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Articles by Rishikesh Kumar Rishi
Page 70 of 102
How to make longer subplot tick marks in Matplotlib?
To make longer subplot tick marks in matplotlib, we can use tick_params() method for minor and major ticks length and width.StepsAdd a subplot to the current figure using subplot() method.Plot a range(2) values for x and y data points.Turn the minor ticks of the colorbar ON without extruding into the "extend regions".Use tick_params for changing the appearance of ticks and tick labels.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ax1 = plt.subplot() ax1.plot(range(2), range(2), linewidth=2) ax1.minorticks_on() ax1.tick_params('both', length=20, width=2, which='major') ax1.tick_params('both', length=10, width=1, which='minor') plt.show()Output
Read MoreBold font weight for LaTeX axes label in Matplotlib
To make bold font weight LaTeX axes label in matplotlib, we can take the following steps−Create x and y data points using numpy.Using subplot() method, add a subplot to the current figure.Set x and y ticks with data points x and y using set_xticks and set_yticks methods, respectively.Plot x and y using plot() method with color=red.To set bold font weight, we can use LaTeX representation.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, font_manager as fm plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True plt.rcParams["font.fantasy"] = "Comic Sans MS" x = np.array([1, 2, 3, ...
Read MoreHow to obtain the same font in Matplotlib output as in LaTex output?
To make bold font weight LaTeX axes label in matplotlib, we can take the following steps−Create data points for x.Create data points for y, i.e., y=sin(x).Plot the curve x and y with LaTex representation.To activate the label, use legend() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, font_manager as fm fprop = fm.FontProperties(fname='/usr/share/fonts/truetype/malayalam/Karumbi.ttf') plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 10, 1000) y = np.sin(x) plt.plot(x, y, label=r'$\sin (x)$', c="red", lw=2) plt.title(label=r'$\sin (x)$', fontproperties=fprop) plt.show()Output
Read MoreIs it possible to plot implicit equations using Matplotlib?
Matplotlib does not support the functionality to plot implicit equations, however, you can try a code like the one we have shown here.StepsCreate xrange and yrange data points using numpy.Return coordinate matrices from coordinate vectors using meshgrid() method.Create an equation from x and y.Create a 3D contour using contour() method with x, y and the equation.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 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) equation = np.sin(x) - ...
Read MoreSetting the aspect ratio of a 3D plot in Matplotlib
To set the aspect ratio of a 3D plot in matplotlib, we can take the following steps−Using figure() method, create a new figure or activate an existing figure.Get the current axes, creating one if necessary, with projection='3d'.Create data points, R, Y and z, using numpy.Create a surface plot using R, Y and z.Set the aspect ratio using set_aspect('auto').Save the figure using savefig() method.Examplefrom matplotlib import pyplot as plt from matplotlib import cm import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.gca(projection='3d') R, Y = np.meshgrid(np.arange(0, 100, 1), np.arange(0, 60, 1)) z = ...
Read MoreHow I can get a Cartesian coordinate system in Matplotlib?
To plot a Cartesian coordinate system in matplotlib, we can take the following Steps −Initialize a variable (N) with a value.Create random data points for x and y.Plot the points using scatter method with x and y data points.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True N = 50 x = np.random.rand(N) y = np.random.rand(N) plt.scatter(x, y) plt.show()Output
Read MoreGetting empty tick labels before showing a plot in Matplotlib
To get empty tick labels before showing a plot in matplotlib, we can take the following Steps −Create a list of data points.Add a subplot to the current figure using subplot() method.Set ticks and ticklabels using set_xticks() method and set_xticklabels() method.To get the empty tick labels, use get_xticklabels(which='minor').To display the method, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = [1, 2, 3, 4] ax1 = plt.subplot() ax1.set_xticks(x) ax1.set_xticklabels(["one", "two", "three", "four"]) print("Empty tick labels: ", ax1.get_xticklabels(which='minor')) plt.show()Output
Read MoreGaussian filtering an image with NaN in Python Matplotlib
Gaussian filtering an image with NaN values makes all the values of a matrix NaN, which produces an NaN valued matrix.StepsCreate a figure and a set of subplots.Create a matrix with NaN value in that matrix.Display the data as an image, i.e., on a 2D regular raster, data.Apply Gaussian filter on the data.Display the data as an image, i.e., on a 2D regular raster, gaussian_filter_data.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt from scipy.ndimage import gaussian_filter plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, axes = plt.subplots(2) data = np.array([[1., 1.2, 0.89, ...
Read MoreHow to change the figsize for matshow() in Jupyter notebook using Matplotlib?
To change the figsize for mathshow, we can use figsize in figure method argument and use fignum in matshow() method.StepsCreate a new figure or activate an existing figure using figure() method.Create a dataframe using Pandas.Use matshow() method to display an array as a matrix in a new figure window.The argument fignum can take the values None, int, or FalseIf *None*, create a new figure window with automatic numbering.If a nonzero integer, draw into the figure with the given number. Create one, if it does not exist.If 0, use the current axes (or create one if it does not exist).To display ...
Read MoreHow do I change the font size of ticks of matplotlib.pyplot.colorbar.ColorbarBase?
To change the font size of ticks of a colorbar, we can take the following steps−Create a random data set of 5☓5 dimension.Display the data as an image, i.e., on a 2D regular raster.Create a colorbar with a scalar mappable object image.Initialize a variable for fontsize to change the tick size of the colorbar.Use axis tick_params() method to set the tick size of the colorbar.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 data = np.random.rand(5, 5) im = plt.imshow(data, interpolation="nearest", cmap="copper") cbar = plt.colorbar(im) tick_font_size ...
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