smpl.plot

Simplified plotting.

acorr(x, *[, data])	Plot the autocorrelation of x.
angle_spectrum(x[, Fs, Fc, window, pad_to, ...])	Plot the angle spectrum.
annotate(text, xy, *args, **kwargs)	Annotate the point xy with text text.
arrow(x, y, dx, dy, **kwargs)	Add an arrow to the Axes.
auto(*adata[, funcs])	Automatically loop over functions and fit the best one.
autoscale([enable, axis, tight])	Autoscale the axis view to the data (toggle).
autumn()	Set the colormap to 'autumn'.
axes([arg])	Add an axes to the current figure and make it the current axes.
axhline([y, xmin, xmax])	Add a horizontal line across the Axes.
axhspan(ymin, ymax[, xmin, xmax])	Add a horizontal span (rectangle) across the Axes.
axis(*args[, emit])	Convenience method to get or set some axis properties.
axline(xy1[, xy2, slope])	Add an infinitely long straight line.
axvline([x, ymin, ymax])	Add a vertical line across the Axes.
axvspan(xmin, xmax[, ymin, ymax])	Add a vertical span (rectangle) across the Axes.
bar(x, height[, width, bottom, align, data])	Make a bar plot.
bar_label(container[, labels, fmt, ...])	Label a bar plot.
barbs(*args[, data])	Plot a 2D field of barbs.
barh(y, width[, height, left, align])	Make a horizontal bar plot.
bone()	Set the colormap to 'bone'.
box([on])	Turn the axes box on or off on the current axes.
boxplot(x[, notch, sym, vert, whis, ...])	Draw a box and whisker plot.
broken_barh(xranges, yrange, *[, data])	Plot a horizontal sequence of rectangles.
cla()	Clear the current axes.
clabel(CS[, levels])	Label a contour plot.
clf()	Clear the current figure.
clim([vmin, vmax])	Set the color limits of the current image.
close([fig])	Close a figure window.
cohere(x, y[, NFFT, Fs, Fc, detrend, ...])	Plot the coherence between x and y.
colorbar([mappable, cax, ax])	Add a colorbar to a plot.
connect(s, func)	Bind function func to event s.
contour(*args[, data])	Plot contour lines.
contourf(*args[, data])	Plot filled contours.
cool()	Set the colormap to 'cool'.
copper()	Set the colormap to 'copper'.
csd(x, y[, NFFT, Fs, Fc, detrend, window, ...])	Plot the cross-spectral density.
cycler(*args, **kwargs)	Create a new Cycler object from a single positional argument, a pair of positional arguments, or the combination of keyword arguments.
data(*data[, function])	Plot datay against datax via fit()
delaxes([ax])	Remove an ~.axes.Axes (defaulting to the current axes) from its figure.
disconnect(cid)	Disconnect the callback with id cid.
draw()	Redraw the current figure.
draw_all([force])	Redraw all stale managed figures, or, if force is True, all managed figures.
draw_if_interactive()	Redraw the current figure if in interactive mode.
errorbar(x, y[, yerr, xerr, fmt, ecolor, ...])	Plot y versus x as lines and/or markers with attached errorbars.
eventplot(positions[, orientation, ...])	Plot identical parallel lines at the given positions.
figaspect(arg)	Calculate the width and height for a figure with a specified aspect ratio.
figimage(X[, xo, yo, alpha, norm, cmap, ...])	Add a non-resampled image to the figure.
figlegend(*args, **kwargs)	Place a legend on the figure.
fignum_exists(num)	Return whether the figure with the given id exists.
figtext(x, y, s[, fontdict])	Add text to figure.
figure([num, figsize, dpi, facecolor, ...])	Create a new figure, or activate an existing figure.
fill(*args[, data])	Plot filled polygons.
fill_between(x, y1[, y2, where, ...])	Fill the area between two horizontal curves.
fill_betweenx(y, x1[, x2, where, step, ...])	Fill the area between two vertical curves.
findobj([o, match, include_self])	Find artist objects.
fit(func, *adata, **kwargs)	Fit and plot function to datax and datay.
flag()	Set the colormap to 'flag'.
function(func, *args, **kwargs)	Plot function func between xmin and xmax
gca(**kwargs)	Get the current Axes.
gcf()	Get the current figure.
gci()	Get the current colorable artist.
get(obj, *args, **kwargs)	Return the value of an .Artist's property, or print all of them.
get_backend()	Return the name of the current backend.
get_cmap([name, lut])	Get a colormap instance, defaulting to rc values if name is None.
get_current_fig_manager()	Return the figure manager of the current figure.
get_figlabels()	Return a list of existing figure labels.
get_fignums()	Return a list of existing figure numbers.
get_plot_commands()	Get a sorted list of all of the plotting commands.
get_scale_names()	Return the names of the available scales.
getp(obj, *args, **kwargs)	Return the value of an .Artist's property, or print all of them.
ginput([n, timeout, show_clicks, mouse_add, ...])	Blocking call to interact with a figure.
gray()	Set the colormap to 'gray'.
grid([visible, which, axis])	Configure the grid lines.
hexbin(x, y[, C, gridsize, bins, xscale, ...])	Make a 2D hexagonal binning plot of points x, y.
hist(x[, bins, range, density, weights, ...])	Plot a histogram.
hist2d(x, y[, bins, range, density, ...])	Make a 2D histogram plot.
hlines(y, xmin, xmax[, colors, linestyles, ...])	Plot horizontal lines at each y from xmin to xmax.
hot()	Set the colormap to 'hot'.
hsv()	Set the colormap to 'hsv'.
imread(fname[, format])	Read an image from a file into an array.
imsave(fname, arr, **kwargs)	Save an array as an image file.
imshow(X[, cmap, norm, aspect, ...])	Display data as an image, i.e., on a 2D regular raster.
inferno()	Set the colormap to 'inferno'.
install_repl_displayhook()	Install a repl display hook so that any stale figure are automatically redrawn when control is returned to the repl.
interactive(b)	Set whether to redraw after every plotting command (e.g.
ioff()	Disable interactive mode.
ion()	Enable interactive mode.
isinteractive()	Return whether plots are updated after every plotting command.
jet()	Set the colormap to 'jet'.
legend(*args, **kwargs)	Place a legend on the Axes.
locator_params([axis, tight])	Control behavior of major tick locators.
loglog(*args, **kwargs)	Make a plot with log scaling on both the x and y axis.
magma()	Set the colormap to 'magma'.
magnitude_spectrum(x[, Fs, Fc, window, ...])	Plot the magnitude spectrum.
margins(*margins[, x, y, tight])	Set or retrieve autoscaling margins.
matshow(A[, fignum])	Display an array as a matrix in a new figure window.
minorticks_off()	Remove minor ticks from the Axes.
minorticks_on()	Display minor ticks on the Axes.
new_figure_manager(num, *args, **kwargs)	Create a new figure manager instance.
nipy_spectral()	Set the colormap to 'nipy_spectral'.
pause(interval)	Run the GUI event loop for interval seconds.
pcolor(*args[, shading, alpha, norm, cmap, ...])	Create a pseudocolor plot with a non-regular rectangular grid.
pcolormesh(*args[, alpha, norm, cmap, vmin, ...])	Create a pseudocolor plot with a non-regular rectangular grid.
phase_spectrum(x[, Fs, Fc, window, pad_to, ...])	Plot the phase spectrum.
pie(x[, explode, labels, colors, autopct, ...])	Plot a pie chart.
pink()	Set the colormap to 'pink'.
plasma()	Set the colormap to 'plasma'.
plot(*args[, scalex, scaley, data])	Plot y versus x as lines and/or markers.
plot2d(datax, datay, dataz, **kwargs)	Creates a 2D-Plot.
plot2d_kwargs(kwargs)	Set default plot2d_kwargs if not set.
plot_date(x, y[, fmt, tz, xdate, ydate, data])	Plot coercing the axis to treat floats as dates.
plot_kwargs(kwargs)	Set default plot_kwargs if not set.
plotting()
polar(*args, **kwargs)	Make a polar plot.
prism()	Set the colormap to 'prism'.
psd(x[, NFFT, Fs, Fc, detrend, window, ...])	Plot the power spectral density.
quiver(*args[, data])	Plot a 2D field of arrows.
quiverkey(Q, X, Y, U, label, **kwargs)	Add a key to a quiver plot.
rc(group, **kwargs)	Set the current .rcParams. group is the grouping for the rc, e.g., for lines.linewidth the group is lines, for axes.facecolor, the group is axes, and so on. Group may also be a list or tuple of group names, e.g., (xtick, ytick). kwargs is a dictionary attribute name/value pairs, e.g.,::.
rc_context([rc, fname])	Return a context manager for temporarily changing rcParams.
rcdefaults()	Restore the .rcParams from Matplotlib's internal default style.
register_cmap([name, cmap, override_builtin])	Add a colormap to the set recognized by get_cmap().
rgrids([radii, labels, angle, fmt])	Get or set the radial gridlines on the current polar plot.
savefig(*args, **kwargs)	Save the current figure.
sca(ax)	Set the current Axes to ax and the current Figure to the parent of ax.
scatter(x, y[, s, c, marker, cmap, norm, ...])	A scatter plot of y vs.
sci(im)	Set the current image.
semilogx(*args, **kwargs)	Make a plot with log scaling on the x axis.
semilogy(*args, **kwargs)	Make a plot with log scaling on the y axis.
set_cmap(cmap)	Set the default colormap, and applies it to the current image if any.
set_loglevel(*args, **kwargs)	Set Matplotlib's root logger and root logger handler level, creating the handler if it does not exist yet.
setp(obj, *args, **kwargs)	Set one or more properties on an .Artist, or list allowed values.
show(*[, block])	Display all open figures.
specgram(x[, NFFT, Fs, Fc, detrend, window, ...])	Plot a spectrogram.
spring()	Set the colormap to 'spring'.
spy(Z[, precision, marker, markersize, ...])	Plot the sparsity pattern of a 2D array.
stackplot(x, *args[, labels, colors, ...])	Draw a stacked area plot.
stairs(values[, edges, orientation, ...])	A stepwise constant function as a line with bounding edges or a filled plot.
stem(*args[, linefmt, markerfmt, basefmt, ...])	Create a stem plot.
step(x, y, *args[, where, data])	Make a step plot.
streamplot(x, y, u, v[, density, linewidth, ...])	Draw streamlines of a vector flow.
subplot(*args, **kwargs)	Add an Axes to the current figure or retrieve an existing Axes.
subplot2grid(shape, loc[, rowspan, colspan, fig])	Create a subplot at a specific location inside a regular grid.
subplot_mosaic(mosaic, *[, sharex, sharey, ...])	Build a layout of Axes based on ASCII art or nested lists.
subplot_tool([targetfig])	Launch a subplot tool window for a figure.
subplots([nrows, ncols, sharex, sharey, ...])	Create a figure and a set of subplots.
subplots_adjust([left, bottom, right, top, ...])	Adjust the subplot layout parameters.
summer()	Set the colormap to 'summer'.
suptitle(t, **kwargs)	Add a centered suptitle to the figure.
switch_backend(newbackend)	Close all open figures and set the Matplotlib backend.
table([cellText, cellColours, cellLoc, ...])	Add a table to an ~.axes.Axes.
text(x, y, s[, fontdict])	Add text to the Axes.
thetagrids([angles, labels, fmt])	Get or set the theta gridlines on the current polar plot.
tick_params([axis])	Change the appearance of ticks, tick labels, and gridlines.
ticklabel_format(*[, axis, style, ...])	Configure the .ScalarFormatter used by default for linear axes.
tight_layout(*[, pad, h_pad, w_pad, rect])	Adjust the padding between and around subplots.
title(label[, fontdict, loc, pad, y])	Set a title for the Axes.
tricontour(*args, **kwargs)	Draw contour lines on an unstructured triangular grid.
tricontourf(*args, **kwargs)	Draw contour regions on an unstructured triangular grid.
tripcolor(*args[, alpha, norm, cmap, vmin, ...])	Create a pseudocolor plot of an unstructured triangular grid.
triplot(*args, **kwargs)	Draw a unstructured triangular grid as lines and/or markers.
twinx([ax])	Make and return a second axes that shares the x-axis.
twiny([ax])	Make and return a second axes that shares the y-axis.
uninstall_repl_displayhook()	Uninstall the Matplotlib display hook.
unv(arr)	Return the nominal values of the numbers in NumPy array arr.
usd(arr)	Return the standard deviations of the numbers in NumPy array arr.
violinplot(dataset[, positions, vert, ...])	Make a violin plot.
viridis()	Set the colormap to 'viridis'.
vlines(x, ymin, ymax[, colors, linestyles, ...])	Plot vertical lines at each x from ymin to ymax.
waitforbuttonpress([timeout])	Blocking call to interact with the figure.
winter()	Set the colormap to 'winter'.
xcorr(x, y[, normed, detrend, usevlines, ...])	Plot the cross correlation between x and y.
xkcd([scale, length, randomness])	Turn on xkcd sketch-style drawing mode.
xlabel(xlabel[, fontdict, labelpad, loc])	Set the label for the x-axis.
xlim(*args, **kwargs)	Get or set the x limits of the current axes.
xscale(value, **kwargs)	Set the x-axis scale.
xticks([ticks, labels])	Get or set the current tick locations and labels of the x-axis.
ylabel(ylabel[, fontdict, labelpad, loc])	Set the label for the y-axis.
ylim(*args, **kwargs)	Get or set the y-limits of the current axes.
yscale(value, **kwargs)	Set the y-axis scale.
yticks([ticks, labels])	Get or set the current tick locations and labels of the y-axis.

Functions

smpl.plot.auto(*adata, funcs=None, **kwargs)

Automatically loop over functions and fit the best one.

funcsfunction array

functions to consider as fit. Default all smpl.functions.

**kwargsoptional

see plot_kwargs().

The best fit function and it’s parameters. Also a lambda function where the parameters are already applied.

smpl.plot.data(*data, function=None, **kwargs)

Plot datay against datax via fit()

dataxarray_like

X data either as unp.uarray or np.array or list

datayarray_like

Y data either as unp.uarray or np.array or list

functionfunc,optional

Fit function with parameters: x, params

**kwargsoptional

see plot_kwargs().

array_like

Optimized fit parameters of function to datax and datay

smpl.plot.fit(func, *adata, **kwargs)

Fit and plot function to datax and datay.

dataxarray_like

X data either as unp.uarray or np.array or list

datayarray_like

Y data either as unp.uarray or np.array or list

functionfunc

Fit function with parameters: x, params

**kwargsoptional

see plot_kwargs().

Fit parameters can be fixed via kwargs eg. a=5.

array_like

Optimized fit parameters of function to datax and datay. If datay is complex, both the real and imaginary part are returned.

>>> from smpl import functions as f
>>> from smpl import plot
>>> param = plot.fit([0,1,2],[0,1,2],f.line)
>>> plot.unv(param).round()[0]
1.0

(Source code, png, hires.png, pdf)

smpl.plot.function(func, *args, **kwargs)

Plot function func between xmin and xmax

funcfunction

Function to be plotted between xmin and xmax, only taking array_like x as parameter

*argsoptional

arguments for func

**kwargsoptional

see plot_kwargs().

smpl.plot.plot2d(datax, datay, dataz, **kwargs)

Creates a 2D-Plot.

**kwargsoptional

see plot2d_kwargs().

smpl.plot.plot2d_kwargs(kwargs)

Set default plot2d_kwargs if not set.

plot2d_kwargs	default	description
xaxis	None	.
yaxis	None	.
zaxis	None	.
logz	True	Colorbar in logarithmic scale.
style	image	Plot via an image (‘image’) or scatter (‘scatter’).
interpolation	nearest	Only ‘nearest’ or ‘bilinear’ for nonuniformimage. Check https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html#interpolations-for-imshow
cmap	viridis	Good default color map for missing datapoints since it does not include white.

smpl.plot.plot_kwargs(kwargs)

Set default plot_kwargs if not set.

plot_kwargs	default	description
xlabel		X axis label
ylabel		Y axis label
label	None	Legend name of plotted data
fmt	.	Format for plotting fit function
units	None	Units of the fit parameters as strings. Displayed in the Legend
save	None	File to save the plot
lpos	0	Legend position
tight	True	tight_layout
prange	None	Limit the plot of the fit to given range
sigmas	0	Color the array of given sigma times uncertainty. Only works if the fit function is coded with unp
data_sigmas	1	Color the array of given sigma times uncertainty. Only works if the data has uncertainties
init	False	Initialize a new plot
ss	True	save, add legends and grid to the plot
also_data	True	also plot the data
also_fit	True	also plot the fit
auto_fit	False	automatically fit
logy	False	logarithmic x axis
logx	False	logarithmic y axis
function_color	None	Color of the function plot
data_color	None	Color of the data plot
fit_color	None	Color of the fit plot
fit_fmt		Format of the fit plot
residue	False	Display difference between fit and data in a second plot
residue_err	True	Differences between fit and data will have errorbars
show	False	Call plt.show()
size	None	Size of the plot as a tuple (x,y). Only has an effect if init is True
number_format	{0:.4g}	Format to display numbers.
interpolate	False	Enable interpolation of the data.
interpolate_fmt		Either format string or linestyle tuple.
interpolate_label	None	Label for the interpolation.
extrapolate	True	Enable extrapolation of whole data if fit range is limited by frange or fselector.
extrapolate_min	None	Lower extrapolation bound
extrapolate_max	None	Higher extrapolation bound
extrapolate_fmt	–	Format of the extrapolation line
extrapolate_hatch	||	Extrapolation shape/hatch for filled area in case of sigmas>0. See https://matplotlib.org/stable/gallery/shapes_and_collections/hatch_style_reference.html
bbox_to_anchor	None	Position in a tuple (x,y),Shift position of the legend out of the main pane.
ncol	None	Columns in the legend if used with bbox_to_anchor.
steps	1000	resolution of the plotted function
fitinline	False	No newlines for each fit parameter
grid	True	Enable grid for the plot
hist	False	Enable histogram plot
stairs	False	Enable stair plot
capsize	5	size of cap on error bar plot
axes	None	set current axis
linestyle	None	linestyle, only active if `fmt`=None
xspace	linspace	xspace gets called with xspace(xmin,xmax,steps) in function() to get the points of the function that will be drawn.

Set default fit_kwargs if not set.

fit_kwargs	default	description
params	None	Initial fit parameters
fixed_params	True	Enable fixing parameters by choosing the same-named variables from kwargs.
maxfev	10000	Maximum function evaluations during fitting.
epsfcn	0.0001	Suitable step length for jacobian approximation.
xvar	None	Variable in fit function parameters that corresponds to the x axis. If it is None the last of the alphabetical sorted parameters is used.
autotqdm	True	Auto fitting display tqdm
fitter	Fitter.AUTO	Choose from :class:`Fitter`s.

Set default data_kwargs if not set.

data_kwargs	default	description
frange	None	Limit the fit to given range. First integer is the lowest and second the highest index.
fselector	None	Function that takes x and y as parameters and returns an array mask in order to limit the data points for fitting. Alternatively a mask for selecting elements from datax and datay.
sortbyx	True	Enable sorting the x and y data so that x is sorted.
bins	0	Number of bins for histogram
binunc	poisson_dist	Number of bins for histogram
xerror	True	enable xerrors
yerror	True	enable yerrors

smpl.plot.unv(arr)

Return the nominal values of the numbers in NumPy array arr.

Elements that are not numbers with uncertainties (derived from a class from this module) are passed through untouched (because a numpy.array can contain numbers with uncertainties and pure floats simultaneously).

If arr is of type unumpy.matrix, the returned array is a numpy.matrix, because the resulting matrix does not contain numbers with uncertainties.

smpl.plot.usd(arr)

Return the standard deviations of the numbers in NumPy array arr.

Elements that are not numbers with uncertainties (derived from a class from this module) are passed through untouched (because a numpy.array can contain numbers with uncertainties and pure floats simultaneously).

If arr is of type unumpy.matrix, the returned array is a numpy.matrix, because the resulting matrix does not contain numbers with uncertainties.