mirror of
https://github.com/cdtools-developers/cdtools.git
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396 lines
14 KiB
Python
396 lines
14 KiB
Python
from __future__ import division, print_function, absolute_import
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from CDTools.tools import data
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import numpy as np
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import torch as t
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import h5py
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import pytest
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import os
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import datetime
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from pathlib import Path
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#
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# First, we write a few fixtures to generate specific data files we
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# want with deliberate pathologies.
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#
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# * Energy defined but no wavelength
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# * Wavelength defined but no energy
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# * Distance and pixel pitch defined but no corner position or basis
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# * Corner position and basis defined but no distance or pixel pitch
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# * No mask defined
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# * Mask defined
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#
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# Each file will get a fixture that loads the cxi file but also loads
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# a dictionary with the relevant information for the cxi file
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#
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#
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# This just grabs the directory whose name matches the file we're running
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@pytest.fixture(scope='module')
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def datadir(request):
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filename = request.module.__file__
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test_dir, _ = os.path.splitext(filename)
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return Path(test_dir)
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@pytest.fixture(scope='module')
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def ptycho_cxi_1():
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"""Creates an example file for CXI ptychography. This file is defined
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to have everything done as correctly as possible with lots of attributes
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defined. It will return both a dictionary describing what is expected
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to be loaded and a file with the data stored in it.
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"""
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expected = {}
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f = h5py.File('ptycho_cxi_1',driver='core',backing_store=False)
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# Start by defining the basic structure
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f.create_dataset('cxi_version', data=150)
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f.create_dataset('number_of_entries',data=1)
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# Then define a bunch of metadata for entry_1
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e1f = f.create_group('entry_1')
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expected['entry metadata'] = {}
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e1e = expected['entry metadata']
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e1e['start_time'] = datetime.datetime.now().isoformat()
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e1f['start_time'] = np.string_(e1e['start_time'])
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e1e['end_time'] = datetime.datetime.now().isoformat()
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e1f['end_time'] = np.string_(e1e['end_time'])
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e1e['experiment_identifier'] = 'Fake Experiment 1'
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e1f['experiment_identifier'] = np.string_(e1e['experiment_identifier'])
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e1e['experiment_description'] = 'A fully defined ptychography experiment to test the data loading'
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e1f['experiment_description'] = np.string_(e1e['experiment_description'])
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e1e['program_name'] = 'CDTools'
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e1f['program_name'] = np.string_(e1e['program_name'])
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e1e['title'] = 'The one experiment we did'
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e1f['title'] = np.string_(e1e['title'])
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# Set up the sample info
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s1f = e1f.create_group('sample_1')
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expected['sample info'] = {}
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s1e = expected['sample info']
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s1e['name'] = 'Fake Sample'
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s1f['name'] = np.string_(s1e['name'])
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s1e['description'] = 'A sample that isn\'t real'
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s1f['description'] = np.string_(s1e['description'])
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s1e['unit_cell_group'] = 'P1'
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s1f['unit_cell_group'] = np.string_(s1e['unit_cell_group'])
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s1e['concentration'] = np.float32(np.random.rand())
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s1f['concentration'] = s1e['concentration']
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s1e['mass'] = np.float32(np.random.rand())
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s1f['mass'] = s1e['mass']
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s1e['temperature'] = np.float32(np.random.rand()*100)
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s1f['temperature'] = s1e['temperature']
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s1e['thickness'] = np.float32(np.random.rand()*1e-7)
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s1f['thickness'] = s1e['thickness']
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s1e['unit_cell_volume'] = np.float32(np.random.rand() * 1e-27)
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s1f['unit_cell_volume'] = s1e['unit_cell_volume']
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s1e['unit_cell'] = np.array([1,1,1,90,90,90]).astype(np.float32)
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s1f.create_dataset('unit_cell',data = s1e['unit_cell'])
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i1f = e1f.create_group('instrument_1')
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source1f = i1f.create_group('source_1')
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energy = np.float32(1.3618e-16) #Joules, = 850 eV
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source1f['energy'] = energy
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expected['wavelength'] = np.float32(1.9864459e-25) / energy
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source1f['wavelength'] = expected['wavelength']
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d1f = i1f.create_group('detector_1')
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expected['detector'] = {}
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d1e = expected['detector']
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d1e['distance'] = np.float32(0.3)
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d1f['distance'] = d1e['distance']
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d1e['basis'] = np.array([[0,-30e-6,0],
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[-20e-6,0,0]]).astype(np.float32).transpose()
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d1f.create_dataset('basis_vectors',data=d1e['basis'])
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d1f['x_pixel_size'] = np.float32(20e-6)
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d1f['y_pixel_size'] = np.float32(30e-6)
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d1e['corner'] = np.array((2550e-6,3825e-6,0.3)).astype(np.float32)
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d1f.create_dataset('corner_position', data=d1e['corner'])
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# Remember the format for the CXI file differs from the format used
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# internally
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mask = np.zeros((100,256,256)).astype(np.uint32)
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expected['mask'] = np.ones((100,256,256)).astype(np.uint8)
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d1f.create_dataset('mask',data=mask)
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data1f = e1f.create_group('data_1')
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data = np.random.rand(100,256,256).astype(np.float32)
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expected['data'] = data
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d1f.create_dataset('data',data=data)
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data1f['data'] = h5py.SoftLink('/entry_1/instrument_1/detector_1/data')
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d1f['data'].attrs['axes'] = np.string_('translation:y:x')
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expected['axes'] = ['translation','y','x']
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g1f = s1f.create_group('geometry_1')
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translations = np.arange(300).reshape((100,3)).astype(np.float32)
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g1f.create_dataset('translation',data=translations)
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data1f['translation'] = h5py.SoftLink('/entry_1/sample_1/geometry_1/translation')
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d1f['translation'] = h5py.SoftLink('/entry_1/sample_1/geometry_1/translation')
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expected['translations'] = -translations.transpose()
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return f, expected
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@pytest.fixture(scope='module')
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def ptycho_cxi_2():
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"""Creates an example file for CXI ptychography. This file is defined
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to have a subset of things missing. In particular, it:
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* Defines the wavelength but not the energy
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* Defines the corner position but not the sample-detector distance
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* Defines pixel sizes but no basis vectors
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* Doesn't define a mask
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* Only defines data in the relevant places, not under data_1
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* Doesn't explicitly define axes for the data arrays
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* Is missing many allowed metadata attributes
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"""
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expected = {}
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f = h5py.File('ptycho_cxi_2',driver='core',backing_store=False)
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# Start by defining the basic structure
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f.create_dataset('cxi_version', data=150)
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f.create_dataset('number_of_entries',data=1)
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# Then define a bunch of metadata for entry_1
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e1f = f.create_group('entry_1')
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expected['entry metadata'] = {}
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e1e = expected['entry metadata']
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e1e['title'] = 'The one experiment we did'
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e1f['title'] = np.string_(e1e['title'])
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# Set up the sample info
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s1f = e1f.create_group('sample_1')
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expected['sample info'] = {}
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s1e = expected['sample info']
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s1e['temperature'] = np.float32(np.random.rand()*100)
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s1f['temperature'] = s1e['temperature']
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i1f = e1f.create_group('instrument_1')
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source1f = i1f.create_group('source_1')
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energy = np.float32(1.3618e-16) #Joules, = 850 eV
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expected['wavelength'] = np.float32(1.9864459e-25) / energy
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source1f['wavelength'] = expected['wavelength']
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d1f = i1f.create_group('detector_1')
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expected['detector'] = {}
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d1e = expected['detector']
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d1e['distance'] = np.float32(0.3)
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d1e['basis'] = np.array([[0,-30e-6,0],
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[-20e-6,0,0]]).astype(np.float32).transpose()
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d1f['x_pixel_size'] = np.float32(20e-6)
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d1f['y_pixel_size'] = np.float32(30e-6)
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d1e['corner'] = np.array((2550e-6,3825e-6,0.3)).astype(np.float32)
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d1f.create_dataset('corner_position', data=d1e['corner'])
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# Remember the format for the CXI file differs from the format used
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# internally
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expected['mask'] = None
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data1f = e1f.create_group('data_1')
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data = np.random.rand(100,256,256).astype(np.float32)
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expected['data'] = data
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d1f.create_dataset('data',data=data)
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expected['axes'] = None
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g1f = s1f.create_group('geometry_1')
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translations = np.arange(300).reshape((100,3)).astype(np.float32)
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g1f.create_dataset('translation',data=translations)
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expected['translations'] = -translations.transpose()
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return f, expected
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@pytest.fixture(scope='module')
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def ptycho_cxi_3():
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"""Creates an example file for CXI ptychography. This file is defined
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to have a different subset of information missing. In particular, it:
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* Has no sample_1 group
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* Defines the energy but not the wavelength of light
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* Has the data only defined under the data_1 group, not in the relevant places
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* Defines the detector basis but no pixel sizes
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* Defines a mask as all pixels flagged as "above the background"
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* Defines the sample to detector distance but no corner location
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* Is missing some of the allowed metadata
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"""
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expected = {}
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f = h5py.File('ptycho_cxi_3',driver='core',backing_store=False)
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# Start by defining the basic structure
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f.create_dataset('cxi_version', data=150)
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f.create_dataset('number_of_entries',data=1)
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# Then define a bunch of metadata for entry_1
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e1f = f.create_group('entry_1')
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expected['entry metadata'] = {}
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e1e = expected['entry metadata']
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e1e['start_time'] = datetime.datetime.now().isoformat()
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e1f['start_time'] = np.string_(e1e['start_time'])
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e1e['end_time'] = datetime.datetime.now().isoformat()
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e1f['end_time'] = np.string_(e1e['end_time'])
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# Set up the sample info
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expected['sample info'] = None
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i1f = e1f.create_group('instrument_1')
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source1f = i1f.create_group('source_1')
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energy = np.float32(1.3618e-16) #Joules, = 850 eV
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source1f['energy'] = energy
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expected['wavelength'] = np.float32(1.9864459e-25) / energy
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d1f = i1f.create_group('detector_1')
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expected['detector'] = {}
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d1e = expected['detector']
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d1e['distance'] = np.float32(0.3)
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d1f['distance'] = d1e['distance']
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d1e['basis'] = np.array([[0,-30e-6,0],
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[-20e-6,0,0]]).astype(np.float32).transpose()
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d1f.create_dataset('basis_vectors',data=d1e['basis'])
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d1e['corner'] = None
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# Remember the format for the CXI file differs from the format used
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# internally
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mask = np.ones((100,256,256)).astype(np.uint32) * 0x00001000
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expected['mask'] = np.ones((100,256,256)).astype(np.uint8)
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d1f.create_dataset('mask',data=mask)
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data1f = e1f.create_group('data_1')
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data = np.random.rand(100,256,256).astype(np.float32)
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expected['data'] = data
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data1f.create_dataset('data',data=data)
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data1f['data'].attrs['axes'] = np.string_('translation:y:x')
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expected['axes'] = ['translation','y','x']
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translations = np.arange(300).reshape((100,3)).astype(np.float32)
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data1f.create_dataset('translation',data=translations)
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expected['translations'] = -translations.transpose()
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return f, expected
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@pytest.fixture(scope='module')
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def real_ptycho_CSX(datadir):
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"""Loads a real ptychography file from CSX @ NSLS-II along with a
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dictionary describing what is expected to be loaded from it.
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"""
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#file_obj = h5py.File(datadir/'example_CSX_Bragg.cxi','r')
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#expected = {}
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#return file_obj, expected
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pass
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@pytest.fixture(scope='module')
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def real_ptycho_HXN(datadir):
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"""Loads a real ptychography file from HXN @ NSLS-II along with a
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dictionary describing what is expected to be loaded from it.
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"""
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pass
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@pytest.fixture(scope='module')
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def real_ptycho_COSMIC(datadir):
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"""Loads a real ptychography file from COSMIC @ ALS along with a
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dictionary describing what is expected to be loaded from it.
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"""
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pass
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@pytest.fixture(scope='module')
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def test_ptycho_cxis(ptycho_cxi_1, ptycho_cxi_2, ptycho_cxi_3):
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"""Loads a list of tuples of ptychography CXI files and dictionaries,
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describing the expected output from various functions on being called
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on the cxi files.
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"""
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return [ptycho_cxi_1, ptycho_cxi_2, ptycho_cxi_3]
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#
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# Now we have a bunch of tests of the data loading capabilities
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#
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def test_get_entry_info(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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entry_info = data.get_entry_info(cxi)
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for key in expected['entry metadata']:
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assert entry_info[key] == expected['entry metadata'][key]
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def test_get_sample_info(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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sample_info = data.get_sample_info(cxi)
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if sample_info is None and \
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('sample info' not in expected or
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expected['sample info'] is None):
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# Valid if no sample info is defined at all
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continue
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for key in expected['sample info']:
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if isinstance(expected['sample info'][key],np.ndarray):
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assert np.allclose(sample_info[key],
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expected['sample info'][key])
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else:
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assert sample_info[key] == expected['sample info'][key]
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def test_get_wavelength(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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assert np.isclose(expected['wavelength'],data.get_wavelength(cxi))
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def test_get_detector_geometry(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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distance, basis, corner = data.get_detector_geometry(cxi)
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assert np.isclose(distance,expected['detector']['distance'])
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assert np.allclose(basis,expected['detector']['basis'])
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if isinstance(expected['detector']['corner'], np.ndarray):
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assert np.allclose(corner, expected['detector']['corner'])
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else:
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assert corner == expected['detector']['corner']
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def test_get_mask(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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mask = data.get_mask(cxi)
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if expected['mask'] is None and mask is None:
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continue
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assert np.all(data.get_mask(cxi) == expected['mask'])
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def test_get_data(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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patterns, axes = data.get_data(cxi)
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assert np.allclose(patterns, expected['data'])
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assert axes == expected['axes']
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def test_get_ptycho_translations(test_ptycho_cxis):
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for cxi, expected in test_ptycho_cxis:
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assert np.allclose(data.get_ptycho_translations(cxi),
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expected['translations'])
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#
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# Then, write a test for the data saving. It should create a .cxi file
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# using the data seving tools, and then check that when read with the
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# .cxi reading tools that it gets the same things that were written.
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#
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