import numpy as np
def permgrid(m, n):
inds = np.indices((m,) * n, dtype='float')
return inds.reshape(n, -1).T
# Создаем матрицу перестановок
a = permgrid(10, 4)
# Перемножаем матрицу
a *= 0.001
def task(coef):
ad = float(coef[0] + coef[1] * coef[2] - coef[3])
if coef[0] != 0:
ad = ad / coef[0]
else:
ad = ad / 100
return ad
# Применяем функцию, итерируясь по строкам матрицы
task_result = np.apply_along_axis(task, 1, a)
# Вектор преобразуем из строки в столбец
task_result = np.reshape(task_result, (-1, 1))
# Присоединяем столбец к исходной матрице
a = np.concatenate((a, task_result), axis=1)import numpy as np
def trunc(values, decs=0):
stepper = 10.0 ** decs
return np.trunc(values * stepper) / stepper
a = np.random.sample((10, 5))
print(a)
a = trunc(a, 2)
print(a)[[0.80774294 0.49759797 0.12831778 0.0507127 0.93884821]
[0.40449397 0.66256411 0.68941394 0.9249191 0.24395077]
[0.04315995 0.18290855 0.5908672 0.2102119 0.81539927]
[0.35844866 0.5186572 0.29508712 0.57636076 0.64102832]
[0.94639274 0.09793527 0.73766807 0.80979653 0.84808608]
[0.46454466 0.58734548 0.63087822 0.10865253 0.82981857]
[0.8473419 0.23920123 0.3373125 0.4772781 0.35829208]
[0.03148842 0.70653864 0.85633527 0.72635685 0.47321859]
[0.76828975 0.08494009 0.45071368 0.79358861 0.6005338 ]
[0.3820037 0.02684243 0.1404288 0.04466791 0.32699522]]
[[0.8 0.49 0.12 0.05 0.93]
[0.4 0.66 0.68 0.92 0.24]
[0.04 0.18 0.59 0.21 0.81]
[0.35 0.51 0.29 0.57 0.64]
[0.94 0.09 0.73 0.8 0.84]
[0.46 0.58 0.63 0.1 0.82]
[0.84 0.23 0.33 0.47 0.35]
[0.03 0.7 0.85 0.72 0.47]
[0.76 0.08 0.45 0.79 0.6 ]
[0.38 0.02 0.14 0.04 0.32]]