image_obj->GETPIXELDATA() + + ;reads in ROI mask + image_obj->READFILE, 'ROImask.hdr' + roi_mask = image_obj->GETPIXELDATA() + index = where(roi_mask gt 0) + roi_fourD = fltarr(column,row,n_slices,n_timepoints) + roi_mask[index] = 100.0 + + for i = 0, n_timepoints -1 do begin + + roi_fourD[*,*,*,i] = roi_mask + + endfor + + tumour_vox = dyn_array[*,*,*,0:6]*roi_fourD[*,*,*,0:6]/100.0 + + ;----------------------------------AIFs + ;accurate AIF + if aif_type eq '1' then begin + ;AIF from randomly chosen patient from bladder data + restore, 'PhantomAIF.dat' + ca = fit_ext + aif_cap = 4 ; this sets the first four timepoints to zero. + baseline_cap = 5.0; check this + timepoints = findgen(n_timepoints)*2.5/60; timepoints in minutes + endif + + ;overestimated AIF (scale x1.5) + if aif_type eq '2' then begin + ;AIF from randomly chosen patient from bladder data + restore, 'PhantomAIF.dat' + ca = fit_ext*1.5 + aif_cap = 4 ; this sets the first four timepoints to zero. + baseline_cap = 5.0; check this + timepoints = findgen(n_timepoints)*2.5/60; timepoints in minutes + endif + + ;underestimated AIF (scale x0.5) + if aif_type eq '3' then begin + ;AIF from randomly chosen patient from bladder data + restore, 'PhantomAIF.dat' + ca = fit_ext*0.5 + aif_cap = 4 ; this sets the first four timepoints to zero. + baseline_cap = 5.0; check this + timepoints = findgen(n_timepoints)*2.5/60 ; timepoints in minutes + endif + + ;-------------------------------- Add noise to images + + sigmaDYN = mean_baseline/snr_dyn + dyn_array_noisy = randomgauss(1,sigmaDYN,dyn_array); adds gaussian noise + sigmaVFA = mean_baseline/snr_vfa + Fa_array_noisy = randomgauss(2,sigmaVFA,Fa_array); adds gaussian noise + + actual_sigma = {sigmaDYN:sigmaDYN, sigmaVFA:sigmaVFA} + noisefree_images = fltarr(s[1],s[2],s[3],n_timepoints + nfa) + noisefree_images[*,*,*,0:n_timepoints-1] = dyn_array + noisefree_images[*,*,*,n_timepoints:*] = fa_array + + ;----------------------------- fit T1 mapping and tracer kinetic model to data using 'in house' DCEMRIprocessor code + + DCEMRIprocessor_freeS0_define; defines all variables needed for the DCEMRIprocessor object + processor = obj_new('DCEMRIprocessor_freeS0') + + processor->GET_DATA, $ ; input data to dcemriProcessor object + TR = TR, $ + alpha_dyn = alpha_dyn, $ + alpha_vfa = alpha_fa, $ + n_timepoints = n_timepoints, $ + n_slices = n_slices, $ + row = row, $ + column = column, $ + relaxivity = r, $ + timepoints = timepoints, $ + DCE_timeseries = dyn_array_noisy, $ + O_DCE_timeseries = dyn_array_noisy, $ + vfa_images = fa_array_noisy, $ + O_vfa_images = fa_array_noisy, $ + ROI_mask = ROI_fourD, $ + noisefree_images = noisefree_images + + Fp_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1); define arrays to hold parameter estimates + FE_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + vp_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + ve_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + T1_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + S0d_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + S0v_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + ost_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + FA_array_repeats = fltarr(s[1],s[2],s[3],n_repeats+1) + + ; make a folder in directory to save parameter estimates + CD, CURRENT=c + string = c + '\' + fit_type + '_snrDYN' + strtrim(string(snr_dyn,FORMAT = '( 2(I5))'),1) + '_snrVFA' + strtrim(string(snr_vfa,FORMAT = '( 2(I5))'),1) + '_' + aif_type + File_MKdir, string + + ; main function to fit models. Parameter estimates and fits are outputed in a structure + ; fits to n_vox_fit voxels once + output_struct = processor->Generate_maps(fit_type,'phantom',ca = ca,/update,T1_datatype = 'vfa',model = model, ostfORf = ostfORf,FAfORf = FAfORf, aif_cap = aif_cap,baseline_cap = baseline_cap, n_vox_fit = n_vox_fit) ; fits model for the first time. Outputs a structure containing parameter maps for each parameter. + + ref_timeseries = output_struct.ref_timeseries + ref_vfa_images = output_struct.ref_vfa_images + + ; repeat fits to n_vox_fit voxels (Monte Carlo experiement) + for i = 0, n_repeats do begin; For each repeat maps are recorded into arrays below. + + Fp_array_repeats[*,*,*,i] = output_struct.Fp_map + FE_array_repeats[*,*,*,i] = output_struct.FE_map + vp_array_repeats[*,*,*,i] = output_struct.vp_map + ve_array_repeats[*,*,*,i] = output_struct.ve_map + T1_array_repeats[*,*,*,i] = output_struct.T1_map + S0d_array_repeats[*,*,*,i] = output_struct.S0d_map + S0v_array_repeats[*,*,*,i] = output_struct.S0v_map + ost_array_repeats[*,*,*,i] = output_struct.ost_map + FA_array_repeats[*,*,*,i] = output_struct.flip_angle_map + + if i le n_repeats - 1 then begin + + seed_d = i+2 + seed_vfa = i+3 + ; adds different sample of noise to noise-free images + dyn_array_noisy = randomgauss(seed_d,sigmaDYN,dyn_array); adds a new sample of noise to the noisefree data + Fa_array_noisy = randomgauss(seed_vfa,sigmaVFA,Fa_array) + ;updates images in DCEMRIprocessor object + processor->GET_DATA, $ + DCE_timeseries = dyn_array_noisy,$ + vfa_images = fa_array_noisy ; updates the dce and vfa images in dcemriprocessor. + ;refits to new images + output_struct = processor->Generate_maps(fit_type,'phantom',T1_datatype = 'vfa',ca = ca,n_vox_fit = n_vox_fit, model = model, ostfORf = ostfORf,aif_cap = aif_cap, baseline_cap = baseline_cap); repeat fitting to new noisy data + + endif + + endfor + + ;saves parameter maps + save,Fp_array_repeats,filename = string + '\Fp.dat' + save,FE_array_repeats,filename = string + '\FE.dat' + save,vp_array_repeats,filename = string + '\vp.dat' + save,ve_array_repeats,filename = string + '\ve.dat' + save,T1_array_repeats,filename = string + '\T1.dat' + save,S0d_array_repeats,filename = string + '\S0d.dat' + save,S0v_array_repeats,filename = string + '\S0v.dat' + save,ost_array_repeats,filename = string + '\ost.dat' + + return, 1 + obj_destroy,processor + +END + + diff --git a/Joint Fitting/sample_from_array.pro b/Joint Fitting/sample_from_array.pro new file mode 100644 index 0000000..fb7218d --- /dev/null +++ b/Joint Fitting/sample_from_array.pro @@ -0,0 +1,49 @@ +function sample_from_array,array,no_samples,seed_no,no_replacement = no_replacement + +; a function to take random samples from an array with or without replacement. To sample without replacement add the /no_replacement keyword. +;print,array,no_samples +if n_elements(no_replacement) eq 0 then begin + +sample_array = fltarr(no_samples) + +s = n_elements(array) + +index_array = floor(s*randomu(seed_no,no_samples)) + +sample_array = array[index_array] + +endif + +if n_elements(no_replacement) gt 0 then begin + +sample_array = fltarr(no_samples) +index_array = fltarr(no_samples) + +s = n_elements(array) + +index_array[0] = floor(s*randomu(seed_no,1)) + + +for i = 1, no_samples -1 do begin + +index_array[i] = floor(s*randomu(seed_no,1)) + +index_1 = where(index_array[i] eq index_array[0:i-1],n) + +while n gt 0 do begin + + index_array[i] = floor(s*randomu(seed_no,1)) + + index_1 = where(index_array[i] eq index_array[0:i-1],n) + +endwhile + +endfor + +sample_array = array[index_array] + +endif + +return, sample_array + +end diff --git a/Joint Fitting/split_for.pro b/Joint Fitting/split_for.pro new file mode 100644 index 0000000..f8b5476 --- /dev/null +++ b/Joint Fitting/split_for.pro @@ -0,0 +1,283 @@ +;+ +;PURPOSE +; to split a for loop into N object parallel processes +;SYNTAX +; split_for, start, finish[, varnames=varnames, nsplit=nsplit, $ +; outvar=outvar, commands=commands, $ +; ctvariable_name=ctvariable_name, struct2pass1=struct2pass1,$ +; struct2pass2=struct2pass2, struct2pass3=struct2pass3,$ +; struct2pass4=struct2pass4, struct2pass5=struct2pass5, $ +; silent=silent, waittime=waittime,$ +; struct2out1=struct2out1,$ +; struct2out2=struct2out2, struct2out3=struct2out3,$ +; struct2out4=struct2out4, struct2out5=struct2out5] +; test=test +;INPUTS +; start: begining index for the for loop, note only loops increasing by +; 1 are allowed +; finish: ending index for the for loop +; commands: string array of commands. DO NOT INCLUDE COMMENTS with ';' +; ctvariable_name: a string scalar set to the name of the for loop index +; [default to 'i'] +; varnames: a string array of variable names you want passed +; to the child prcocess note that you have to +; pass tructures with the struct2pass keywords +; struct2pass[1...5]: structure to pass to child process +; outvar: string array of names of output variables +; this will be output to a variable with this name followed by +; a number denoted which string it came from. if you want to +; pull out a structure you must use the struct2out keywords +; waittime: time between tests to see if threads are complete [1] +; silent: set to suppress output +; struct2out[1...5]: structure to pull out of child +; process... [currently not implemented] +; debug: set to the number of the thread you want to debug +; /halt: set to place a STOP command before and after you run +; the batch script if debug is set +; levoff: how many levels up do you want to grab your variable names from +; wait_interval: time between each split +;EXAMPLE +; kk=10 +; split_for, 0, 10, commands=[$ +; 'print, i', 'kk++', 'mmm=kk*i'], varnames='kk', $ +; outvar='mmm' +; +; print, mmm0, mmm1 +; +;TO DO +; pass structures out +; maybe allow users to define an expression to +; combine the variables output from the strings +; but is that really any easier than them just doing it? +; notes... for simplicity, this code only accepts for loops +; which increase the ctvariable by 1 +; +;Written by R. da Silva, UCSC, 9-17-10 +;Updated by R. da Silva, UCSC, 3-14-11 == fixed some bugs + + +pro split_for, start, finish, varnames=varnames, nsplit=nsplit, $ + outvar=outvar, commands=commands, $ + ctvariable_name=ctvariable_name, struct2pass1=struct2pass1,$ + struct2pass2=struct2pass2, struct2pass3=struct2pass3,$ + struct2pass4=struct2pass4, struct2pass5=struct2pass5, $ + silent=silent, waittime=waittime,$ + struct2out1=struct2out1,$ + struct2out2=struct2out2, struct2out3=struct2out3,$ + struct2out4=struct2out4, struct2out5=struct2out5, test=test, $ + after_loop_commands=after_loop_commands, debug=debug, $ + levoff=levoff, halt=halt, wait_interval=wait_interval +;if ~keyword_set(levoff) then if scope_level() EQ 2 then levoff=2 + +fluff='x123123' +basename=fluff+'batch.pro' +basenamereduced = fluff+'batch +if n_elements(debug) NE 0 AND x_chkfil('simple_batch_451451', /silent) EQ 0 then begin + splog, 'simple batch file not written, writing and calling self recursively' + openw, lun2, 'simple_batch_451451', /get_lun + printf, lun2, 'p'+rstring(debug)+basename + close, lun2 + free_lun, lun2 + if keyword_set(levoff) then l1=levoff-1 else l1=-1 + split_for, start, finish, varnames=varnames, nsplit=nsplit, $ + outvar=outvar, commands=commands, $ + ctvariable_name=ctvariable_name, struct2pass1=struct2pass1,$ + struct2pass2=struct2pass2, struct2pass3=struct2pass3,$ + struct2pass4=struct2pass4, struct2pass5=struct2pass5, $ + silent=silent, waittime=waittime,$ + struct2out1=struct2out1,$ + struct2out2=struct2out2, struct2out3=struct2out3,$ + struct2out4=struct2out4, struct2out5=struct2out5, test=test, $ + after_loop_commands=after_loop_commands, debug=debug, levoff=l1, halt=halt +endif else begin + + if keyword_set(levoff) EQ 0 then levoff=0 + if keyword_set(silent) then verbose = 0 else verbose =1 + if not keyword_set(waittime) then waittime =1 + if not keyword_set(ctvariable_name) then ctvariable_name='i' +;first you need to make your IDL bridges + if not keyword_set(nsplit) then nsplit=2 + nsplit = nsplit < !CPU.HW_NCPU + + + nsplit=nsplit < (finish-start+1) ;don't want to duplicated jobs with too many threads + + step=ceil((finish-start+1.)/nsplit) + fin_arr=start+step*(findgen(nsplit)+ 1) + min_fin_arr=min(where(fin_arr GE finish)) + nsplit=min_fin_arr+1 + if keyword_set(verbose) then splog, 'Splitting job into ', nsplit, ' threads' + +;now we need to write the batch files that tell the child processes what to do + + for i=0, nsplit-1 do begin + openw,lun, 'p'+rstring(i)+basename, /get_lun + if i NE nsplit-1 then printf,lun, 'for '+ctvariable_name+'='+$ + rstring(start+i*step)+','+rstring(start+(i+1)*step-1)+' do begin &$' else $ + printf,lun, 'for '+ctvariable_name+'='+$ + rstring(start+i*step)+','+rstring(finish)+' do begin &$' + for j=0, n_elements(commands)-1 do printf, lun, commands[j]+' &$' + printf, lun, 'endfor' + if n_elements(after_loop_commands) NE 0 then $ + for j=0, n_elements(after_loop_commands)-1 do printf, lun, $ + after_loop_commands[j] +; printf, lun, 'splog, "*-*-*-*-*-*-*-*-*-*"' +; printf, lun, 'splog, "completed bridge '+rstring(i)+'"' +; printf, lun, 'splog, "*-*-*-*-*-*-*-*-*-*"' + close, lun + free_lun, lun + endfor + if keyword_set(test) then begin + splog, 'batch files have been written' + splog, '/test has been set so you can examine them' + STOP + endif + + + if n_elements(debug) EQ 0 then begin + obridge=obj_new("IDL_IDLBridge", output= FILE_EXPAND_PATH('log.log')) + + if nsplit GT 1 then begin + for i=1, nsplit-1 do begin + obridge=[obridge, obj_new("IDL_IDLBridge",output= FILE_EXPAND_PATH('log' + strtrim(string(i),1) + '.log'))] + endfor + + endif + + ;spawn + ;spawn, 'pwd', pwd + pwd = FILE_EXPAND_PATH('') + fluffx123123pwd=pwd +;now we pass variables and run the batch files + for i=0, n_elements(obridge)-1 do begin + ;need to pass variables... + ;structures are complicated so I have to kludge this.... + if keyword_set(struct2pass1) then $ + struct_pass, struct2pass1, obridge[i], lev=-2+levoff + if keyword_set(struct2pass2) then $ + struct_pass, struct2pass2, obridge[i], lev=-2+levoff + if keyword_set(struct2pass3) then $ + struct_pass, struct2pass3, obridge[i], lev=-2+levoff + if keyword_set(struct2pass4) then $ + struct_pass, struct2pass4, obridge[i], lev=-2+levoff + if keyword_set(struct2pass5) then $ + struct_pass, struct2pass5, obridge[i], lev=-2+levoff + if n_elements(varnames) NE 0 then $ + for j=0, n_elements(varnames)-1 do begin + + + ;move to the right directory + ;print, 'which_bridge', i +; obridge[i]->setvar, 'which_bridge', i + obridge[i]->setvar, 'fluffx123123pwd', fluffx123123pwd + +if keyword_set(wait_interval) then wait, wait_interval + obridge[i]->IDL_IDLBridge::execute, "cd, fluffx123123pwd" + ; + ;obridge[i]->IDL_IDLBridge::execute, "cd, C:\Users\ben dickie\IDLWorkspace82\Default" + obridge[i]->setvar, varnames[j], (scope_varfetch(varnames[j],level=-1+levoff)) + + + + endfor +; print, obridge[i] ->getvar(varnames[0]) +; print, obridge[i] ->getvar(varnames[1]) +; print, obridge[i] ->getvar(varnames[2]) +; print, obridge[i] ->getvar(varnames[3]) + + + ;run the batch files + ; print, '9',SCOPE_LEVEL() + + + oBridge[i]->IDL_IDLBridge::execute, '@' + 'p'+rstring(i)+basename,/nowait + IF(~OBJ_VALID(oBridge[i]))THEN BEGIN + void=DIALOG_MESSAGE(/ERROR,'Unable to access ' $ + + 'an IDL_IDLBridge object') + + ENDIF + ;print, obridge[i] ->status() + endfor + + + if keyword_set(verbose) then splog, 'Commands have been sent to threads' +;---------------------------------------------------- +;now we wait until the bridges are all done + alldone=0 + while alldone EQ 0 do begin + fins=0 + for i=0, nsplit-1 do begin + fins+=(obridge[i]->status() NE 1) + ;print, i, (obridge[i]->status() EQ 2) + endfor + wait, waittime + if fins EQ nsplit then alldone=1 + endwhile + if keyword_set(verbose) then splog, 'All threads complete' +;---------------------------------------------------- +;now we get our outputs out + if n_elements(outvar) NE 0 then begin + for j=0, n_elements(outvar)-1 do begin + for i=0, nsplit-1 do begin + ;use scopevarfetch with level=0 to make variables with the string names... with + (scope_varfetch(outvar[j]+rstring(i),$ + level=-1+levoff,/enter))=$ + obridge[i]->getvar(outvar[j]) + endfor + endfor + endif + +;---------------------------------------------------- +;now we delete our temp batch files + for i=0, nsplit-1 do begin + openw,lun, '@p'+rstring(i)+basename, /delete + print, 'deleted' + close, lun + free_lun, lun + endfor + +; you have to burn your idl bridges + for i=0, nsplit-1 do begin + obj_destroy, obridge[i] + endfor + endif else begin ;debug mode + splog, 'Entering Debug Mode testing thread ', debug +;pass variables to here + if keyword_set(struct2pass1) then $ + (scope_varfetch(scope_varname(struct2pass1, level=-1+levoff), level=0, /enter))=struct2pass1 + if keyword_set(struct2pass2) then $ + (scope_varfetch(scope_varname(struct2pass2, level=-1+levoff), level=0, /enter))=struct2pass2 + if keyword_set(struct2pass3) then $ + (scope_varfetch(scope_varname(struct2pass3, level=-1+levoff), level=0, /enter))=struct2pass3 + if keyword_set(struct2pass4) then $ + (scope_varfetch(scope_varname(struct2pass4, level=-1+levoff), level=0, /enter))=struct2pass4 + if keyword_set(struct2pass5) then $ + (scope_varfetch(scope_varname(struct2pass5, level=-1+levoff), level=0, /enter))=struct2pass5 + if n_elements(varnames) NE 0 then $ + for j=0, n_elements(varnames)-1 do $ + (scope_varfetch(varnames[j], level=0, /enter))=scope_varfetch(varnames[j], level=-1+levoff) +;run one of the batch files... stupid IDL execute can't handle batch files so I have to make +;a batch file which calls the batch file... ugh... + which_bridge=debug + splog, 'all variables have been passed' + +;I could avoid duplicated memory by replcaing all references to these variables +;to be (scope_varfetch(varname, level=-1)) but that seems annoying + + + if keyword_set(halt) then STOP + splog, $ + 'running batch file all lines in error message for' + splog, ' SPLIT_FOR refer to lines of the batch file' + @simple_batch_451451 + splog, 'if the batch file did not run then simply type @simple_batch_451451 to the command line now' + if keyword_set(halt) then STOP + endelse + splog, 'clean up' + if x_chkfil('simple_batch_451451',/silent) then begin + openw, lun3, 'simple_batch_451451', /get_lun, /delete + close, lun3 + free_lun, lun3 + endif +endelse +end diff --git a/Joint Fitting/tofts_ost_expc.pro b/Joint Fitting/tofts_ost_expc.pro new file mode 100644 index 0000000..8f7e948 --- /dev/null +++ b/Joint Fitting/tofts_ost_expc.pro @@ -0,0 +1,38 @@ +PRO Tofts_ost_expC,timepoints, Result, data + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON ost, T10_ost + + n_timepoints_ost = n_elements(timepoints) + + Ct = FLTARR(n_timepoints_ost) + data = FLTARR(n_timepoints_ost) + + Ktrans = result[0] + ve = result[1] + ost = result[2] + + timepoints_adjusted = timepoints-ost + + index = where(timepoints_adjusted lt 0) ; finds the timepoints that are negative + + timepoints_adjusted[index] = 0.0 ; sets the negative to zero + + adjusted_ca_for_ost = interpol(AIF[0:n_timepoints_ost-1],timepoints,timepoints_adjusted) + + X = [timepoints,adjusted_ca_for_ost] + + const = Ktrans/ve + + int1 = Expconvolution(const,X) + + Ct = Ktrans*int1 + + E1_0 = exp(-TR / T10_ost) ; no units + R1_t = (1.0 / T10_ost) + (r * Ct) ; units of s-1 + T1_t = 1.0 / R1_t ;units of s + E1_t = exp(-TR / T1_t) ; no units + + data = baseline * (1.0 - (cos(rad_dyn) * E1_0)) / (1.0 - E1_0) * (1.0 - E1_t) / (1.0 - (cos(rad_dyn) * E1_t)) + +END diff --git a/Joint Fitting/twocxm_ifit_dc.pro b/Joint Fitting/twocxm_ifit_dc.pro new file mode 100644 index 0000000..e7497cb --- /dev/null +++ b/Joint Fitting/twocxm_ifit_dc.pro @@ -0,0 +1,111 @@ +Pro TwoCXM_ifit_dc,timepoints, result, data + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON ve_vp_constraints, constrain + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + + t_factor = mean(timepoints[1:n_timepoints-1] - timepoints[0:n_timepoints-2]) + + Fp = result[2] + vp = result[3] + ve = result[4] + FE = result[5] + ost = result[7] + f = result[9] + + if constrain eq 'yes' then begin + + if ve + vp lt 1.0 then begin + + if ost gt 0 then begin + + AIF_time = timepoints - ost + + adj_AIF = interpol(AIF,timepoints,AIF_time) ; adjusting AIF for difference in ost between AIF and voxel. + + endif else begin ; if data is synthetic and has no offset time we don't need to adjust AIF + + adj_AIF = AIF + + endelse + + Tp_i = (Fp+FE)/vp + Te_i = FE/ve + Tb_i = Fp/vp + + K_p = 0.5*(Tp_i + Te_i + sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i)) + K_m = 0.5*(Tp_i + Te_i - sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i)) + E = (K_p - Tb_i)/(K_p - K_m) + + a1 = exp(-K_m*timepoints) + a2 = exp(-K_p*timepoints) + + int1 = convol(adj_AIF,a1,center = 0,/edge_zero)*t_factor + int2 = convol(adj_AIF,a2,center = 0,/edge_zero)*t_factor + + Ct = Fp*(E*int1 + (1.0-E)*int2) + + R1_t = Ct*r + 1.0/T10_v + + E1 = exp(-TR*R1_t) + + S0d_temp = baseline*((1- cos(f*rad_dyn)*exp(-TR/T10_v))/(sin(f*rad_dyn)*(1-exp(-TR/T10_v)))) + + result[0] = S0v + result[1] = T10_v + result[6] = S0d_temp + + data = S0d_temp*sin(f*rad_dyn)*(1-E1)/(1-E1*cos(f*rad_dyn)) ; S0d is calculated in LS_startparams + + + endif else begin + + data = fltarr(n_timepoints) + + endelse + + endif else begin ; if unconstrained fitting + + if ost gt 0 then begin + + AIF_time = timepoints - ost + + adj_AIF = interpol(AIF,timepoints,AIF_time) ; adjusting AIF for difference in ost between AIF and voxel. + + endif else begin ; if data is synthetic and has no offset time we don't need to adjust AIF + + adj_AIF = AIF + + endelse + + Tp_i = (Fp+FE)/vp + Te_i = FE/ve + Tb_i = Fp/vp + + K_p = 0.5*(Tp_i + Te_i + sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i)) + K_m = 0.5*(Tp_i + Te_i - sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i)) + E = (K_p - Tb_i)/(K_p - K_m) + + a1 = exp(-K_m*timepoints) + a2 = exp(-K_p*timepoints) + + int1 = convol(adj_AIF,a1,center = 0,/edge_zero)*t_factor + int2 = convol(adj_AIF,a2,center = 0,/edge_zero)*t_factor + + Ct = Fp*(E*int1 + (1.0-E)*int2) + + R1_t = Ct*r + 1.0/T10_v + + E1 = exp(-TR*R1_t) + + S0d_temp = baseline*((1- cos(f*rad_dyn)*exp(-TR/T10_v))/(sin(f*rad_dyn)*(1-exp(-TR/T10_v)))) + + result[0] = S0v + result[1] = T10_v + result[6] = S0d_temp + + data = S0d_temp*sin(f*rad_dyn)*(1-E1)/(1-E1*cos(f*rad_dyn)) + + endelse + + END diff --git a/Joint Fitting/twocxm_vfa_jfit_dc.pro b/Joint Fitting/twocxm_vfa_jfit_dc.pro new file mode 100644 index 0000000..a48586c --- /dev/null +++ b/Joint Fitting/twocxm_vfa_jfit_dc.pro @@ -0,0 +1,120 @@ +pro twoCXM_vfa_jfit_dc, x_meas, result, data3 + + COMMON fit_params, TR,rad_dyn,rad_vfa,Inv_times,r,T10_v,S0d,S0v,baseline,n_timepoints,AIF,adj_AIF + COMMON TwoCXM_params,E,K_m,K_p + COMMON ve_vp_constraints, constrain + COMMON S0_info, equal_and_free, unequal_and_free, equal_by_baseline + + timepoints = x_meas[0:n_timepoints-1] + + rad_vfa = x_meas[n_timepoints:*] + + t_factor = mean(timepoints[1:n_timepoints-1] - timepoints[0:n_timepoints-2]) + + S0v_temp = result[0] + T10_v_temp = result[1] + Fp = result[2] + vp = result[3] + ve = result[4] + FE = result[5] + S0d_temp = result[6] ; S0v is passed later on if required. Updates common block. + ost = result[7] + f = result[9] + + result[8] = (Fp*FE)/(Fp+FE); setting the value for Ktrans + + if constrain eq 'yes' then begin ; reject parameters where ve + vp > 1 + + if ve + vp lt 1.0 then begin + + + AIF_time = timepoints - ost + + adj_AIF = interpol(AIF,timepoints,AIF_time) ; adjusting AIF for difference in ost between AIF and voxel. + + + Tp_i = (Fp + FE)/vp + + Te_i = FE/ve + + Tb_i = Fp/vp + + K_p = (Tp_i + Te_i + sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i))/2 + K_m = (Tp_i + Te_i - sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i))/2 + E = (K_p - Tb_i)/(K_p-K_m) + + ;X = [timepoints, adj_ca] + + ;calculating the time_series curve + ;int1 = ExpConvolution(K_m,X) + ;int2 = ExpConvolution(K_p,X) + + a1 = exp(-K_m*timepoints) + a2 = exp(-K_p*timepoints) + + int1 = convol(adj_AIF,a1,center = 0,/edge_zero)*t_factor + int2 = convol(adj_AIF,a2,center = 0,/edge_zero)*t_factor + + Ct = Fp*(E*int1 + (1.0-E)*int2) + + R1_t = Ct*r + 1.0/T10_v_temp + E1 = exp(-TR*R1_t) + +; print, rad_dyn +; print, rad_vfa + + data1 = S0d_temp*sin(f*rad_dyn)*(1-E1)/(1-E1*cos(f*rad_dyn)) + + data2 = S0v_temp*sin(f*rad_vfa)*(1-exp(-TR/T10_v_temp))/(1- cos(f*rad_vfa)*exp(-TR/T10_v_temp)) + + data3 = [data1,data2] + + endif else begin + + data3 = fltarr(n_timepoints + 3) + + endelse + + endif else begin + + + AIF_time = timepoints - ost + + adj_AIF = interpol(AIF,timepoints,AIF_time) ; adjusting AIF for difference in ost between AIF and voxel. + + Tp_i = (Fp + FE)/vp + + Te_i = FE/ve + + Tb_i = Fp/vp + + K_p = (Tp_i + Te_i + sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i))/2 + K_m = (Tp_i + Te_i - sqrt(( Tp_i + Te_i)*( Tp_i + Te_i) - 4*Te_i*Tb_i))/2 + E = (K_p - Tb_i)/(K_p-K_m) + + ;X = [timepoints, adj_ca] + + ;calculating the time_series curve + ;int1 = ExpConvolution(K_m,X) + ;int2 = ExpConvolution(K_p,X) + + a1 = exp(-K_m*timepoints) + a2 = exp(-K_p*timepoints) + + int1 = convol(adj_AIF,a1,center = 0,/edge_zero)*t_factor + int2 = convol(adj_AIF,a2,center = 0,/edge_zero)*t_factor + + Ct = Fp*(E*int1 + (1.0-E)*int2) + + R1_t = Ct*r + 1.0/T10_v_temp + E1 = exp(-TR*R1_t) + + data1 = S0d_temp*sin(f*rad_dyn)*(1-E1)/(1-E1*cos(f*rad_dyn)) + + data2 = S0v_temp*sin(f*rad_vfa)*(1-exp(-TR/T10_v_temp))/(1- cos(f*rad_vfa)*exp(-TR/T10_v_temp)) + + data3 = [data1,data2] + + endelse + +end \ No newline at end of file