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"""
===============================
Fill the area between two lines
===============================
This example shows how to use `~.axes.Axes.fill_between` to color the area
between two lines.
"""
import matplotlib.pyplot as plt
import numpy as np
# %%
#
# Basic usage
# -----------
# The parameters *y1* and *y2* ca... | stable__gallery__lines_bars_and_markers__fill_between_demo | 3 | figure_003.png | Fill the area between two lines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/fill_between_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-fill-between-demo-py | https://matplotlib.org/stable/_downloads/264a8be4de96930763e780682bdaba2d/fill_between_demo.py | fill_between_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
========================================
Fill the area between two vertical lines
========================================
Using `~.Axes.fill_betweenx` to color along the horizontal direction between
two curves.
"""
import matplotlib.pyplot as plt
import numpy as np
y = np.arange(0.0, 2, 0.01)
x1 = np.sin(2 * np.... | stable__gallery__lines_bars_and_markers__fill_betweenx_demo | 0 | figure_000.png | Fill the area between two vertical lines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/fill_betweenx_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-fill-betweenx-demo-py | https://matplotlib.org/stable/_downloads/25520da3172b0ab1766f2f0bd31a49f6/fill_betweenx_demo.py | fill_betweenx_demo.py | lines_bars_and_markers | ok | 2 | null | |
"""
========================================
Fill the area between two vertical lines
========================================
Using `~.Axes.fill_betweenx` to color along the horizontal direction between
two curves.
"""
import matplotlib.pyplot as plt
import numpy as np
y = np.arange(0.0, 2, 0.01)
x1 = np.sin(2 * np.... | stable__gallery__lines_bars_and_markers__fill_betweenx_demo | 1 | figure_001.png | Fill the area between two vertical lines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/fill_betweenx_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-fill-betweenx-demo-py | https://matplotlib.org/stable/_downloads/25520da3172b0ab1766f2f0bd31a49f6/fill_betweenx_demo.py | fill_betweenx_demo.py | lines_bars_and_markers | ok | 2 | null | |
"""
========================
Bar chart with gradients
========================
Matplotlib does not natively support gradients. However, we can emulate a
gradient-filled rectangle by an `.AxesImage` of the right size and coloring.
In particular, we use a colormap to generate the actual colors. It is then
sufficient to... | stable__gallery__lines_bars_and_markers__gradient_bar | 0 | figure_000.png | Bar chart with gradients — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/gradient_bar.html#sphx-glr-download-gallery-lines-bars-and-markers-gradient-bar-py | https://matplotlib.org/stable/_downloads/e83fa918d4012d4ca7e2bd48e7ab0935/gradient_bar.py | gradient_bar.py | lines_bars_and_markers | ok | 1 | null | |
"""
=========
Hat graph
=========
This example shows how to create a `hat graph`_ and how to annotate it with
labels.
.. _hat graph: https://doi.org/10.1186/s41235-019-0182-3
"""
import matplotlib.pyplot as plt
import numpy as np
def hat_graph(ax, xlabels, values, group_labels):
"""
Create a hat graph.
... | stable__gallery__lines_bars_and_markers__hat_graph | 0 | figure_000.png | Hat graph — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/hat_graph.html#sphx-glr-download-gallery-lines-bars-and-markers-hat-graph-py | https://matplotlib.org/stable/_downloads/ff9b887ec7665e75d3992d3af408be52/hat_graph.py | hat_graph.py | lines_bars_and_markers | ok | 1 | null | |
"""
=============================================
Discrete distribution as horizontal bar chart
=============================================
Stacked bar charts can be used to visualize discrete distributions.
This example visualizes the result of a survey in which people could rate
their agreement to questions on a ... | stable__gallery__lines_bars_and_markers__horizontal_barchart_distribution | 0 | figure_000.png | Discrete distribution as horizontal bar chart — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/horizontal_barchart_distribution.html#sphx-glr-download-gallery-lines-bars-and-markers-horizontal-barchart-distribution-py | https://matplotlib.org/stable/_downloads/77d0d6c2d02582d80df43b9b9e78610c/horizontal_barchart_distribution.py | horizontal_barchart_distribution.py | lines_bars_and_markers | ok | 1 | null | |
"""
=========
JoinStyle
=========
The `matplotlib._enums.JoinStyle` controls how Matplotlib draws the corners
where two different line segments meet. For more details, see the
`~matplotlib._enums.JoinStyle` docs.
"""
import matplotlib.pyplot as plt
from matplotlib._enums import JoinStyle
JoinStyle.demo()
plt.show()... | stable__gallery__lines_bars_and_markers__joinstyle | 0 | figure_000.png | JoinStyle — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/joinstyle.html#sphx-glr-download-gallery-lines-bars-and-markers-joinstyle-py | https://matplotlib.org/stable/_downloads/6bb713e635f8898fbc28683331020d84/joinstyle.py | joinstyle.py | lines_bars_and_markers | ok | 1 | null | |
"""
===============================
Dashed line style configuration
===============================
The dashing of a line is controlled via a dash sequence. It can be modified
using `.Line2D.set_dashes`.
The dash sequence is a series of on/off lengths in points, e.g.
``[3, 1]`` would be 3pt long lines separated by 1p... | stable__gallery__lines_bars_and_markers__line_demo_dash_control | 0 | figure_000.png | Dashed line style configuration — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/line_demo_dash_control.html#sphx-glr-download-gallery-lines-bars-and-markers-line-demo-dash-control-py | https://matplotlib.org/stable/_downloads/1c02700bb13e6571e774c10ba73db267/line_demo_dash_control.py | line_demo_dash_control.py | lines_bars_and_markers | ok | 1 | null | |
"""
==============================
Lines with a ticked patheffect
==============================
Ticks can be added along a line to mark one side as a barrier using
`~matplotlib.patheffects.TickedStroke`. You can control the angle,
spacing, and length of the ticks.
The ticks will also appear appropriately in the leg... | stable__gallery__lines_bars_and_markers__lines_with_ticks_demo | 0 | figure_000.png | Lines with a ticked patheffect — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/lines_with_ticks_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-lines-with-ticks-demo-py | https://matplotlib.org/stable/_downloads/3269caad4b186ff2ba73f725b2cb5a12/lines_with_ticks_demo.py | lines_with_ticks_demo.py | lines_bars_and_markers | ok | 1 | null | |
"""
==========
Linestyles
==========
Simple linestyles can be defined using the strings "solid", "dotted", "dashed"
or "dashdot". More refined control can be achieved by providing a dash tuple
``(offset, (on_off_seq))``. For example, ``(0, (3, 10, 1, 15))`` means
(3pt line, 10pt space, 1pt line, 15pt space) with no of... | stable__gallery__lines_bars_and_markers__linestyles | 0 | figure_000.png | Linestyles — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/linestyles.html#sphx-glr-download-gallery-lines-bars-and-markers-linestyles-py | https://matplotlib.org/stable/_downloads/79cca01aa25ff65b23b051f7e4ca55f5/linestyles.py | linestyles.py | lines_bars_and_markers | ok | 1 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 0 | figure_000.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 1 | figure_001.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 2 | figure_002.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 3 | figure_003.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 4 | figure_004.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 5 | figure_005.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 6 | figure_006.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
================
Marker reference
================
Matplotlib supports multiple categories of markers which are selected using
the ``marker`` parameter of plot commands:
- `Unfilled markers`_
- `Filled markers`_
- `Markers created from TeX symbols`_
- `Markers created from Paths`_
For a list of all markers see a... | stable__gallery__lines_bars_and_markers__marker_reference | 7 | figure_007.png | Marker reference — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/marker_reference.html#unfilled-markers | https://matplotlib.org/stable/_downloads/af914017c64db37d6e814a5e9cdfb4a2/marker_reference.py | marker_reference.py | lines_bars_and_markers | ok | 8 | null | |
"""
==============
Markevery Demo
==============
The ``markevery`` property of `.Line2D` allows drawing markers at a subset of
data points.
The list of possible parameters is specified at `.Line2D.set_markevery`.
In short:
- A single integer N draws every N-th marker.
- A tuple of integers (start, N) draws every N-t... | stable__gallery__lines_bars_and_markers__markevery_demo | 0 | figure_000.png | Markevery Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/markevery_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-markevery-demo-py | https://matplotlib.org/stable/_downloads/d4832f59edf5628fed3ec2eee2cecbf9/markevery_demo.py | markevery_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
==============
Markevery Demo
==============
The ``markevery`` property of `.Line2D` allows drawing markers at a subset of
data points.
The list of possible parameters is specified at `.Line2D.set_markevery`.
In short:
- A single integer N draws every N-th marker.
- A tuple of integers (start, N) draws every N-t... | stable__gallery__lines_bars_and_markers__markevery_demo | 1 | figure_001.png | Markevery Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/markevery_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-markevery-demo-py | https://matplotlib.org/stable/_downloads/d4832f59edf5628fed3ec2eee2cecbf9/markevery_demo.py | markevery_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
==============
Markevery Demo
==============
The ``markevery`` property of `.Line2D` allows drawing markers at a subset of
data points.
The list of possible parameters is specified at `.Line2D.set_markevery`.
In short:
- A single integer N draws every N-th marker.
- A tuple of integers (start, N) draws every N-t... | stable__gallery__lines_bars_and_markers__markevery_demo | 2 | figure_002.png | Markevery Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/markevery_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-markevery-demo-py | https://matplotlib.org/stable/_downloads/d4832f59edf5628fed3ec2eee2cecbf9/markevery_demo.py | markevery_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
==============
Markevery Demo
==============
The ``markevery`` property of `.Line2D` allows drawing markers at a subset of
data points.
The list of possible parameters is specified at `.Line2D.set_markevery`.
In short:
- A single integer N draws every N-th marker.
- A tuple of integers (start, N) draws every N-t... | stable__gallery__lines_bars_and_markers__markevery_demo | 3 | figure_003.png | Markevery Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/markevery_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-markevery-demo-py | https://matplotlib.org/stable/_downloads/d4832f59edf5628fed3ec2eee2cecbf9/markevery_demo.py | markevery_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
==============================
Plotting masked and NaN values
==============================
Sometimes you need to plot data with missing values.
One possibility is to simply remove undesired data points. The line plotted
through the remaining data will be continuous, and not indicate where the
missing data is lo... | stable__gallery__lines_bars_and_markers__masked_demo | 0 | figure_000.png | Plotting masked and NaN values — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/masked_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-masked-demo-py | https://matplotlib.org/stable/_downloads/285cf9001b13973e75842eb0b810371f/masked_demo.py | masked_demo.py | lines_bars_and_markers | ok | 1 | null | |
"""
==================
Multicolored lines
==================
The example shows two ways to plot a line with the a varying color defined by
a third value. The first example defines the color at each (x, y) point.
The second example defines the color between pairs of points, so the length
of the color value list is one ... | stable__gallery__lines_bars_and_markers__multicolored_line | 0 | figure_000.png | Multicolored lines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/multicolored_line.html#sphx-glr-download-gallery-lines-bars-and-markers-multicolored-line-py | https://matplotlib.org/stable/_downloads/dde8bce4a3266a4b3702098ddc49f236/multicolored_line.py | multicolored_line.py | lines_bars_and_markers | ok | 3 | null | |
"""
==============================================
Mapping marker properties to multivariate data
==============================================
This example shows how to use different properties of markers to plot
multivariate datasets. Here we represent a successful baseball throw as a
smiley face with marker size m... | stable__gallery__lines_bars_and_markers__multivariate_marker_plot | 0 | figure_000.png | Mapping marker properties to multivariate data — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/multivariate_marker_plot.html#sphx-glr-download-gallery-lines-bars-and-markers-multivariate-marker-plot-py | https://matplotlib.org/stable/_downloads/0c9f82be1ea4cded0763a4430f4a0e83/multivariate_marker_plot.py | multivariate_marker_plot.py | lines_bars_and_markers | ok | 1 | null | |
"""
============================
Power spectral density (PSD)
============================
Plotting power spectral density (PSD) using `~.Axes.psd`.
The PSD is a common plot in the field of signal processing. NumPy has
many useful libraries for computing a PSD. Below we demo a few examples
of how this can be accompli... | stable__gallery__lines_bars_and_markers__psd_demo | 0 | figure_000.png | Power spectral density (PSD) — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/psd_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-psd-demo-py | https://matplotlib.org/stable/_downloads/5297dff52c244336df5a0ee552a4abbf/psd_demo.py | psd_demo.py | lines_bars_and_markers | ok | 4 | null | |
"""
=============
Scatter Demo2
=============
Demo of scatter plot with varying marker colors and sizes.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cbook as cbook
# Load a numpy record array from yahoo csv data with fields date, open, high,
# low, close, volume, adj_close from the mpl-d... | stable__gallery__lines_bars_and_markers__scatter_demo2 | 0 | figure_000.png | Scatter Demo2 — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_demo2.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-demo2-py | https://matplotlib.org/stable/_downloads/5b9eb7dec3f843b16e67ad82e4647a08/scatter_demo2.py | scatter_demo2.py | lines_bars_and_markers | ok | 1 | null | |
"""
============================
Scatter plot with histograms
============================
Add histograms to the x-axes and y-axes margins of a scatter plot.
This layout features a central scatter plot illustrating the relationship
between x and y, a histogram at the top displaying the distribution of x, and a
histog... | stable__gallery__lines_bars_and_markers__scatter_hist | 0 | figure_000.png | Scatter plot with histograms — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_hist.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-hist-py | https://matplotlib.org/stable/_downloads/3e1134ffd2662d0ad0c453c6dfb7882d/scatter_hist.py | scatter_hist.py | lines_bars_and_markers | ok | 2 | null | |
"""
============================
Scatter plot with histograms
============================
Add histograms to the x-axes and y-axes margins of a scatter plot.
This layout features a central scatter plot illustrating the relationship
between x and y, a histogram at the top displaying the distribution of x, and a
histog... | stable__gallery__lines_bars_and_markers__scatter_hist | 1 | figure_001.png | Scatter plot with histograms — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_hist.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-hist-py | https://matplotlib.org/stable/_downloads/3e1134ffd2662d0ad0c453c6dfb7882d/scatter_hist.py | scatter_hist.py | lines_bars_and_markers | ok | 2 | null | |
"""
===============================
Scatter plot with masked values
===============================
Mask some data points and add a line demarking
masked regions.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
N = 100
r0 = 0.6
x = 0.9 * np.... | stable__gallery__lines_bars_and_markers__scatter_masked | 0 | figure_000.png | Scatter plot with masked values — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_masked.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-masked-py | https://matplotlib.org/stable/_downloads/68d80e3d1e3f3561a71b3e5c8efae907/scatter_masked.py | scatter_masked.py | lines_bars_and_markers | ok | 1 | null | |
"""
===============
Marker examples
===============
Example with different ways to specify markers.
See also the `matplotlib.markers` documentation for a list of all markers and
:doc:`/gallery/lines_bars_and_markers/marker_reference` for more information
on configuring markers.
.. redirect-from:: /gallery/lines_bars... | stable__gallery__lines_bars_and_markers__scatter_star_poly | 0 | figure_000.png | Marker examples — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_star_poly.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-star-poly-py | https://matplotlib.org/stable/_downloads/bec52923c4e8bde35b6455fdff6def07/scatter_star_poly.py | scatter_star_poly.py | lines_bars_and_markers | ok | 1 | null | |
"""
==========================
Scatter plot with a legend
==========================
To create a scatter plot with a legend one may use a loop and create one
`~.Axes.scatter` plot per item to appear in the legend and set the ``label``
accordingly.
The following also demonstrates how transparency of the markers
can be... | stable__gallery__lines_bars_and_markers__scatter_with_legend | 0 | figure_000.png | Scatter plot with a legend — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_with_legend.html#sphx-glr-download-gallery-lines-bars-and-markers-scatter-with-legend-py | https://matplotlib.org/stable/_downloads/e296fc40ba715311fdebebae0ecf1c71/scatter_with_legend.py | scatter_with_legend.py | lines_bars_and_markers | ok | 3 | null | |
"""
=========
Line plot
=========
Create a basic line plot.
"""
import matplotlib.pyplot as plt
import numpy as np
# Data for plotting
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)
fig, ax = plt.subplots()
ax.plot(t, s)
ax.set(xlabel='time (s)', ylabel='voltage (mV)',
title='About as simple as... | stable__gallery__lines_bars_and_markers__simple_plot | 0 | figure_000.png | Line plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/simple_plot.html#sphx-glr-download-gallery-lines-bars-and-markers-simple-plot-py | https://matplotlib.org/stable/_downloads/841352d8ea6065fce570abdf6225ef02/simple_plot.py | simple_plot.py | lines_bars_and_markers | ok | 1 | null | |
"""
==========================================================
Shade regions defined by a logical mask using fill_between
==========================================================
"""
import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0.0, 2, 0.01)
s = np.sin(2*np.pi*t)
fig, ax = plt.subplots()
ax.pl... | stable__gallery__lines_bars_and_markers__span_regions | 0 | figure_000.png | Shade regions defined by a logical mask using fill_between — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/span_regions.html#sphx-glr-download-gallery-lines-bars-and-markers-span-regions-py | https://matplotlib.org/stable/_downloads/ae69400014c751155c2d298248eb41e6/span_regions.py | span_regions.py | lines_bars_and_markers | ok | 1 | null | |
"""
========================
Spectrum representations
========================
The plots show different spectrum representations of a sine signal with
additive noise. A (frequency) spectrum of a discrete-time signal is calculated
by utilizing the fast Fourier transform (FFT).
"""
import matplotlib.pyplot as plt
import... | stable__gallery__lines_bars_and_markers__spectrum_demo | 0 | figure_000.png | Spectrum representations — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/spectrum_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-spectrum-demo-py | https://matplotlib.org/stable/_downloads/b8c57e62999229824f455e779d286772/spectrum_demo.py | spectrum_demo.py | lines_bars_and_markers | ok | 1 | null | |
"""
===========================
Stackplots and streamgraphs
===========================
"""
# %%
# Stackplots
# ----------
#
# Stackplots draw multiple datasets as vertically stacked areas. This is
# useful when the individual data values and additionally their cumulative
# value are of interest.
import matplotlib.p... | stable__gallery__lines_bars_and_markers__stackplot_demo | 0 | figure_000.png | Stackplots and streamgraphs — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/stackplot_demo.html#streamgraphs | https://matplotlib.org/stable/_downloads/a4ca2d398a778f09d428679d85cdef43/stackplot_demo.py | stackplot_demo.py | lines_bars_and_markers | ok | 2 | null | |
"""
===========
Stairs Demo
===========
This example demonstrates the use of `~.matplotlib.pyplot.stairs` for stepwise
constant functions. A common use case is histogram and histogram-like data
visualization.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import StepPatch
np.random.... | stable__gallery__lines_bars_and_markers__stairs_demo | 0 | figure_000.png | Stairs Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/stairs_demo.html#stairs-demo | https://matplotlib.org/stable/_downloads/99b2228ef8ead5b15771558e042ee4f3/stairs_demo.py | stairs_demo.py | lines_bars_and_markers | ok | 2 | null | |
"""
=========
Stem plot
=========
`~.pyplot.stem` plots vertical lines from a baseline to the y-coordinate and
places a marker at the tip.
"""
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
plt.stem(x, y)
plt.show()
# %%
#
# The position of the baseline ... | stable__gallery__lines_bars_and_markers__stem_plot | 0 | figure_000.png | Stem plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/stem_plot.html#stem-plot | https://matplotlib.org/stable/_downloads/605cad767f8ac8bf813bcd4941015322/stem_plot.py | stem_plot.py | lines_bars_and_markers | ok | 2 | null | |
"""
=========
Step Demo
=========
This example demonstrates the use of `.pyplot.step` for piece-wise constant
curves. In particular, it illustrates the effect of the parameter *where*
on the step position.
.. note::
For the common case that you know the edge positions, use `.pyplot.stairs`
instead.
The circ... | stable__gallery__lines_bars_and_markers__step_demo | 0 | figure_000.png | Step Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/step_demo.html#step-demo | https://matplotlib.org/stable/_downloads/f8a42a328abce5e8455725246cb68710/step_demo.py | step_demo.py | lines_bars_and_markers | ok | 2 | null | |
"""
====================================
Timeline with lines, dates, and text
====================================
How to create a simple timeline using Matplotlib release dates.
Timelines can be created with a collection of dates and text. In this example,
we show how to create a simple timeline using the dates for ... | stable__gallery__lines_bars_and_markers__timeline | 0 | figure_000.png | Timeline with lines, dates, and text — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/timeline.html#timeline-with-lines-dates-and-text | https://matplotlib.org/stable/_downloads/e4e3bbd0b1c82e93b916e64bd632f7a9/timeline.py | timeline.py | lines_bars_and_markers | ok | 1 | null | |
"""
=================
hlines and vlines
=================
This example showcases the functions hlines and vlines.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
t = np.arange(0.0, 5.0, 0.1)
s = np.exp(-t) + np.sin(2 * np.pi * t) + 1
nse = np... | stable__gallery__lines_bars_and_markers__vline_hline_demo | 0 | figure_000.png | hlines and vlines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/vline_hline_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-vline-hline-demo-py | https://matplotlib.org/stable/_downloads/fcbc14b23962009bcf6e5a7d52e939c8/vline_hline_demo.py | vline_hline_demo.py | lines_bars_and_markers | ok | 1 | null | |
"""
===========================
Cross- and auto-correlation
===========================
Example use of cross-correlation (`~.Axes.xcorr`) and auto-correlation
(`~.Axes.acorr`) plots.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
x, y = np.r... | stable__gallery__lines_bars_and_markers__xcorr_acorr_demo | 0 | figure_000.png | Cross- and auto-correlation — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/lines_bars_and_markers/xcorr_acorr_demo.html#sphx-glr-download-gallery-lines-bars-and-markers-xcorr-acorr-demo-py | https://matplotlib.org/stable/_downloads/fad6b154bf9cffbaaac152da639e6889/xcorr_acorr_demo.py | xcorr_acorr_demo.py | lines_bars_and_markers | ok | 1 | null | |
"""
================
Anchored Artists
================
This example illustrates the use of the anchored objects without the
helper classes found in :mod:`mpl_toolkits.axes_grid1`. This version
of the figure is similar to the one found in
:doc:`/gallery/axes_grid1/simple_anchored_artists`, but it is
implemented using o... | stable__gallery__misc__anchored_artists | 0 | figure_000.png | Anchored Artists — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/anchored_artists.html#sphx-glr-download-gallery-misc-anchored-artists-py | https://matplotlib.org/stable/_downloads/56dd8a42c5506d6f4b030f191ab55a38/anchored_artists.py | anchored_artists.py | misc | ok | 1 | null | |
"""
==================================
Identify whether artists intersect
==================================
The lines intersecting the rectangle are colored in red, while the others
are left as blue lines. This example showcases the `.intersects_bbox` function.
"""
import matplotlib.pyplot as plt
import numpy as np... | stable__gallery__misc__bbox_intersect | 0 | figure_000.png | Identify whether artists intersect — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/bbox_intersect.html#sphx-glr-gallery-misc-bbox-intersect-py | https://matplotlib.org/stable/_downloads/832476b1f1a894c408ecb93acb7b935c/bbox_intersect.py | bbox_intersect.py | misc | ok | 1 | null | |
"""
==============
Manual Contour
==============
Example of displaying your own contour lines and polygons using ContourSet.
"""
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.contour import ContourSet
from matplotlib.path import Path
# %%
# Contour lines for each level are a list/tuple ... | stable__gallery__misc__contour_manual | 0 | figure_000.png | Manual Contour — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/contour_manual.html#sphx-glr-download-gallery-misc-contour-manual-py | https://matplotlib.org/stable/_downloads/6f6ddec07749bdbe4eea6b25d5dc81a6/contour_manual.py | contour_manual.py | misc | ok | 2 | null | |
"""
==============
Manual Contour
==============
Example of displaying your own contour lines and polygons using ContourSet.
"""
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.contour import ContourSet
from matplotlib.path import Path
# %%
# Contour lines for each level are a list/tuple ... | stable__gallery__misc__contour_manual | 1 | figure_001.png | Manual Contour — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/contour_manual.html#sphx-glr-download-gallery-misc-contour-manual-py | https://matplotlib.org/stable/_downloads/6f6ddec07749bdbe4eea6b25d5dc81a6/contour_manual.py | contour_manual.py | misc | ok | 2 | null | |
"""
=============
Coords Report
=============
Override the default reporting of coords as the mouse moves over the Axes
in an interactive backend.
"""
import matplotlib.pyplot as plt
import numpy as np
def millions(x):
return '$%1.1fM' % (x * 1e-6)
# Fixing random state for reproducibility
np.random.seed(1968... | stable__gallery__misc__coords_report | 0 | figure_000.png | Coords Report — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/coords_report.html#sphx-glr-download-gallery-misc-coords-report-py | https://matplotlib.org/stable/_downloads/3cf562cde19e200420cb83f024dd891a/coords_report.py | coords_report.py | misc | ok | 1 | null | |
"""
=================
Custom projection
=================
Showcase Hammer projection by alleviating many features of Matplotlib.
"""
import numpy as np
import matplotlib
from matplotlib.axes import Axes
import matplotlib.axis as maxis
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplo... | stable__gallery__misc__custom_projection | 0 | figure_000.png | Custom projection — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/custom_projection.html#sphx-glr-download-gallery-misc-custom-projection-py | https://matplotlib.org/stable/_downloads/2de7d801cc807aadc92f195e3402760b/custom_projection.py | custom_projection.py | misc | ok | 1 | null | |
"""
============
Customize Rc
============
I'm not trying to make a good-looking figure here, but just to show
some examples of customizing `.rcParams` on the fly.
If you like to work interactively, and need to create different sets
of defaults for figures (e.g., one set of defaults for publication, one
set for inter... | stable__gallery__misc__customize_rc | 0 | figure_000.png | Customize Rc — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/customize_rc.html#sphx-glr-download-gallery-misc-customize-rc-py | https://matplotlib.org/stable/_downloads/d10d0de4c4efa82daca1fa3f98c048cd/customize_rc.py | customize_rc.py | misc | ok | 1 | null | |
"""
==========
AGG filter
==========
Most pixel-based backends in Matplotlib use `Anti-Grain Geometry (AGG)`_ for
rendering. You can modify the rendering of Artists by applying a filter via
`.Artist.set_agg_filter`.
.. _Anti-Grain Geometry (AGG): http://agg.sourceforge.net/antigrain.com
"""
import matplotlib.pyplot ... | stable__gallery__misc__demo_agg_filter | 0 | figure_000.png | AGG filter — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/demo_agg_filter.html#sphx-glr-download-gallery-misc-demo-agg-filter-py | https://matplotlib.org/stable/_downloads/5787bdd3c2fb5d84c40860c89508a642/demo_agg_filter.py | demo_agg_filter.py | misc | ok | 1 | null | |
"""
==========
Ribbon box
==========
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cbook
from matplotlib import colors as mcolors
from matplotlib.image import AxesImage
from matplotlib.transforms import Bbox, BboxTransformTo, TransformedBbox
class RibbonBox:
original_image = pl... | stable__gallery__misc__demo_ribbon_box | 0 | figure_000.png | Ribbon box — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/demo_ribbon_box.html#sphx-glr-download-gallery-misc-demo-ribbon-box-py | https://matplotlib.org/stable/_downloads/c7b27332a2e53923edb7ffb5315d4fa3/demo_ribbon_box.py | demo_ribbon_box.py | misc | ok | 1 | null | |
"""
==============================
Add lines directly to a figure
==============================
You can add artists such as a `.Line2D` directly to a figure. This is
typically useful for visual structuring.
.. redirect-from:: /gallery/pyplots/fig_x
"""
import matplotlib.pyplot as plt
import matplotlib.lines as lin... | stable__gallery__misc__fig_x | 0 | figure_000.png | Add lines directly to a figure — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/fig_x.html#sphx-glr-download-gallery-misc-fig-x-py | https://matplotlib.org/stable/_downloads/9081f921ee64a1df1186094d7dd9a8d3/fig_x.py | fig_x.py | misc | ok | 1 | null | |
"""
===========
Fill spiral
===========
"""
import matplotlib.pyplot as plt
import numpy as np
theta = np.arange(0, 8*np.pi, 0.1)
a = 1
b = .2
for dt in np.arange(0, 2*np.pi, np.pi/2.0):
x = a*np.cos(theta + dt)*np.exp(b*theta)
y = a*np.sin(theta + dt)*np.exp(b*theta)
dt = dt + np.pi/4.0
x2 = a*np... | stable__gallery__misc__fill_spiral | 0 | figure_000.png | Fill spiral — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/fill_spiral.html#sphx-glr-download-gallery-misc-fill-spiral-py | https://matplotlib.org/stable/_downloads/61f5d448be497db6a30387b809ee77d1/fill_spiral.py | fill_spiral.py | misc | ok | 1 | null | |
"""
============
Findobj Demo
============
Recursively find all objects that match some criteria
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.text as text
a = np.arange(0, 3, .02)
b = np.arange(0, 3, .02)
c = np.exp(a)
d = c[::-1]
fig, ax = plt.subplots()
plt.plot(a, c, 'k--', a, d, 'k:'... | stable__gallery__misc__findobj_demo | 0 | figure_000.png | Findobj Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/findobj_demo.html#sphx-glr-download-gallery-misc-findobj-demo-py | https://matplotlib.org/stable/_downloads/4095e40bfdaeea40b5ebf921dca65a60/findobj_demo.py | findobj_demo.py | misc | ok | 1 | null | |
"""
========================================================
Building histograms using Rectangles and PolyCollections
========================================================
Using a path patch to draw rectangles.
The technique of using lots of `.Rectangle` instances, or the faster method of
using `.PolyCollection`, ... | stable__gallery__misc__histogram_path | 0 | figure_000.png | Building histograms using Rectangles and PolyCollections — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/histogram_path.html#sphx-glr-download-gallery-misc-histogram-path-py | https://matplotlib.org/stable/_downloads/5397c6ff8f61d4375f2fa83fa0eaf135/histogram_path.py | histogram_path.py | misc | ok | 2 | null | |
"""
==========
Hyperlinks
==========
This example demonstrates how to set a hyperlinks on various kinds of elements.
This currently only works with the SVG backend.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
# %%
fig = plt.figure()
s = plt.scatter([1, 2, 3], [4, 5, 6])
s.s... | stable__gallery__misc__hyperlinks_sgskip | 0 | figure_000.png | Hyperlinks — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/hyperlinks_sgskip.html#sphx-glr-download-gallery-misc-hyperlinks-sgskip-py | https://matplotlib.org/stable/_downloads/00c94fd2ec27d6cef4b040acefbf730d/hyperlinks_sgskip.py | hyperlinks_sgskip.py | misc | ok | 2 | null | |
"""
==========
Hyperlinks
==========
This example demonstrates how to set a hyperlinks on various kinds of elements.
This currently only works with the SVG backend.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
# %%
fig = plt.figure()
s = plt.scatter([1, 2, 3], [4, 5, 6])
s.s... | stable__gallery__misc__hyperlinks_sgskip | 1 | figure_001.png | Hyperlinks — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/hyperlinks_sgskip.html#sphx-glr-download-gallery-misc-hyperlinks-sgskip-py | https://matplotlib.org/stable/_downloads/00c94fd2ec27d6cef4b040acefbf730d/hyperlinks_sgskip.py | hyperlinks_sgskip.py | misc | ok | 2 | null | |
"""
======================
Plotting with keywords
======================
Some data structures, like dict, `structured numpy array
<https://numpy.org/doc/stable/user/basics.rec.html#structured-arrays>`_
or `pandas.DataFrame` provide access to labelled data via string index access
``data[key]``.
For these data types, M... | stable__gallery__misc__keyword_plotting | 0 | figure_000.png | Plotting with keywords — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/keyword_plotting.html#sphx-glr-download-gallery-misc-keyword-plotting-py | https://matplotlib.org/stable/_downloads/0c0bceec5b66dc4841d06be6852509dc/keyword_plotting.py | keyword_plotting.py | misc | ok | 1 | null | |
"""
===============
Matplotlib logo
===============
This example generates the current matplotlib logo.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
import matplotlib.font_manager
from matplotlib.patches import PathPatch, Rectangle
from matplotlib.text import TextPath
import matp... | stable__gallery__misc__logos2 | 0 | figure_000.png | Matplotlib logo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/logos2.html#sphx-glr-download-gallery-misc-logos2-py | https://matplotlib.org/stable/_downloads/0846c3e5d114c457e124451aea9e558a/logos2.py | logos2.py | misc | ok | 3 | null | |
"""
===============
Matplotlib logo
===============
This example generates the current matplotlib logo.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
import matplotlib.font_manager
from matplotlib.patches import PathPatch, Rectangle
from matplotlib.text import TextPath
import matp... | stable__gallery__misc__logos2 | 1 | figure_001.png | Matplotlib logo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/logos2.html#sphx-glr-download-gallery-misc-logos2-py | https://matplotlib.org/stable/_downloads/0846c3e5d114c457e124451aea9e558a/logos2.py | logos2.py | misc | ok | 3 | null | |
"""
===============
Matplotlib logo
===============
This example generates the current matplotlib logo.
"""
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
import matplotlib.font_manager
from matplotlib.patches import PathPatch, Rectangle
from matplotlib.text import TextPath
import matp... | stable__gallery__misc__logos2 | 2 | figure_002.png | Matplotlib logo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/logos2.html#sphx-glr-download-gallery-misc-logos2-py | https://matplotlib.org/stable/_downloads/0846c3e5d114c457e124451aea9e558a/logos2.py | logos2.py | misc | ok | 3 | null | |
"""
===================
Packed-bubble chart
===================
Create a packed-bubble chart to represent scalar data.
The presented algorithm tries to move all bubbles as close to the center of
mass as possible while avoiding some collisions by moving around colliding
objects. In this example we plot the market share... | stable__gallery__misc__packed_bubbles | 0 | figure_000.png | Packed-bubble chart — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/packed_bubbles.html#sphx-glr-download-gallery-misc-packed-bubbles-py | https://matplotlib.org/stable/_downloads/81bc179821dc9808604c256bcb20b3b0/packed_bubbles.py | packed_bubbles.py | misc | ok | 1 | null | |
"""
===============
Patheffect Demo
===============
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import patheffects
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 3))
ax1.imshow([[1, 2], [2, 3]])
txt = ax1.annotate("test", (1., 1.), (0., 0),
arrowprops=dict(arrowst... | stable__gallery__misc__patheffect_demo | 0 | figure_000.png | Patheffect Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/patheffect_demo.html#sphx-glr-download-gallery-misc-patheffect-demo-py | https://matplotlib.org/stable/_downloads/1403c9176f441d71ec67e54e239b695e/patheffect_demo.py | patheffect_demo.py | misc | ok | 1 | null | |
"""
=================================
Rasterization for vector graphics
=================================
Rasterization converts vector graphics into a raster image (pixels). It can
speed up rendering and produce smaller files for large data sets, but comes
at the cost of a fixed resolution.
Whether rasterization sho... | stable__gallery__misc__rasterization_demo | 0 | figure_000.png | Rasterization for vector graphics — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/rasterization_demo.html#sphx-glr-download-gallery-misc-rasterization-demo-py | https://matplotlib.org/stable/_downloads/7aecd0ee1c8d945fad9779db5ebd3185/rasterization_demo.py | rasterization_demo.py | misc | ok | 1 | null | |
"""
======================
Set and get properties
======================
The pyplot interface allows you to use ``setp`` and ``getp`` to
set and get object properties respectively, as well as to do
introspection on the object.
Setting with ``setp``
=====================
To set the linestyle of a line to be dashed, y... | stable__gallery__misc__set_and_get | 0 | figure_000.png | Set and get properties — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/set_and_get.html#sphx-glr-download-gallery-misc-set-and-get-py | https://matplotlib.org/stable/_downloads/1164b1c779f1bc16a7184125264f2b1a/set_and_get.py | set_and_get.py | misc | ok | 1 | null | |
"""
==========================
Apply SVG filter to a line
==========================
Demonstrate SVG filtering effects which might be used with Matplotlib.
Note that the filtering effects are only effective if your SVG renderer
support it.
"""
import io
import xml.etree.ElementTree as ET
import matplotlib.pyplot as... | stable__gallery__misc__svg_filter_line | 0 | figure_000.png | Apply SVG filter to a line — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/svg_filter_line.html#sphx-glr-download-gallery-misc-svg-filter-line-py | https://matplotlib.org/stable/_downloads/9f8aa7731c3c1bf0306b6dce55bacda0/svg_filter_line.py | svg_filter_line.py | misc | ok | 1 | null | |
"""
==============
SVG filter pie
==============
Demonstrate SVG filtering effects which might be used with Matplotlib.
The pie chart drawing code is borrowed from pie_demo.py
Note that the filtering effects are only effective if your SVG renderer
support it.
"""
import io
import xml.etree.ElementTree as ET
import ... | stable__gallery__misc__svg_filter_pie | 0 | figure_000.png | SVG filter pie — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/svg_filter_pie.html#svg-filter-pie | https://matplotlib.org/stable/_downloads/15ebd41aec6ebf084ad5797ba93359e4/svg_filter_pie.py | svg_filter_pie.py | misc | ok | 1 | null | |
"""
==========
Table Demo
==========
Demo of table function to display a table within a plot.
"""
import matplotlib.pyplot as plt
import numpy as np
data = [[ 66386, 174296, 75131, 577908, 32015],
[ 58230, 381139, 78045, 99308, 160454],
[ 89135, 80552, 152558, 497981, 603535],
[ 78415, 8... | stable__gallery__misc__table_demo | 0 | figure_000.png | Table Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/table_demo.html#table-demo | https://matplotlib.org/stable/_downloads/017058e784e2a359b3a7dd004a3e0379/table_demo.py | table_demo.py | misc | ok | 1 | null | |
"""
=======================
TickedStroke patheffect
=======================
Matplotlib's :mod:`.patheffects` can be used to alter the way paths
are drawn at a low enough level that they can affect almost anything.
The :ref:`patheffects guide<patheffects_guide>`
details the use of patheffects.
The `~matplotlib.pathef... | stable__gallery__misc__tickedstroke_demo | 0 | figure_000.png | TickedStroke patheffect — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/tickedstroke_demo.html#tickedstroke-patheffect | https://matplotlib.org/stable/_downloads/ee238568c97acaa88c1fecf30916a9a7/tickedstroke_demo.py | tickedstroke_demo.py | misc | ok | 4 | null | |
"""
======================
transforms.offset_copy
======================
This illustrates the use of `.transforms.offset_copy` to
make a transform that positions a drawing element such as
a text string at a specified offset in screen coordinates
(dots or inches) relative to a location given in any
coordinates.
Every ... | stable__gallery__misc__transoffset | 0 | figure_000.png | transforms.offset_copy — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/transoffset.html#transforms-offset-copy | https://matplotlib.org/stable/_downloads/51f71780b1f0e8c2b3d14e33ae33f05f/transoffset.py | transoffset.py | misc | ok | 1 | null | |
"""
===========
Zorder Demo
===========
The drawing order of artists is determined by their ``zorder`` attribute, which
is a floating point number. Artists with higher ``zorder`` are drawn on top.
You can change the order for individual artists by setting their ``zorder``.
The default value depends on the type of the ... | stable__gallery__misc__zorder_demo | 0 | figure_000.png | Zorder Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/zorder_demo.html#zorder-demo | https://matplotlib.org/stable/_downloads/1f573e76544733470b40b7cc1018cdb9/zorder_demo.py | zorder_demo.py | misc | ok | 2 | null | |
"""
===========
Zorder Demo
===========
The drawing order of artists is determined by their ``zorder`` attribute, which
is a floating point number. Artists with higher ``zorder`` are drawn on top.
You can change the order for individual artists by setting their ``zorder``.
The default value depends on the type of the ... | stable__gallery__misc__zorder_demo | 1 | figure_001.png | Zorder Demo — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/misc/zorder_demo.html#zorder-demo | https://matplotlib.org/stable/_downloads/1f573e76544733470b40b7cc1018cdb9/zorder_demo.py | zorder_demo.py | misc | ok | 2 | null | |
"""
=======================
Plot 2D data on 3D plot
=======================
Demonstrates using ax.plot's *zdir* keyword to plot 2D data on
selective axes of a 3D plot.
"""
import matplotlib.pyplot as plt
import numpy as np
ax = plt.figure().add_subplot(projection='3d')
# Plot a sin curve using the x and y axes.
x =... | stable__gallery__mplot3d__2dcollections3d | 0 | figure_000.png | Plot 2D data on 3D plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/2dcollections3d.html#sphx-glr-download-gallery-mplot3d-2dcollections3d-py | https://matplotlib.org/stable/_downloads/82806b819d5516f91bb92a2c94296201/2dcollections3d.py | 2dcollections3d.py | mplot3d | ok | 1 | null | |
"""
=====================
Demo of 3D bar charts
=====================
A basic demo of how to plot 3D bars with and without shading.
"""
import matplotlib.pyplot as plt
import numpy as np
# set up the figure and Axes
fig = plt.figure(figsize=(8, 3))
ax1 = fig.add_subplot(121, projection='3d')
ax2 = fig.add_subplot(12... | stable__gallery__mplot3d__3d_bars | 0 | figure_000.png | Demo of 3D bar charts — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/3d_bars.html#sphx-glr-download-gallery-mplot3d-3d-bars-py | https://matplotlib.org/stable/_downloads/b2426003d482f6dc8125fd971aafd3d4/3d_bars.py | 3d_bars.py | mplot3d | ok | 1 | null | |
"""
=====================================
Clip the data to the axes view limits
=====================================
Demonstrate clipping of line and marker data to the axes view limits. The
``axlim_clip`` keyword argument can be used in any of the 3D plotting
functions.
"""
import matplotlib.pyplot as plt
import nu... | stable__gallery__mplot3d__axlim_clip | 0 | figure_000.png | Clip the data to the axes view limits — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/axlim_clip.html#sphx-glr-download-gallery-mplot3d-axlim-clip-py | https://matplotlib.org/stable/_downloads/69439e0cb9599c9022501fdf410371ff/axlim_clip.py | axlim_clip.py | mplot3d | ok | 1 | null | |
"""
========================================
Create 2D bar graphs in different planes
========================================
Demonstrates making a 3D plot which has 2D bar graphs projected onto
planes y=0, y=1, etc.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np... | stable__gallery__mplot3d__bars3d | 0 | figure_000.png | Create 2D bar graphs in different planes — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/bars3d.html#sphx-glr-download-gallery-mplot3d-bars3d-py | https://matplotlib.org/stable/_downloads/5b023f7fea1b0a1fc6abfea4090951a1/bars3d.py | bars3d.py | mplot3d | ok | 1 | null | |
"""
===================
3D box surface plot
===================
Given data on a gridded volume ``X``, ``Y``, ``Z``, this example plots the
data values on the volume surfaces.
The strategy is to select the data from each surface and plot
contours separately using `.axes3d.Axes3D.contourf` with appropriate
parameters *... | stable__gallery__mplot3d__box3d | 0 | figure_000.png | 3D box surface plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/box3d.html#sphx-glr-download-gallery-mplot3d-box3d-py | https://matplotlib.org/stable/_downloads/2f55e7d3c6f1f46dcc05e217087e84df/box3d.py | box3d.py | mplot3d | ok | 1 | null | |
"""
=================================
Plot contour (level) curves in 3D
=================================
This is like a contour plot in 2D except that the ``f(x, y)=c`` curve is
plotted on the plane ``z=c``.
"""
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
ax = ... | stable__gallery__mplot3d__contour3d | 0 | figure_000.png | Plot contour (level) curves in 3D — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/contour3d.html#sphx-glr-download-gallery-mplot3d-contour3d-py | https://matplotlib.org/stable/_downloads/6989ade00e7a8f65a6687d825416ba7c/contour3d.py | contour3d.py | mplot3d | ok | 1 | null | |
"""
===========================================================
Plot contour (level) curves in 3D using the extend3d option
===========================================================
This modification of the :doc:`contour3d` example uses ``extend3d=True`` to
extend the curves vertically into 'ribbons'.
"""
import ma... | stable__gallery__mplot3d__contour3d_2 | 0 | figure_000.png | Plot contour (level) curves in 3D using the extend3d option — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/contour3d_2.html#sphx-glr-download-gallery-mplot3d-contour3d-2-py | https://matplotlib.org/stable/_downloads/1531a5c0cde762fac88bcce62a5bdefc/contour3d_2.py | contour3d_2.py | mplot3d | ok | 1 | null | |
"""
=====================================
Project contour profiles onto a graph
=====================================
Demonstrates displaying a 3D surface while also projecting contour 'profiles'
onto the 'walls' of the graph.
See :doc:`contourf3d_2` for the filled version.
"""
import matplotlib.pyplot as plt
from mp... | stable__gallery__mplot3d__contour3d_3 | 0 | figure_000.png | Project contour profiles onto a graph — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/contour3d_3.html#sphx-glr-download-gallery-mplot3d-contour3d-3-py | https://matplotlib.org/stable/_downloads/b38e7e6affb8627f98fe832e54458e99/contour3d_3.py | contour3d_3.py | mplot3d | ok | 1 | null | |
"""
===============
Filled contours
===============
`.Axes3D.contourf` differs from `.Axes3D.contour` in that it creates filled
contours, i.e. a discrete number of colours are used to shade the domain.
This is like a `.Axes.contourf` plot in 2D except that the shaded region
corresponding to the level c is graphed on ... | stable__gallery__mplot3d__contourf3d | 0 | figure_000.png | Filled contours — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/contourf3d.html#sphx-glr-download-gallery-mplot3d-contourf3d-py | https://matplotlib.org/stable/_downloads/d441affd37b47c7dcc7eb8b36352778e/contourf3d.py | contourf3d.py | mplot3d | ok | 1 | null | |
"""
===================================
Project filled contour onto a graph
===================================
Demonstrates displaying a 3D surface while also projecting filled contour
'profiles' onto the 'walls' of the graph.
See :doc:`contour3d_3` for the unfilled version.
"""
import matplotlib.pyplot as plt
from ... | stable__gallery__mplot3d__contourf3d_2 | 0 | figure_000.png | Project filled contour onto a graph — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/contourf3d_2.html#sphx-glr-download-gallery-mplot3d-contourf3d-2-py | https://matplotlib.org/stable/_downloads/397c15d5008710bca03d5708217557c0/contourf3d_2.py | contourf3d_2.py | mplot3d | ok | 1 | null | |
"""
=======================================
Custom hillshading in a 3D surface plot
=======================================
Demonstrates using custom hillshading in a 3D surface plot.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cbook, cm
from matplotlib.colors import LightSource
# ... | stable__gallery__mplot3d__custom_shaded_3d_surface | 0 | figure_000.png | Custom hillshading in a 3D surface plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/custom_shaded_3d_surface.html#sphx-glr-download-gallery-mplot3d-custom-shaded-3d-surface-py | https://matplotlib.org/stable/_downloads/3b9ac21ecf6a0b30550b0fb236dcec5a/custom_shaded_3d_surface.py | custom_shaded_3d_surface.py | mplot3d | ok | 1 | null | |
"""
============
3D errorbars
============
An example of using errorbars with upper and lower limits in mplot3d.
"""
import matplotlib.pyplot as plt
import numpy as np
ax = plt.figure().add_subplot(projection='3d')
# setting up a parametric curve
t = np.arange(0, 2*np.pi+.1, 0.01)
x, y, z = np.sin(t), np.cos(3*t), ... | stable__gallery__mplot3d__errorbar3d | 0 | figure_000.png | 3D errorbars — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/errorbar3d.html#sphx-glr-download-gallery-mplot3d-errorbar3d-py | https://matplotlib.org/stable/_downloads/7393bf5548239a03c1f437616d7da22e/errorbar3d.py | errorbar3d.py | mplot3d | ok | 1 | null | |
"""
=====================
Fill between 3D lines
=====================
Demonstrate how to fill the space between 3D lines with surfaces. Here we
create a sort of "lampshade" shape.
"""
import matplotlib.pyplot as plt
import numpy as np
N = 50
theta = np.linspace(0, 2*np.pi, N)
x1 = np.cos(theta)
y1 = np.sin(theta)
z... | stable__gallery__mplot3d__fillbetween3d | 0 | figure_000.png | Fill between 3D lines — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/fillbetween3d.html#sphx-glr-download-gallery-mplot3d-fillbetween3d-py | https://matplotlib.org/stable/_downloads/95d823ebdf4a1590b38e6c3ba1874be8/fillbetween3d.py | fillbetween3d.py | mplot3d | ok | 1 | null | |
"""
=========================
Fill under 3D line graphs
=========================
Demonstrate how to create polygons which fill the space under a line
graph. In this example polygons are semi-transparent, creating a sort
of 'jagged stained glass' effect.
"""
import math
import matplotlib.pyplot as plt
import numpy a... | stable__gallery__mplot3d__fillunder3d | 0 | figure_000.png | Fill under 3D line graphs — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/fillunder3d.html#sphx-glr-download-gallery-mplot3d-fillunder3d-py | https://matplotlib.org/stable/_downloads/76b7ceeb0e946ed74946217ca457ef89/fillunder3d.py | fillunder3d.py | mplot3d | ok | 1 | null | |
"""
==============================
Create 3D histogram of 2D data
==============================
Demo of a histogram for 2D data as a bar graph in 3D.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
fig = plt.figure()
ax = fig.add_subplot(pr... | stable__gallery__mplot3d__hist3d | 0 | figure_000.png | Create 3D histogram of 2D data — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/hist3d.html#sphx-glr-download-gallery-mplot3d-hist3d-py | https://matplotlib.org/stable/_downloads/1c178669fa7845fc12cb2b519ae951fd/hist3d.py | hist3d.py | mplot3d | ok | 1 | null | |
"""
===============
2D images in 3D
===============
This example demonstrates how to plot 2D color coded images (similar to
`.Axes.imshow`) as a plane in 3D.
Matplotlib does not have a native function for this. Below we build one by relying
on `.Axes3D.plot_surface`. For simplicity, there are some differences to
`.Ax... | stable__gallery__mplot3d__imshow3d | 0 | figure_000.png | 2D images in 3D — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/imshow3d.html#sphx-glr-download-gallery-mplot3d-imshow3d-py | https://matplotlib.org/stable/_downloads/85c98843408756006b0ab8798a3b9590/imshow3d.py | imshow3d.py | mplot3d | ok | 1 | null | |
"""
===================
Intersecting planes
===================
This examples demonstrates drawing intersecting planes in 3D. It is a generalization
of :doc:`/gallery/mplot3d/imshow3d`.
Drawing intersecting planes in `.mplot3d` is complicated, because `.mplot3d` is not a
real 3D renderer, but only projects the Artist... | stable__gallery__mplot3d__intersecting_planes | 0 | figure_000.png | Intersecting planes — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/intersecting_planes.html#sphx-glr-download-gallery-mplot3d-intersecting-planes-py | https://matplotlib.org/stable/_downloads/68e888ee31fb17abb06115e5c35bf104/intersecting_planes.py | intersecting_planes.py | mplot3d | ok | 1 | null | |
"""
================
Parametric curve
================
This example demonstrates plotting a parametric curve in 3D.
"""
import matplotlib.pyplot as plt
import numpy as np
ax = plt.figure().add_subplot(projection='3d')
# Prepare arrays x, y, z
theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
z = np.linspace(-2, 2, 10... | stable__gallery__mplot3d__lines3d | 0 | figure_000.png | Parametric curve — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/lines3d.html#sphx-glr-download-gallery-mplot3d-lines3d-py | https://matplotlib.org/stable/_downloads/7ae7882b92eea4ad03cff7c603d2a6dd/lines3d.py | lines3d.py | mplot3d | ok | 1 | null | |
"""
================
Lorenz attractor
================
This is an example of plotting Edward Lorenz's 1963 `"Deterministic Nonperiodic
Flow"`_ in a 3-dimensional space using mplot3d.
.. _"Deterministic Nonperiodic Flow":
https://journals.ametsoc.org/view/journals/atsc/20/2/1520-0469_1963_020_0130_dnf_2_0_co_2.xml
... | stable__gallery__mplot3d__lorenz_attractor | 0 | figure_000.png | Lorenz attractor — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/lorenz_attractor.html#sphx-glr-download-gallery-mplot3d-lorenz-attractor-py | https://matplotlib.org/stable/_downloads/7bcb50501dff2222c41e6dd71664c10f/lorenz_attractor.py | lorenz_attractor.py | mplot3d | ok | 1 | null | |
"""
=============================
2D and 3D Axes in same figure
=============================
This example shows a how to plot a 2D and a 3D plot on the same figure.
"""
import matplotlib.pyplot as plt
import numpy as np
def f(t):
return np.cos(2*np.pi*t) * np.exp(-t)
# Set up a figure twice as tall as it is ... | stable__gallery__mplot3d__mixed_subplots | 0 | figure_000.png | 2D and 3D Axes in same figure — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/mixed_subplots.html#sphx-glr-download-gallery-mplot3d-mixed-subplots-py | https://matplotlib.org/stable/_downloads/d97169a8850133651928362d22fa2ffb/mixed_subplots.py | mixed_subplots.py | mplot3d | ok | 1 | null | |
"""
=========================
Automatic text offsetting
=========================
This example demonstrates mplot3d's offset text display.
As one rotates the 3D figure, the offsets should remain oriented the
same way as the axis label, and should also be located "away"
from the center of the plot.
This demo triggers ... | stable__gallery__mplot3d__offset | 0 | figure_000.png | Automatic text offsetting — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/offset.html#sphx-glr-download-gallery-mplot3d-offset-py | https://matplotlib.org/stable/_downloads/83a4da0793b08ae8f45786e3c9b4e373/offset.py | offset.py | mplot3d | ok | 1 | null | |
"""
============================
Draw flat objects in 3D plot
============================
Demonstrate using `.pathpatch_2d_to_3d` to 'draw' shapes and text on a 3D plot.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Circle, PathPatch
from matplotlib.text import TextPath
from ... | stable__gallery__mplot3d__pathpatch3d | 0 | figure_000.png | Draw flat objects in 3D plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/pathpatch3d.html#sphx-glr-download-gallery-mplot3d-pathpatch3d-py | https://matplotlib.org/stable/_downloads/ab0fba45e231f940e29a0a3aacac8776/pathpatch3d.py | pathpatch3d.py | mplot3d | ok | 1 | null | |
"""
====================
Generate 3D polygons
====================
Demonstrate how to create polygons in 3D. Here we stack 3 hexagons.
"""
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
# Coordinates of a hexagon
angles = np.linspace(0, 2 * np.pi, 6, endpo... | stable__gallery__mplot3d__polys3d | 0 | figure_000.png | Generate 3D polygons — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/polys3d.html#sphx-glr-download-gallery-mplot3d-polys3d-py | https://matplotlib.org/stable/_downloads/54fadf20e54a727a7a5d9dd83e7a9e3b/polys3d.py | polys3d.py | mplot3d | ok | 1 | null | |
"""
========================
3D plot projection types
========================
Demonstrates the different camera projections for 3D plots, and the effects of
changing the focal length for a perspective projection. Note that Matplotlib
corrects for the 'zoom' effect of changing the focal length.
The default focal leng... | stable__gallery__mplot3d__projections | 0 | figure_000.png | 3D plot projection types — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/projections.html#sphx-glr-download-gallery-mplot3d-projections-py | https://matplotlib.org/stable/_downloads/9b22f16328066c6a0d023743cb5c6241/projections.py | projections.py | mplot3d | ok | 1 | null | |
"""
==============
3D quiver plot
==============
Demonstrates plotting directional arrows at points on a 3D meshgrid.
"""
import matplotlib.pyplot as plt
import numpy as np
ax = plt.figure().add_subplot(projection='3d')
# Make the grid
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
np.arange(-... | stable__gallery__mplot3d__quiver3d | 0 | figure_000.png | 3D quiver plot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/quiver3d.html#sphx-glr-download-gallery-mplot3d-quiver3d-py | https://matplotlib.org/stable/_downloads/19a0072d80eefa5dc179a38243c1da91/quiver3d.py | quiver3d.py | mplot3d | ok | 1 | null | |
"""
==============
3D scatterplot
==============
Demonstration of a basic scatterplot in 3D.
"""
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
def randrange(n, vmin, vmax):
"""
Helper function to make an array of random numbers having ... | stable__gallery__mplot3d__scatter3d | 0 | figure_000.png | 3D scatterplot — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/scatter3d.html#sphx-glr-download-gallery-mplot3d-scatter3d-py | https://matplotlib.org/stable/_downloads/faa507e7c87c72109d38e6eaffdc42e0/scatter3d.py | scatter3d.py | mplot3d | ok | 1 | null | |
"""
=======
3D stem
=======
Demonstration of a stem plot in 3D, which plots vertical lines from a baseline
to the *z*-coordinate and places a marker at the tip.
"""
import matplotlib.pyplot as plt
import numpy as np
theta = np.linspace(0, 2*np.pi)
x = np.cos(theta - np.pi/2)
y = np.sin(theta - np.pi/2)
z = theta
fi... | stable__gallery__mplot3d__stem3d_demo | 0 | figure_000.png | 3D stem — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/stem3d_demo.html#sphx-glr-download-gallery-mplot3d-stem3d-demo-py | https://matplotlib.org/stable/_downloads/c0fc774cc7f31ac97da140bcecf8167e/stem3d_demo.py | stem3d_demo.py | mplot3d | ok | 3 | null | |
"""
====================
3D plots as subplots
====================
Demonstrate including 3D plots as subplots.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
from mpl_toolkits.mplot3d.axes3d import get_test_data
# set up a figure twice as wide as it is tall
fig = plt.figure(figsize... | stable__gallery__mplot3d__subplot3d | 0 | figure_000.png | 3D plots as subplots — Matplotlib 3.10.8 documentation | https://matplotlib.org/stable/gallery/mplot3d/subplot3d.html#sphx-glr-download-gallery-mplot3d-subplot3d-py | https://matplotlib.org/stable/_downloads/c4f54a042d9a81d3afae26490415434f/subplot3d.py | subplot3d.py | mplot3d | ok | 1 | null |
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