def test_nddata_core_add(self):
for ix in range(num_random_tests):
random_coords = [np.r_[0:random.randint(1,6)] for dim in test_dims]
random_axis = list(zip(test_dims, random_coords))
random_axis1 = random.sample(random_axis, 3)
random_axis2 = random.sample(random_axis, 3)
dims1 = [axis[0] for axis in random_axis1]
coords1 = [axis[1] for axis in random_axis1]
shape1 = [coord.size for coord in coords1]
values1 = np.random.randn(*shape1)
data1 = nddata.nddata_core(values1, dims1, coords1)
dims2 = [axis[0] for axis in random_axis2]
coords2 = [axis[1] for axis in random_axis2]
shape2 = [coord.size for coord in coords2]
values2 = np.random.randn(*shape2)
data2 = nddata.nddata_core(values2, dims2, coords2)
data = data1 + data2
self.assertTrue(data._self_consistent())
assert_array_equal((data1+1).values, values1+1)
assert_array_equal((data1+1.).values, values1+1.)
assert_array_equal((data1+1.j).values, values1+1.j)
def test_ndim(self):
values = np.r_[1:10].reshape(3, 3)
x = np.r_[0:3]
y = np.r_[0:3]
data = nddata.nddata_core(values, ["x", "y"], [x, y])
self.assertEqual(data.ndim, 2)
def construct_random_data(self):
random_dims = random.sample(test_dims, random.randint(1,len(test_dims)))
random_coords = [np.r_[0:random.randint(1,6)] for dim in random_dims]
shape = [coord.size for coord in random_coords]
random_values = np.random.randn(*shape)
data = nddata.nddata_core(random_values, random_dims, random_coords)
return data,random_dims,random_values,random_coords
def get_random_nddata_list(seed_axis=0, seed_data=0):
"""
Pre-generate a list of randomized tuple (nddata, np.array) for all the
test cases here
"""
random.seed(seed_axis)
random_axes = [
random.sample(
list(
zip(test_dims,
[np.r_[0:random.randint(1, 6)] for _ in test_dims])),
3,
) for _ in range(3)
]
random.seed(seed_data)
nddata_list = []
for random_axis in random_axes:
dims = [axis[0] for axis in random_axis]
coords = [axis[1] for axis in random_axis]
shape = [coord.size for coord in coords]
values = np.random.randn(*shape)
nddata_list.append((nddata.nddata_core(values, dims, coords), values))
# nddata_list.append((nddata.nddata_core(), np.array([]))) # UserWarning: Github #37
return nddata_list
import sys
sys.path.append('..')
import dnplab
from dnplab.core.nddata import nddata_core
import numpy as np
x = np.r_[1:100]
values = np.random.randn(len(x))
data = nddata_core(values, ['x'], [x])
print(data)
dnplab.dnpResults.plot(data)
dnplab.dnpResults.show()
def test_nddata_core_math_div_by_zero():
with pytest.warns(RuntimeWarning):
nddata.nddata_core(values=np.array([1, 2, 3]),
coords=[np.array([3, 2, 1])],
dims=["x"]) / 0
def test_nddata_core_math_operators(self):
for ix in range(num_random_tests):
random_coords = [np.r_[0:random.randint(1,6)] for dim in test_dims]
random_axis = list(zip(test_dims, random_coords))
random_axis = random.sample(random_axis, 3)
dims = [axis[0] for axis in random_axis]
coords = [axis[1] for axis in random_axis]
shape = [coord.size for coord in coords]
values = np.random.randn(*shape)
data = nddata.nddata_core(values, dims, coords)
random_array = np.random.randn(*shape)
#__add__
assert_array_equal((data+1).values, values+1)
assert_array_equal((data+1.).values, values+1.)
assert_array_equal((data+1.j).values, values+1.j)
assert_array_equal((data+random_array).values, values+random_array)
#__sub__
assert_array_equal((data-1).values, values-1)
assert_array_equal((data-1.).values, values-1.)
assert_array_equal((data-1.j).values, values-1.j)
assert_array_equal((data-random_array).values, values-random_array)
#__mult__
assert_array_equal((data*1).values, values*1)
assert_array_equal((data*1.).values, values*1.)
assert_array_equal((data*1.j).values, values*1.j)
assert_array_equal((data*random_array).values, values*random_array)
#__truediv__
assert_array_equal((data/1).values, values/1)
assert_array_equal((data/1.).values, values/1.)
assert_array_equal((data/1.j).values, values/1.j)
assert_array_equal((data/random_array).values, values/random_array)
#__radd__
assert_array_equal((1+data).values, 1+values)
assert_array_equal((1.+data).values, 1.+values)
assert_array_equal((1.j+data).values, 1.j+values)
assert_array_equal((random_array+data).values, random_array+values)
#__rsub__
assert_array_equal((1-data).values, 1-values)
assert_array_equal((1.-data).values, 1.-values)
assert_array_equal((1.j-data).values, 1.j-values)
assert_array_equal((random_array-data).values, random_array-values)
#__rmult__
assert_array_equal((1*data).values, 1*values)
assert_array_equal((1.*data).values, 1.*values)
assert_array_equal((1.j*data).values, 1.j*values)
assert_array_equal((random_array*data).values, random_array*values)
#__rtruediv__
assert_array_equal((1/data).values, 1/values)
assert_array_equal((1./data).values, 1./values)
assert_array_equal((1.j/data).values, 1.j/values)
assert_array_equal((random_array/data).values, random_array/values)