比较数组中的值并计算范围 Numpy Python
Comparing values in an array and calculating the difference in ranges Numpy Python
我正在尝试编写一个函数来检查某个值是否在 val
103.0, 58.8, 35, -47
的值范围内下降超过 100,值从 103 变为 -47,即 - 150 也 58.8, 35, -47
值从 58 变为 -47,减少了 -105。所以这些是 2 个案例,从初始值下降到等于或超过 -100 的值。它检查数组中的每个值是否有 -100 的下降,直到数组的末尾。因此,如果它采用数字 7.4
,那么它将检查数组的其余部分是否为 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8
,如果值为 1180.9
,则它将检查值 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8
。我怎么能用 numpy 做到这一点。
import numpy as np
val = np.array([7.4, 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8])
val2 = np.array([46.5, 55.7, 7.0, 19.6, 7.6, 36.5, 34.7, 101.9, 179.7, 85.5])
val3 = np.array([120, 20, -80, -5.5])
differences = 100
def run(values):
minimums = np.subtract.accumulate(values)
print(f'Number it has been below or equal to {differences} is {values}')
return minimums
print(run(val))
print(run(val2))
print(run(val3))
预期输出:
Number it has been below or equal to -100 is 3
Number it has been below or equal to -100 is 0
Number it has been below or equal to -100 is 2
import numpy as np
val = np.array([7.4, 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8])
val2 = np.array([46.5, 55.7, 7.0, 19.6, 7.6, 36.5, 34.7, 101.9, 179.7, 85.5])
val3 = np.array([120, 20, -80, -5.5])
def run( arr, limit ):
row_mins = np.triu( arr[None, : ] - arr[ :, None ] ).min(axis = 1 )
return np.count_nonzero( row_mins <= -limit )
展开:
def run( arr, limit ):
# Uncomment the print statements to see what is happening.
temp = arr[None, : ] - arr[ :, None ] # difference of each element all elements
# print( temp )
temp1 = np.triu( temp ) # Keep the upper triangle, set lower to zero
# print( temp1 )
row_mins = temp1.min( axis = 1 ) # Minimum for each row
# print( row_mins )
return np.count_nonzero( row_mins <= -limit ) # Count how many row_mins are <= limit
结果:
run(val, 100) # 3
run(val2, 100) # 0
run(val3, 100) # 2
我正在尝试编写一个函数来检查某个值是否在 val
103.0, 58.8, 35, -47
的值范围内下降超过 100,值从 103 变为 -47,即 - 150 也 58.8, 35, -47
值从 58 变为 -47,减少了 -105。所以这些是 2 个案例,从初始值下降到等于或超过 -100 的值。它检查数组中的每个值是否有 -100 的下降,直到数组的末尾。因此,如果它采用数字 7.4
,那么它将检查数组的其余部分是否为 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8
,如果值为 1180.9
,则它将检查值 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8
。我怎么能用 numpy 做到这一点。
import numpy as np
val = np.array([7.4, 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8])
val2 = np.array([46.5, 55.7, 7.0, 19.6, 7.6, 36.5, 34.7, 101.9, 179.7, 85.5])
val3 = np.array([120, 20, -80, -5.5])
differences = 100
def run(values):
minimums = np.subtract.accumulate(values)
print(f'Number it has been below or equal to {differences} is {values}')
return minimums
print(run(val))
print(run(val2))
print(run(val3))
预期输出:
Number it has been below or equal to -100 is 3
Number it has been below or equal to -100 is 0
Number it has been below or equal to -100 is 2
import numpy as np
val = np.array([7.4, 1180.9, 0.6, 103.0, 58.8, 35, -47, 47.2, 78.1, 37.8])
val2 = np.array([46.5, 55.7, 7.0, 19.6, 7.6, 36.5, 34.7, 101.9, 179.7, 85.5])
val3 = np.array([120, 20, -80, -5.5])
def run( arr, limit ):
row_mins = np.triu( arr[None, : ] - arr[ :, None ] ).min(axis = 1 )
return np.count_nonzero( row_mins <= -limit )
展开:
def run( arr, limit ):
# Uncomment the print statements to see what is happening.
temp = arr[None, : ] - arr[ :, None ] # difference of each element all elements
# print( temp )
temp1 = np.triu( temp ) # Keep the upper triangle, set lower to zero
# print( temp1 )
row_mins = temp1.min( axis = 1 ) # Minimum for each row
# print( row_mins )
return np.count_nonzero( row_mins <= -limit ) # Count how many row_mins are <= limit
结果:
run(val, 100) # 3
run(val2, 100) # 0
run(val3, 100) # 2