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Page 1939 of 2109
Explain how reflection works in .NET framework
A C# program compiles to a DLL assembly that contains the compiled C# code along with the metadata for the runtime, and other resources. C# provides a reflection API that lets us inspect the metadata and compiled code at runtime.Using reflection, it's possible to −Access the assembly metadata for all types inside the assemblyObtain a list of types and their members (methods, properties, etc.)Dynamically invoke the type members at runtime.Instantiate objects by only providing their nameBuild assembliesIn a traditional program, when you compile the source code to the machine code, the compiler removes all the metadata about the code. However, ...
Read MoreWhat is the preferred way to set Matplotlib figure/axes properties?
To set the properties of a plot, we can get the current axis of the plot. After that, we can perform several set_* methods to set the properties of the plot.StepsCreate a figure and a set of subplots using subplots() method with figsize=(5, 5).Create x and y data points using numpy.Plot x and y using plot() method.Set the title and labels (for X and Y axis) using set_xlabel() and set_ylabel() methods.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 fig, ax = plt.subplots() x = np.linspace(-1, 1, 10) y = ...
Read MoreHow to remove gaps between bars in Matplotlib bar chart?
To remove gaps between bars, we can change the align value to center in the argument of bar() method.StepsCreate a dictionary called data with two keys, milk and water.Get the list of keys and values in the dictionay.Using subplots() method, create a figure and add a set of two subplots.On axis 2, use bar method to plot bars without gaps. Set the width attribute as 1.0. Set the title using set_title() method.Use tight_layout() to adjust the padding between and around the subplots.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = {'milk': 12, 'water': ...
Read MoreRotate theta=0 on a Matplotlib polar plot
To set theta=0 on a matplotlib polar plot, we can take the following steps −Create random theta in the range of 0 to 100; convert them into radian.Using set_theta_zero_location() method, we can set the location of theta to 0.Plot theta_in_rad and data_r using plot() method.Set the title of the plot using title() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import random plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True theta_in_rad = [float(i) * np.pi / 180.0 for i in range(0, 100, 10)] data_r = random.sample(range(70, 90), 10) ax = plt.subplot(111, polar=True) ax.set_theta_zero_location("W") ax.plot(theta_in_rad, data_r, color='r', linewidth=3) ax.set_title("Example", ...
Read MoreWhat is the difference between plt.close() and plt.clf() in Matplotlib?
plt.figure() - Create a new figure or activate an existing figure.plt.figure().close() - Close a figure window.close() by itself closes the current figureclose(h), where h is a Figure instance, closes that figureclose(num) closes figure number numclose(name), where name is a string, closes the figure with that labelclose('all') closes all the figure windowsplt.figure().clear() - It is the same as clf.plt.cla() - Clear the current axes.plt.clf() - Clear the current figure.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-1, 1, 10) y = np.linspace(1, 2, 10) plt.plot(x, y, c='red') plt.title("First Plot") plt.show() ...
Read MoreHow to plot data from multiple two-column text files with legends in Matplotlib?
To plot data from multiple two-column text files with legends in matplotlib, we can take the following steps −Import genfromtxt from pylab. It has several options to read data from a text file and plot the data.Read two text files, test.txt and test1.txt (having two columns of data), using genfromtxt and store the data in two variables, firstfiledata and secondfiledata.Plot the data using plot() method. label will be displayed as the legend.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt; from pylab import genfromtxt; plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True firstfiledata = genfromtxt("test.txt"); secondfiledata = genfromtxt("test1.txt"); plt.plot(firstfiledata[:, 0], firstfiledata[:, 1], label="test.txt ...
Read MoreHide Matplotlib descriptions in Jupyter notebook
To hide matplotlib descriptions of an instance while calling plot() method, we can take the following steps −Open Ipython instance.import numpy as npfrom matplotlib, import pyplot as pltCreate points for x, i.e., np.linspace(1, 10, 1000)Now, plot the line using plot() method.To hide the instance, use plt.plot(x); i.e., (with semi-colon)Or, use _ = plt.plot(x)ExampleIn [1]: import numpy as np In [2]: from matplotlib import pyplot as plt In [3]: x = np.linspace(1, 10, 1000) In [4]: plt.plot(x) Out[4]: [] In [5]: plt.plot(x); In [6]: _ = plt.plot(x) In [7]:OutputOut[4]: []
Read MorePlot multiple columns of Pandas DataFrame using Seaborn
To plot multiple columns of Pandas DataFrame using Seaborn, we can take the following steps −Make a dataframe using Pandas.Plot a bar using Seaborn's barplot() method.Rotate the xticks label by 45 angle.To display the figure, use show() method.Exampleimport pandas import matplotlib.pylab as plt import seaborn as sns import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = pandas.DataFrame({"X-Axis": [np.random.randint(10) for i in range(10)], "YAxis": [i for i in range(10)]}) bar_plot = sns.barplot(x='X-Axis', y='Y-Axis', data=df) plt.xticks(rotation=45) plt.show()Output
Read MoreHow to display Matplotlib Y-axis range using absolute values rather than offset values?
To display Y-axis range using absolute values rather than offset values, we can take the following steps −Create x_data and y_data data points in the range of 100 to 1000.Create a figure and a set of subplots using subplots() method.Plot x_data and y_data using plot() method.If a parameter is not set, the corresponding property of the formatter is left unchanged using ticklabel_format() method with useOffset=False.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_date = range(100, 1000, 100) y_data = range(100, 1000, 100) fig, ax = plt.subplots() ax.plot(x_date, y_data) ax.ticklabel_format(useOffset=False) plt.show()Output
Read MoreDrawing lines between two plots in Matplotlib
To draw lines between two plots in matplotlib, we can take the following steps −Create a new figure or activate an existing figure.Add two axes (ax1 and ax2) to the figure as part of a subplot arrangement.Create random data x and y using numpy.Plot x and y data points on both the axes (ax1 and ax2) with color=red and marker=diamond.Initialize two variables, i and j to get the diffirent data points on the subplot.Make xy and mn tuple for positions to add a patch on the subplots.Add a patch that connects two points (possibly in different axes), con1 and con2.Add artists for con1 ...
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