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The Agile Manifesto first appeared in 2001. It sought to alter the software creation process. The manifesto has four key aspects, but few people are aware of the 12 Agile Principles. They provide more specific explanations of the process in which agile product development can be carried out. After many years, nearly all companies claim that they provide "agile services", but most only pay lip service to the Agile Manifesto's ideas and concepts. The software development industry has also evolved dramatically. It's worth revisiting the agile standards to check their meanings and whether they're still relevant.Timely and Consistent Delivery of ... Read More
This guide presents the seven fundamental Software Testing Principles that any software tester and quality assurance professional should understand.6 Principles of Software TestingExhaustive testing is not possibleEarly testingDefect clusteringPesticide paradoxTesting is context-dependentAbsence of errors fallacyBackgroundWhen performing software testing, one must achieve optimal test results without straying from the target. But how do we know if we are using the best research strategy? To do so, we must adhere to certain fundamental research standards.Consider the following circumstance: we are transferring a file from Folder A to Folder B. Consider all of the many ways by which we can test this.Aside from ... Read More
To export an SVG file from a matplotlib figure, 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 random x and y data points using numpy.Plot x and y data points using plot() method.Save the .svg format file using savefig() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() x = np.random.rand(10) y = np.random.rand(10) ax.plot(x, y, ls='dotted', linewidth=2, color='red') plt.savefig("myimg.svg")OutputWhen we execute this code, it will create an SVG file called "myimg.svg" and ... Read More
To plot a time series in Python using matplotlib, we can take the following steps −Create x and y points using numpy.Plot the created x and y points using plot() method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import datetime import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.array([datetime.datetime(2021, 1, 1, i, 0) for i in range(24)]) y = np.random.randint(100, size=x.shape) plt.plot(x, y) plt.show()Output
To give sns.clustermap a dataset, we can take the following steps −Set multiple theme parameters in one step.Load an example dataset from the online repository (requires Internet).Return item and drop from the frame. Raise KeyError if not found, using pop() method.Plot a matrix dataset as a hierarchically-clustered heatmap using clustermap() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import seaborn as sns plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True sns.set_theme(color_codes=True) iris = sns.load_dataset("iris") species = iris.pop("species") g = sns.clustermap(iris) plt.show()OutputRead More
To plot 3D graphs using Python, we can take the following steps −Create a new figure or activate an existing figure using figure() method.Get the 3D axes object.Make x, y, and z lists for data points.Add 3D scatter points using scatter3D() method, with x, y, and z data points with markersize=150 and marker=diamond.To display the figure, use show() method.Examplefrom mpl_toolkits.mplot3d import Axes3D from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = Axes3D(fig) x = [2, 4, 6, 3, 1] y = [1, 6, 8, 1, 3] z = [3, 4, 10, 3, 1] ax.scatter3D(x, y, ... Read More
To sharex when using subplot2grid, we can take the following steps −Create random data, t, x, y1 and y2 using numpy.Create a new figure or activate an existing figure using figure() method.Create a subplot at a specific location inside a regular grid with colspan=3 and rowspan=2.Create a subplot at a specific location inside a regular grid with colspan=3 and sharex=ax1 (step 3).Plot curve using t and y1 and y2 using plot() method.Adjust the padding between and around the subplots.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 t = np.arange(0.0, ... Read More
To add a text into a rectangle in matplotlib, we can add a label in annotate method at the center point of the rectangle.StepsCreate a figure or activate an existing figure using figure() method.Add a subplot arrangement in the current axis.To add a rectangle in the plot, use Rectangle() class to get the rectangle object.Add a rectangle patch on the plot.To add text label in the rectangle, we can get the center value of the rectangle, i.e., cx and cy.Use annotate() method to place text on the rectangle.Limit x and y axes to get a visible rectangle.To display the figure, use show() method.Examplefrom matplotlib ... Read More
To get the center of a set of points, we can add all the elements of the list and divide that sum with the length of the list so that result could be the center of the corresponding axes.StepsMake two lists of data points.Plot x and y data points using plot() method.Get the center tuple of the x and y data points.Place the center point on the plot.Annotate the center as label for center of the x and y data points.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 x = [5, ... Read More
To set color to a rectangle in matplotlib, we can take the following steps −Create a figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.A rectangle is defined via an anchor point with width and heights.Add a rectangle patch to the plot.Set the x and y limit using xlim() and ylim() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, patches plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111) rectangle = patches.Rectangle((0, 0), 3, 3, edgecolor='orange', facecolor="green", linewidth=7) ax.add_patch(rectangle) plt.xlim([-5, 5]) plt.ylim([-5, 5]) ... Read More