Visualize Cactus Data

This module provides functions to plot various Cactus data types, such as 2D RegData, TimeSeries.

postcactus.visualize.adj_limits(var, units=1.0, aspect='equal', axes=None)

Set limits of axes to coordinate range of data.

Parameters

  • var – Data from which to take coordinate range.

  • units (float or pair of floats.) – Units for x and y coordinates.

  • aspect (string or float) – Aspect ratio of axes.

  • axes (matplotlib.axes instance or None) – Which axes to adjust. Defaults to current axes.

postcactus.visualize.color_bar(image=None, cax=None, ax=None, label=None, ticks=None, **kwargs)

Adds a colorbar with optional label.

Parameters

  • image – Object to which the colorbar refers, e.g. the result of imshow.

  • cax – Existing colorbar axes, see matplotlibs colorbar().

  • ax – Axes where to insert colorbar axes, see matplotlibs colorbar().

  • label – Colorbar label.

  • ticks – location of the ticks.

Unknown keyword arguments are passed to matplotlibs colorbar()

Returns

Colorbar instance.

postcactus.visualize.get_color_map(name, over=None, under=None, masked=None)

Get color map by name and set special colors for out-of-range values.

Parameters

  • name (string) – Name of the colormap.

  • over (Matplotlib color or None.) – Color for too large values.

  • under (Matplotlib color or None.) – Color for too large values.

  • masked (Matplotlib color or None.) – Color for masked values.

Returns

Matplotlib color map.

postcactus.visualize.plot_color(var, mask=None, axes=None, vmin=None, vmax=None, units=1.0, cmap=None, interpolation='nearest', bar=False, barlabel=None, barticks=None, barshrink=1, barextend='neither', **kwargs)

Makes a 2D color plot of RegData instances.

Parameters

  • var (RegData instance) – 2D data to plot.

  • mask (RegData or numpy array or None) – Optional mask for the plot.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • vmin (float or None) – Minimum value for color scale. Defaults to data minimum.

  • vmax (float or None) – Maximum value for color scale. Defaults to data maximum.

  • units (float or pair of floats.) – Units for x and y coordinates.

  • cmap (Matplotlib colormap) – Colormap to use for the plot.

  • interpolation (string) – Interpolation method, see matplotlib imshow(). Defaults to nearest point.

  • bar (bool) – Whether to add a colorbar.

  • barlabel (string or None) – Label for the colorbar.

  • barticks (list of floats or None) – Locations of the colorbar ticks. Default: choose automatic.

  • barshrink (float) – Factor to shrink the colorbar.

  • barextend (str) – Whether to show the colors for out of range values at the ends of the colorbar.

Unknown keyword arguments are passed to matplotlibs imshow()

Returns

Image object.

Return type

matplotlib.image.AxesImage object.

postcactus.visualize.plot_color_direct(red, green, blue, mask=None, axes=None, vmax=None, units=1.0, interpolation='nearest', **kwargs)

Makes a 2D image with color components given by 3 RegData instances.

Parameters

  • red (RegData instance) – 2D data for red component.

  • green (RegData instance) – 2D data for green component.

  • blue (RegData instance) – 2D data for blue component.

  • mask (RegData or numpy array or None) – Optional mask for the plot.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • vmax (float or None) – Maximum value for color scale. Defaults to data maximum.

  • units (float or pair of floats.) – Units for x and y coordinates.

  • interpolation (string) – Interpolation method, see matplotlib imshow(). Defaults to nearest point.

Unknown keyword arguments are passed to matplotlibs imshow()

postcactus.visualize.plot_contour(var, levels, mask=None, axes=None, units=1.0, labels=False, labelfmt='%g', neg_solid=False, **kwargs)

Makes a contour plot of RegData instances.

Parameters

  • var (RegData instance) – 2D data to plot.

  • levels (list of floats) – Level contours to draw.

  • mask (RegData or numpy array) – Optional mask for the data.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • units (float or pair of floats.) – Units for x and y coordinates.

  • labels (bool) – If True, add lables to contours.

  • labelfmt (str or None) – Format string for contour labels.

  • neg_solid (bool) – Whether to draw negative contours solid or wtih default.

Unknown keyword arguments are passed to matplotlibs contour()

Returns

Contour lines.

Return type

QuadContourSet object.

postcactus.visualize.plot_contourf(var, levels, mask=None, axes=None, units=1.0, **kwargs)

Makes a filled contour plot of RegData instances.

Parameters

  • var (RegData instance) – 2D data to plot.

  • levels (list of floats) – Level contours to draw.

  • mask (RegData or numpy array) – Optional mask for the data.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • units (float or pair of floats.) – Units for x and y coordinates.

Unknown keyword arguments are passed to matplotlibs contour()

Returns

Contour lines.

Return type

QuadContourSet object.

postcactus.visualize.plot_grid_struct(data, units=1.0, axes=None, facecolor=None, edgecolor=None, **kwargs)

Plots grid structure of CompData or RegData objects.

Parameters

  • data (RegData or CompData) – Data for which to plot the structure.

  • units (float or pair of floats.) – Units for x and y coordinates.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • edgecolor (list of colors or None) – Which colors to use for the edges of the components on different levels. Will be repeated if shorter than number of refinement levels.

  • facecolor (list of colors or None) – Like edgecolor, but for the interior of the components.

Unknown keyword arguments are passed to matplotlibs patches.Rectangle()

postcactus.visualize.plot_integral_curves(vec, mask=None, num_seed=800, seglength=0.1, seed_pos=None, axes=None, units=1.0, **kwargs)

Plots integral curves of a vector field. Seed positions are choosen randomly.

Parameters

  • vec (pair of callable objects.) – Data to plot. Must be 2D.

  • num_seed (int) – Desired number of lines.

  • seglength (float) – Length of lines as fraction of figure size.

  • seedpos (Nx2 numpy array or None) – Positions where to begin the integral curves or None.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

  • units (float or pair of floats.) – Units for x and y coordinates.

Unknown keyword arguments are passed to matplotlibs plot()

postcactus.visualize.plot_ts(ts, units=1.0, axes=None, **kwargs)

Plots a TimeSeries object.

Parameters

  • ts (TimeSeries instance) – Time series to plot.

  • units (float or pair of floats.) – Units for t and y coordinates.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

Unknown keyword arguments are passed to matplotlibs plot()

Returns

Result of matplotlibs plot() function.

postcactus.visualize.plot_vectors(vec, mask=None, narrows=800, vmax=None, unit=1.0, x0=None, x1=None, axes=None, **kwargs)

Plots a vector field. Resamples data to get desired number of arrows.

Parameters

  • vec (vector of RegData) – Data to plot. Must be 2D.

  • mask (RegData or numpy array) – Optional mask for the data.

  • narrows (int) – Desired number of arrows.

  • vmax (float or None) – Maximum length assumed for scaling vectors.

  • unit (float) – Unit for both x and y coordinates.

  • x0 (length-2 float list/array or None) – Sample region lower left coordinate. Default: use data coordinate range.

  • x1 (length-2 float list/array or None) – Sample region upper right coordinate. Default: use data coordinate range.

  • axes (matplotlib.axes instance or None) – Which axes to use for the plot. Defaults to current axes.

Unknown keyword arguments are passed to matplotlibs quiver()

postcactus.visualize.sample_vectors(vec, mask=None, narrows=800, x0=None, x1=None)

Samples a vector field for plotting purposes.

Parameters

  • vec (2D vector of 2D RegData) – Vector to sample.

  • mask (RegData or numpy array) – Optional mask for the data.

  • narrows (int) – Desired number of arrows.

  • x0 (length-2 float list/array or None) – Sample region lower left coordinate. Default: use data coordinate range.

  • x1 (length-2 float list/array or None) – Sample region upper right coordinate. Default: use data coordinate range.

The results of this function are

cdlength-2 tuple of lists or arrays

x- and y-coordinates of the samples.

dlength-2 tuple of lists or arrays

x- and y-components of sampled vectors.

vmaxfloat

Maximum length of all sampled vectors.

lfloat

Average distance between sampled vectors.

Returns

A tuple (cd,d,vmax,l)

postcactus.visualize.savefig_multi(name, formats, **kwargs)

Save current figure in multiple formats.

Parameters

  • name (string) – Filename without extension.

  • formats (string) – Comma-separated list of file formats.

Unknown keyword arguments are passed to matplotlibs savefig()

postcactus.visualize.set_tick_color(color, axes=None)

Set tick color.

Parameters

  • color – Tick color.

  • axes – Axes for which to change the tick color or None for current axes.