##Description
This is a partial port of some numpy functions for skulpt. Mainly, focused on
ndarray and its respective functions. See below for the currently supported functions.
- improved internal attribute handling
- improved internal buffer handling
- added
ndarray.T attribute - added
__getattr__ - added
__setattr__ - added
numpy.vdot
Example:
import numpy as np
a = np.array([[1, 2], [3, 4]])
print(a)
a.shape = (4,)
print(a)
a.shape = (1, 2, 2)
print(a.T)
a.shape = 4
print(a)
a = np.array([[1j, 2j], [3j, 4j]])
b = [1, 2, 3, 4]
c = np.vdot(a, b)
print(c)##Supported
###ndarray Currently all attributes are readonly. Though
-
__str__ -
__repr__ -
__len__ -
shape -
ndim -
data -
dtype -
size -
tolist -
fill -
[], with slices -
operators: +, -, /, *, **, %, neg, pos, xor, shift -
reshape -
copy -
__iter__
###functions
- linspace
- array
- ones
- zeros
- full
- empty
- arange
- asarray
###trigonomeric Some of the functions rely on math.js, but you can use the module without it. All functions that require the library are going to throw an python exception if they cannot call mathjs.
- dot (mathjs)
- sin
- cos
- tan
- sinh (mathjs)
- cosh (mathjs)
- tanh (mathjs)
- arctan
- arcsin
- arccos
###Examples
import numpy as np
a = [[1, 2], [3, 4]]
b = np.array(a, ndmin=3, dtype=float)
print "np.array(a, ndmin=3a, dtype=float)"
c = np.ones(b.shape)
print "np.ones(b.shape): %s" % (c,)
d = np.zeros(b.shape)
print "np.zeros(b.shape): %s" % (d,)
print "__str__: %s" % b
print "__repr__: %r" % b
print "__len__: %s" % len(b)
print "shape %s" % (b.shape,)
print "ndim %s" % b.ndmin
print "data: %s" % (b.data,)
print "dtype: %s" % b.dtype
print "size %s" % b.size
print "b.tolist %s" % (b.tolist(),)
b.fill(9)
print "b.fill(9): %s" % (b,)
b[0, 0, 0] = 2
print "b[0, 0, 0] = 2: %s" % (b,)
print ""
print "np.full((2,2), 2.0)"
c = np.full((2,2), 2.0, int)
print "===================="
print " operations"
print "===================="
print "c = %s" % (c,)
print "c + 2 = %s" % (c + 2,)
print "c - 2 = %s" % (c - 2,)
print "c * 2 = %s" % (c * 2,)
print "c / 2 = %s" % (c / 2,)
print "c ** 2 = %s" % (c ** 2,)
print "+c = %s" % (+c,)
print "-c = %s" % (-c,)
print "===================="
print " trigonometric "
print "===================="
c = np.full((2,2), 0, int)
print "c = %s" % (c,)
print "np.sin(c) = %s" % (np.sin(c),)
print "np.cos(c) = %s" % (np.cos(c),)
print "np.tan(c) = %s" % (np.tan(c),)
print "np.arcsin(c) = %s" % (np.arcsin(c),)
print "np.arccos(c) = %s" % (np.arccos(c),)
print "np.arctan(c) = %s" % (np.arctan(c),)
print "np.sinh(c) = %s" % (np.sinh(c),)
print "np.cosh(c) = %s" % (np.cosh(c),)
print "np.tanh(c) = %s" % (np.tanh(c),)
print "np.sin([0,1]) = %s" % (np.sin([0,1]),)
print "np.sin((0,1)) = %s" % (np.sin((0,1)),)
print "===================="
print " various "
print "===================="
ar = np.arange(3.0)
print "np.arange(3.0): %s, dtype: %s" % (ar, ar.dtype)
ar = np.arange(3)
print "np.arange(3): %s, dtype: %s" % (ar, ar.dtype)
ar = np.arange(3,7)
print "np.arange(3,7): %s, dtype: %s" % (ar, ar.dtype)
ar = np.arange(3,7, 2)
print "np.arange(3,7, 2): %s, dtype: %s" % (ar, ar.dtype)
ar = np.linspace(2.0, 3.0, num=5)
print "np.linspace(2.0, 3.0, num=5): %s" % (ar,)
ar = np.linspace(2.0, 3.0, num=5, endpoint=False)
print "np.linspace(2.0, 3.0, num=5, endpoint=False): %s" % (ar,)
ar = np.linspace(2.0, 3.0, num=5, retstep=True)
print "np.linspace(2.0, 3.0, num=5, retstep=True): %s" % (ar,)