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dstansbydstansby
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Apply isort to tutorials
1 parent 9771b71 commit a8d1469

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‎.pre-commit-config.yaml

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@@ -41,3 +41,10 @@ repos:
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"--skip",
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"doc/users/project/credits.rst"
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]
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- repo: https://github.com/pycqa/isort
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rev: 5.11.2
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hooks:
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- id: isort
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name: isort (python)
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args: ['--force-sort-within-sections', 'true']
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files: ^tutorials/

‎tutorials/advanced/blitting.py

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"""
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.pyplot as plt
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x = np.linspace(0, 2 * np.pi, 100)
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fig, ax = plt.subplots()

‎tutorials/advanced/path_tutorial.py

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could use this code:
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"""
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import matplotlib.pyplot as plt
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from matplotlib.path import Path
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import matplotlib.patches as patches
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from matplotlib.path import Path
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import matplotlib.pyplot as plt
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verts = [
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(0., 0.), # left, bottom
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# ax.add_patch(patch)
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import numpy as np
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import matplotlib.patches as patches
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import matplotlib.path as path
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‎tutorials/advanced/patheffects_guide.py

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without any effect:
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"""
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import matplotlib.pyplot as plt
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import matplotlib.patheffects as path_effects
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import matplotlib.pyplot as plt
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fig = plt.figure(figsize=(5, 1.5))
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text = fig.text(0.5, 0.5, 'Hello path effects world!\nThis is the normal '

‎tutorials/advanced/transforms_tutorial.py

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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.patches as mpatches
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import matplotlib.pyplot as plt
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x = np.arange(0, 10, 0.005)
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y = np.exp(-x/2.) * np.sin(2*np.pi*x)

‎tutorials/colors/colorbar_only.py

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For more information see the :mod:`~matplotlib.colorbar` API.
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"""
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots(figsize=(6, 1))
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fig.subplots_adjust(bottom=0.5)

‎tutorials/colors/colormap-manipulation.py

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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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from matplotlib.colors import ListedColormap, LinearSegmentedColormap
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from matplotlib.colors import LinearSegmentedColormap, ListedColormap
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import matplotlib.pyplot as plt
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viridis = mpl.colormaps['viridis'].resampled(8)
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‎tutorials/colors/colormapnorms.py

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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.colors as colors
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import matplotlib.cbook as cbook
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from matplotlib import cm
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import matplotlib.cbook as cbook
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import matplotlib.colors as colors
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import matplotlib.pyplot as plt
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N = 100
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X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]

‎tutorials/colors/colormaps.py

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# sphinx_gallery_thumbnail_number = 2
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from colorspacious import cspace_converter
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import numpy as np
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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from colorspacious import cspace_converter
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# %%
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#

‎tutorials/colors/colors.py

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The following plot illustrates the effect of transparency.
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"""
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import matplotlib.pyplot as plt
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from matplotlib.patches import Rectangle
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import numpy as np
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from matplotlib.patches import Rectangle
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots(figsize=(6.5, 1.65), layout='constrained')
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ax.add_patch(Rectangle((-0.2, -0.35), 11.2, 0.7, color='C1', alpha=0.8))
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for i, alpha in enumerate(np.linspace(0, 1, 11)):
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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th = np.linspace(0, 2*np.pi, 128)
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‎tutorials/intermediate/arranging_axes.py

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# we use `~.Axes.annotate`, but other examples could be `~.Axes.plot`,
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# `~.Axes.pcolormesh`, etc.
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.pyplot as plt
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fig, axs = plt.subplots(ncols=2, nrows=2, figsize=(5.5, 3.5),
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layout="constrained")
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# add an artist, in this case a nice label in the middle...

‎tutorials/intermediate/artists.py

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# sphinx_gallery_capture_repr = ('__repr__',)
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import numpy as np
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import matplotlib.pyplot as plt
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fig = plt.figure()

‎tutorials/intermediate/autoscale.py

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# extends the axis limits 5% beyond the data limits (-2π, 2π).
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import numpy as np
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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‎tutorials/intermediate/color_cycle.py

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"""
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from cycler import cycler
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import numpy as np
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import matplotlib.pyplot as plt
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# %%

‎tutorials/intermediate/constrainedlayout_guide.py

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# sphinx_gallery_thumbnail_number = 18
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.colors as mcolors
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import matplotlib.gridspec as gridspec
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import numpy as np
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import matplotlib.pyplot as plt
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plt.rcParams['savefig.facecolor'] = "0.8"
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plt.rcParams['figure.figsize'] = 4.5, 4.

‎tutorials/intermediate/imshow_extent.py

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directly continue with the discussion of the results.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.gridspec import GridSpec
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import matplotlib.pyplot as plt
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def index_to_coordinate(index, extent, origin):

‎tutorials/intermediate/tight_layout_guide.py

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# sphinx_gallery_thumbnail_number = 7
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.pyplot as plt
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plt.rcParams['savefig.facecolor'] = "0.8"
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‎tutorials/introductory/animation_tutorial.py

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how to create such animations and the different options available.
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"""
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import matplotlib.pyplot as plt
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import matplotlib.animation as animation
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import numpy as np
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import matplotlib.animation as animation
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import matplotlib.pyplot as plt
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# %%
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# Animation Classes
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# =================

‎tutorials/introductory/customizing.py

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rcParams can be modified directly, for example:
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"""
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from cycler import cycler
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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from cycler import cycler
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import matplotlib.pyplot as plt
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mpl.rcParams['lines.linewidth'] = 2
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mpl.rcParams['lines.linestyle'] = '--'
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data = np.random.randn(50)

‎tutorials/introductory/images.py

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"""
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import matplotlib.pyplot as plt
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import numpy as np
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from PIL import Image
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import numpy as np
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import matplotlib.pyplot as plt
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# %%
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# .. _importing_data:

‎tutorials/introductory/lifecycle.py

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# sphinx_gallery_thumbnail_number = 10
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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data = {'Barton LLC': 109438.50,
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'Frami, Hills and Schmidt': 103569.59,

‎tutorials/introductory/pyplot.py

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# Generating visualizations with pyplot is very quick:
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import matplotlib.pyplot as plt
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plt.plot([1, 2, 3, 4])
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plt.ylabel('some numbers')
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plt.show()

‎tutorials/introductory/quick_start.py

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import numpy as np
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# sphinx_gallery_thumbnail_number = 3
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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# %%
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#

‎tutorials/text/annotations.py

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# of these arguments are ``(x, y)`` tuples:
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import numpy as np
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots(figsize=(3, 3))
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# artists are interpreted as a pixel coordinate, i.e., the radius of the
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# circles in above example are 10 pixels and 5 pixels, respectively.
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from matplotlib.patches import Circle
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from mpl_toolkits.axes_grid1.anchored_artists import AnchoredDrawingArea
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from matplotlib.patches import Circle
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fig, ax = plt.subplots(figsize=(3, 3))
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ada = AnchoredDrawingArea(40, 20, 0, 0,
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loc='upper right', pad=0., frameon=False)
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# corresponding to 0.1 and 0.4 in data coordinates and will be
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# automatically scaled when the view limits of the axes change.
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from matplotlib.patches import Ellipse
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fig, ax = plt.subplots(figsize=(3, 3))
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box = AnchoredAuxTransformBox(ax.transData, loc='upper left')
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el = Ellipse((0, 0), width=0.1, height=0.4, angle=30) # in data coordinates!

‎tutorials/text/text_intro.py

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# `~matplotlib.axes.Axes.set_xlabel` and `~matplotlib.axes.Axes.set_ylabel`
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# methods.
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.pyplot as plt
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x1 = np.linspace(0.0, 5.0, 100)
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y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
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‎tutorials/text/text_props.py

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upper right.
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"""
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import matplotlib.pyplot as plt
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import matplotlib.patches as patches
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import matplotlib.pyplot as plt
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# build a rectangle in axes coords
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left, width = .25, .5

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