# -*- 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()