import numpy as np
Create an empty vector of length 10:
Z = np.zeros(10) print(Z)
How to find the memory size of any array
Z = np.zeros((10,10))
print("%d bytes" % (Z.size * Z.itemsize))
Create a vector with a range of 10 to 49
# Z = np.arange(10,50) # print(Z)
Invert a vector (the first element becomes the last)
# Z = np.arange(50) # Z = Z[::-1] # print(Z)
Create a 3x3 matrix with values from 0 to 8
# Z = np.arange(9).reshape(3,3) # print(Z)
The positional index of non-0 elements in array [1,2,0,0,4,0] was found
nz = np.nonzero([1,2,0,0,4,0])
Create a 3x3 identity matrix
# Z = np.eye(3)
Create a two-dimensional array, where the boundary value is 1 and the other values are 0
# Z = np.ones((10,10)) # Z[1:-1,1:-1] = 0
For an existing array, how to add a boundary filled with 0
# Z = np.ones((5,5)) # Z = np.pad(Z, pad_width=1, mode='constant', constant_values=0) # print(Z)
Normalize a 5x5 random matrix
# Z = np.random.random((5,5)) # Zmax, Zmin = Z.max(), Z.min() # Z = (Z - Zmin)/(Zmax - Zmin) # print(Z)
Create a custom dtype that describes the color as (RGBA) four unsigned bytes
# color = np.dtype([("r", np.ubyte, 1),
# ("g", np.ubyte, 1),
# ("b", np.ubyte, 1),
# ("a", np.ubyte, 1)])
# color
What is the product of a 5x3 matrix multiplied by a 3x2 matrix
# Z = np.dot(np.ones((5,3)), np.ones((3,2))) # print(Z)
Given a one-dimensional array, negate all elements between 3 and 8
# Z = np.arange(11) # Z[(3 < Z) & (Z <= 8)] *= -1 # print(Z)
How to round a floating point array from zero
# Z = np.random.uniform(-10,+10,10) # print (np.copysign(np.ceil(np.abs(Z)), Z))
How to find common elements in two arrays
# Z1 = np.random.randint(0,10,10) # Z2 = np.random.randint(0,10,10) # print(np.intersect1d(Z1,Z2))
How to get the date of yesterday, today and tomorrow
# yesterday = np.datetime64('today', 'D') - np.timedelta64(1, 'D')
# today = np.datetime64('today', 'D')
# tomorrow = np.datetime64('today', 'D') + np.timedelta64(1, 'D')
# print ("Yesterday is " + str(yesterday))
# print ("Today is " + str(today))
# print ("Tomorrow is "+ str(tomorrow))
Create a random vector of length 10 with a range from 0 to 1, but excluding 0 and 1
# Z = np.linspace(0,1,11,endpoint=False)[1:] # print (Z)
Convert a 10x2 matrix in Cartesian coordinates to polar coordinates
# Z = np.random.random((10,2)) # X,Y = Z[:,0], Z[:,1] # R = np.sqrt(X**2+Y**2) # T = np.arctan2(Y,X) # print (R) # print (T)
Create a vector with a length of 10 and replace the maximum value in the vector with 1
# Z = np.random.random(10) # Z[Z.argmax()] = 0 # print (Z)
How to convert a 32-bit floating point number (float) to a corresponding integer (integer)
# Z = np.arange(10, dtype=np.int32) # Z = Z.astype(np.float32, copy=False) # print (Z)
Subtract the average of each row in a matrix
# X = np.random.rand(5, 10) # # Recent versions of numpy # Y = X - X.mean(axis=1, keepdims=True) # print(Y)
How to accumulate the elements of vector (X) to array (F) according to index list (I)
# X = [1,2,3,4,5,6] # I = [1,3,9,3,4,1] # F = np.bincount(I,X) # print (F)
Consider an array of dimensions (5,5,3) and how to multiply it by an array of dimensions (5,5)
# A = np.ones((5,5,3)) # B = 2*np.ones((5,5)) # print (A * B[:,:,None])
How to calculate the average of an array through a sliding window
# def moving_average(a, n=3) : # ret = np.cumsum(a, dtype=float) # ret[n:] = ret[n:] - ret[:-n] # return ret[n - 1:] / n # Z = np.arange(20) # print(moving_average(Z, n=3))
How to negate a Boolean value or change the sign of a floating-point number in place
# Z = np.random.randint(0,2,100) # np.logical_not(Z, out=Z)
How to find the most frequent value in an array
# Z = np.random.randint(0,10,50) # print (np.bincount(Z).argmax())
For a one-dimensional array X, calculate the average of the 95% confidence interval after it is bootstrapped
# X = np.random.randn(100) # random 1D array # N = 1000 # number of bootstrap samples # idx = np.random.randint(0, X.size, (N, X.size)) # means = X[idx].mean(axis=1) # confint = np.percentile(means, [2.5, 97.5]) # print (confint)