You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
164 lines
6.6 KiB
164 lines
6.6 KiB
"""
|
|
These tests require that you have a specific ND2 file created by the developer of nd2reader. You will never need to
|
|
run them unless you're Jim Rybarski.
|
|
|
|
"""
|
|
from nd2reader import Nd2
|
|
import numpy as np
|
|
from datetime import datetime
|
|
import unittest
|
|
|
|
|
|
class FunctionalTests(unittest.TestCase):
|
|
def setUp(self):
|
|
self.nd2 = Nd2("/var/nd2s/FYLM-141111-001.nd2")
|
|
|
|
def tearDown(self):
|
|
self.nd2.close()
|
|
|
|
def test_shape(self):
|
|
self.assertEqual(self.nd2.height, 1280)
|
|
self.assertEqual(self.nd2.width, 800)
|
|
|
|
def test_date(self):
|
|
self.assertEqual(self.nd2.date, datetime(2014, 11, 11, 15, 59, 19))
|
|
|
|
# def test_length(self):
|
|
# # This will fail until we address issue #59
|
|
# self.assertEqual(len(self.nd2), 17808)
|
|
|
|
def test_frames(self):
|
|
self.assertEqual(len(self.nd2.frames), 636)
|
|
|
|
def test_fovs(self):
|
|
self.assertEqual(len(self.nd2.fields_of_view), 8)
|
|
|
|
def test_channels(self):
|
|
self.assertTupleEqual(tuple(sorted(self.nd2.channels)), ('BF', 'GFP'))
|
|
|
|
def test_z_levels(self):
|
|
self.assertTupleEqual(tuple(self.nd2.z_levels), (0, 1, 2))
|
|
|
|
def test_image(self):
|
|
image = self.nd2[14]
|
|
self.assertEqual(image.field_of_view, 2)
|
|
self.assertEqual(image.frame_number, 0)
|
|
self.assertAlmostEqual(image.timestamp, 19.0340758)
|
|
self.assertEqual(image.channel, 'BF')
|
|
self.assertEqual(image.z_level, 1)
|
|
self.assertEqual(image.height, self.nd2.height)
|
|
self.assertEqual(image.width, self.nd2.width)
|
|
|
|
def test_last_image(self):
|
|
image = self.nd2[30526]
|
|
self.assertEqual(image.frame_number, 635)
|
|
|
|
def test_bad_image(self):
|
|
image = self.nd2[13]
|
|
self.assertIsNone(image)
|
|
|
|
def test_iteration(self):
|
|
images = [image for image in self.nd2[:10]]
|
|
self.assertEqual(len(images), 10)
|
|
|
|
def test_iteration_step(self):
|
|
images = [image for image in self.nd2[:10:2]]
|
|
self.assertEqual(len(images), 5)
|
|
|
|
def test_iteration_backwards(self):
|
|
images = [image for image in self.nd2[:10:-1]]
|
|
self.assertEqual(len(images), 10)
|
|
|
|
def test_get_image_by_attribute_ok(self):
|
|
image = self.nd2.get_image(4, 0, "GFP", 1)
|
|
self.assertIsNotNone(image)
|
|
image = self.nd2.get_image(4, 0, "BF", 0)
|
|
self.assertIsNotNone(image)
|
|
image = self.nd2.get_image(4, 0, "BF", 1)
|
|
self.assertIsNotNone(image)
|
|
|
|
def test_images(self):
|
|
self.assertTupleEqual((self.nd2[0].z_level, self.nd2[0].channel), (0, 'BF'))
|
|
self.assertIsNone(self.nd2[1])
|
|
self.assertTupleEqual((self.nd2[2].z_level, self.nd2[2].channel), (1, 'BF'))
|
|
self.assertTupleEqual((self.nd2[3].z_level, self.nd2[3].channel), (1, 'GFP'))
|
|
self.assertTupleEqual((self.nd2[4].z_level, self.nd2[4].channel), (2, 'BF'))
|
|
self.assertIsNone(self.nd2[5])
|
|
self.assertTupleEqual((self.nd2[6].z_level, self.nd2[6].channel), (0, 'BF'))
|
|
self.assertIsNone(self.nd2[7])
|
|
self.assertTupleEqual((self.nd2[8].z_level, self.nd2[8].channel), (1, 'BF'))
|
|
self.assertTupleEqual((self.nd2[9].z_level, self.nd2[9].channel), (1, 'GFP'))
|
|
self.assertTupleEqual((self.nd2[10].z_level, self.nd2[10].channel), (2, 'BF'))
|
|
self.assertIsNone(self.nd2[11])
|
|
self.assertTupleEqual((self.nd2[12].z_level, self.nd2[12].channel), (0, 'BF'))
|
|
self.assertIsNone(self.nd2[13])
|
|
self.assertTupleEqual((self.nd2[14].z_level, self.nd2[14].channel), (1, 'BF'))
|
|
self.assertTupleEqual((self.nd2[15].z_level, self.nd2[15].channel), (1, 'GFP'))
|
|
self.assertTupleEqual((self.nd2[16].z_level, self.nd2[16].channel), (2, 'BF'))
|
|
self.assertIsNone(self.nd2[17])
|
|
self.assertTupleEqual((self.nd2[18].z_level, self.nd2[18].channel), (0, 'BF'))
|
|
self.assertIsNone(self.nd2[19])
|
|
self.assertIsNone(self.nd2[47])
|
|
self.assertTupleEqual((self.nd2[48].z_level, self.nd2[48].channel), (0, 'BF'))
|
|
self.assertIsNone(self.nd2[49])
|
|
self.assertTupleEqual((self.nd2[50].z_level, self.nd2[50].channel), (1, 'BF'))
|
|
self.assertIsNone(self.nd2[51])
|
|
self.assertTupleEqual((self.nd2[52].z_level, self.nd2[52].channel), (2, 'BF'))
|
|
self.assertIsNone(self.nd2[53])
|
|
self.assertTupleEqual((self.nd2[54].z_level, self.nd2[54].channel), (0, 'BF'))
|
|
|
|
def test_get_image_by_attribute_none(self):
|
|
# Should handle missing images without an exception
|
|
image = self.nd2.get_image(4, 0, "GFP", 0)
|
|
self.assertIsNone(image)
|
|
|
|
def test_index(self):
|
|
# Do indexes get added to images properly?
|
|
for n, image in enumerate(self.nd2):
|
|
if image is not None:
|
|
self.assertEqual(n, image.index)
|
|
if n > 50:
|
|
break
|
|
|
|
def test_select(self):
|
|
# If we take the first 20 GFP images, they should be identical to the first 20 items iterated from select()
|
|
# if we set our criteria to just "GFP"
|
|
manual_images = []
|
|
for _, image in zip(range(20), self.nd2):
|
|
if image is not None and image.channel == 'GFP':
|
|
manual_images.append(image)
|
|
filter_images = []
|
|
|
|
for image in self.nd2.select(channels='GFP'):
|
|
filter_images.append(image)
|
|
if len(filter_images) == len(manual_images):
|
|
break
|
|
for a, b in zip(manual_images, filter_images):
|
|
self.assertTrue(np.array_equal(a, b))
|
|
|
|
def test_filter_order_all(self):
|
|
# If we select every possible image using select(), we should just get every image in order
|
|
n = 0
|
|
for image in self.nd2.select(channels=['BF', 'GFP'], z_levels=[0, 1, 2], fields_of_view=list(range(8))):
|
|
while True:
|
|
indexed_image = self.nd2[n]
|
|
if indexed_image is not None:
|
|
break
|
|
n += 1
|
|
self.assertTrue(np.array_equal(image, indexed_image))
|
|
n += 1
|
|
if n > 100:
|
|
break
|
|
|
|
def test_filter_order_subset(self):
|
|
# Test that images are always yielded in increasing order. This guarantees that no matter what subset of images
|
|
# we're filtering, we still get them in the chronological order they were acquired
|
|
n = -1
|
|
for image in self.nd2.select(channels='BF', z_levels=[0, 1], fields_of_view=[1, 2, 4]):
|
|
self.assertGreater(image.index, n)
|
|
self.assertEqual(image.channel, 'BF')
|
|
self.assertIn(image.field_of_view, (1, 2, 4))
|
|
self.assertIn(image.z_level, (0, 1))
|
|
n = image.index
|
|
if n > 100:
|
|
break
|