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Articles by Rishikesh Kumar Rishi
Page 17 of 102
Matplotlib – Difference between plt.subplots() and plt.figure()
plt.figure() − Creates a new figure or activates an existing figure.plt.subplots() − Creates a figure and a set of subplots.Let's take an example to understand the difference between plt.subplots() and plt.figure().StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure. Use plt.figure() method.Create a figure and a set of subplots. Use plt.subplots() method.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create a new figure using plt.figure fig1 = plt.figure("Figure 1 ...
Read MoreMatplotlib – How to show the coordinates of a point upon mouse click?
To create a custom mouse cursor in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Bind the function *mouse_event* to the event *button_press_event*.Create x and y data points using numpy.Plot the x and y data points using plot() 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 def mouse_event(event): print('x: {} and y: {}'.format(event.xdata, event.ydata)) fig = plt.figure() cid = fig.canvas.mpl_connect('button_press_event', mouse_event) ...
Read MoreHow to read an input image and print it into an array in matplotlib?
To read an input image and print it into an array in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Read an image from a file into an array. Use plt.imread() method.Print the Numpy array of the image.To turn off the axis, use axis('off') method.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 im = plt.imread("forest.jpg") print("Numpy array of the image is: ", im) im = plt.imshow(im) plt.axis('off') plt.show()OutputIt will produce the following output −On the ...
Read MoreHow to create minor ticks for a polar plot in matplotlib?
To create minor ticks for a polar plot in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create r (radius) and theta data points using numpy.Add a subplot to the current figure.Iterate the points between 0 to 360 with step=10 and plot them to get the ticks.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # radius and theta for the polar plot r = np.arange(0, 5, 0.1) theta = 2 ...
Read MoreHow to plot an animated image matrix in matplotlib?
To plot an animated image matrix in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Make an animation by repeatedly calling a function *update*.Inside the update method, create a 6×6 dimension of matrix and display the data as an image, i.e., on a 2D regular raster.Turn off the axes using set_axis_off().To display the figure, use Show() method.Examplefrom matplotlib.animation import FuncAnimation import matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() def ...
Read MoreHow to put a title for a curved line in Python Matplotlib?
To put a title for a curved line in Python Matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points such that the line would be a curve.Plot the x and y data points.Place a title for the curve plot using plt.title() 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 # Create x and y data points x = np.linspace(-1, 1, 50) y = 2**x + 1 # Plot ...
Read MoreMatplotlib – How to plot the FFT of signal with correct frequencies on the X-axis?
To plot the FFT (Fast Fourier Transform) of a signal with correct frequencies on the X-axis in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize two variables, N and m, to calculate nu.Create the signal (a sine wave) using numpy. Compute the one-dimensional discrete Fourier Transform.Return the Discrete Fourier Transform sample frequencies.Plot the freq and fourier transform 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 = 256 t = np.arange(N) m ...
Read MoreWhen is plt.Show() required to show a plot and when is it not?
plt.Show() would help whenever there is no interactive plot.fig.Show() would help to display all the figures if it is interactive.Let's take an example to observe the difference between plt.Show() and fig.Show().StepsOpen iPython shell.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Plot a line using plot() method.Display the figure using Show() method.To display the figure, use Show() method with block=False.Exampleimport numpy as np from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create a new figure fig ...
Read MoreSaving a 3D-plot in a PDF 3D with Python
To save a 3D-plot in a PDF with Python, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Create u, v, x, y and z data points using numpy.Plot a 3D wireframe.Set the title of the plot.Save the current figure using savefig() 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(111, projection='3d') u, v = np.mgrid[0:2 * np.pi:30j, ...
Read MoreHow to control the border of a bar patch in matplotlib?
To control the border of a bar patch in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a list of heights and a tuple for labels.Use the bar() method with edgecolor in the argument to control the color of the bar patch. Here we have used edgecolor='green'.Set the ticks and labels of the X-axis.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 height = [3, 12, 5, 18, 45] labels = ('P1', 'P2', 'P3', 'P4', ...
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