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Articles by Rishikesh Kumar Rishi
Page 43 of 102
How to plot a phase spectrum in Matplotlib in Python?
To plot a phase spectrum, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get random seed value.Initialize dt for sampling interval and find sampling frequency.Create random data points for t.To generate noise, get nse, r, cnse and s using numpy.Create a figure and a set of subplots using subplots() method.Set the title of the plot.Plot the phase spectrum.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True np.random.seed(0) dt = 0.01 # sampling interval Fs = 1 ...
Read MoreHow can I generate more colors on a pie chart in Matplotlib?
To generate more colors on a pie chart in Matplotlib, we can generate n number of colors and dataStepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable, n, for number of data samples.Create random data points using numpy.Create a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Create a pie chart using pie() method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import random import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True n = 40 color = ["#" + ...
Read MoreVertical Histogram in Python and Matplotlib
To plot vertical histogram in Python and Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a list of data points.Plot a histogram with vertical orientation.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 x = [1, 2, 3, 1, 2, 3, 4, 1, 3, 4, 5] plt.hist(x, orientation="vertical") plt.show()Output
Read MoreHow can I dynamically update my Matplotlib figure as the data file changes?
To update a Matplotlib figure as the data file changes, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize variables m and n, to get a set of subplots.Create a list of colors, to plot color dynamically.Plot dynamic data points using plot() method with random data points.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import random plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True m = 2 n = 4 fix, axes = plt.subplots(nrows=m, ncols=n) hexadecimal_alphabets = '0123456789ABCDEF' color = ["#" ...
Read MoreHow to save Matplotlib 3d rotating plots?
To save Matplotlib 3d roatating plots, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Return a tuple X, Y, Z with a test data set.Plot a 3D wireframe.Rotate the axis with an angle.Redraw the current figure.Run the GUI event loop for some seconds.To display the figure, use show() method.Examplefrom mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111, ...
Read MoreHow can I draw inline line labels in Matplotlib?
To draw inline labels in Matplotlib, we can use labelLines() method. −StepsSet the figure size and adjust the padding between and around the subplots.Create random data points x using numpy and a list of data points, A.Iterate the list of A, and plot X and a (iterated item) with label.Label all the lines with their respective legends, for lines drawn.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt from labellines import labelLines plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True X = np.linspace(0, 1, 500) A = [1, 2, 5, 10, 20] ...
Read MoreHow to plot magnitude spectrum in Matplotlib in Python?
To plot magintude spectrum, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get random seed value.Initialize dt for sampling interval and find the sampling frequency.Create random data points for t.To generate noise, get nse, r, cnse and s using numpyCreate a figure and a set of subplots, using subplots() method.Set the title of the plot.Plot the magnitude spectrum.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True np.random.seed(0) dt = 0.01 # sampling interval Fs = ...
Read MoreHow to plot signal in Matplotlib in Python?
To get the signal plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get random seed value.Initialize dt for sampling interval and find the sampling frequency.Create random data points for t.To generate noise, get nse, r, cnse and s using numpy.Create a figure and a set of subplots using subplots() method.Set the title of the plot.Plot t and s data points.Set x and y labels.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True np.random.seed(0) dt ...
Read MoreTweaking axis labels and names orientation for 3D plots in Matplotlib
To tweak axis labels and names orientation for 3D plots in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure with facecolor=white.Get the current figure with 3d projection.Set X, Y and Z Axis labels with linespacing.Plot the data points using plot() method.Set the axis distance.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 figure = plt.figure(facecolor='w') ax = figure.gca(projection='3d') xLabel = ax.set_xlabel('X-axis', linespacing=3.2) yLabel = ax.set_ylabel('Y-axis', linespacing=3.1) zLabel = ax.set_zlabel('Z-Axis', ...
Read MorePlotting scatter points with clover symbols in Matplotlib
To plot scatter points with clover symbols in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x, y and z data points using numpy.Plot x, y and s using scatter() method.Set X and Y axes labels.Place a legend at the upper left of the plot.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(0.0, 50.0, 2.0) y = x ** 1.3 + np.random.rand(*x.shape) * 30.0 s = np.random.rand(*x.shape) * 800 + 500 ...
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