matplotlib.pyplot.imshow — Matplotlib 3.9.0 documentation
matplotlib.pyplot.imshow# matplotlib.pyplot.imshow(X, cmap=None, norm=None, *, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, interpolation_stage=None, filternorm=True, filterrad=4.0, resample=None, url=None, data=None, **kwargs)[source]# Display data as an image, i.e., on a 2D regular raster. The input may either be actual RGB(A) data, or 2D scalar da
matplotlib.pyplot.subplot — Matplotlib 3.9.0 documentation
matplotlib.pyplot.subplot# matplotlib.pyplot.subplot(*args, **kwargs)[source]# Add an Axes to the current figure or retrieve an existing Axes. This is a wrapper of Figure.add_subplot which provides additional behavior when working with the implicit API (see the notes section). Call signatures: subplot(nrows, ncols, index, **kwargs) subplot(pos, **kwargs) subplot(**kwargs) subplot(ax) Parameters: *
Spectrogram — Matplotlib 3.9.0 documentation
import matplotlib.pyplot as plt import numpy as np # Fixing random state for reproducibility np.random.seed(19680801) dt = 0.0005 t = np.arange(0.0, 20.5, dt) s1 = np.sin(2 * np.pi * 100 * t) s2 = 2 * np.sin(2 * np.pi * 400 * t) # create a transient "chirp" s2[t <= 10] = s2[12 <= t] = 0 # add some noise into the mix nse = 0.01 * np.random.random(size=len(t)) x = s1 + s2 + nse # the signal NFFT = 1
matplotlib.pyplot — Matplotlib 3.5.3 documentation
matplotlib.pyplot# matplotlib.pyplot is a state-based interface to matplotlib. It provides an implicit, MATLAB-like, way of plotting. It also opens figures on your screen, and acts as the figure GUI manager. pyplot is mainly intended for interactive plots and simple cases of programmatic plot generation: import numpy as np import matplotlib.pyplot as plt x = np.arange(0, 5, 0.1) y = np.sin(x) plt.
Thumbnail gallery — 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.pyplot.specgram — Matplotlib 3.9.0 documentation
matplotlib.pyplot.specgram# matplotlib.pyplot.specgram(x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, cmap=None, xextent=None, pad_to=None, sides=None, scale_by_freq=None, mode=None, scale=None, vmin=None, vmax=None, *, data=None, **kwargs)[source]# Plot a spectrogram. Compute and plot a spectrogram of data in x. Data are split into NFFT length segments and the spectrum
Text properties and layout — 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/
Ipython Directive — sampledoc 1.0 documentation
Ipython Directive¶ The ipython directive is a stateful ipython shell for embedding in sphinx documents. It knows about standard ipython prompts, and extracts the input and output lines. These prompts will be renumbered starting at 1. The inputs will be fed to an embedded ipython interpreter and the outputs from that interpreter will be inserted as well. For example, code blocks like the following:
Plots with different scales — Matplotlib 3.0.0 documentation
Plots with different scales# Two plots on the same Axes with different left and right scales. The trick is to use two different Axes that share the same x axis. You can use separate matplotlib.ticker formatters and locators as desired since the two Axes are independent. Such Axes are generated by calling the Axes.twinx method. Likewise, Axes.twiny is available to generate Axes that share a y axis
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matplotlib.colors.Colormap — Matplotlib 3.9.0 documentation
matplotlib.pyplot.subplots — Matplotlib 3.9.0 documentation
matplotlib.pyplot.xlabel — Matplotlib 3.9.0 documentation
3D plots as subplots — Matplotlib 3.9.0 documentation
matplotlib.pyplot.hist — Matplotlib 3.9.0 documentation
matplotlib.pyplot.xscale — Matplotlib 3.9.0 documentation
matplotlib.pyplot — Matplotlib 3.5.2 documentation
Tutorials — Matplotlib 3.9.0 documentation
https://matplotlib.org/stable/users/installing.html