trial_viewer

Tools to visulize data after collection.

Warning

this module is unfinished, so it is undocumented.

Classes:

ColumnDataSource(*args, **kwargs)

Maps names of columns to sequences or arrays.

Legend(*args, **kwargs)

Render informational legends for a plot.

LegendItem(*args, **kwargs)

Span(*args, **kwargs)

Render a horizontal or vertical line span.

tqdm(*_, **__)

Decorate an iterable object, returning an iterator which acts exactly like the original iterable, but prints a dynamically updating progressbar every time a value is requested.

Functions:

factor_cmap(field_name, palette, factors[, …])

Create a DataSpec dict that applies a client-side CategoricalColorMapper transformation to a ColumnDataSource column.

figure(**kwargs)

Create a new Figure for plotting.

glob(pathname, *[, recursive])

Return a list of paths matching a pathname pattern.

gridplot(children[, sizing_mode, …])

Create a grid of plots rendered on separate canvases.

load_subject_data(data_dir, subject_name[, …])

load_subject_dir(data_dir[, steps, grad, which])

Parameters
  • data_dir (str) – A path to a directory with Subject style hdf5 files

show(obj[, browser, new, notebook_handle, …])

Immediately display a Bokeh object or application.

step_viewer(grad_data)

trial_viewer(step_data[, roll_type, …])

Parameters
  • bar

load_subject_data(data_dir, subject_name, steps=True, grad=True)[source]
load_subject_dir(data_dir, steps=True, grad=True, which=None)[source]
Parameters
  • data_dir (str) – A path to a directory with Subject style hdf5 files

  • steps (bool) – Whether to return full trial-level data for each step

  • grad (bool) – Whether to return summarized step graduation data.

  • which (list) – A list of subjects to subset the loaded subjects to

step_viewer(grad_data)[source]
trial_viewer(step_data, roll_type='ewm', roll_span=100, bar=False)[source]
Parameters
  • bar

  • roll_span

  • roll_type

  • step_data