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Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
[example needed] The complete description of the Risch algorithm takes over 100 pages. [1] The Risch–Norman algorithm is a simpler, faster, but less powerful variant that was developed in 1976 by Arthur Norman. Some significant progress has been made in computing the logarithmic part of a mixed transcendental-algebraic integral by Brian L ...
Moreover, complementary Python packages are available; SciPy is a library that adds more MATLAB-like functionality and Matplotlib is a plotting package that provides MATLAB-like plotting functionality. Although matlab can perform sparse matrix operations, numpy alone cannot perform such operations and requires the use of the scipy.sparse library.
normalization of dimensional quantities (dividing both the RMS difference and the standard deviation of the "test" field by the standard deviation of the observations) so that the "observed" point is plotted at unit distance from the origin along the x-axis, and statistics for different fields (with different units) can be shown in a single plot;
Python's is operator may be used to compare object identities (comparison by reference), and comparisons may be chained—for example, a <= b <= c. Python uses and, or, and not as Boolean operators. Python has a type of expression named a list comprehension, and a more general expression named a generator expression. [78]
A simple example is fitting a line in two dimensions to a set of observations. Assuming that this set contains both inliers, i.e., points which approximately can be fitted to a line, and outliers, points which cannot be fitted to this line, a simple least squares method for line fitting will generally produce a line with a bad fit to the data including inliers and outliers.
An example of the construction of a Cantor set: if you keep removing the central third of a line segment infinitely, you will end up with a shape that appears to have zero length but has an uncountably infinite number of points, each of which has an infinitesimal neighborhood of other points.
Figures 8 and 9 illustrate the gain margin and phase margin for a different amount of feedback β. The feedback factor is chosen smaller than in Figure 6 or 7, moving the condition | β A OL | = 1 to lower frequency. In this example, 1 / β = 77 dB, and at low frequencies A FB ≈ 77 dB as well. Figure 8 shows the gain plot.