305 lines
12 KiB
Python
305 lines
12 KiB
Python
'''
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Unit test for the low level vds interface for eiger
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https://support.hdfgroup.org/HDF5/docNewFeatures/VDS/HDF5-VDS-requirements-use-cases-2014-12-10.pdf
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'''
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from ..common import ut
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import numpy as np
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import h5py as h5
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import tempfile
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@ut.skipUnless(h5.version.hdf5_version_tuple >= (1, 9, 233),
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'VDS requires HDF5 >= 1.9.233')
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class TestEigerLowLevel(ut.TestCase):
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def setUp(self):
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self.working_dir = tempfile.mkdtemp()
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self.fname = ['raw_file_1.h5', 'raw_file_2.h5', 'raw_file_3.h5']
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k = 0
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for outfile in self.fname:
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filename = self.working_dir + outfile
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f = h5.File(filename, 'w')
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f['data'] = np.ones((20, 200, 200))*k
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k += 1
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f.close()
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f = h5.File(self.working_dir+'raw_file_4.h5', 'w')
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f['data'] = np.ones((18, 200, 200))*3
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self.fname.append('raw_file_4.h5')
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self.fname = [self.working_dir+ix for ix in self.fname]
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f.close()
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def test_eiger_low_level(self):
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self.outfile = self.working_dir + 'eiger.h5'
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with h5.File(self.outfile, 'w', libver='latest') as f:
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vdset_shape = (78, 200, 200)
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vdset_max_shape = vdset_shape
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virt_dspace = h5.h5s.create_simple(vdset_shape, vdset_max_shape)
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dcpl = h5.h5p.create(h5.h5p.DATASET_CREATE)
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dcpl.set_fill_value(np.array([-1]))
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# Create the source dataset dataspace
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k = 0
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for foo in self.fname:
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in_data = h5.File(foo, 'r')['data']
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src_shape = in_data.shape
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max_src_shape = src_shape
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in_data.file.close()
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src_dspace = h5.h5s.create_simple(src_shape, max_src_shape)
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# Select the source dataset hyperslab
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src_dspace.select_hyperslab(start=(0, 0, 0),
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stride=(1, 1, 1),
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count=(1, 1, 1),
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block=src_shape)
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virt_dspace.select_hyperslab(start=(k, 0, 0),
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stride=(1, 1, 1),
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count=(1, 1, 1),
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block=src_shape)
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dcpl.set_virtual(virt_dspace, foo.encode('utf-8'),
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b'data', src_dspace)
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k += src_shape[0]
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# Create the virtual dataset
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h5.h5d.create(f.id, name=b"data", tid=h5.h5t.NATIVE_INT16,
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space=virt_dspace, dcpl=dcpl)
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f = h5.File(self.outfile, 'r')['data']
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self.assertEqual(f[10, 100, 10], 0.0)
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self.assertEqual(f[30, 100, 100], 1.0)
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self.assertEqual(f[50, 100, 100], 2.0)
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self.assertEqual(f[70, 100, 100], 3.0)
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f.file.close()
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def tearDown(self):
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import os
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for f in self.fname:
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os.remove(f)
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os.remove(self.outfile)
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if __name__ == "__main__":
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ut.main()
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'''
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Unit test for the low level vds interface for excalibur
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https://support.hdfgroup.org/HDF5/docNewFeatures/VDS/HDF5-VDS-requirements-use-cases-2014-12-10.pdf
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'''
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class ExcaliburData:
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FEM_PIXELS_PER_CHIP_X = 256
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FEM_PIXELS_PER_CHIP_Y = 256
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FEM_CHIPS_PER_STRIPE_X = 8
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FEM_CHIPS_PER_STRIPE_Y = 1
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FEM_STRIPES_PER_MODULE = 2
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@property
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def sensor_module_dimensions(self):
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x_pixels = self.FEM_PIXELS_PER_CHIP_X * self.FEM_CHIPS_PER_STRIPE_X
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y_pixels = self.FEM_PIXELS_PER_CHIP_Y * self.FEM_CHIPS_PER_STRIPE_Y * self.FEM_STRIPES_PER_MODULE
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return y_pixels, x_pixels,
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@property
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def fem_stripe_dimensions(self):
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x_pixels = self.FEM_PIXELS_PER_CHIP_X * self.FEM_CHIPS_PER_STRIPE_X
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y_pixels = self.FEM_PIXELS_PER_CHIP_Y * self.FEM_CHIPS_PER_STRIPE_Y
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return y_pixels, x_pixels,
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def generate_sensor_module_image(self, value, dtype='uint16'):
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dset = np.empty(shape=self.sensor_module_dimensions, dtype=dtype)
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dset.fill(value)
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return dset
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def generate_fem_stripe_image(self, value, dtype='uint16'):
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dset = np.empty(shape=self.fem_stripe_dimensions, dtype=dtype)
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dset.fill(value)
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return dset
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@ut.skipUnless(h5.version.hdf5_version_tuple >= (1, 9, 233),
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'VDS requires HDF5 >= 1.9.233')
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class TestExcaliburLowLevel(ut.TestCase):
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def create_excalibur_fem_stripe_datafile(self, fname, nframes, excalibur_data,scale):
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shape = (nframes,) + excalibur_data.fem_stripe_dimensions
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max_shape = (nframes,) + excalibur_data.fem_stripe_dimensions
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chunk = (1,) + excalibur_data.fem_stripe_dimensions
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with h5.File(fname, 'w', libver='latest') as f:
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dset = f.create_dataset('data', shape=shape, maxshape=max_shape, chunks=chunk, dtype='uint16')
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for data_value_index in np.arange(nframes):
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dset[data_value_index] = excalibur_data.generate_fem_stripe_image(data_value_index*scale)
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def setUp(self):
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self.working_dir = tempfile.mkdtemp()
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self.fname = ["stripe_%d.h5" % stripe for stripe in range(1,7)]
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self.fname = [self.working_dir+ix for ix in self.fname]
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nframes = 5
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self.edata = ExcaliburData()
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k=0
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for raw_file in self.fname:
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self.create_excalibur_fem_stripe_datafile(raw_file, nframes, self.edata,k)
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k+=1
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def test_excalibur_low_level(self):
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excalibur_data = self.edata
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self.outfile = self.working_dir+'excalibur.h5'
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vdset_stripe_shape = (1,) + excalibur_data.fem_stripe_dimensions
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vdset_stripe_max_shape = (5, ) + excalibur_data.fem_stripe_dimensions
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vdset_shape = (5,
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excalibur_data.fem_stripe_dimensions[0] * len(self.fname) + (10 * (len(self.fname)-1)),
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excalibur_data.fem_stripe_dimensions[1])
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vdset_max_shape = (5,
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excalibur_data.fem_stripe_dimensions[0] * len(self.fname) + (10 * (len(self.fname)-1)),
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excalibur_data.fem_stripe_dimensions[1])
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vdset_y_offset = 0
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# Create the virtual dataset file
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with h5.File(self.outfile, 'w', libver='latest') as f:
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# Create the source dataset dataspace
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src_dspace = h5.h5s.create_simple(vdset_stripe_shape, vdset_stripe_max_shape)
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# Create the virtual dataset dataspace
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virt_dspace = h5.h5s.create_simple(vdset_shape, vdset_max_shape)
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# Create the virtual dataset property list
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dcpl = h5.h5p.create(h5.h5p.DATASET_CREATE)
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dcpl.set_fill_value(np.array([0x01]))
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# Select the source dataset hyperslab
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src_dspace.select_hyperslab(start=(0, 0, 0), count=(1, 1, 1), block=vdset_stripe_max_shape)
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for raw_file in self.fname:
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# Select the virtual dataset hyperslab (for the source dataset)
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virt_dspace.select_hyperslab(start=(0, vdset_y_offset, 0),
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count=(1, 1, 1),
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block=vdset_stripe_max_shape)
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# Set the virtual dataset hyperslab to point to the real first dataset
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dcpl.set_virtual(virt_dspace, raw_file.encode('utf-8'),
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b"/data", src_dspace)
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vdset_y_offset += vdset_stripe_shape[1] + 10
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# Create the virtual dataset
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dset = h5.h5d.create(f.id, name=b"data",
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tid=h5.h5t.NATIVE_INT16, space=virt_dspace, dcpl=dcpl)
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assert(f['data'].fillvalue == 0x01)
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f = h5.File(self.outfile,'r')['data']
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self.assertEqual(f[3,100,0], 0.0)
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self.assertEqual(f[3,260,0], 1.0)
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self.assertEqual(f[3,350,0], 3.0)
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self.assertEqual(f[3,650,0], 6.0)
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self.assertEqual(f[3,900,0], 9.0)
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self.assertEqual(f[3,1150,0], 12.0)
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self.assertEqual(f[3,1450,0], 15.0)
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f.file.close()
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def tearDown(self):
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import os
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for f in self.fname:
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os.remove(f)
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os.remove(self.outfile)
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'''
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Unit test for the low level vds interface for percival
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https://support.hdfgroup.org/HDF5/docNewFeatures/VDS/HDF5-VDS-requirements-use-cases-2014-12-10.pdf
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'''
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@ut.skipUnless(h5.version.hdf5_version_tuple >= (1, 9, 233),
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'VDS requires HDF5 >= 1.9.233')
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class TestPercivalLowLevel(ut.TestCase):
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def setUp(self):
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self.working_dir = tempfile.mkdtemp()
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self.fname = ['raw_file_1.h5','raw_file_2.h5','raw_file_3.h5']
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k = 0
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for outfile in self.fname:
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filename = self.working_dir + outfile
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f = h5.File(filename,'w')
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f['data'] = np.ones((20,200,200))*k
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k +=1
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f.close()
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f = h5.File(self.working_dir+'raw_file_4.h5','w')
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f['data'] = np.ones((19,200,200))*3
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self.fname.append('raw_file_4.h5')
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self.fname = [self.working_dir+ix for ix in self.fname]
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f.close()
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def test_percival_low_level(self):
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self.outfile = self.working_dir + 'percival.h5'
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with h5.File(self.outfile, 'w', libver='latest') as f:
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vdset_shape = (1,200,200)
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num = h5.h5s.UNLIMITED
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vdset_max_shape = (num,)+vdset_shape[1:]
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virt_dspace = h5.h5s.create_simple(vdset_shape, vdset_max_shape)
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dcpl = h5.h5p.create(h5.h5p.DATASET_CREATE)
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dcpl.set_fill_value(np.array([-1]))
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# Create the source dataset dataspace
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k = 0
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for foo in self.fname:
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in_data = h5.File(foo, 'r')['data']
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src_shape = in_data.shape
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max_src_shape = (num,)+src_shape[1:]
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in_data.file.close()
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src_dspace = h5.h5s.create_simple(src_shape, max_src_shape)
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# Select the source dataset hyperslab
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src_dspace.select_hyperslab(start=(0, 0, 0),
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stride=(1,1,1),
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count=(num, 1, 1),
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block=(1,)+src_shape[1:])
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virt_dspace.select_hyperslab(start=(k, 0, 0),
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stride=(4,1,1),
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count=(num, 1, 1),
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block=(1,)+src_shape[1:])
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dcpl.set_virtual(virt_dspace, foo.encode('utf-8'), b'data', src_dspace)
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k+=1
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# Create the virtual dataset
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dset = h5.h5d.create(f.id, name=b"data", tid=h5.h5t.NATIVE_INT16, space=virt_dspace, dcpl=dcpl)
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f = h5.File(self.outfile,'r')
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sh = f['data'].shape
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line = f['data'][:8,100,100]
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foo = np.array(2*list(range(4)))
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f.close()
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self.assertEqual(sh,(79,200,200),)
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np.testing.assert_array_equal(line,foo)
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def tearDown(self):
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import os
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for f in self.fname:
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os.remove(f)
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os.remove(self.outfile)
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@ut.skipUnless(h5.version.hdf5_version_tuple >= (1, 10, 2),
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'get_ / set_virtual_prefix requires HDF5 >= 1.10.2')
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def test_virtual_prefix(tmp_path):
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(tmp_path / 'a').mkdir()
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(tmp_path / 'b').mkdir()
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src_file = h5.File(tmp_path / 'a' / 'src.h5', 'w')
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src_file['data'] = np.arange(10)
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vds_file = h5.File(tmp_path / 'b' / 'vds.h5', 'w')
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layout = h5.VirtualLayout(shape=(10,), dtype=np.int64)
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layout[:] = h5.VirtualSource('src.h5', 'data', shape=(10,))
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vds_file.create_virtual_dataset('data', layout, fillvalue=-1)
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# Path doesn't resolve
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np.testing.assert_array_equal(vds_file['data'], np.full(10, fill_value=-1))
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path_a = bytes(tmp_path / 'a')
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dapl = h5.h5p.create(h5.h5p.DATASET_ACCESS)
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dapl.set_virtual_prefix(path_a)
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vds_id = h5.h5d.open(vds_file.id, b'data', dapl=dapl)
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vds = h5.Dataset(vds_id)
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# Now it should find the source file and read the data correctly
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np.testing.assert_array_equal(vds[:], np.arange(10))
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# Check that get_virtual_prefix gives back what we put in
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assert vds.id.get_access_plist().get_virtual_prefix() == path_a
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