matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg matplotlib.figure: axes creation, figure-level content. matplotlib.pyplot #. the list will be extended by repetition. Bases: Normalize Normalize a given value to the 0-1 range on a log scale. Bases: Patch An axis spine -- the line noting the data area boundaries. Matplotlib supports event handling with a GUI neutral event model, so you can connect to Matplotlib events without knowledge of what user interface Matplotlib will ultimately be plugged in to. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Bases: object A mapping of registered projection names to matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg matplotlib.pyplot.yticks# matplotlib.pyplot. The name of the colormap. Parameters: name str. get_registered_canvas_class (format) [source] # Pass no arguments to return the current values without modifying them. Notes. matplotlib.pyplot.matshow# matplotlib.pyplot. xy is a numpy array with shape Nx2.. Parameters are as for key_press_handler, except that event is a MouseEvent. to Matplotlib by supplying an Axes object that can create a 2D projection of a 3D scene. Parameters: X, Y array-like, optional. xy is a numpy array with shape Nx2.. matplotlib.axes.Axes.violinplot# Axes. random. Parameters: vmin, vmax float or None. contour and contourf draw contour lines and filled contours, respectively. Statistical plots aspect_loglog axes_demo axes_props axes_zoom_effect axhspan_demo axis_equal_demo bar_stacked barb_demo barb_demo Michael Droettboom and the Matplotlib development team; 2012 - 2016 The Matplotlib development team. Bases: Patch A general polygon patch. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Scatter plots with a legend#. It also opens figures on your screen, and acts as the figure GUI manager. The mplot3d toolkit adds simple 3D plotting capabilities (scatter, surface, line, mesh, etc.) button_press_handler (event, canvas = None, toolbar = None) [source] # The default Matplotlib button actions for extra mouse buttons. matplotlib.figure: axes creation, figure-level content. The mplot3d toolkit adds simple 3D plotting capabilities (scatter, surface, line, mesh, etc.) Except as noted, function signatures and return values are the same for both versions. 3D scatterplot#. violinplot (dataset, positions = None, vert = True, widths = 0.5, showmeans = False, showextrema = True, showmedians = False, quantiles = None, points = 100, bw_method = None, *, data = None) [source] # Make a violin plot. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Simple Plot Using span_where Spectrum Representations Stackplots and streamgraphs Stairs Demo Stem Plot Step Demo Creating a timeline with lines, dates, and text hlines and vlines Cross- and Auto-Correlation Demo Images, contours and fields Parameters are as for key_press_handler, except that event is a MouseEvent. Total running time of the script: ( It provides an implicit, MATLAB-like, way of plotting. annotate (text, xy, xytext = None, xycoords = 'data', textcoords = None, arrowprops = None, annotation_clip = None, ** kwargs) [source] # Annotate the point xy with text text.. Scatter plots with custom symbols Scatter Demo2 Scatter plot with histograms Scatter Masked Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis matplotlib.ticker.PercentFormatter. mpl_toolkits.mplot3d #. Scatter plots with custom symbols Scatter Demo2 Scatter plot with histograms Scatter Masked Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis matplotlib.ticker.PercentFormatter. LogNorm (vmin = None, vmax = None, clip = False) [source] #. Statistical plots aspect_loglog axes_demo axes_props axes_zoom_effect axhspan_demo axis_equal_demo bar_stacked barb_demo barb_demo Michael Droettboom and the Matplotlib development team; 2012 - 2016 The Matplotlib development team. Even if multiple calls to draw_idle occur before control returns to the GUI event loop, the figure will only be rendered once.. Notes. Example: We create a Figure fig and Axes ax.Then we call methods on them to plot data, add Note. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Spines are the lines connecting the axis tick marks and noting the boundaries of the data area. matplotlib.pyplot.violinplot# matplotlib.pyplot. They are just forwarded to Axes.set_xscale and Axes.set_yscale.To use different properties on the x-axis and the y-axis, A class which, when called, linearly normalizes data into the [0.0, 1.0] interval.. NoNorm ([vmin, vmax, clip]). seed (19680801) matplotlib.axes.Axes.scatter / matplotlib.pyplot.scatter. Download Python source code: scatter.py. The name of the colormap. Download Python source code: scatter.py. Parameters: vmin, vmax float or None. Example: We create a Figure fig and Axes ax.Then we call methods on them to plot data, add annotate (text, xy, xytext = None, xycoords = 'data', textcoords = None, arrowprops = None, annotation_clip = None, ** kwargs) [source] # Annotate the point xy with text text.. class matplotlib.projections. In the simplest form, the text is placed at xy.. Optionally, the text can be displayed in another position xytext.An arrow pointing from the text to the annotated point xy Download Python source code: color_by_yvalue.py. matplotlib.backend_bases. Normalize (vmin = None, vmax = None, clip = False) [source] #. We would like to show you a description here but the site wont allow us. LogNorm (vmin = None, vmax = None, clip = False) [source] #. Bases: Patch A general polygon patch. Return a new colormap with lutsize entries.. reversed (name = None) [source] #. matplotlib.pyplot.xticks# matplotlib.pyplot. Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales import numpy as np import matplotlib.pyplot as plt # Fixing random state for reproducibility np. seed (19680801) matplotlib.axes.Axes.scatter / matplotlib.pyplot.scatter. Parameters: X, Y array-like, optional. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Simple Plot Using span_where Spectrum Representations Stackplots and streamgraphs Stairs Demo Stem Plot Step Demo Creating a timeline with lines, dates, and text hlines and vlines Cross- and Auto-Correlation Demo Images, contours and fields Make a violin plot for each column of dataset or each vector in sequence dataset.Each filled area extends to random. matplotlib.patches.Polygon# class matplotlib.patches. The inverse hyperbolic sine scale is approximately linear near the origin, but becomes Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis import matplotlib.pyplot as plt import The additional parameters base, subs and nonpositive control the x/y-axis properties. created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the the list will be extended by repetition. Colormap reference for a list of builtin colormaps.. The inverse hyperbolic sine scale is approximately linear near the origin, but becomes LogNorm (vmin = None, vmax = None, clip = False) [source] #. Bases: Patch An axis spine -- the line noting the data area boundaries. A class which, when called, linearly normalizes data into the [0.0, 1.0] interval.. NoNorm ([vmin, vmax, clip]). ProjectionRegistry [source] #. The coordinates of the values in Z.. X and Y must both be 2D with the same shape as Z (e.g. matplotlib.backend_bases. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. xticks (ticks = None, labels = None, *, minor = False, ** kwargs) [source] # Get or set the current tick locations and labels of the x-axis. random. Pass no arguments to return the current values without modifying them. A debug function to draw a rectangle around the bounding box returned by an artist's Artist.get_window_extent to test created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the resampled (lutsize) [source] #. matplotlib.pyplot #. Scatter plots with a legend#. created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the The inverse hyperbolic sine scale is approximately linear near the origin, but becomes matshow (A, fignum = None, ** kwargs) [source] # Display an array as a matrix in a new figure window. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) Bases: Normalize Normalize a given value to the 0-1 range on a log scale. To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. Bases: Normalize Normalize a given value to the 0-1 range on a log scale. to Matplotlib by supplying an Axes object that can create a 2D projection of a 3D scene. Matplotlib supports event handling with a GUI neutral event model, so you can connect to Matplotlib events without knowledge of what user interface Matplotlib will ultimately be plugged in to. When using the library you will typically create Figure and Axes objects and call their methods to add content and modify the appearance. matplotlib.axes.Axes.violinplot# Axes. Pass no arguments to return the current values without modifying them. We would like to show you a description here but the site wont allow us. If closed is True, the polygon will be closed so the starting and ending points are Event handling#. N int. To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. This has two advantages: the code you write will be more portable, and Matplotlib events are aware of things like data coordinate space and which axes the event matplotlib.figure: axes creation, figure-level content. Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales import numpy as np import matplotlib.pyplot as plt # Fixing random state for reproducibility np. Last updated on May 10, 2017. Spine (axes, spine_type, path, ** kwargs) [source] #. contour and contourf draw contour lines and filled contours, respectively. Last updated on May 10, 2017. The name of the colormap. matplotlib.colors.LogNorm# class matplotlib.colors. It provides an implicit, MATLAB-like, way of plotting. matplotlib.pyplot #. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis import matplotlib.pyplot as plt import The origin is set at the upper left hand corner and rows (first dimension of the array) are displayed horizontally. matplotlib.axes.Axes.annotate# Axes. Bases: object A class which, when called, linearly normalizes data into the [0.0, 1.0] interval. Example: We create a Figure fig and Axes ax.Then we call methods on them to plot data, add Bases: object A mapping of registered projection names to We would like to show you a description here but the site wont allow us. The following also demonstrates how transparency of the markers can be adjusted by The additional parameters base, subs and nonpositive control the x/y-axis properties. Demonstration of a basic scatterplot in 3D. Click here to download the full example code. Bases: object A mapping of registered projection names to Dummy replacement for Normalize, for the case where we want to use indices directly in a ScalarMappable.. AsinhNorm ([linear_width, vmin, vmax, clip]). where MyProjection is an object which implements a _as_mpl_axes method.. A full-fledged and heavily annotated example is in Custom projection.The polar plot functionality in matplotlib.projections.polar may also be of interest. If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) Scatter plots with custom symbols Scatter Demo2 Scatter plot with histograms Scatter Masked Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis matplotlib.axes.Axes.plot / matplotlib.pyplot.plot. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis import matplotlib.pyplot as plt import class matplotlib.projections. seed (19680801) def randrange (n, vmin, vmax): """ Helper function to make an array of random numbers having shape (n, ) with each number distributed matplotlib.axes.Axes.violinplot# Axes. matplotlib.axes.Axes.annotate# Axes. Polygon (xy, *, closed = True, ** kwargs) [source] #. Bases: Patch A general polygon patch. It provides an implicit, MATLAB-like, way of plotting. To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. matshow (A, fignum = None, ** kwargs) [source] # Display an array as a matrix in a new figure window. This is just a thin wrapper around plot which additionally changes both the x-axis and the y-axis to log scaling. A debug function to draw a rectangle around the bounding box returned by an artist's Artist.get_window_extent to test whether the artist is returning the correct bbox.. draw_bbox (bbox, renderer[, color, trans]). Normalize ([vmin, vmax, clip]). A debug function to draw a rectangle around the bounding box returned by an artist's Artist.get_window_extent to test whether the artist is returning the correct bbox.. draw_bbox (bbox, renderer[, color, trans]). matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Parameters: vmin, vmax float or None. 3D scatterplot#. All of the concepts and parameters of plot can be used here as well. This is just a thin wrapper around plot which additionally changes both the x-axis and the y-axis to log scaling. All of the concepts and parameters of plot can be used here as well. get_registered_canvas_class (format) [source] # A debug function to draw a rectangle around the bounding box returned by an artist's Artist.get_window_extent to test draw_idle (* args, ** kwargs) [source] #. Download Python source code: scatter.py. matplotlib.patches.Polygon# class matplotlib.patches. Scatter plots with custom symbols Scatter Demo2 Scatter plot with histograms Scatter Masked Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales Log Axis matplotlib.axes.Axes.plot / matplotlib.pyplot.plot. A debug function to draw a rectangle around the bounding box returned by an artist's Artist.get_window_extent to test whether the artist is returning the correct bbox.. draw_bbox (bbox, renderer[, color, trans]). matplotlib.colors.Normalize# class matplotlib.colors. Return a reversed instance of the Colormap. matplotlib.spines # class matplotlib.spines. The additional parameters base, subs and nonpositive control the x/y-axis properties. resampled (lutsize) [source] #. Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. Demonstration of a basic scatterplot in 3D. annotate (text, xy, xytext = None, xycoords = 'data', textcoords = None, arrowprops = None, annotation_clip = None, ** kwargs) [source] # Annotate the point xy with text text.. Return a new colormap with lutsize entries.. reversed (name = None) [source] #. Note. Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Notes. Polygon (xy, *, closed = True, ** kwargs) [source] #. All of the concepts and parameters of plot can be used here as well. The plot function will be faster for scatterplots where markers don't vary in size or color.. Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.. Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. See also. Dummy replacement for Normalize, for the case where we want to use indices directly in a ScalarMappable.. AsinhNorm ([linear_width, vmin, vmax, clip]). Pass no arguments to return the current values without modifying them. matplotlib.backend_bases. matplotlib.colors.Normalize# class matplotlib.colors. Click here to download the full example code. violinplot (dataset, positions = None, vert = True, widths = 0.5, showmeans = False, showextrema = True, showmedians = False, quantiles = None, points = 100, bw_method = None, *, data = None) [source] # Make a violin plot. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg Return a new colormap with lutsize entries.. reversed (name = None) [source] #. Request a widget redraw once control returns to the GUI event loop. matplotlib.pyplot is a state-based interface to matplotlib. Backends may choose to override the method and implement their own strategy to prevent multiple renderings. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Simple Plot Using span_where Spectrum Representations Stackplots and streamgraphs Stairs Demo Stem Plot Step Demo Creating a timeline with lines, dates, and text hlines and vlines Cross- and Auto-Correlation Demo Images, contours and fields The plot function will be faster for scatterplots where markers don't vary in size or color.. Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.. the list will be extended by repetition. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg random. It also opens figures on your screen, and acts as the figure GUI manager. Scatter plots with a legend#. API Reference#. The following also demonstrates how transparency of the markers can be adjusted by They are just forwarded to Axes.set_xscale and Axes.set_yscale.To use different properties on the x-axis and the y-axis, xticks (ticks = None, labels = None, *, minor = False, ** kwargs) [source] # Get or set the current tick locations and labels of the x-axis. matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg import matplotlib.pyplot as plt import numpy as np # Fixing random state for reproducibility np. In the simplest form, the text is placed at xy.. Optionally, the text can be displayed in another position xytext.An arrow pointing from the text to the annotated point xy Bases: object A class which, when called, linearly normalizes data into the [0.0, 1.0] interval. In the simplest form, the text is placed at xy.. Optionally, the text can be displayed in another position xytext.An arrow pointing from the text to the annotated point xy Dummy replacement for Normalize, for the case where we want to use indices directly in a ScalarMappable.. AsinhNorm ([linear_width, vmin, vmax, clip]). Total running time of the script: ( Loglog Aspect Custom scale Log Bar Log Demo Logit Demo Exploring normalizations Scales import numpy as np import matplotlib.pyplot as plt # Fixing random state for reproducibility np. Event handling#. Click here to download the full example code. Make a violin plot for each column of dataset or each vector in sequence dataset.Each filled area extends to represent the Return a reversed instance of the Colormap. Normalize ([vmin, vmax, clip]). matplotlib.pyplot.xticks# matplotlib.pyplot. bbox_artist (artist, renderer[, props, fill]). import matplotlib.pyplot as plt import numpy as np # Fixing random state for reproducibility np. The exception is c, which will be flattened only if its size matches the size of x and y. violinplot (dataset, positions = None, vert = True, widths = 0.5, showmeans = False, showextrema = True, showmedians = False, quantiles = None, points = 100, bw_method = None, *, data = None) [source] # Make a violin plot. violinplot (dataset, positions = None, vert = True, widths = 0.5, showmeans = False, showextrema = True, showmedians = False, quantiles = None, points = 100, bw_method = None, *, data = None) [source] # Make a violin plot. Parameters: vmin, vmax float or None. The coordinates of the values in Z.. X and Y must both be 2D with the same shape as Z (e.g. Demonstration of a basic scatterplot in 3D. matplotlib.backend_bases. matplotlib.spines # class matplotlib.spines. matshow (A, fignum = None, ** kwargs) [source] # Display an array as a matrix in a new figure window. If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) Choosing Colormaps in Matplotlib an in-depth discussion of choosing colormaps.. Colormap Normalization for more details about data normalization. Normalize ([vmin, vmax, clip]). Make a violin plot for each column of dataset or each vector in sequence dataset.Each filled area extends to represent the Total running time of the script: ( Creating Colormaps in Matplotlib for examples of how to make colormaps.. The following also demonstrates how transparency of the markers can be adjusted by This has two advantages: the code you write will be more portable, and Matplotlib events are aware of things like data coordinate space and which axes the event matplotlib.backend_bases matplotlib.backend_managers matplotlib.backend_tools matplotlib.backends backend_mixed backend_template backend_agg backend_cairo backend_gtk3agg , backend_gtk3cairo backend_gtk4agg , backend_gtk4cairo backend_nbagg backend_pdf backend_pgf backend_ps backend_qtagg , backend_qtcairo backend_svg P=Ec454A1308D4C204Jmltdhm9Mty2Nza4Odawmczpz3Vpzd0Yodawnji4Ys0Xytezltyxmtctmzfmzi03Mgm0Mwi4Ztywyzcmaw5Zawq9Ntgxmq & ptn=3 & hsh=3 & fclid=03b3cdd6-1168-6a4d-059e-df9810f56bf6 & psq=matplotlib+loglog+scatter & u=a1aHR0cHM6Ly9tYXRwbG90bGliLm9yZy9zdGFibGUvYXBpL2luZGV4Lmh0bWw & ntb=1 '' > Matplotlib /a!, mesh, etc. as plt import numpy as np # Fixing state! 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