Release version 0.8.2

What's Changed

• Fix for issue 22 by @blakeaw in #23

Full Changelog: v0.8.1...v0.8.2

v0.8.1

What's Changed

• Fix/iss20 by @blakeaw in #21

Full Changelog: v0.8.0...v0.8.1

Release version 0.8.0

What's Changed

• Added asymmetric diffusion estimator. by @blakeaw in #19

Full Changelog: v0.7.0...v0.8.0

v0.7.0

Includes first version of new streamlit app interface.

v0.6.0

The expected type of the input -peak-to-tail for the command line interface was changed from int to float.

v0.5.0

Added new threshold_noise option so that users can specify whether to use the standard deviation (default) or the standard error of signal in the tail region for thresholding and early termination of the fitting.

v0.4.0

Release of development version 0.4.0 with updates including:

1. New options define how the peak and tail signal are computed when applying the thresholding for images to determine whether to terminate the fitting.
   

2. New AnisotropicGaussianFit class for fitting images with anisotropic diffusion along the major (x,y) axes; the x and y axes can have different diffusion coefficients.
   

3. Additional output file from the CLI to store the measured diffusion coefficients and some other fitting diagnostics.
   

4. Additional output file from the CLI to store the input arguments used for the diffusionfit run.
   

v0.3.0

Added

• Function to export fitting results to csv file (export_to_csv) in DiffusionFitBase.
• Abstract property function (fitting_parameters) to compile the fitting parameters from step 1 fitting into a DataFrame. This is used by export_to_csv function.
• main.py calls the export_to_csv function to save the fitting data to csv files.
• Time-resolved diffusion coefficient estimation (time_resolved_diffusion property function) and display function (display_time_resolved_dc). The plot is also part of the output files now when running from the command line (main.py).
• Added additional property functions to DiffusionFitBase: fit_times, step1_rmse, step2_rsquared, effective_time.
• The command line run script (main.py) prints the Effective Time as part of Dstar_values DataFrame.
• New models module defining diffusion model functions to use when doing the fitting. Functions from this module are used by the fitting classes.
• New dependency on Numba and its use to improve performance of some numerical functions.
• New fitting class PointClarkFit for fitting fluorescent signal of receptor-based peptide sensors during peptide diffusion.
• Function in the DiffusionFitBase to write out the step 1 fits as an ImageJ compatible tif image trajectory.
• Funtionality to estimate the loss rate of the diffusing species.
• New optional input arguments for the command line version: -center, --time-resolved, --ignore-threshold, --write-tif, --loss-rate, --point-clark.
• Docstrings to functions in the models.py module.
• New pip install section in the README.

Changed

• Changed the cmap used for step 1 experiment and 2D fit images from gray to viridis
• Replaced the ER goodness of fit metric with RSSE (Root Standard deviation of the Squared Error)
• Changed the way the thresholding is done after step 1 fitting. Now it terminates when mean(peak-region) <= mean(tail-region) + peak-to-tail * std(tail-region) and uses radial selections from the image instead of computing values from the Line-ROI.
• The required argument signal_to_noise in main.py arguments was changed to optional keyword argument -peak-to-tail with default value of 3. This is used in the new step 1 thresholding.
• In DiffusionFitBase class the member function model was changed to intensity_model, linear_model was changed to diffusion_model, and the _fit_step1 and fit_step2 functions were changed to _fit_intensity and _fit_diffusion, respectively.
• Updated the initial description, What's new in, License, and Documentation and Usage sections in the README.