I wish to create a variable array of numbers in numpy while skipping a chunk of numbers. For instance, If I have the variables:
m = 5
k = 3
num = 50
I want to create a linearly spaced numpy array starting at num and ending at num - k, skip k numbers and continue the array generation. Then repeat this process m times. For example, the above would yield:
np.array([50, 49, 48, 47, 44, 43, 42, 41, 38, 37, 36, 35, 32, 31, 30, 29, 26, 25, 24, 23])
How can I accomplish this via Numpy?
You can try:
import numpy as np
m = 5
k = 3
num = 50
np.hstack([np.arange(num - 2*i*k, num - (2*i+1)*k - 1, -1) for i in range(m)])
It gives:
array([50, 49, 48, 47, 44, 43, 42, 41, 38, 37, 36, 35, 32, 31, 30, 29, 26,
25, 24, 23])
Edit:
@JanChristophTerasa posted an answer (now deleted) that avoided Python loops by masking some elements of an array obtained using np.arange(). Here is a solution inspired by that idea. It works much faster than the above one:
import numpy as np
m = 5
k = 3
num = 50
x = np.arange(num, num - 2*k*m , -1).reshape(-1, 2*k)
x[:, :k+1].ravel()
We can use a mask and np.tile:
def mask_and_tile(m=5, k=3, num=50):
a = np.arange(num, num - 2 * m * k, -1) # create numbers
mask = np.ones(k * 2, dtype=bool) # create mask
mask[k+1:] = False # set appropriate elements to False
mask = np.tile(mask, m) # repeat mask m times
result = a[mask] # mask our numbers
return result
Or we can use a mask and just toggle the appropriate element:
def mask(m=5, k=3, num=50):
a = np.arange(num, num - 2 * m * k, -1) # create numbers
mask = np.ones_like(a, dtype=bool).reshape(-1, k)
mask[1::2] = False
mask[1::2, 0] = True
result = a[mask.flatten()]
return result
This will work fine:
import numpy as np
m = 5
k = 3
num = 50
h=0
x = np.array([])
for i in range(m):
x = np.append(x, range(num-h,num-h-k-1,-1))
h+=2*k
print(x)
Output
[50. 49. 48. 47. 44. 43. 42. 41. 38. 37. 36. 35. 32. 31. 30. 29. 26. 25.
24. 23.]
np.append
One way of doing this is making a 2D grid and calculating each number based on its position in the grid, then flattening it to a 1D array.
import numpy as np
num=50
m=5
k=3
# coordinates in a grid of width k+1 and height m
y, x = np.mgrid[:m, :k+1]
# a=[[50-0, 50-1, 50-2, 50-3], [50-0-2*3*1, 50-1-2*3*1, ...], [50-0-2*3*2...]...]
a = num - x - 2 * k * y
print(a.ravel())
