def plot_design_matrix(design_matrix, rescale=True, ax=None, output_file=None):
"""Plot a design matrix provided as a DataFrame
Parameters
----------
design matrix : pandas DataFrame,
Describes a design matrix.
rescale : bool, optional
Rescale columns magnitude for visualization or not.
ax : axis handle, optional
Handle to axis onto which we will draw design matrix.
output_file : string or None, optional,
The name of an image file to export the plot to. Valid extensions
are .png, .pdf, .svg. If output_file is not None, the plot
is saved to a file, and the display is closed.
Returns
-------
ax: axis handle
The axis used for plotting.
"""
# We import _set_mpl_backend because just the fact that we are
# importing it sets the backend
# normalize the values per column for better visualization
_, X, names = check_design_matrix(design_matrix)
if rescale:
X = X / np.maximum(1.e-12, np.sqrt(np.sum(X**2, 0))) # pylint: disable=no-member
if ax is None:
max_len = np.max([len(str(name)) for name in names])
fig_height = 1 + .1 * X.shape[0] + .04 * max_len
if fig_height < 3:
fig_height = 3
elif fig_height > 10:
fig_height = 10
plt.figure(figsize=(1 + .23 * len(names), fig_height))
ax = plt.subplot(1, 1, 1)
ax.imshow(X, interpolation='nearest', aspect='auto')
ax.set_label('conditions')
ax.set_ylabel('scan number')
ax.set_xticks(range(len(names)))
ax.set_xticklabels(names, rotation=60, ha='left')
# Set ticks above, to have a display more similar to the display of a
# corresponding dataframe
ax.xaxis.tick_top()
plt.tight_layout()
if output_file is not None:
plt.savefig(output_file)
plt.close()
ax = None
return ax
def plot_design_matrix(design_matrix, rescale=True, ax=None, output_file=None):
"""Plot a design matrix provided as a :class:`pandas.DataFrame`.
Parameters
----------
design matrix : :class:`pandas.DataFrame`
Describes a design matrix.
rescale : :obj:`bool`, optional
Rescale columns magnitude for visualization or not.
Default=True.
ax : :class:`matplotlib.axes.Axes`, optional
Handle to axes onto which we will draw the design matrix.
%(output_file)s
Returns
-------
ax : :class:`matplotlib.axes.Axes`
The axes used for plotting.
"""
# normalize the values per column for better visualization
_, X, names = check_design_matrix(design_matrix)
if rescale:
X = X / np.maximum(1.e-12, np.sqrt(np.sum(X**2, 0))) # pylint: disable=no-member
if ax is None:
max_len = np.max([len(str(name)) for name in names])
fig_height = 1 + .1 * X.shape[0] + .04 * max_len
if fig_height < 3:
fig_height = 3
elif fig_height > 10:
fig_height = 10
plt.figure(figsize=(1 + .23 * len(names), fig_height))
ax = plt.subplot(1, 1, 1)
ax.imshow(X, interpolation='nearest', aspect='auto')
ax.set_label('conditions')
ax.set_ylabel('scan number')
ax.set_xticks(range(len(names)))
ax.set_xticklabels(names, rotation=60, ha='left')
# Set ticks above, to have a display more similar to the display of a
# corresponding dataframe
ax.xaxis.tick_top()
plt.tight_layout()
if output_file is not None:
plt.savefig(output_file)
plt.close()
ax = None
return ax