You are reading an old version of the documentation (v2.0.2). For the latest version see https://matplotlib.org/stable/
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/
Examples
Examples# This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the API in general and some demonstrate specific applications in tutorial form. Also check out our user guide for more detailed illustrations. Release Highlights# These examples illustrate the main features of the releases of scikit-learn.
statistics example code: histogram_demo_cumulative.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/ """ ========================================================== Demo of using histograms to plot a cumulative distribution ========================================================== This shows how to plot a cumulative, normalized histogram as a step function in order to visualize
pylab_examples example code: contourf_demo.py — Matplotlib 2.0.2 documentation
import numpy as np import matplotlib.pyplot as plt origin = 'lower' #origin = 'upper' delta = 0.025 x = y = np.arange(-3.0, 3.01, delta) X, Y = np.meshgrid(x, y) Z1 = plt.mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = plt.mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1) Z = 10 * (Z1 - Z2) nr, nc = Z.shape # put NaNs in one corner: Z[-nr//6:, -nc//6:] = np.nan # contourf will convert these to mask
pylab_examples example code: colorbar_tick_labelling_demo.py — Matplotlib 2.0.2 documentation
"""Produce custom labelling for a colorbar. Contributed by Scott Sinclair """ import matplotlib.pyplot as plt import numpy as np from matplotlib import cm from numpy.random import randn # Make plot with vertical (default) colorbar fig, ax = plt.subplots() data = np.clip(randn(250, 250), -1, 1) cax = ax.imshow(data, interpolation='nearest', cmap=cm.coolwarm) ax.set_title('Gaussian noise with vertic
api example code: colorbar_only.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/ ''' ==================== Customized colorbars ==================== This example shows how to build colorbars without an attached mappable. ''' import matplotlib.pyplot as plt import matplotlib as mpl # Make a figure and axes with dimensions as desired. fig = plt.figure(figsize=(8
Matplotlib Examples — 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/
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
images_contours_and_fields example code: interpolation_methods.py — Matplotlib 2.0.2 documentation
''' Show all different interpolation methods for imshow ''' import matplotlib.pyplot as plt import numpy as np # from the docs: # If interpolation is None, default to rc image.interpolation. See also # the filternorm and filterrad parameters. If interpolation is 'none', then # no interpolation is performed on the Agg, ps and pdf backends. Other # backends will fall back to 'nearest'. # # http://ma
shapes_and_collections example code: artist_reference.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/ """ Reference for matplotlib artists This example displays several of matplotlib's graphics primitives (artists) drawn using matplotlib API. A full list of artists and the documentation is available at http://matplotlib.org/api/artist_api.html. Copyright (c) 2010, Bartosz Telencz
pylab_examples example code: boxplot_demo.py — Matplotlib 2.0.2 documentation
import matplotlib.pyplot as plt import numpy as np # fake up some data spread = np.random.rand(50) * 100 center = np.ones(25) * 50 flier_high = np.random.rand(10) * 100 + 100 flier_low = np.random.rand(10) * -100 data = np.concatenate((spread, center, flier_high, flier_low), 0) # basic plot plt.boxplot(data) # notched plot plt.figure() plt.boxplot(data, 1) # change outlier point symbols plt.figure
axes_grid example code: demo_parasite_axes2.py — Matplotlib 2.0.2 documentation
""" Parasite axis demo The following code is an example of a parasite axis. It aims to show a user how to plot multiple different values onto one single plot. Notice how in this example, par1 and par2 are both calling twinx meaning both are tied directly to the x-axis. From there, each of those two axis can behave separately from the each other, meaning they can take on separate values from themse
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Welcome to imbalanced-learn documentation!
Examples — Matplotlib 3.9.0 documentation
Thumbnail gallery — Matplotlib 1.3.x documentation