sliceplots.one_dimensional module

Module containing useful 1D plotting abstractions on top of matplotlib.

sliceplots.one_dimensional.plot_multicolored_line(*, ax=None, x, y, other_y, cmap='viridis', vmin=None, vmax=None, linewidth=2, alpha=1)

Plots a line colored based on the values of another array.

Plots the curve y(x), colored based on the values in other_y.

Parameters:

• ax (Axes, optional) – Axes instance, for plotting, defaults to None. If None, a new Figure will be created.

• y (1d array_like) – The dependent variable.

• x (1d array_like) – The independent variable.

• other_y (1d array_like) – The values whose magnitude will be converted to colors.

• cmap (str, optional) – The used colormap (defaults to “viridis”).

• vmin (float, optional) – Lower normalization limit

• vmax (float, optional) – Upper normalization limit

• linewidth (float, optional (default 2)) – Width of the plotted line

• alpha (float, optional (default 1)) – Line transparency, between 0 and 1

Returns:

ax, line – Main Axes and plotted line

Return type:

Axes, LineCollection

Raises:

AssertionError – If the length of y and other_y do not match.

References

matplotlib example.

Examples

We plot a curve and color it based on the value of its first derivative.

import numpy as np
from matplotlib import pyplot

from sliceplots import plot_multicolored_line

x = np.linspace(0, 3 * np.pi, 500)
y = np.sin(x)
dydx = np.gradient(y) * 100  # first derivative

_, ax = pyplot.subplots()

plot_multicolored_line(ax=ax, x=x, y=y, other_y=dydx)

ax.set(ylabel="y", xlabel="x")

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

sliceplots.one_dimensional.plot1d_break_x(*, ax=None, h_axis, v_axis, param, slice_opts)

Line plot with a broken x-axis.

Parameters:

• ax (Axes, optional) – Axes instance, for plotting. If None, a new Figure will be created. Defaults to None.

• h_axis (1d array_like) – x-axis data.

• v_axis (1d array_like) – y-axis data.

• param (dict) – Axes limits and labels.

• slice_opts (dict) – Options for plotted line.

Returns:

ax_left, ax_right – Left and right Axes of the split plot.

Return type:

tuple of Axes

Examples

import numpy as np
from matplotlib import pyplot

from sliceplots import plot1d_break_x

uu = np.linspace(0, np.pi, 128)
data = np.cos(uu - 0.5) * np.cos(uu.reshape(-1, 1) - 1.0)

_, ax = pyplot.subplots()

plot1d_break_x(
    ax=ax,
    h_axis=uu,
    v_axis=data[data.shape[0] // 2, :],
    param={
        "xlim_left": (0, 1),
        "xlim_right": (2, 3),
        "xlabel": r"$x$ ($\mu$m)",
        "ylabel": r"$\rho$ (cm${}^{-3}$)",
    },
    slice_opts={"ls": "--", "color": "#d62728"})

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

sliceplots.one_dimensional.plot1d(*, ax=None, h_axis, v_axis, xlabel='', ylabel='', **kwargs)

Plot the data with given labels and plot options.

Parameters:

• ax (class:~matplotlib.axes.Axes, optional) – Axes instance, for plotting. If None, a new Figure will be created. Defaults to None.

• h_axis (np.ndarray) – x-axis data.

• v_axis (np.ndarray) – y-axis data.

• xlabel (str, optional) – x-axis label.

• ylabel (str, optional) – y-axis label.

• kwargs (dict, optional) – Other arguments for plot().

Returns:

ax – Modified Axes, containing plot.

Return type:

Axes

Examples

>>> import numpy as np

>>> uu = np.linspace(0, np.pi, 128)
>>> data = np.cos(uu - 0.5) * np.cos(uu.reshape(-1, 1) - 1.0)

>>> plot1d(
...     h_axis=uu,
...     v_axis=data[data.shape[0] // 2, :],
...     xlabel=r"$z$ ($\mu$m)",
...     ylabel=r"$a_0$",
...     xlim=[0, 3],
...     ylim=[-1, 1],
...     color="#d62728",
... )  
<Axes: xlabel='$z$ ($\\mu$m)', ylabel='$a_0$'>