advanced_debugging: Added argument to log_call to silence logging. Updated changes throughout dependencies.
advanced_image_processing: Moved SPAMS functions out to the spams_sandbox module. Cleaned up debug output. Provided output for intermediate results to aid in addressing issue #22.
batch_learner: Renamed batch_generate_save_dictionary and generate_save_dictionary to be more appropriate. Changed some storage locations. Created another array logger for storing resumable portion.
HDF5_logger: Removed Debug from both logger classes names as it is no longer relevant and they are not limited to debug information. Changed debug method of EmptyArrayLogger and HDF5ArrayLogger to __nonzero__ with a __bool__ reference to it for forward compatibility with Python 3. This allows easy checking of whether logging is occurring. Renamed internal HDF5 handler of HDF5ArrayLogger to be more accurate. Changed default group_name for generate_HDF5_array_logger to be the current directory. Updated changed throughout dependencies.
spams_sandbox: Created to contain function to sandbox SPAMS in a separate process. However, it still does not address issue #33. Though, with the workaround in ( 22987dbcc746ae51cb7afd57575412ba088e0917 ) it works.
advanced_image_processing: Renamed one of the debug layers to match with its compatriots.
advanced_image_processing: Changed an is type check to isinstance.
advanced_numpy: Changed some is type tests to isinstance.
HDF5_serializers: Changed some is type tests to isinstance.
HDF5_logger: Changed an is type test to isinstance.
HDF5_logger: Added __contains__ overload for the loggers to check to see if a particular name already exists in the log file.
HDF5_logger: Added __getitem__ to the loggers to restore a value from the HDF5 log.
read_config: Added code to drop comment string (beginning with __comment__) from lists and dictionaries.
advanced_image_processing: Reformatted arguments to skimage.measure.regionprops to be cleaner and more obvious.
advanced_image_processing: Provided second logger callback for storing information to resume a run. Also, provided checks to avoid running parts that have already been run. Thaddresses, partially, issue #22.
batch_learner: Now, creates resume logger callback and checks to see if neurons already exists before running. Also, a resume flag has been added to the configure file. If present and set to true, it will attempt to resume from a previous run. If not, it will wipe all data and start over. This addresses, partially, issue #22.
advanced_image_processing: Refactored generate_neurons so that the post-processing step is done in postprocess_data, which vastly simplifies generate_neurons. Also, moved neuron output to generate_neurons to give a clear separation between it and generate_save_neurons.
batch_learner: Removed code for saving neurons and moved it to generate_neurons.
advanced_image_processing: Removed generate_neurons in favor of merging content with generate_save_neurons.
batch_learner: Changed generate_save_neurons to contain the contents of generate_save_neurons.
batch_learner: Added additional parameter, run_stage, which determines whether to run until completing preprocessing, dictionary (learning), or all. This fixes #22.
advanced_image_processing: Added function removing_lines to linearly interpolate values for lines that are filled with zeros (due to registration artifacts). Fixes #5.
advanced_image_processing: Added check for uninterpolated region.
advanced_numpy: Added the quantile function to provide an interface similar to MATLAB's quantile for scipy.stats.mstats.mquantiles.
advanced_numpy: Modified the function quantile in the following ways. Added the axis argument. Forced even numpy.ndarrays or single values into numpy.ma.MaskedArray. Set the fill value to numpy.nan. Updated the doctests and documentation. Noted the single probability case as well as including a test for it.
advanced_numpy: Added the function get_quantiles, which is refactored from quantile. This function properly formats the quantiles into an array of probability divisions.
advanced_image_processing: Added the function extract_f0. This is a rough working copy. However, it does implement an F_{0} estimation and as such fixes #6.