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# -*- coding: utf-8 -*-
"""
Created on Tue Nov 3 15:07:16 2017
@author: Suhas Somnath
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import sys
import unittest
import warnings
import numpy as np
from numpy.testing import assert_array_equal
from sidpy.sid.dimension import Dimension
sys.path.insert(0, "../../sidpy/")
if sys.version_info.major == 3:
unicode = str
class TestDimension(unittest.TestCase):
def test_values_as_array(self):
name = 'Bias'
values = np.random.rand(5)
descriptor = Dimension(values, name)
for expected, actual in zip([name, values],
[descriptor.name, descriptor.values]):
self.assertTrue(np.all([x == y for x, y in zip(expected, actual)]))
def test_values_as_length(self):
name = 'Bias'
units = 'V'
values = np.arange(5)
descriptor = Dimension(len(values), name, units=units)
for expected, actual in zip([name, units],
[descriptor.name, descriptor.units]):
self.assertTrue(np.all([x == y for x, y in zip(expected, actual)]))
self.assertTrue(np.allclose(values, descriptor.values))
def test_copy(self):
name = 'Bias'
units = 'V'
values = np.arange(5)
descriptor = Dimension(values, name, units=units)
copy_descriptor = descriptor.copy()
for expected, actual in zip([copy_descriptor.name, copy_descriptor.units],
[descriptor.name, descriptor.units]):
self.assertTrue(np.all([x == y for x, y in zip(expected, actual)]))
self.assertTrue(np.allclose(copy_descriptor.values, descriptor.values))
copy_descriptor.units = 'eV'
self.assertFalse(copy_descriptor.units == descriptor.units)
copy_descriptor = descriptor + 1
self.assertFalse(np.allclose(copy_descriptor.values, descriptor.values))
def test_repr(self):
name = 'Bias'
values = np.arange(5)
descriptor = Dimension(values, name)
actual = '{}'.format(descriptor)
quantity = 'generic'
units = 'generic'
expected = '{}: {} ({}) of size {}'.format(name, quantity, units, values.shape)
self.assertEqual(actual, expected)
def test_change_name(self):
name = 'Bias'
values = np.arange(5)
descriptor = Dimension(values, name)
with self.assertRaises(AttributeError):
descriptor.name = 'Voltage'
def test_inequality_req_inputs(self):
name = 'X'
quantity = "Length"
units = 'nm'
self.assertTrue(Dimension(5, name) == Dimension(5, name))
self.assertFalse(Dimension(5, 'Y') == Dimension(5, name))
self.assertFalse(Dimension(4, name) == Dimension(5, name))
self.assertTrue(
Dimension(5, units=units) == Dimension(5, units=units))
self.assertFalse(
Dimension(5, units='pm') == Dimension(5, units=units))
self.assertTrue(
Dimension(5, quantity=quantity) == Dimension(5, quantity=quantity))
self.assertFalse(
Dimension(5, quantity='Bias') == Dimension(5, quantity=quantity))
self.assertFalse(
Dimension(np.arange(5)) == Dimension(np.arange(5) + 1))
def test_dimensionality(self):
vals = np.ones((2, 2))
expected = 'Dimension can only be 1 dimensional'
with self.assertRaises(Exception) as context:
_ = Dimension(vals, "x", )
self.assertTrue(expected in str(context.exception))
def test_info(self):
expected = "X - Bias (mV): [0. 1. 2. 3. 4.]"
dim = Dimension(np.arange(5), "X", "Bias", "mV")
self.assertTrue(dim.info, expected)
def test_values_smaller_than_min_size(self):
with self.assertRaises(TypeError) as context:
_ = Dimension(0, name="x")
self.assertTrue("When specifying the size of a Dimension, values "
"should at be integers > 1" in str(context.exception))
def test_empty_array_values(self):
with self.assertRaises(TypeError) as context:
_ = Dimension([], name="x")
self.assertTrue("When specifying values over which a parameter is "
"varied, values should not be an empty array"
"" in str(context.exception))
def test_dimension_size_1(self):
dim = Dimension(1)
self.assertIsInstance(dim, Dimension)
assert_array_equal(np.array(dim), [0])
def test_single_valued_dimension(self):
dim = Dimension([1.23])
self.assertIsInstance(dim, Dimension)
assert_array_equal(np.array(dim), [1.23])
def test_conv2arr_values(self):
arr = np.arange(5)
vals = [5, arr, arr.tolist(), tuple(arr)]
vals_expected = arr
for v in vals:
dim = Dimension(v, "x")
self.assertIsInstance(dim, Dimension)
assert_array_equal(np.array(dim), vals_expected)
def test_dimension_type(self):
dim_types = ["spatial", "Spatial", "reciprocal", "Reciprocal",
"spectral", "Spectral", "temporal", "Temporal",
"frame", "Frame", "time", "Time", "stack", "Stack"]
dim_vals_expected = [1, 1, 2, 2, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4]
dim_names_expected = ["SPATIAL", "SPATIAL", "RECIPROCAL", "RECIPROCAL",
"SPECTRAL", "SPECTRAL", "TEMPORAL", "TEMPORAL",
"TEMPORAL", "TEMPORAL", "TEMPORAL", "TEMPORAL",
"TEMPORAL", "TEMPORAL"]
for dt, dv, dn in zip(dim_types, dim_vals_expected, dim_names_expected):
dim = Dimension(5, "x", dimension_type=dt)
self.assertEqual(dim.dimension_type.value, dv)
self.assertEqual(dim.dimension_type.name, dn)
def test_dimension_type(self):
dim_types = ["spatial", "Spatial", "reciprocal", "Reciprocal",
"spectral", "Spectral", "temporal", "Temporal",
"frame", "Frame", "time", "Time", "stack", "Stack"]
dim_vals_expected = [1, 1, 2, 2, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4]
dim_names_expected = ["SPATIAL", "SPATIAL", "RECIPROCAL", "RECIPROCAL",
"SPECTRAL", "SPECTRAL", "TEMPORAL", "TEMPORAL",
"TEMPORAL", "TEMPORAL", "TEMPORAL", "TEMPORAL",
"TEMPORAL", "TEMPORAL"]
for dt, dv, dn in zip(dim_types, dim_vals_expected, dim_names_expected):
dim = Dimension(5, "x", dimension_type=dt)
self.assertEqual(dim.dimension_type.value, dv)
self.assertEqual(dim.dimension_type.name, dn)
def test_unknown_dimension_type(self):
dim_type = "bad_name"
expected_wrn = ["Supported dimension types for plotting are only: [",
"Setting DimensionType to UNKNOWN"]
with warnings.catch_warnings(record=True) as w:
_ = Dimension(5, "x", dimension_type=dim_type)
self.assertTrue(expected_wrn[0] in str(w[0].message))
self.assertTrue(expected_wrn[1] in str(w[1].message))
def test_add(self):
name = 'Bias'
units = 'V'
values = np.arange(5)
descriptor = Dimension(values, name, units=units)
descriptor = descriptor + 3.
self.assertIsInstance(descriptor, Dimension)
if __name__ == '__main__':
unittest.main()
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