TransportMaps.Diagnostics.Plotting
¶
Module Contents¶
Classes¶
Base object for every object in the module. |
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Base object for every object in the module. |
Functions¶
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Compute the conditionals aligned with the axis |
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Plot the conditionals aligned with the axis |
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Plot the conditionals aligned with the axis |
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Compute the random conditionals |
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Plot the random conditionals |
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Plot the marginals aligned with the axis |
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Plot the marginals aligned with the axis |
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- class TransportMaps.Diagnostics.Plotting.AlignedConditionalsObject(nplots, X_list, Y_list, pdfEval_list)[source]¶
Bases:
TransportMaps.ObjectBase.TMO
Base object for every object in the module.
This object provides functions for storage and parallelization.
- TransportMaps.Diagnostics.Plotting.computeAlignedConditionals(distribution, dimensions_vec=0, range_vec=[-3, 3], numPointsXax=30, do_diag=True, mpi_pool=None)[source]¶
Compute the conditionals aligned with the axis
- Parameters:
distribution (
Distribution
) – distribution \(\pi\)dimensions_vec (list of int) – list of dimensions to be displayed. Default 0: display 10 dimensions at most.
range_vec (
list
) – range to be displayed. Either alist
[2] of integers, or alist
[d] oflist
[2] of integers.numPointsXax (int) – number of points for each axis.
do_diag (bool) – whether to include the one dimensional conditionals on the diagonal
mpi_pool (
mpi_map.MPI_Pool
) – pool of processes
- Returns:
- (
AlignedConditionalsObject
) – object storing all the necessary evaluated values
- (
- TransportMaps.Diagnostics.Plotting.plotAlignedConditionals(distribution=None, data=None, dimensions_vec=0, range_vec=[-3, 3], numPointsXax=30, numCont=15, figname=None, show_flag=True, do_diag=True, show_title=False, show_axis=True, title='Aligned conditionals', vartitles=None, fig=None, ret_handles=False, mpi_pool=None)[source]¶
Plot the conditionals aligned with the axis
- Parameters:
distribution (
Distribution
) – distribution \(\pi\)data (
AlignedConditionalsObject
) – output ofcomputeAlignedConditionals()
dimensions_vec (list of int) – list of dimensions to be displayed. Default 0: display 10 dimensions at most.
range_vec (
list
) – range to be displayed. Either alist
[2] of integers, or alist
[d] oflist
[2] of integers.numPointsXax (int) – number of points for each axis.
numCont (int) – number of contours in the contour plots.
figname (str) – if defined, store the figure in the provided path.
show_flag (bool) – whether to show the plot before returning
do_diag (bool) – whether to include the one dimensional conditionals on the diagonal
show_title (bool) – whether to show the title
show_axis (bool) – whether to show the axis
title (str) – title for the figure
vartitles (list) – list of titles for each variable
fig (figure) – matplotlib figure object if one wants to re-useit.
mpi_pool (
mpi_map.MPI_Pool
) – pool of processesret_handles (bool) – whether to return the axes handles
- TransportMaps.Diagnostics.Plotting.plotAlignedSliceMap(tr_map, dimensions_vec=0, pointEval=0, range_vec=[-4, 4], numPointsXax=30, numCont=30, figname=None, show_flag=True, tickslabelsize=6, show_title=False, fig=None, mpi_pool=None)[source]¶
Plot the conditionals aligned with the axis
- Parameters:
tr_map (
TriangularTransportMap
) – Triangular transport mapdimensions_vec (list of int) – list of dimensions to be displayed. Default 0: display 10 dimensions at most.
pointEval (
ndarray`[:math:`d
]) – anchor point. Default is zero.range_vec (
list
) – range to be displayed. Either alist
[2] of integers, or alist
[d] oflist
[2] of integers.numPointsXax (int) – number of points for each axis.
numCont (int) – number of contours in the contour plots.
figname (str) – if defined, store the figure in the provided path.
show_flag (bool) – whether to show the plot before returning
show_title (bool) – whether to show a title on top of the figure
fig (figure) – matplotlib figure object if one wants to re-use it.
mpi_pool (
mpi_map.MPI_Pool
) – pool of processes
- class TransportMaps.Diagnostics.Plotting.RandomConditionalsObject(nplots, X_list, Y_list, pdfEval_list, Q_rand_list)[source]¶
Bases:
TransportMaps.ObjectBase.TMO
Base object for every object in the module.
This object provides functions for storage and parallelization.
- TransportMaps.Diagnostics.Plotting.computeRandomConditionals(distribution, num_conditionalsXax=0, pointEval=None, range_vec=[-3, 3], numPointsXax=30, Q_rand_list=None, mpi_pool=None)[source]¶
Compute the random conditionals
- Parameters:
distribution (
Distribution
) – distribution \(\pi\)num_conditionalsXax (int) – number of random conditionals per axis
pointEval (
ndarray`[:math:`d
]) – anchor point. Default is zero.range_vec (:class:`tuple`[2]) – range to be displayed.
numPointsXax (int) – number of points for each axis.
Q_rand_list (list) – list of random directions.
mpi_pool (
mpi_map.MPI_Pool
) – pool of processes
- TransportMaps.Diagnostics.Plotting.plotRandomConditionals(distribution=None, data=None, num_conditionalsXax=0, pointEval=None, range_vec=[-3, 3], numPointsXax=30, numCont=15, Q_rand_list=None, figname=None, show_flag=True, show_title=False, title='Random conditionals', fig=None, mpi_pool=None)[source]¶
Plot the random conditionals
- Parameters:
distribution (
Distribution
) – distribution \(\pi\)data (
RandomConditionalsObject
) – output ofcomputeRandomConditionals()
num_conditionalsXax (int) – number of random conditionals per axis
pointEval (
ndarray`[:math:`d
]) – anchor point. Default is zero.range_vec (:class:`tuple`[2]) – range to be displayed.
numPointsXax (int) – number of points for each axis.
numCont (int) – number of contours in the contour plots.
figname (str) – if defined, store the figure in the provided path.
show_flag (bool) – whether to show the plot before returning
show_title (bool) – whether to show the title
fig (figure) – matplotlib figure object if one wants to re-use it.
mpi_pool (
mpi_map.MPI_Pool
) – pool of processes
- TransportMaps.Diagnostics.Plotting.plotAlignedMarginals(mat_points, mat_points2=None, dimensions_vec=0, range_vec=None, scatter=False, colormap='jet', white_background=True, levels=10, do_diag=True, figname=None, show_flag=True, show_axis=False, title='Marginals along coordinate axes', vartitles=None, fig=None, ret_handles=False, mpi_pool=None)[source]¶
Plot the marginals aligned with the axis
- Parameters:
mat_points (ndarray) – first dataset
mat_points2 (ndarray) – second dataset (optional)
dimensions_vec (list of int) – list of dimensions to be displayed. Default 0: display 10 dimensions at most.
range_vec (list of
tuple
[2]) – range to be displayed.scatter (bool) – whether to plot a scatter plots instead of densities
colormap (str) – colormap to be used
white_background (bool) – whether to have a white background of to use the last layer of the colormap
levels (int or list) – number of levels to be displayed or list of values defining the levels.
do_diag (bool) – whether to include the one dimensional marginals on the diagonal
numPointsXax (int) – number of points for each axis.
numCont (int) – number of contours in the contour plots.
figname (str) – if defined, store the figure in the provided path.
show_flag (bool) – whether to show the plot before returning
show_axis (bool) – whether to show the axis of the plot
vartitles (list) – list of titles for each variable
fig (figure) – matplotlib figure object if one wants to re-use it.
mpi_pool (
mpi_map.MPI_Pool
) – pool of processesret_handles (bool) – whether to return the axes handles
- Returns:
(fig, [list]) – figure handle and dictionary of handles
- TransportMaps.Diagnostics.Plotting.plotAlignedScatters(mat_points, dimensions_vec=0, do_diag=True, s=5, bins=10, show_axis=True, axis_fmt=None, figname=None, show_flag=True, show_title=False, title='Marginals along coordinate axes', vartitles=None, fig=None)[source]¶
Plot the marginals aligned with the axis
- Parameters:
mat_points (
ndarray
[\(m,d\)]) – samplesdimensions_vec (list of int) – list of dimensions to be displayed. Default 0: display 10 dimensions at most.
do_diag (bool) – whether to include the one dimensional marginals on the diagonal
s (int) – size of scatter points
bins (int) – number of bins for one dimensional plots
show_axis (bool) – whether to show the axis
axis_fmt (list) – list of matplotlib formatters
figname (str) – if defined, store the figure in the provided path.
show_flag (bool) – whether to show the plot before returning
show_title (bool) – whether to show the title
title (str) – title for the figure
vartitles (list) – list of titles for each variable
fig (figure) – matplotlib figure object if one wants to re-use it.
- TransportMaps.Diagnostics.Plotting.plotGradXMap(tmap, base_distribution=None, nsamples=1000, show_cbar=True, show_ticks=True, title='Intensity coefficients map', cmap='Blues', mpi_pool=None, show_flag=True)[source]¶