AnniesLasso.tests.TestLassoCannonModel.setUp() - Code Metrics - Inspection of "Merge pull request #1 from andycasey/code" - andycasey/AnniesLasso - Measure and Improve Code Quality continuously with Scrutinizer

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by Andy

created 2015-11-21 10:08 UTC

AnniesLasso.tests.TestLassoCannonModel.setUp() A

↳ Parent: AnniesLasso.tests.TestLassoCannonModel

Complexity

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Total Lines

Duplication

Lines	0
Ratio	0 %

Metric	Value
dl	0
loc	14
rs	9.4286
cc	2

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Unit tests for the lasso model class and associated functions.
"""

import numpy as np
import unittest
from AnniesLasso import lasso, utils


class TestLassoCannonModel(unittest.TestCase):

    def setUp(self):

        # Initialise some faux data and labels.
        labels = "ABCDE"
        N_labels = len(labels)
        N_stars = np.random.randint(1, 500)
        N_pixels = np.random.randint(1, 10000)
        shape = (N_stars, N_pixels)

        self.valid_training_labels = np.rec.array(
            np.random.uniform(size=(N_stars, N_labels)),
            dtype=[(label, '<f8') for label in labels])

        self.valid_fluxes = np.random.uniform(size=shape)
        self.valid_flux_uncertainties = np.random.uniform(size=shape)

    def get_model(self):
        return lasso.LassoCannonModel(
            self.valid_training_labels, self.valid_fluxes,
            self.valid_flux_uncertainties)

    def test_init(self):
        self.assertIsNotNone(self.get_model())

    def test_remind_myself_to_write_unit_tests_for_these_functions(self):
        m = self.get_model()
        m.label_vector = "A + B + C"
        self.assertIsNotNone(m.label_vector)

        with self.assertRaises(NotImplementedError):
            m.train()

        m._trained = True
        with self.assertRaises(NotImplementedError):
            m.predict(None)

        with self.assertRaises(NotImplementedError):
            m.fit([], [])
    

1			#!/usr/bin/env python
2			# -- coding: utf-8 --
3
4			"""
5			Unit tests for the lasso model class and associated functions.
6			"""
7
8			import numpy as np
9			import unittest
10			from AnniesLasso import lasso, utils
11
12
13			class TestLassoCannonModel(unittest.TestCase):
14
15			def setUp(self):
			0 ignored issues – show Duplication introduced 2015-11-21 09:58 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Duplicated code is one of the most pungent code smells. If you need to duplicate the same code in three or more different places, we strongly encourage you to look into extracting the code into a single class or operation. You can also find more detailed suggestions in the “Code” section of your repository. Loading history...
16			# Initialise some faux data and labels.
17			labels = "ABCDE"
18			N_labels = len(labels)
19			N_stars = np.random.randint(1, 500)
20			N_pixels = np.random.randint(1, 10000)
21			shape = (N_stars, N_pixels)
22
23			self.valid_training_labels = np.rec.array(
24			np.random.uniform(size=(N_stars, N_labels)),
25			dtype=[(label, '<f8') for label in labels])
26
27			self.valid_fluxes = np.random.uniform(size=shape)
28			self.valid_flux_uncertainties = np.random.uniform(size=shape)
29
30			def get_model(self):
31			return lasso.LassoCannonModel(
32			self.valid_training_labels, self.valid_fluxes,
33			self.valid_flux_uncertainties)
34
35			def test_init(self):
36			self.assertIsNotNone(self.get_model())
37
38			def test_remind_myself_to_write_unit_tests_for_these_functions(self):
39			m = self.get_model()
40			m.label_vector = "A + B + C"
41			self.assertIsNotNone(m.label_vector)
42
43			with self.assertRaises(NotImplementedError):
44			m.train()
45
46			m._trained = True
47			with self.assertRaises(NotImplementedError):
48			m.predict(None)
49
50			with self.assertRaises(NotImplementedError):
51			m.fit([], [])
52

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AnniesLasso.tests.TestLassoCannonModel.setUp() A

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