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12 def create_array(): 13 """Creates a simple 3D numpy array with unique values at each 14 location in the matrix. 15 16 """ 17 rows, cols, depth = 2, 3, 4 18 arr = numpy.zeros((rows, cols, depth), 'i') 19 count = 0 20 for i in range(rows): 21 for j in range(cols): 22 for k in range(depth): 23 arr[i,j,k] = count 24 count += 1 25 return arr
11 def create_empty_arrays(): 12 oneD_empty = np.empty(5) 13 twoD_empty = np.empty((5,4)) 14 threeD_empty = np.empty((5,4,3)) 15 16 print('1D array') 17 print(oneD_empty) 18 19 print('2D array') 20 print(twoD_empty) 21 22 print('3D array') 23 print(threeD_empty)
90 def create_from_numpy(self, arr): 91 return gpuarray.to_gpu(arr.astype(self.dtype))
22 def array(shape, dtype): 23 return numpy.random.uniform(-1, 1, shape).astype(dtype)
37 def test_construct(self): 38 a = bf.ndarray(self.known_vals, dtype='f32') 39 np.testing.assert_equal(a, self.known_array)
27 def create_empty_channels(width, height, num_channels): 28 return np.array(num_channels*[height*[np.zeros(width)]])
100 def zeros(shape, dtype=float): 101 """ 102 Array of zeros. 103 104 Return an array of given shape and type, filled with zeros. 105 106 Parameters 107 ---------- 108 shape : {sequence of ints, int} 109 Shape of the array 110 dtype : data-type, optional 111 The desired data-type for the array, default is np.float64. 112 113 Returns 114 ------- 115 out : bharray 116 Array of zeros of given shape, dtype, and order. 117 """ 118 ret = empty(shape, dtype) 119 ret.fill(0) 120 return ret
211 def ones(shape, dtype=float): 212 dtype = _dtype_dct[dtype] 213 return _array_factory(shape, dtype(1), dtype)