api example code: sankey_demo_rankine.py — Matplotlib 2.0.2 documentation
You are reading an old version of the documentation (v2.0.2). For the latest version see https://matplotlib.org/stable/ """ =================== Rankine power cycle =================== Demonstrate the Sankey class with a practical example of a Rankine power cycle. """ import matplotlib.pyplot as plt from matplotlib.sankey import Sankey fig = plt.figure(figsize=(8, 9)) ax = fig.add_subplot(1, 1, 1,
pyplot — Matplotlib 1.3.1 documentation
matplotlib.pyplot¶ Provides a MATLAB-like plotting framework. pylab combines pyplot with numpy into a single namespace. This is convenient for interactive work, but for programming it is recommended that the namespaces be kept separate, e.g.:
pylab_examples example code: arrow_simple_demo.py — Matplotlib 2.0.2 documentation
You are reading an old version of the documentation (v2.0.2). For the latest version see https://matplotlib.org/stable/
Matplotlib: Python plotting — Matplotlib 2.0.0 documentation
Matplotlib: Visualization with Python Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Create publication quality plots. Make interactive figures that can zoom, pan, update. Customize visual style and layout. Export to many file formats. Embed in JupyterLab and Graphical User I
color example code: colormaps_reference.py — Matplotlib 2.0.2 documentation
""" ================== Colormap reference ================== Reference for colormaps included with Matplotlib. This reference example shows all colormaps included with Matplotlib. Note that any colormap listed here can be reversed by appending "_r" (e.g., "pink_r"). These colormaps are divided into the following categories: Sequential: These colormaps are approximately monochromatic colormaps vary
matplotlib.axes.Axes.plot — Matplotlib 3.10.3 documentation
matplotlib.axes.Axes.plot# Axes.plot(*args, scalex=True, scaley=True, data=None, **kwargs)[source]# Plot y versus x as lines and/or markers. Call signatures: plot([x], y, [fmt], *, data=None, **kwargs) plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs) The coordinates of the points or line nodes are given by x, y. The optional parameter fmt is a convenient way for defining basic formatting like
Customizing Location of Subplot Using GridSpec — Matplotlib 2.0.2 documentation
GridSpec specifies the geometry of the grid that a subplot will be placed. The number of rows and number of columns of the grid need to be set. Optionally, the subplot layout parameters (e.g., left, right, etc.) can be tuned. SubplotSpec specifies the location of the subplot in the given GridSpec. subplot2grid() a helper function that is similar to subplot() but uses 0-based indexing and let subpl
matplotlib.axes.Axes.quiver — Matplotlib 3.10.3 documentation
matplotlib.axes.Axes.quiver# Axes.quiver(*args, data=None, **kwargs)[source]# Plot a 2D field of arrows. Call signature: X, Y define the arrow locations, U, V define the arrow directions, and C optionally sets the color. The arguments X, Y, U, V, C are positional-only. Arrow length The default settings auto-scales the length of the arrows to a reasonable size. To change this behavior see the scale
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