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ECM.py
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from sddsdata import sddsdata
import numpy as np
import scipy.io as sio
import os
import shutil
import gzip
import time
import glob
import pickle
from zip_mat import save_zip
import timestamp_helpers as th
class ECLDMON:
def __init__(self, complete_path, ecm_part):
if ecm_part not in ['a', 'b']:
raise ValueError
if complete_path.endswith('.mat.gz'):
temp_filename = complete_path.split('.gz')[0]
#print 'temp_filename', temp_filename
with open(temp_filename, "wb") as tmp:
shutil.copyfileobj(gzip.open(complete_path), tmp)
dict_ecld = sio.loadmat(temp_filename)
os.remove(temp_filename)
elif complete_path.endswith('.mat'):
dict_ecld = sio.loadmat(complete_path)
else:
print('Unknown file extension for ECLDMON file. Should be ' +
'.mat or .mat.gz')
ecld_mon_rescaled = dict_ecld['eclm_data']
TOTAL_GAIN = np.float_(np.squeeze(dict_ecld['TOTAL_GAIN']))
#compensate detector gain
for ii in range(len(TOTAL_GAIN)):
ecld_mon_rescaled[:,ii*16:(ii+1)*16] = ecld_mon_rescaled[:,ii*16:(ii+1)*16]/TOTAL_GAIN[ii]
#compensate integration time
self.time_vect = np.squeeze(dict_ecld['PROFILE_CYCLE_TIME'])
self.integ_time = self.time_vect[4]-self.time_vect[3];
ecld_mon_rescaled = ecld_mon_rescaled/self.integ_time
self.SC_numb = int(dict_ecld['SC_NUMBER'])
self.x_channels = 2.17*np.arange(0, 48.)
if ecm_part == 'a':
self.ecld_mat = ecld_mon_rescaled[:,0:48]
self.gain3 = TOTAL_GAIN[0:3]
else:
self.ecld_mat = ecld_mon_rescaled[:,48:96]
self.gain3 = TOTAL_GAIN[3:6]
def total_vs_channel(self):
return np.sum(self.ecld_mat,0)
def total_vs_time(self):
return np.sum(self.ecld_mat,1)
def profile(self, t_obs):
ind_min = np.argmin(np.abs(self.time_vect-t_obs))
return self.ecld_mat[ind_min,:]
def total_at_time(self, t_obs, chann_list=None):
temp = self.profile(t_obs)
if chann_list == None:
return np.sum(temp)
else:
return np.sum(np.take(temp, chann_list))
def make_pickle(start_from_last=True, pickle_name_ecm='ecm_overview.pkl', pickle_name_bct='bct_overview.pkl', mat_folder='ecm/', mat_file_prefix='SPSmeas_', t_obs_1st_inj=1.5, n_points_to_cut=10, SPSuser_blacklist = []):
with open(pickle_name_bct) as fid:
beams_bct = pickle.load(fid)
semcloud_lists = get_ecm_tstamps_from_filenames(mat_folder, SPSuser_blacklist, beams_bct)
try:
with open(pickle_name_ecm) as fid:
ecm_dict = pickle.load(fid)
except IOError:
print "I CREATE (!) the ecm pickle file"
ecm_dict = {'1a':{}, '1b':{}, '2a':{}, '2b':{}}
for ecm_id in '1a 1b 2a 2b'.split():
ecm_device = int(ecm_id[0])
ecm_part = ecm_id[-1]
beams_ecm = ecm_dict[ecm_id]
for SPSuser in beams_bct.keys():
if SPSuser in SPSuser_blacklist:
continue
t_stamps_ecm = np.array(semcloud_lists[ecm_device][SPSuser])
if len(t_stamps_ecm) == 0:
print 'No ECM data for user: %s'%SPSuser
continue
if not(SPSuser in beams_ecm.keys()):
beams_ecm[SPSuser] = {}
beams_ecm[SPSuser]['timestamp_bct'] = []
beams_ecm[SPSuser]['timestamp_ecm'] = []
beams_ecm[SPSuser]['ecld_1st_inj'] = []
beams_ecm[SPSuser]['ecld_max'] = []
beams_ecm[SPSuser]['int_time'] = []
beams_ecm[SPSuser]['gain_av'] = []
beams_ecm[SPSuser]['gain_sigma'] = []
N_cycles = len(beams_bct[SPSuser]['timestamp_float'])
for ii in range(N_cycles):
t_stamp = beams_bct[SPSuser]['timestamp_float'][ii]
if start_from_last and len(beams_ecm[SPSuser]['timestamp_bct']) > 0:
if t_stamp <= beams_ecm[SPSuser]['timestamp_bct'][-1]:
continue
elif t_stamp in beams_ecm[SPSuser]['timestamp_bct']:
continue
print '%s %s %d/%d'%(ecm_id, SPSuser, ii, N_cycles - 1)
idx_nearest = np.argmin(np.abs(t_stamps_ecm - t_stamp))
difference = t_stamps_ecm[idx_nearest] - t_stamp
print 'difference %s s'%difference
found = False
for jj in [0,1,-1,2,-2,3,-3,4,-4,5,-5,6,-6,7,-7]:
if (idx_nearest+jj > 0) and (idx_nearest+jj) < len(t_stamps_ecm):
filename_ecm = mat_file_prefix + SPSuser + '_SEMCLOUD%d'%int(ecm_device) + ('_%d.mat.gz'%t_stamps_ecm[idx_nearest+jj])
curr_ecm = ECLDMON(mat_folder + '%s/SEMCLOUD%d/'%(SPSuser, ecm_device) + filename_ecm, ecm_part)
print curr_ecm.SC_numb, beams_bct[SPSuser]['SC_numb_vect'][ii]
if curr_ecm.SC_numb == beams_bct[SPSuser]['SC_numb_vect'][ii]:
beams_ecm[SPSuser]['ecld_1st_inj'].append(curr_ecm.total_at_time(t_obs_1st_inj))
beams_ecm[SPSuser]['int_time'].append(curr_ecm.integ_time)
beams_ecm[SPSuser]['gain_av'].append(np.mean(curr_ecm.gain3))
beams_ecm[SPSuser]['gain_sigma'].append(np.mean(curr_ecm.gain3))
beams_ecm[SPSuser]['ecld_max'].append(np.min(curr_ecm.total_vs_time()[:-n_points_to_cut]))
beams_ecm[SPSuser]['timestamp_bct'].append(t_stamp)
beams_ecm[SPSuser]['timestamp_ecm'].append(t_stamps_ecm[idx_nearest+jj])
print 'OK', jj
found = True
break
if not found:
print 'Nofile', t_stamp
ind_sorted = np.argsort(beams_ecm[SPSuser]['timestamp_bct'])
for kk in beams_ecm[SPSuser].keys():
beams_ecm[SPSuser][kk] = list(np.take(beams_ecm[SPSuser][kk], ind_sorted))
with open(pickle_name_ecm, 'w') as fid:
pickle.dump(ecm_dict,fid)
def get_ecm_tstamps_from_filenames(ecm_mat_folder, SPSuser_blacklist, beams_bct):
semcloud_lists = {1:{},2:{}}
for SPSuser in beams_bct.keys():
if SPSuser in SPSuser_blacklist:
continue
for ecm_device in [1,2]:
semcloud_lists[ecm_device][SPSuser] = []
try:
list_ecm_files = os.listdir(ecm_mat_folder+'/%s/SEMCLOUD%d/'%(SPSuser, ecm_device))
for filen in list_ecm_files:
t_stamp_curr = float((filen.split('_')[-1]).split('.mat')[0])
semcloud_lists[ecm_device][SPSuser].append(t_stamp_curr)
except OSError as err:
print err
semcloud_lists[ecm_device][SPSuser] = np.sort(semcloud_lists[ecm_device][SPSuser])
return semcloud_lists
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
acq_comment = data['ACQ-COMMENT'].tostring()
cycle_length = np.float_(data['CYCLE-LENGTH'])
date = data['DATE'].tostring()
device_name = data['DEVICE-NAME'].tostring()
number_profiles = np.int_(data['NUMBER-PROFILES'])
number_strips = np.int_(data['NUMBER-STRIPS'])
profile_cycle_time = np.float_(data['PROFILE-CYCLE-TIME']) / 1e3
sc_number = np.int_(data['SC-NUMBER'])
time = data['TIME'].tostring()
timestamp_millisecond = np.int_(data['TIMESTAMP-MILLISECOND'])
timestamp_second = np.int_(data['TIMESTAMP-SECOND'])
timing_user = data['TIMING-USER'].tostring()
total_gain = data['TOTAL-GAIN']
eclm_data = np.zeros((number_profiles, number_strips))
for ii in range(number_profiles):
key_string = 'SEM-PROFILE-%d'%(ii+1)
eclm_data[ii,:] = data[key_string]
device_name = in_complete_path.split('-')[0].split('/')[-1]
us_string = in_complete_path.split('-')[1].split('.')[-1]
dict_meas = {
'ACQ_COMMENT':acq_comment,
'DATE':date,
'DEVICE_NAME':device_name,
'NUMBER_PROFILES':number_profiles,
'NUMBER_STRIPS':number_strips,
'PROFILE_CYCLE_TIME':profile_cycle_time,
'SC_NUMBER':sc_number,
'TIME':time,
'TIMESTAMP_MILLISECOND':timestamp_millisecond,
'TIMESTAMP_SECOND':timestamp_second,
'TIMING_USER':timing_user,
'TOTAL_GAIN':total_gain,
'eclm_data':eclm_data,
'device_name':device_name,
'SPSuser':us_string
}
return dict_meas
def sdds_to_file(in_complete_path, mat_filename_prefix='SPSmeas_', outp_folder='ecm/'):
dict_meas = sdds_to_dict(in_complete_path)
us_string = dict_meas['SPSuser']
t_stamp_unix = dict_meas['TIMESTAMP_SECOND']
device_name = dict_meas['device_name']
out_directory = outp_folder + us_string +'/'+ device_name
out_filename = '%s%s_%s_%d'%(mat_filename_prefix, us_string, device_name, t_stamp_unix)
out_complete_path = out_directory +'/'+ out_filename
if not os.path.isdir(out_directory):
print 'I create folder: '+ out_directory
os.makedirs(out_directory)
sio.savemat(out_complete_path, dict_meas, oned_as='row')
save_zip(out_complete_path)
def make_mat_files(start_time, end_time='Now', data_folder='/user/slops/data/SPS_DATA/OP_DATA/SEM_CLOUD/',
SPSuser=None, filename_converted='ecm_converted.txt'):
if type(start_time) is str:
start_tstamp_unix = th.localtime2unixstamp(start_time)
if end_time == 'Now':
end_tstamp_unix = time.mktime(time.localtime())
elif type(end_time) is str:
end_tstamp_unix = th.localtime2unixstamp(end_time)
try:
with open(filename_converted, 'r') as fid:
list_converted = fid.read().split('\n')
except IOError:
list_converted = []
print '\nConverting data in folder: %s\n'%data_folder
file_list = glob.glob(data_folder + '*.sdds*')
for filename in file_list:
complete_path = filename
t_str_sdds = complete_path.split('.sdds')[0].split('_')[-2] +' '+ complete_path.split('.sdds')[0].split('_')[-1]
tstamp_filename = time.mktime(time.strptime(t_str_sdds,'%d-%m-%y %H-%M-%S'))
if not(tstamp_filename > start_tstamp_unix and tstamp_filename < end_tstamp_unix):
continue
if SPSuser != None:
user_filename = filename.split('.')[-2]
if user_filename != SPSuser:
continue
if filename in list_converted:
continue
try:
print complete_path
sdds_to_file(complete_path)
with open(filename_converted, 'a+') as fid:
fid.write(filename+'\n')
except Exception as err:
print 'Skipped:'
print complete_path
print 'Got exception:'
print err