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feat: fill in the known physical coordinates from edd.SetupNXdataProc…
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…essor. Also give data_types to all variables in the same Reader.
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@keara-soloway
keara-soloway committed Oct 11, 2024
1 parent b285cc0 commit d3cc1a1
Showing 1 changed file with 50 additions and 16 deletions.
66 changes: 50 additions & 16 deletions CHAP/edd/reader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -540,8 +540,8 @@ def read(self, filename, dataset_id, detectors=None):
# 14 + 4n: lower bound
# 15 + 4n: upper bound
# 16 + 4n: no. points
# (For scan types 1, 4: n = 1)
# (For scan types 2, 3, 5: n = 1 or 2)
# (For scan types 1, 4: n = 0)
# (For scan types 2, 3, 5: n = 0 or 1)

# For scan type 5 only:
# 21: bin axis
Expand Down Expand Up @@ -575,37 +575,37 @@ def read(self, filename, dataset_id, detectors=None):
# UNstructured with a single actual coordinate
# (dataset_pont_index).
signals = [
{'name': 'labx', 'shape': [],
{'name': 'labx', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'labx',
'data_type': 'smb_par'}},
{'name': 'laby', 'shape': [],
{'name': 'laby', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'laby',
'data_type': 'smb_par'}},
{'name': 'labz', 'shape': [],
{'name': 'labz', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'labz',
'data_type': 'smb_par'}},
{'name': 'ometotal', 'shape': [],
{'name': 'ometotal', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'degrees', 'local_name': 'ometotal',
'data_type': 'smb_par'}},
{'name': 'presample_intensity', 'shape': [],
{'name': 'presample_intensity', 'shape': [], 'dtype': 'uint64',
'attrs': {'units': 'counts', 'local_name': 'a3ic1',
'data_type': 'scan_column'}},
{'name': 'postsample_intensity', 'shape': [],
{'name': 'postsample_intensity', 'shape': [], 'dtype': 'uint64',
'attrs': {'units': 'counts', 'local_name': 'diode',
'data_type': 'scan_column'}},
{'name': 'dwell_time_actual', 'shape': [],
{'name': 'dwell_time_actual', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'seconds', 'local_name': 'sec',
'data_type': 'scan_column'}},
{'name': 'SCAN_N', 'shape': [],
{'name': 'SCAN_N', 'shape': [], 'dtype': 'uint8',
'attrs': {'units': 'n/a', 'local_name': 'SCAN_N',
'data_type': 'smb_par'}},
{'name': 'rsgap_size', 'shape': [],
{'name': 'rsgap_size', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'rsgap_size',
'data_type': 'smb_par'}},
{'name': 'x_effective', 'shape': [],
{'name': 'x_effective', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'x_effective',
'data_type': 'smb_par'}},
{'name': 'z_effective', 'shape': [],
{'name': 'z_effective', 'shape': [], 'dtype': 'float64',
'attrs': {'units': 'mm', 'local_name': 'z_effective',
'data_type': 'smb_par'}},
]
Expand All @@ -617,7 +617,7 @@ def read(self, filename, dataset_id, detectors=None):
detector_config = DetectorConfig(detectors=detectors)
for d in detector_config.detectors:
signals.append(
{'name': d.id, 'attrs': d.attrs,
{'name': d.id, 'attrs': d.attrs, 'dtype': 'uint64',
'shape': d.attrs.get('shape', (4096,))})

# Attributes to attach for use by edd.StrainAnalysisProcessor:
Expand All @@ -630,6 +630,7 @@ def read(self, filename, dataset_id, detectors=None):
# of the dataset. Also find the number of points / scan.
if scan_type == 0:
scan_npts = 1
fly_axis_values = None
else:
self.logger.warning(
'Assuming scan parameters are identical for all scans.')
Expand All @@ -644,6 +645,11 @@ def read(self, filename, dataset_id, detectors=None):
})
scan_npts = dataset_lines[0][16]
fly_axis_labels = [axes_labels[dataset_lines[0][13]]]
fly_axis_values = {fly_axis_labels[0]:
np.round(np.linspace(
dataset_lines[0][14], dataset_lines[0][15],
dataset_lines[0][16]), 3)}
scan_shape = (len(fly_axis_values[fly_axis_labels[0]]),)
if scan_type in (2, 3, 5):
signals.append({
'name': axes_labels[dataset_lines[0][17]],
Expand All @@ -655,14 +661,42 @@ def read(self, filename, dataset_id, detectors=None):
if scan_type == 5:
attrs['bin_axis'] = axes_labels[dataset_lines[0][21]]
fly_axis_labels.append(axes_labels[dataset_lines[0][17]])
fly_axis_values[fly_axis_labels[-1]] = np.round(
np.linspace(dataset_lines[0][18], dataset_lines[0][19],
dataset_lines[0][20]), 3)
scan_shape = (*scan_shape,
len(fly_axis_values[fly_axis_labels[-1]]))
attrs['fly_axis_labels'] = fly_axis_labels

# Set up the single unstructured dataset coordinate
dataset_npts = len(dataset_lines) * scan_npts
coords = [{'name': 'dataset_point_index',
'values': list(range(len(dataset_lines) * scan_npts)),
'values': list(range(dataset_npts)),
'attrs': {'units': 'n/a'}}]

return {'coords': coords, 'signals': signals, 'attrs': attrs}
# Set up the list of data_points to fill out the known values
# of the physical "coordinates"
data_points = []
for i in range(dataset_npts):
l = dataset_lines[i // scan_npts]
data_point = {
'dataset_point_index': i,
'labx': l[3], 'laby': l[4], 'labz': l[5],
'ometotal': l[6] + l[7]}
if fly_axis_values:
scan_step_index = i % scan_npts
scan_steps = np.ndindex(scan_shape[::-1])
ii = 0
while ii <= scan_step_index:
scan_step = next(scan_steps)
ii += 1
scan_step_indices = scan_step[::-1]
for iii, (k, v) in enumerate(fly_axis_values.items()):
data_point[k] = v[scan_step_indices[iii]]
data_points.append(data_point)

return {'coords': coords, 'signals': signals,
'attrs': attrs, 'data_points': data_points}


class UpdateNXdataReader(Reader):
Expand Down

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