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Commit 1e1409d8 authored by Gröne, Tjark Leon Raphael's avatar Gröne, Tjark Leon Raphael
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Update file maxwell_integrate_to_h5.py

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maxwell_integrate_to_h5.py
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...@@ -136,44 +136,117 @@ def integrate_ims_in_dir(path_im, path_int, dtype_im=".tif", dtype_int=".dat"): ...@@ -136,44 +136,117 @@ def integrate_ims_in_dir(path_im, path_int, dtype_im=".tif", dtype_int=".dat"):
print(f"File {output_file} already exists. Removing it to create a new one.") print(f"File {output_file} already exists. Removing it to create a new one.")
os.remove(output_file) os.remove(output_file)
with h5py.File(output_file, "w") as f:
# Top-level NXroot
nxroot = f.create_group(subdir_name)
nxroot.attrs["NX_class"] = np.string_("NXroot")
nxroot.attrs["default"] = np.string_("1.1")
for idx, result in enumerate(results_data, start=1): with h5py.File(output_file, "w") as h5:
entry_name = f"{idx}.1" entry = h5.create_group(f"/{subdir_name}")
entry = nxroot.create_group(entry_name) entry.attrs["NX_class"] = "NXentry"
entry.attrs["NX_class"] = np.string_("NXentry") entry.attrs["default"] = "last_plot" # reference to the last spectrum
entry.attrs["default"] = np.string_("plotdata")
# Create full measurement group
meas = entry.create_group("measurement")
meas.attrs["NX_class"] = np.string_("NXcollection")
meas.attrs["filename"] = np.string_(result["filename"])
meas.create_dataset("q", data=result["q"])
meas.create_dataset("I", data=result["I"])
meas.create_dataset("dI", data=result["dI"])
# Create plotdata group with proper NXdata spec
plot = entry.create_group("plotdata")
plot.attrs["NX_class"] = np.string_("NXdata")
plot.attrs["signal"] = np.string_("I")
plot.attrs["axes"] = np.string_("q")
plot.attrs["title"] = np.string_(result["filename"])
plot.create_dataset("q", data=result["q"])
dset_I = plot.create_dataset("I", data=result["I"])
dset_I.attrs["long_name"] = np.string_(result["filename"])
plot["I"].attrs["long_name"] = "Intensity"
plot["q"].attrs["long_name"] = "Ang^-1"
plot.create_dataset("dI", data=result["dI"])
plot["dI"].attrs["long_name"] = np.string_("Uncertainty in I")
for idx, result in enumerate(results_data, start=1):
scan_name = f"{idx:03d}" # e.g., '001'
scan_group = entry.create_group(scan_name)
# Instrument / Detector group
detector = scan_group.create_group("instrument/detector")
detector.attrs["NX_class"] = "NXdetector"
chunk_size = min(len(result["I"]), 1000)
detector.create_dataset("q", data=np.asarray(result["q"], dtype=np.float64), chunks=(chunk_size,))
detector.create_dataset("I", data=np.asarray(result["I"], dtype=np.float64), chunks=(chunk_size,))
detector.create_dataset("dI", data=np.asarray(result["dI"], dtype=np.float64), chunks=(chunk_size,))
# Add interpretation info (optional for PyMca)
detector["I"].attrs["interpretation"] = "spectrum"
# Measurement group (holds soft links)
meas = scan_group.create_group("measurement")
meas.attrs["NX_class"] = "NXdata"
meas.attrs["signal"] = "I"
meas.attrs["axes"] = "q"
meas.attrs["filename"] = result["filename"]
meas["I"] = h5py.SoftLink(f"/{subdir_name}/{scan_name}/instrument/detector/I")
meas["q"] = h5py.SoftLink(f"/{subdir_name}/{scan_name}/instrument/detector/q")
meas["dI"] = h5py.SoftLink(f"/{subdir_name}/{scan_name}/instrument/detector/dI")
# Optional display-friendly names
meas["I"].attrs["long_name"] = "Intensity"
meas["q"].attrs["long_name"] = "Q [1/A]"
# For PyMca auto-plot:
scan_group.attrs["default"] = "measurement"
# Optional global default plot group
if idx == len(results_data): # mark the last one as global default
entry["last_plot"] = h5py.SoftLink(f"/{subdir_name}/{scan_name}/measurement")
# Title or metadata
entry["title"] = "Collected Q-I scans"
h5.flush()
# h5 = h5py.File(output_file, "w")
# h5["/entry/instrument/q/data"] = result["q"]
# h5["/entry/instrument/I/data"] = result["I"]
# h5["/entry/instrument/dI/data"] = result["dI"]
# h5["/entry/title"] = subdir_name
# h5["/entry"].attrs["NX_class"] = u"NXentry"
# h5["/entry/instrument"].attrs["NX_class"] = u"NXinstrument"
# h5["/entry/instrument/q/"].attrs["NX_class"] = u"NXdetector"
# h5["/entry/instrument/I/"].attrs["NX_class"] = u"NXdetector"
# h5["/entry/instrument/dI/"].attrs["NX_class"] = u"NXdetector"
# h5["/entry/instrument/q/data"].attrs["interpretation"] = u"Dataset"
# h5["/entry/instrument/I/data"].attrs["interpretation"] = u"Dataset"
# h5["/entry/instrument/dI/data"].attrs["interpretation"] = u"Dataset"
# h5["/entry/measurement/q"] = h5py.SoftLink("/entry/instrument/q/data")
# h5["/entry/measurement/I"] = h5py.SoftLink("/entry/instrument/I/data")
# h5["/entry/measurement/dI"] = h5py.SoftLink("/entry/instrument/dI/data")
# h5["/entry/measurement"].attrs["NX_class"] = u"NXcollection"
# h5["/entry/measurement"].attrs["signal"] = u"I"
# h5["/entry"].attrs["default"] = u"measurement"
# # Top-level NXroot
# nxroot = f.create_group(subdir_name)
# nxroot.attrs["NX_class"] = np.string_("NXroot")
# nxroot.attrs["default"] = np.string_("1.1")
# for idx, result in enumerate(results_data, start=1):
# entry_name = f"{idx}.1"
# entry = nxroot.create_group(entry_name)
# entry.attrs["NX_class"] = np.string_("NXentry")
# entry.attrs["default"] = np.string_("plotdata")
# # Create full measurement group
# meas = entry.create_group("measurement")
# meas.attrs["NX_class"] = np.string_("NXcollection")
# meas.attrs["filename"] = np.string_(result["filename"])
# meas.create_dataset("q", data=result["q"])
# meas.create_dataset("I", data=result["I"])
# meas.create_dataset("dI", data=result["dI"])
# # Create plotdata group with proper NXdata spec
# plot = entry.create_group("plotdata")
# plot.attrs["NX_class"] = np.string_("NXdata")
# plot.attrs["signal"] = np.string_("I")
# plot.attrs["axes"] = np.string_("q")
# plot.attrs["title"] = np.string_(result["filename"])
# plot.create_dataset("q", data=result["q"])
# dset_I = plot.create_dataset("I", data=result["I"])
# dset_I.attrs["long_name"] = np.string_(result["filename"])
# plot["I"].attrs["long_name"] = "Intensity"
# plot["q"].attrs["long_name"] = "Ang^-1"
# plot.create_dataset("dI", data=result["dI"])
# plot["dI"].attrs["long_name"] = np.string_("Uncertainty in I")
h5.flush()
h5.close()
print(f"✅ HDF5 file '{output_file}' created with {len(results_data)} spectra.") print(f"✅ HDF5 file '{output_file}' created with {len(results_data)} spectra.")
# # Sort results_data by filename # # Sort results_data by filename
# def natural_sort_key(item): # def natural_sort_key(item):
......
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