Plotting of results

class fret_tester.Plotter2D(**kwargs)

Class for producing 2D plots

These are typically plots of where the two lifetimes were tested independently, producing a 2D plot with the p-values color-coded.

make_axes(nrows, n, ax_or_subspec, fig, colorbar='on')

Create matplotlib Axes objects for plotting

Parameters:

• nrows (int) – Number of rows. Only has an effect if ax_or_subspec is a SubplotSpec instance.
• n (int) – Number plotss. Only has an effect if ax_or_subspec is a SubplotSpec instance.
• ax_or_subspec (list of matplotlib Axes or matplotlib SupblotSpec or None) – If this is a SubplotSpec instance, create new Axes on a grid in ax_or_subspec. If this is a list of Axes, just use those. If None, create a SubplotSpec that fills the whole figure.
• fig (matplotlib.figure.Figure) – Figure to create the Axes on. Only applicable if ax_or_subspec is a SubplotSpec instance.
• colorbar ({“on”, “empty”, “off”}, optional) – If “on” or “empty”, create addtional Axes (of cbar_width width) intended for a colorbar (if ax_or_subspec is a SubplotSpec instance) or use the last element of ax_or_subspec as colorbar Axes (if it is a list of Axes). Defaults to “on”.

Returns:

• ax (list of matplotlib.axes.Axes) – Axes for plots
• cbar_ax (matplotlib.axes.Axes or None) – Axes for colorbar (if colorbar is “on” or “empty”) or None (if colorbar is “off”).

time_unit

String describing the time unit

This is used in axis labels.

norm = <matplotlib.colors.LogNorm object>

p-value color map normalization. Logarithmic by default.

pval_range = (0.01, 1.0)

p-value range

cmap = 'binary'

p-value color map

plot(test_times, p_vals, truth=None, ax=None)

Draw a single 2D plot

These is typically for plots of where the two lifetimes were tested independently, producing a 2D plot with the p-values color-coded.

Parameters:

• test_times (list of lists of float) – test_times[0] specifies the times the first lifetime :math:` au_1` was tested against. test_times[1] specify the times the second lifetime :math:` au_2` was tested against.
• p_vals (array_like, dtype(float), shape(len(test_times[0], len(test_times[1]))) – p-values corresponding to test_times
• truth (tuple of float or None, optional) – If not None, draw lines at these time coordinates to mark the true lifetime combination (if known). Defaults to None.
• ax (matplotlib.axes.Axes or None:) – Axes to draw on. Use matplotlib.pyplot.gca() if None. Defaults to None.

Returns:

• ax (matplotlib.axes.Axes) – Axes for test_times[1]
• axt (matplotlib.axes.Axes) – Axes for test_times[0]

plot_series(test_times, p_vals, truths=None, ax_or_subspec=None, fig=None, nrows=1)

Draw a series of 2D plots

Use plot() to draw a series of plots on a grid.

Parameters:

• test_times (list) – Each entry will be passed to plot() as test_times parameter.
• p_vals (list) – Each entry will be passed to plot() as p_vals parameter.
• truths (list or None, optional) – Each entry will be passed to plot() as truth parameter. Defaults to None.
• ax_or_subspec (list of matplotlib Axes or matplotlib SupblotSpec or None) – If this is a SubplotSpec instance, create new Axes on a grid in ax_or_subspec. If this is a list of Axes, just use those. If None, create a SubplotSpec that fills the whole figure.
• fig (matplotlib.figure.Figure or None) – Only effective if ax_or_subspec is a SubplotSpec instance. If None, use matplotlib.pyplot.gcf(). Defaults to None.
• nrows (int, optional) – Number of rows. Defaults to 1.

Returns:

• ax (list of matplotlib.axes.Axes) – Axes for p-value plots.
• colorbar_ax (matplotlib.axes.Axes) – Axes for colorbar.
• fig (matplotlib.figure.Figure or None) – Only effective if ax_or_subspec is a SubplotSpec instance. If None, use matplotlib.pyplot.gcf(). Defaults to None.
• nrows (int, optional) – Number of rows. Defaults to 1.

Returns:

• ax (list of matplotlib.axes.Axes) – Axes for p-value plots.
• colorbar_ax (matplotlib.axes.Axes) – Axes for colorbar.

class fret_tester.Plotter1D(**kwargs)

Class for producing 1D plots

These are typically plots of lifetimes vs. p-values with fixed ratio between the two lifetimes.

Parameters:**kwargs – Set any of the class attributes (truth_style, …)

pval_scale = 'log'

Scale for the p-value axis

significance = 0.01

Significance threshold

pval_range = (0.001, 1.0)

p-value axis range

make_axes(nrows, n, ax_or_subspec, fig, colorbar='on')

Create matplotlib Axes objects for plotting

Parameters:

• nrows (int) – Number of rows. Only has an effect if ax_or_subspec is a SubplotSpec instance.
• n (int) – Number plotss. Only has an effect if ax_or_subspec is a SubplotSpec instance.
• ax_or_subspec (list of matplotlib Axes or matplotlib SupblotSpec or None) – If this is a SubplotSpec instance, create new Axes on a grid in ax_or_subspec. If this is a list of Axes, just use those. If None, create a SubplotSpec that fills the whole figure.
• fig (matplotlib.figure.Figure) – Figure to create the Axes on. Only applicable if ax_or_subspec is a SubplotSpec instance.
• colorbar ({“on”, “empty”, “off”}, optional) – If “on” or “empty”, create addtional Axes (of cbar_width width) intended for a colorbar (if ax_or_subspec is a SubplotSpec instance) or use the last element of ax_or_subspec as colorbar Axes (if it is a list of Axes). Defaults to “on”.

Returns:

• ax (list of matplotlib.axes.Axes) – Axes for plots
• cbar_ax (matplotlib.axes.Axes or None) – Axes for colorbar (if colorbar is “on” or “empty”) or None (if colorbar is “off”).

time_unit

String describing the time unit

This is used in axis labels.

significance_opts = {'alpha': 0.4, 'color': 'gray', 'ls': 'None', 'lw': 0.001}

Options for plotting the region of significance

plot(test_times, p_vals, truth=None, ax=None)

Draw a single 1D plot

This is typically for plots of lifetimes vs. p-values with fixed ratio between the two lifetimes.

Parameters:

• test_times (list of lists of float) – test_times[0] specifies the times the first lifetime :math:` au_1` was tested against. test_times[1] specify the times the second lifetime :math:` au_2` was tested against.
• p_vals (list of float) – p-values corresponding to test_times
• truth (tuple of float or None, optional) – If not None, draw lines at these time coordinates to mark the true lifetime combination (if known). Defaults to None.
• ax (matplotlib.axes.Axes or None:) – Axes to draw on. Use matplotlib.pyplot.gca() if None. Defaults to None.

Returns:

• ax (matplotlib.axes.Axes) – Axes for test_times[1]
• axt (matplotlib.axes.Axes) – Axes for test_times[0]

plot_series(test_times, p_vals, truths=None, ax_or_subspec=None, fig=None, nrows=1, empty_cbar=False)

Draw a series of 1D plots

Use plot() to draw a series of plots on a grid.

Parameters:

• test_times (list) – Each entry will be passed to plot() as test_times parameter.
• p_vals (list) – Each entry will be passed to plot() as p_vals parameter.
• truths (list or None, optional) – Each entry will be passed to plot() as truth parameter. Defaults to None.
• ax_or_subspec (list of matplotlib Axes or matplotlib SupblotSpec or None) – If this is a SubplotSpec instance, create new Axes on a grid in ax_or_subspec. If this is a list of Axes, just use those. If None, create a SubplotSpec that fills the whole figure.
• fig (matplotlib.figure.Figure or None) – Only effective if ax_or_subspec is a SubplotSpec instance. If None, use matplotlib.pyplot.gcf(). Defaults to None.
• nrows (int, optional) – Number of rows. Defaults to 1.
• empty_cbar (bool, optional) – Whether to allocate an (emtpy) grid entry for a colorbar. This is useful if the plot series is paired with a 2D series (with a color bar) in the same figure. Defaults to False.

Returns:

• ax (list of matplotlib.axes.Axes) – Axes for tt[1], where tt stands for each entry of test_times.
• axt (list of matplotlib.axes.Axes) – Axes for tt[0], where tt stands for each entry of test_times.