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NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
import numpy as np def dlp (A, B, p = 2): cost = np. sum (np. power (np. abs (A-B), p)) return np. power (cost, 1 / p) def twed (A, timeSA, B, timeSB, nu, _lambda): """Compute Time Warp Edit Distance (TWED) for given time series A and B.""" # [distance, DP] = TWED(A, timeSA, B, timeSB, lambda, nu) # # A := Time series A (e.g. [ 10 2 30 4]) # timeSA := Time stamp of time series A (e.g. 1:4) # B ...
Python can winsorize data using SciPy library: import numpy as np from scipy.stats.mstats import winsorize winsorize (np. array ...
Google JAX is a machine learning framework for transforming numerical functions. [1] [2] [3] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).
import numpy as np def comm_mat (m, n): # determine permutation applied by K w = np. arange (m * n). reshape ((m, n), order = "F"). T. ravel (order = "F") # apply this permutation to the rows (i.e. to each column) of identity matrix and return result return np. eye (m * n)[w,:]
This python example uses the percentile function from the numerical library numpy and works in Python 2 and 3. import numpy as np def fivenum ( data ): """Five-number summary.""" return np . percentile ( data , [ 0 , 25 , 50 , 75 , 100 ], method = "midpoint" )
The following Python code implements the Euler–Maruyama method and uses it to solve the Ornstein ... utf-8 -*-import numpy as np import matplotlib.pyplot as plt ...