| np.array() |
|
| np.arange(start, end, step) |
|
| np.linspace(start, end, count) |
from start to end, equal margin |
| np.copy() |
|
|
|
| np.hstack(tuple) |
Stack arrays in sequence horizontally (column wise) |
| np.vstack(tuple) |
Stack arrays in sequence vertically (row wise) |
| numpy.random.rand(d0,d1,d2,...,dN) |
d is dimention,float values betweent 0 and 1 |
| numpy.zeros(shape, dtype=float, order='C') |
order = 'C' is row-major, F is column-major storage in memory |
| numpy.nditer() |
iterator for array |
| np.dot() |
dot product |
| np.cross() |
cross product |
| np.max() |
get maximum value from tensor |
| np.amax(arr, axis) |
get maximum value from given axis |
| np.sum(arr, axis) |
sum of all elements if using default axis |
| np.average(arr, axis，weights) |
average of all elements if using default axis |
| np.mean(arr, axis) |
equal to np.average while weights is 1 |
| np.std() |
standard deviation |
| np.tolist() |
|
| np.isnan(value) |
|
| np.full() |
fill all ndarray with one value |
| np.ones() |
fill all adarray with 1 |
| np.flatten() |
|