rootpy.plotting.contrib.plot_contour_matrix¶
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rootpy.plotting.contrib.
plot_contour_matrix
(arrays, fields, filename, weights=None, sample_names=None, sample_lines=None, sample_colors=None, color_map=None, num_bins=20, num_contours=3, cell_width=2, cell_height=2, cell_margin_x=0.05, cell_margin_y=0.05, dpi=100, padding=0, animate_field=None, animate_steps=10, animate_delay=20, animate_loop=0)[source]¶ Create a matrix of contour plots showing all possible 2D projections of a multivariate dataset. You may optionally animate the contours as a cut on one of the fields is increased. ImageMagick must be installed to produce animations.
Parameters: arrays : list of arrays of shape [n_samples, n_fields]
A list of 2D NumPy arrays for each sample. All arrays must have the same number of columns.
fields : list of strings
A list of the field names.
filename : string
The output filename. If animatation is enabled
animate_field is not None
thenfilename
must have the .gif extension.weights : list of arrays, optional (default=None)
List of 1D NumPy arrays of sample weights corresponding to the arrays in
arrays
.sample_names : list of strings, optional (default=None)
A list of the sample names for the legend. If None, then no legend will be shown.
sample_lines : list of strings, optional (default=None)
A list of matplotlib line styles for each sample. If None then line styles will cycle through ‘dashed’, ‘solid’, ‘dashdot’, and ‘dotted’. Elements of this list may also be a list of line styles which will be cycled through for the contour lines of the corresponding sample.
sample_colors : list of matplotlib colors, optional (default=None)
The color of the contours for each sample. If None, then colors will be selected according to regular intervals along the
color_map
.color_map : a matplotlib color map, optional (default=None)
If
sample_colors is None
then select colors according to regular intervals along this matplotlib color map. Ifcolor_map
is None, then the spectral color map is used.num_bins : int, optional (default=20)
The number of bins along both axes of the 2D histograms.
num_contours : int, optional (default=3)
The number of contour line to show for each sample.
cell_width : float, optional (default=2)
The width, in inches, of each subplot in the matrix.
cell_height : float, optional (default=2)
The height, in inches, of each subplot in the matrix.
cell_margin_x : float, optional (default=0.05)
The horizontal margin between adjacent subplots, as a fraction of the subplot size.
cell_margin_y : float, optional (default=0.05)
The vertical margin between adjacent subplots, as a fraction of the subplot size.
dpi : int, optional (default=100)
The number of pixels per inch.
padding : float, optional (default=0)
The padding, as a fraction of the range of the value along each axes to guarantee around each sample’s contour plot.
animate_field : string, optional (default=None)
The field to animate a cut along. By default no animation is produced. If
animate_field is not None
thenfilename
must end in the .gif extension and an animated GIF is produced.animate_steps : int, optional (default=10)
The number of frames in the animation, corresponding to the number of regularly spaced cut values to show along the range of the
animate_field
.animate_delay : int, optional (default=20)
The duration that each frame is shown in the animation as a multiple of 1 / 100 of a second.
animate_loop : int, optional (default=0)
The number of times to loop the animation. If zero, then loop forever.
Notes
NumPy and matplotlib are required