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To set a Matplotlib rectangle edge to outside of specified width, 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 ax to the figure as part of a subplot arrangement.Initialize a variable line_width to set the rectangle outside of specified width. Use the variables xy, w and h for rectangle's center, width and height.Get a rectangle instance, with xy anchor points and its height and width.Get the offset transformbox instance.Add an artist patch, r (Step 5).Get the container for an OffsetBox ... Read More
To add a cursor to a curve in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create t and s data points using numpy.Create a figure and a set of subplots.Get the cursor class instance, to update the cursor points on the plot.In mouse_event, get the x and y data of the current position of the mouse.Get the x and y data points' indices.Set the x and y positions.Set the text position and redraw agg buffer and mouse event.Plot t and s data points using plot() method.Set some axis ... Read More
To create animated GIF files out of D3.js animation, 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 to the current figure and make it the current axes.Plot a line with empty lists.To initialize the line, pass empty lists.To animate the sine curve, update the sine curve values and return the line instance.Get a movie writer instance using PillowWriter() class.Save the .gif file using PillowWriter.Exampleimport numpy as np from matplotlib import pyplot as plt from matplotlib import animation plt.rcParams["figure.figsize"] ... Read More
To convert matplotlib figure to PIL image object, 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.Plot a list using plot() method.Initialize the in-memory buffer.Save the buffered image.Use PIL image to get the image object.Show the current image.Close the in-memory I/O buffer.Exampleimport io from PIL import Image import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True plt.figure() plt.plot([1, 2]) img_buf = io.BytesIO() plt.savefig(img_buf, format='png') im = Image.open(img_buf) im.show(title="My Image") img_buf.close()OutputRead More
To draw node colormap in matplotlib/netwokx, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Return the cycle graph $C_n$ of cyclically connected nodes.Position the nodes on a circle.Draw the graph G with Matplotlib.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import networkx as nx plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True G = nx.cycle_graph(24) pos = nx.circular_layout(G) nx.draw(G, pos, node_color=range(24), node_size=800, cmap='copper') plt.show()Output
To set two matplotlib imshow() plots to have the same colormap scale, we can take the followingStepsSet the figure size and adjust the padding between and around the subplots.Create d1 and d2 matrices using Numpy.Get the resultant matrix to get the maximum and minmum value.Use amin and amax methods for minimum and maximum values.Create a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement, with nrows=1, ncols=2 at index 1Using imshow() method with vmin and vmax, define the data range that the colormap covers.Repeat steps 6 and 7 with dataTo display ... Read More
To update the X-axis values using Matplotlib animation, 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.Create x and y data points using numpy.Plot x and y data points using plot method on axis (ax).Make an animation by repeatedly calling a function animate that sets the X-axis value as per the frame.To display the figure, use show() method.Exampleimport matplotlib.pylab as plt import matplotlib.animation as animation import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() x ... Read More
We can have checkpoints to verify the Response from a request. This is done by adding scripts in the Tests tab. These scripts get executed if the request has executed successfully.The scripts added under the Tests tab are developed in JavaScript. After a request has been sent and a Response is received, the outcome of these test scripts are reflected in the Test Results tab in the Response. The passed tests are marked ingreen and the failed tests are in red.Input the below tests in the Tests tab −tests["Status Code should be 200"] = responseCode.code === 200 tests["Response time lesser ... Read More
Though Monitors in Postman have many features, it has some disadvantages as well. However, it is up to the end user if he should consider these features as drawbacks for Monitors.Disadvantages of monitors are listed below −Postman Monitors are non-functional provided the Postman server resides in the same server where we are. Thus it makes it difficult to determine the performance of a Collection in a different network.To solve this problem, we need to buy the Postman pro-version. On doing so, the Postman shall then give us another IP address with which we would be able to execute Monitors.Postman Monitors ... Read More
Once a scheduled Collection Monitor gets triggered, we have to analyze the results. Click on the Monitor name available under the Monitors tab.A new window opens in the browser that shall redirect to the Postman account that we are signed in.If we analyze the performance graph of the API in the above image, we see the red bars which depict tests have failed for the request. A green bar points to the fact that tests have passed. On hovering on a particular bar, we shall get date, time, Response time and the percentage of test result for a particular run.Also, ... Read More