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95 lines
2.9 KiB
95 lines
2.9 KiB
"""
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Functions to create artificial nd2 data for testing purposes
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"""
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import six
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import numpy as np
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import struct
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class ArtificialND2(object):
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"""
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Artificial ND2 class (for testing purposes)
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"""
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def __init__(self, file):
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self._fh = open(file, 'wb')
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self.write_version()
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc_value, traceback):
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self.close()
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@property
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def file_handle(self):
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"""
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The file handle to the binary file
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Returns:
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file: the file handle
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"""
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return self._fh
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def close(self):
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"""
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Correctly close the file handle
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"""
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if self._fh is not None:
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self._fh.close()
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def write_version(self):
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"""
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Write file header
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"""
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# write 16 empty bytes
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self._fh.write(bytearray(16))
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# write version info
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version_info = six.b('ND2 FILE SIGNATURE CHUNK NAME01!Ver3.0')
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self._fh.write(version_info)
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@staticmethod
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def create_label_map_bytes():
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"""
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Construct a binary label map
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Returns:
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tuple: (binary data, dictionary data)
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"""
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raw_text = six.b('')
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labels = {
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'image_attributes': "ImageAttributesLV!",
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'image_text_info': "ImageTextInfoLV!",
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'image_metadata': "ImageMetadataLV!",
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'image_metadata_sequence': "ImageMetadataSeqLV|0!",
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'image_calibration': "ImageCalibrationLV|0!",
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'x_data': "CustomData|X!",
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'y_data': "CustomData|Y!",
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'z_data': "CustomData|Z!",
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'roi_metadata': "CustomData|RoiMetadata_v1!",
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'pfs_status': "CustomData|PFS_STATUS!",
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'pfs_offset': "CustomData|PFS_OFFSET!",
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'guid': "CustomData|GUIDStore!",
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'description': "CustomData|CustomDescriptionV1_0!",
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'camera_exposure_time': "CustomData|Camera_ExposureTime1!",
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'camera_temp': "CustomData|CameraTemp1!",
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'acquisition_times': "CustomData|AcqTimesCache!",
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'acquisition_times_2': "CustomData|AcqTimes2Cache!",
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'acquisition_frames': "CustomData|AcqFramesCache!",
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'lut_data': "CustomDataVar|LUTDataV1_0!",
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'grabber_settings': "CustomDataVar|GrabberCameraSettingsV1_0!",
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'custom_data': "CustomDataVar|CustomDataV2_0!",
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'app_info': "CustomDataVar|AppInfo_V1_0!",
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'image_frame_0': "ImageDataSeq|0!"
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}
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data = {}
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# generate random positions and lengths
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lengths = np.random.random_integers(1, 999, len(labels))
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positions = np.subtract(np.cumsum(lengths), lengths[0])
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for length, pos, label in zip(lengths, positions, labels):
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raw_text += six.b(labels[label])
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raw_text += struct.pack('QQ', pos, length)
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data[label] = (pos, length)
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return raw_text, data
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