pyfim.Experiment

class pyfim.Experiment(f, keep_raw=False, include_subfolders=False)

Class that holds raw data for a set of data.

Parameters:

• f ({filename, folder, file object}) –

  Provide either:

  • a CSV file name
  • a CSV file object
  • single folder
  • list of the above

  Lists of files will be merged and objects (columns) will be renumbered.

• keep_raw (bool, optional) – If False, will discard raw data after extraction to save memory.
• include_subfolders (bool, optional) – If True and folder is provided, will also search subfolders for .csv files.

Examples

>>> # Generate an experiment from all csv files in one folder
>>> folder = 'users/downloads/genotype1'
>>> exp = pyfim.Experiment( folder )
>>> # See available analysis
>>> exp.parameters
... ['acc_dst', 'acceleration', 'area', 'bending',...
>>> # Access data
>>> exp.dst_to_origin.head()
...    object_1  object_13  object_15  object_18  object_19      ... 0   0.00000    0.00000        NaN        NaN        NaN
... 1   2.23607    0.00000        NaN        NaN        NaN
... 2   3.60555    1.41421        NaN        NaN        NaN
... 3   3.60555    2.82843        NaN        NaN        NaN
... 4   4.47214    4.24264        0.0        NaN        NaN
>>> # Plot data individual objects over time
>>> ax = exp.dst_to_origin.plot()
>>> plt.show()
>>> # Get mean of all values
>>> exp.mean()

__init__(f, keep_raw=False, include_subfolders=False)

Methods

__init__(f[, keep_raw, include_subfolders])
analyze(p)	Returns analysis for given parameter.
clean_data()	Cleans up the data.
extract_data()	Extracts parameters from .csv file.
mean([p])	Return mean of given parameter over given parameter.
plot_tracks([obj, ax])	Plots traces of tracked objects.
sanity_check()	Does a sanity check of attached data.