spellbook.plot1D#

Lower-level functions for creating 1D / univariate plots

The high-level functions for creating plots, which make use of the functions in this module, can be found in plot.

Functions:

barchart(data, x, fig, grid, gridindex[, ...])

Draw a vertical barchart

boxplot(data, ax[, x, y, orient, lw_mean, ...])

Draw a boxplot

histogram(data, fig, grid, gridindex[, x, ...])

Draw a histogram

Functions#

barchart#

spellbook.plot1D.barchart(data, x, fig, grid, gridindex, xlabel=None, histplot_args={})[source]#

Draw a vertical barchart

Parameters
Return type

matplotlib.axes._axes.Axes

Returns

The axes object drawn. The axes object is already added to the figure, but it is returned as well so that it can be caught for easier access and manipulation

boxplot#

spellbook.plot1D.boxplot(data, ax, x=None, y=None, orient='v', lw_mean=6.0, lw_median=4.0, show_axis=True, show_stats=True)[source]#

Draw a boxplot

histogram#

spellbook.plot1D.histogram(data, fig, grid, gridindex, x=None, xlabel=None, CL_mean=95, lw_mean=6.0, lw_median=4.0, lw_quartiles=2.0, show_histogram=True, show_decorations=True, show_mean=True, show_std=True, show_sem=True, show_median=True, show_quartiles=True, show_min=True, show_max=True, show_axis=True, show_stats=True, histplot_args={}, statsbox_args={}, ymin=None, ymax=None, yscale=None)[source]#

Draw a histogram

../_images/histogram.png

Besides the pure histogram itself, various lines, bands and bars can be drawn that indicate a range of descriptive statistics:

  • a black line for the mean

  • a grey band for the standard deviation

  • a black error bar indicating the confidence interval of the standard error of the mean at a desired level

  • a thick dark blue line for the median

  • thin dashed lines for the 25% and 75% quartiles

  • thin solid lines for the minimum and maximum values

Parameters

  • data (pandas.DataFrame, numpy.ndarray or tf.Tensor) – The data to plot

  • fig (matplotlib.figure.Figure) – The figure on which to draw

  • grid (matplotlib.gridspec.GridSpec) – The grid on the figure in which to draw

  • gridindex (int) – The index of the grid cell in which to draw

  • x (typing.Optional[str]) – Optional. The name of the variable to plot

  • xlabel (typing.Optional[str]) – Optional. The x-axis label.

  • CL_mean (int) – Optional. The confidence level in percent for the uncertainty bar around the mean giving the standard error of the mean

  • lw_mean (float) – Optional. The linewidth of the mean

  • lw_median (float) – Optional. The linewidth of the median

  • lw_quartiles (float) – Optional. The linewidth of the quartiles

  • show_histogram (bool) – Optional. If the histogram should be shown

  • show_decorations (bool) – Optional. If set to False, none of the lines and errors bands/bars indicating the descriptive statistics will be shown

  • show_mean (bool) – Optional. If the mean should be shown

  • show_std (bool) – Optional. If the standard deviation should be shown

  • show_sem (bool) – Optional. If the standard error of the mean should be shown

  • show_median (bool) – Optional. If the median should be shown

  • show_quartiles (bool) – Optional. If the quartiles should be shown

  • show_min (bool) – Optional. If the minimum value / 0% percentile should be shown

  • show_max (bool) – Optional. If the minimum value / 1000% percentile should be shown

  • show_axis (bool) – Optional. If the axes, including labels, ticks and ticklabels should be shown

  • show_stats (bool) – Optional. If a box giving the values of the descriptive statistics should be shown

  • histplot_args (dict) – Optional. Arguments for seaborn.histplot()

  • statsbox_args (dict) – Optional. Arguments for spellbook.plotutils.statsbox()

  • ymin (typing.Optional[float]) – Optional. The lower view limit of the y-axis.

  • ymax (typing.Optional[float]) – Optional. The upper view limit of the y-axis.

  • yscale (typing.Optional[str]) – Optional. The type of scale used for the y-axis. See matplotlib.axes.Axes.set_yscale().

Returns

The axes object drawn. The axes object is already added to the figure, but it is returned as well so that it can be caught for easier access and manipulation.

Return type

matplotlib.axes.Axes

Examples:

  • plotting a pandas.DataFrame

    import matplotlib as mpl
import numpy as np
import pandas as pd
import spellbook as sb

fig = mpl.pyplot.figure(tight_layout=True)
grid = mpl.gridspec.GridSpec(nrows=1, ncols=1)

x = np.random.normal(size=1000)
data = pd.DataFrame({'x': x})
ax = sb.plot1D.histogram(data, fig, grid, gridindex=0, x='x')

  • plotting a numpy.ndarray (tf.Tensor analogous)

    import matplotlib as mpl
import numpy as np
import spellbook as sb

fig = mpl.pyplot.figure(tight_layout=True)
grid = mpl.gridspec.GridSpec(nrows=1, ncols=1)

x = np.random.normal(size=1000)
ax = sb.plot1D.histogram(x, fig, grid, gridindex=0,
                        xlabel='x-axis label')