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Articles by Rishikesh Kumar Rishi
Page 72 of 102
How to rotate Matplotlib annotation to match a line?
To rotate matplotlib annotation to match a line, we can take the following steps−Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.Initialize the variables, m (slope) and c (intercept).Create x and y data points using numpy.Calculate theta to make text rotation.Plot the line using plot() method with x and y.Place text on the line using text() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax ...
Read MoreHow do I close all the open pyplot windows (Matplotlib)?
plt.figure().close(): Close a figure window.close() by itself closes the current figureclose(h), where h is a Figure instance, closes that figureclose(num) closes the figure with number=numclose(name), where name is a string, closes the figure with that labelclose('all') closes all the figure windowsExamplefrom matplotlib import pyplot as plt fig = plt.figure() ax = fig.add_subplot() plt.show() plt.close()OutputNow, swap the statements "plt.show()" and "plt.close()" in the code. You wouldn't get to see any plot as the output because the plot would already have been closed.
Read MorePlotting a horizontal line on multiple subplots in Python using pyplot
To plot a horizontal line on multiple subplots in Python, we can use subplots to get multiple axes and axhline() method to draw a horizontal line.StepsCreate a figure and a set of subplots. Here, we will create 3 subplots.Use axhline() method to draw horizontal lines on each axis.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt fig, (ax1, ax2, ax3) = plt.subplots(3) plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ax1.axhline(y=0.5, xmin=0, xmax=3, c="black", linewidth=2, zorder=0) ax2.axhline(y=0.5, xmin=0, xmax=3, c="red", linewidth=3, zorder=0) ax3.axhline(y=0.5, xmin=0, xmax=3, c="yellow", linewidth=4, zorder=0) plt.show()Output
Read MoreOverlay an image segmentation with Numpy and Matplotlib
To overlay an image segmentation with numpy, we can take the following Steps −Make a masked array of 10×10 dimension.Update the masked array with 1 for some region.Make image data using numpy.Mask an array where a condition is met, to get the masked data.Create a new figure or activate an existing figure using figure() mrthod.Use imshow() method to display data as an image, i.e., on a 2D regular raster.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True mask = np.zeros((10, 10)) mask[3:-3, 3:-3] = 1 im ...
Read MoreHow to limit the number of groups shown in a Seaborn countplot using Matplotlib?
To limit the number of groups shown in a Seaborn countplot, we can use a variable group_count, used in countplot() method arguments.StepsCreate a figure and two sets of subplots.Create a data frame using Pandas, with two keys.Initalize a variable group_count to limit the group count in countplot() method.Use countplot() method to show the counts of observations in each categorical bin using bars.Adjust the padding between and around the subplots.Exampleimport pandas as pd import numpy as np import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True f, axes = plt.subplots(1, 2) df = ...
Read MorePlotting a probability density function by sample with Matplotlib
To plot a probability density function by sample, we can use numpy for x and y data points.StepsCreate x and p data points using numpy.Plot x and p data points using plot() method.Scale X-axis in a range.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(-100, 100) p = np.exp(-x ** 2) plt.plot(x, p) plt.xlim(-20, 20) plt.show()Output
Read MoreHow to plot a 2D matrix in Python with colorbar Matplotlib?
To plot a 2D matrix in Python with colorbar, we can use numpy to create a 2D array matrix and use that matrix in the imshow() method.StepsCreate data2D using numpy.Use imshow() method to display data as an image, i.e., on a 2D regular raster.Create a colorbar for a ScalarMappable instance *mappable* using colorbar() method and imshow() scalar mappable image.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data2D = np.random.random((50, 50)) im = plt.imshow(data2D, cmap="copper_r") plt.colorbar(im) plt.show()Output
Read MoreRotating axis text for each subplot in Matplotlib
To rotate axis text for each subplot, we can use text with rotation in the argument.StepsCreate a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.Adjust the subplot layout parameters using subplots_adjust() method.Add a centered title to the figure using suptitle() method.Set the title of the axis.Set the x and y label of the plot.Create the axis with some co-ordinate points.Add text to the figure with some arguments like fontsize, fontweight and add rotation.Plot a single point and annotate that point with some text and arrowhead.To display the ...
Read MoreLayering a contourf plot and surface_plot in Matplotlib
To layer a contourf plot and surface_plot in matplotlib, we can take the following Steps −Initialize the variables, delta, xrange, yrange, x and y using numpy.Create a new figure or activate an existing figure using figure() method.Get the current axis where projection='3d'.Create a 3d countour plot with x and y data points.Plot the surface with x and y data points.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True delta = 0.025 xrange = np.arange(-5.0, 20.0, delta) yrange = np.arange(-5.0, 20.0, delta) x, y = np.meshgrid(xrange, yrange) ...
Read MorePlotting points on the surface of a sphere in Python's Matplotlib
To plot points on the surface of a sphere in Python, we can use plot_surface() method.StepsCreate a new figure or activate an existing figure using figure() method.Add a set of subplots using add_subplot() method with 3d projection.Initialize a variable, r.Get the theta value for spherical points and x, y, and z data points using numpy.Plot the surface using plot_surface() method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(projection='3d') r = 0.05 u, v = np.mgrid[0:2 * np.pi:30j, 0:np.pi:20j] x = np.cos(u) * ...
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