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Articles by Rishikesh Kumar Rishi
Page 12 of 102
How to make a quiver plot in polar coordinates using Matplotlib?
To make a quiver plot in polar coordinates using Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create radii, thetas, theta and r data points using numpy.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make poly collections of arrows.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True radii = np.linspace(0, 1, 5) thetas = np.linspace(0, 2 * np.pi, 20) theta, r = ...
Read MoreHow to decrease the hatch density in Matplotlib?
To decrease the hatch density in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a customized horizontal hatch class to override the density.Append the horizontal hatch class.Create a new figure or activate an existing figure.Add an 'ax1' to the figure as part of a subplot arrangement.Make lists of data points.Make a bar plot with x and ydata points, with hatch='o', color='green' and edgecolor='red'.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, hatch plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True class MyHorizontalHatch(hatch.HorizontalHatch): def ...
Read MoreHow to give Matplolib imshow plot colorbars a label?
To give matplotlib imshow() plot colorbars a label, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create 5×5 data points using Numpy.Use imshow() method to display the data as an image, i.e., on a 2D regular raster.Create a colorbar for a ScalarMappable instance, im.Set colorbar label using set_label() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(5, 5) im = plt.imshow(data, cmap="copper") cbar = plt.colorbar(im) cbar.set_label("Colorbar") plt.show()Output
Read MoreHow to set a title above each marker which represents a same label in Matplotlib?
To set a title above each marker which represents the same label in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x data points using Numpy.Create four curves, c1, c2, c3 and c4 using plot() method.Place a legend on the figure, such that the same label marker would come together.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, legend_handler plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-10, 10, 100) c1, = plt.plot(x, np.sin(x), ls='dashed', label='y=sin(x)') c2, ...
Read MoreHow to change the color and add grid lines to a Python Matplotlib surface plot?
To change the color and add grid lines to a Python surface plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x, y and h data points using numpy.Create a new figure or activate an existing figure.Get 3D axes object, with figure (from Step 3).Create a surface plot, with orange color, edgecolors and linewidth.Exampleimport numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(-5, 5, 0.25) y = np.arange(-5, 5, 0.25) x, y = np.meshgrid(x, ...
Read MoreHow to find the matplotlib style name?
To find the matplotlib style name, we can take the following steps −import matplotlib.pyplot as pltprint(plt.style.library)Exampleimport matplotlib.pyplot as plt print(plt.style.library)Output{'bmh': RcParams({'axes.edgecolor': '#bcbcbc', 'axes.facecolor': '#eeeeee', 'axes.grid': True, 'axes.labelsize': 'large', 'axes.prop_cycle': cycler('color', ['#348ABD', '#A60628', '#7A68A6', '#467821', '#D55E00', '#CC79A7', '#56B4E9', '#009E73', '#F0E442', '#0072B2']), 'axes.titlesize': 'x-large', 'grid.color': '#b2b2b2', 'grid.linestyle': '--', 'grid.linewidth': 0.5, 'legend.fancybox': True, 'lines.linewidth': 2.0, 'mathtext.fontset': 'cm', 'patch.antialiased': True, 'patch.edgecolor': '#eeeeee', 'patch.facecolor': 'blue', 'patch.linewidth': 0.5, 'text.hinting_factor': 8, 'xtick.direction': 'in', 'ytick.direction': 'in'}), 'classic': RcParams({'_internal.classic_mode': True, 'agg.path.chunksize': 0, ...
Read MoreHow to get an interactive plot of a pyplot when using PyCharm?
To get an interactive plot of a pyplot when using PyCharm, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Set the background style.Plot the data on the axes.To display the figure, use show() method.Exampleimport matplotlib as mpl import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True mpl.use('Qt5Agg') plt.plot(range(10)) plt.show()Output
Read MoreHow to increase the spacing between subplots in Matplotlib with subplot2grid?
To increase the spacing between subplots with subplot2grid, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Add a grid layout to place subplots within a figure.Update the subplot parameters of the grid.Add a subplot to the current figure.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True ax = plt.GridSpec(2, 2) ax.update(wspace=0.5, hspace=0.5) ax1 = plt.subplot(ax[0, :]) ax2 = plt.subplot(ax[1, 0]) ax3 = plt.subplot(ax[1, 1]) plt.show()Output
Read MoreHow to get multiple overlapping plots with independent scaling in Matplotlib?
To get multiple overlapping plots with independent scaling in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot a list of data points using plot() method on a seperate Y-axis and overlapping X-axis.Create a twin Axes sharing the X-axis.Plot a list of data points using plot() method on a seperate Y-axis and overlapping X-axis.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax1 = plt.subplots() ax1.plot([1, 2, 3, 4, 5], color='red') ...
Read MoreHow to display a sequence of images using Matplotlib?
To display a sequence of images using Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of images that have to be drawn.Turn off the axes.Iterate the images and redraw over the axes.Take a pause after each draw.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True images = ['opera.jpg', 'mountain.jpg', '9.jpg'] plt.axis('off') img = None for f in images: im = plt.imread(f) if img is None: img = plt.imshow(im) plt.pause(0.5) else: ...
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