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diffraction image successfully loaded in nexus file

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Emanuele D'Amico
2026-05-05 12:02:39 +02:00
parent 707ce28156
commit a278119be4
1 changed files with 19 additions and 8 deletions
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27
src/main.py
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@@ -382,7 +382,7 @@ def make_nexus_schema_dictionary(substrate_object, layers):
return pld_fabrication
def build_nexus_file(pld_fabrication, output_path, rheed_osc=None):
def build_nexus_file(pld_fabrication, output_path, rheed_osc=None, heatmap_matrix=None):
# NOTE: look at the mail attachment from Emiliano...
with h5py.File(output_path, "w") as f:
nx_pld_entry = f.create_group("pld_fabrication")
@@ -645,10 +645,10 @@ def build_nexus_file(pld_fabrication, output_path, rheed_osc=None):
raise TypeError(te)
# RHEED data section
if rheed_osc is not None:
nx_rheed = nx_pld_entry.create_group("rheed_data")
nx_rheed.attrs["NX_class"] = "NXdata"
nx_rheed = nx_pld_entry.create_group("rheed_data")
nx_rheed.attrs["NX_class"] = "NXdata"
if rheed_osc is not None:
# Asse temporale
t_ds = nx_rheed.create_dataset("time", data=rheed_osc["time"])
t_ds.attrs["units"] = "s"
@@ -682,6 +682,14 @@ def build_nexus_file(pld_fabrication, output_path, rheed_osc=None):
# nx_rheed.attrs["layer_indices"] = [0] # asse layer
# nx_rheed.attrs["time_indices"] = [1] # asse tempo
# nx_rheed.attrs["channel_indices"] = [2]
if heatmap_matrix is not None:
heatmap = nx_rheed.create_dataset("diffraction_image", data=heatmap_matrix)
heatmap.attrs["long_name"] = "Diffraction Image"
heatmap.attrs["units"] = "a.u."
# this is of my own initiative. good???
heatmap.attrs["interpretation"] = "spectrum"
# suggested by DeepSeek, useful?
heatmap.attrs["suggested_colormap"] = "viridis"
return
@@ -721,9 +729,12 @@ if __name__ == "__main__":
# TO-DO: make it format-agnostic. If not possible, make it PNG-only.
if os.path.isfile("tests/LAO_16min50s_736C_STO.bmp"): # if BMP
# if os.path.isfile("tests/LAO_16min50s_736C_STO.png"): # if PNG
with open() as img:
img = Image.open("tests/LAO_16min50s_736C_STO.bmp").convert("L")
mx = np.array(img, dtype=np.uint8)
img = Image.open("tests/LAO_16min50s_736C_STO.bmp").convert("L")
mx = np.array(img, dtype=np.uint8)
normalized_mx = mx.astype(np.float32) / 255.0 # consider deleting???
build_nexus_file(
result, output_path=f"output/sample-{sample_name}-nexus.h5", rheed_osc=rheed_osc
result,
output_path=f"output/sample-{sample_name}-nexus.h5",
rheed_osc=rheed_osc,
heatmap_matrix=normalized_mx,
)