32 lines
1.2 KiB
Python
32 lines
1.2 KiB
Python
import requests
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import h5py
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import hdf5plugin
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requests.post("http://localhost:5232/initialize")
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with h5py.File("compression_benchmark.h5", "r") as f:
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img = f["/entry/data/data"]
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res = requests.put(url="http://localhost:5232/config/internal_generator_image?id=0", data = img[0, :, :].tobytes())
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res = requests.put(url="http://localhost:5232/config/internal_generator_image?id=1", data = img[1, :, :].tobytes())
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res = requests.put(url="http://localhost:5232/config/internal_generator_image?id=2", data = img[2, :, :].tobytes())
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res = requests.put(url="http://localhost:5232/config/internal_generator_image?id=3", data = img[3, :, :].tobytes())
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res = requests.put(url="http://localhost:5232/config/internal_generator_image?id=4", data = img[4, :, :].tobytes())
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start_input = {
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"beam_x_pxl":1090,
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"beam_y_pxl":1136,
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"detector_distance_mm":75,
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"incident_energy_keV":12.4,
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"sample_name":"lyso",
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"unit_cell":{"a":36.9, "b":78.95, "c":78.95, "alpha":90, "beta":90, "gamma":90},
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"images_per_trigger":18,
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"file_prefix":"lyso_test_grid",
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"grid_scan": {
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"n_fast":3,
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"step_x_um": 5.0,
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"step_y_um": -3.0,
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"snake": True
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}
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}
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requests.post("http://localhost:5232/start", json=start_input)
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