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Utility renames and hdf_param_study simplification

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This commit is contained in:
usov_i 2022-01-27 16:11:52 +01:00
parent 10bcabd7f9
commit bcd594fa7e
8 changed files with 286 additions and 282 deletions
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58
pyzebra/app/panel_ccl_compare.py
View File

@ -72,8 +72,8 @@ for (let i = 0; i < js_data.data['fname'].length; i++) {
def create(): def create():
doc = curdoc() doc = curdoc()
det_data1 = [] dataset1 = []
det_data2 = [] dataset2 = []
fit_params = {} fit_params = {}
js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""])) js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
@ -99,17 +99,17 @@ def create():
proposal_textinput.on_change("name", proposal_textinput_callback) proposal_textinput.on_change("name", proposal_textinput_callback)
def _init_datatable(): def _init_datatable():
# det_data2 should have the same metadata to det_data1 # dataset2 should have the same metadata as dataset1
scan_list = [s["idx"] for s in det_data1] scan_list = [s["idx"] for s in dataset1]
hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in det_data1] hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in dataset1]
export = [s["export"] for s in det_data1] export = [s["export"] for s in dataset1]
twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in det_data1] twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in dataset1]
gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in det_data1] gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in dataset1]
omega = [np.median(s["omega"]) if "omega" in s else None for s in det_data1] omega = [np.median(s["omega"]) if "omega" in s else None for s in dataset1]
chi = [np.median(s["chi"]) if "chi" in s else None for s in det_data1] chi = [np.median(s["chi"]) if "chi" in s else None for s in dataset1]
phi = [np.median(s["phi"]) if "phi" in s else None for s in det_data1] phi = [np.median(s["phi"]) if "phi" in s else None for s in dataset1]
nu = [np.median(s["nu"]) if "nu" in s else None for s in det_data1] nu = [np.median(s["nu"]) if "nu" in s else None for s in dataset1]
scan_table_source.data.update( scan_table_source.data.update(
scan=scan_list, scan=scan_list,
@ -163,9 +163,9 @@ def create():
new_data1 = new_data1[:min_len] new_data1 = new_data1[:min_len]
new_data2 = new_data2[:min_len] new_data2 = new_data2[:min_len]
nonlocal det_data1, det_data2 nonlocal dataset1, dataset2
det_data1 = new_data1 dataset1 = new_data1
det_data2 = new_data2 dataset2 = new_data2
_init_datatable() _init_datatable()
file_open_button = Button(label="Open New", width=100, disabled=True) file_open_button = Button(label="Open New", width=100, disabled=True)
@ -201,9 +201,9 @@ def create():
new_data1 = new_data1[:min_len] new_data1 = new_data1[:min_len]
new_data2 = new_data2[:min_len] new_data2 = new_data2[:min_len]
nonlocal det_data1, det_data2 nonlocal dataset1, dataset2
det_data1 = new_data1 dataset1 = new_data1
det_data2 = new_data2 dataset2 = new_data2
_init_datatable() _init_datatable()
upload_div = Div(text="or upload 2 .ccl files:", margin=(5, 5, 0, 5)) upload_div = Div(text="or upload 2 .ccl files:", margin=(5, 5, 0, 5))
@ -213,17 +213,17 @@ def create():
upload_button.on_change("filename", upload_button_callback) upload_button.on_change("filename", upload_button_callback)
def monitor_spinner_callback(_attr, old, new): def monitor_spinner_callback(_attr, old, new):
if det_data1 and det_data2: if dataset1 and dataset2:
pyzebra.normalize_dataset(det_data1, new) pyzebra.normalize_dataset(dataset1, new)
pyzebra.normalize_dataset(det_data2, new) pyzebra.normalize_dataset(dataset2, new)
_update_plot() _update_plot()
monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145) monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145)
monitor_spinner.on_change("value", monitor_spinner_callback) monitor_spinner.on_change("value", monitor_spinner_callback)
def _update_table(): def _update_table():
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data1] fit_ok = [(1 if "fit" in scan else 0) for scan in dataset1]
export = [scan["export"] for scan in det_data1] export = [scan["export"] for scan in dataset1]
scan_table_source.data.update(fit=fit_ok, export=export) scan_table_source.data.update(fit=fit_ok, export=export)
def _update_plot(): def _update_plot():
@ -382,7 +382,7 @@ def create():
def scan_table_source_callback(_attr, _old, new): def scan_table_source_callback(_attr, _old, new):
# unfortunately, we don't know if the change comes from data update or user input # unfortunately, we don't know if the change comes from data update or user input
# also `old` and `new` are the same for non-scalars # also `old` and `new` are the same for non-scalars
for scan1, scan2, export in zip(det_data1, det_data2, new["export"]): for scan1, scan2, export in zip(dataset1, dataset2, new["export"]):
scan1["export"] = export scan1["export"] = export
scan2["export"] = export scan2["export"] = export
_update_preview() _update_preview()
@ -426,14 +426,14 @@ def create():
def _get_selected_scan(): def _get_selected_scan():
ind = scan_table_source.selected.indices[0] ind = scan_table_source.selected.indices[0]
return det_data1[ind], det_data2[ind] return dataset1[ind], dataset2[ind]
merge_from_select = Select(title="scan:", width=145) merge_from_select = Select(title="scan:", width=145)
def merge_button_callback(): def merge_button_callback():
scan_into1, scan_into2 = _get_selected_scan() scan_into1, scan_into2 = _get_selected_scan()
scan_from1 = det_data1[int(merge_from_select.value)] scan_from1 = dataset1[int(merge_from_select.value)]
scan_from2 = det_data2[int(merge_from_select.value)] scan_from2 = dataset2[int(merge_from_select.value)]
if scan_into1 is scan_from1: if scan_into1 is scan_from1:
print("WARNING: Selected scans for merging are identical") print("WARNING: Selected scans for merging are identical")
@ -577,7 +577,7 @@ def create():
fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200) fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
def proc_all_button_callback(): def proc_all_button_callback():
for scan in [*det_data1, *det_data2]: for scan in [*dataset1, *dataset2]:
if scan["export"]: if scan["export"]:
pyzebra.fit_scan( pyzebra.fit_scan(
scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@ -628,7 +628,7 @@ def create():
temp_file = temp_dir + "/temp" temp_file = temp_dir + "/temp"
export_data1 = [] export_data1 = []
export_data2 = [] export_data2 = []
for scan1, scan2 in zip(det_data1, det_data2): for scan1, scan2 in zip(dataset1, dataset2):
if scan1["export"]: if scan1["export"]:
export_data1.append(scan1) export_data1.append(scan1)
export_data2.append(scan2) export_data2.append(scan2)

50
pyzebra/app/panel_ccl_integrate.py
View File

@ -72,7 +72,7 @@ for (let i = 0; i < js_data.data['fname'].length; i++) {
def create(): def create():
doc = curdoc() doc = curdoc()
det_data = [] dataset = []
fit_params = {} fit_params = {}
js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""])) js_data = ColumnDataSource(data=dict(content=["", ""], fname=["", ""], ext=["", ""]))
@ -100,16 +100,16 @@ def create():
proposal_textinput.on_change("name", proposal_textinput_callback) proposal_textinput.on_change("name", proposal_textinput_callback)
def _init_datatable(): def _init_datatable():
scan_list = [s["idx"] for s in det_data] scan_list = [s["idx"] for s in dataset]
hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in det_data] hkl = [f'{s["h"]} {s["k"]} {s["l"]}' for s in dataset]
export = [s["export"] for s in det_data] export = [s["export"] for s in dataset]
twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in det_data] twotheta = [np.median(s["twotheta"]) if "twotheta" in s else None for s in dataset]
gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in det_data] gamma = [np.median(s["gamma"]) if "gamma" in s else None for s in dataset]
omega = [np.median(s["omega"]) if "omega" in s else None for s in det_data] omega = [np.median(s["omega"]) if "omega" in s else None for s in dataset]
chi = [np.median(s["chi"]) if "chi" in s else None for s in det_data] chi = [np.median(s["chi"]) if "chi" in s else None for s in dataset]
phi = [np.median(s["phi"]) if "phi" in s else None for s in det_data] phi = [np.median(s["phi"]) if "phi" in s else None for s in dataset]
nu = [np.median(s["nu"]) if "nu" in s else None for s in det_data] nu = [np.median(s["nu"]) if "nu" in s else None for s in dataset]
scan_table_source.data.update( scan_table_source.data.update(
scan=scan_list, scan=scan_list,
@ -133,7 +133,7 @@ def create():
file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250) file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250)
def file_open_button_callback(): def file_open_button_callback():
nonlocal det_data nonlocal dataset
new_data = [] new_data = []
for f_path in file_select.value: for f_path in file_select.value:
with open(f_path) as file: with open(f_path) as file:
@ -155,7 +155,7 @@ def create():
pyzebra.merge_datasets(new_data, file_data) pyzebra.merge_datasets(new_data, file_data)
if new_data: if new_data:
det_data = new_data dataset = new_data
_init_datatable() _init_datatable()
append_upload_button.disabled = False append_upload_button.disabled = False
@ -175,7 +175,7 @@ def create():
continue continue
pyzebra.normalize_dataset(file_data, monitor_spinner.value) pyzebra.normalize_dataset(file_data, monitor_spinner.value)
pyzebra.merge_datasets(det_data, file_data) pyzebra.merge_datasets(dataset, file_data)
if file_data: if file_data:
_init_datatable() _init_datatable()
@ -184,7 +184,7 @@ def create():
file_append_button.on_click(file_append_button_callback) file_append_button.on_click(file_append_button_callback)
def upload_button_callback(_attr, _old, _new): def upload_button_callback(_attr, _old, _new):
nonlocal det_data nonlocal dataset
new_data = [] new_data = []
for f_str, f_name in zip(upload_button.value, upload_button.filename): for f_str, f_name in zip(upload_button.value, upload_button.filename):
with io.StringIO(base64.b64decode(f_str).decode()) as file: with io.StringIO(base64.b64decode(f_str).decode()) as file:
@ -205,7 +205,7 @@ def create():
pyzebra.merge_datasets(new_data, file_data) pyzebra.merge_datasets(new_data, file_data)
if new_data: if new_data:
det_data = new_data dataset = new_data
_init_datatable() _init_datatable()
append_upload_button.disabled = False append_upload_button.disabled = False
@ -227,7 +227,7 @@ def create():
continue continue
pyzebra.normalize_dataset(file_data, monitor_spinner.value) pyzebra.normalize_dataset(file_data, monitor_spinner.value)
pyzebra.merge_datasets(det_data, file_data) pyzebra.merge_datasets(dataset, file_data)
if file_data: if file_data:
_init_datatable() _init_datatable()
@ -239,16 +239,16 @@ def create():
append_upload_button.on_change("filename", append_upload_button_callback) append_upload_button.on_change("filename", append_upload_button_callback)
def monitor_spinner_callback(_attr, old, new): def monitor_spinner_callback(_attr, old, new):
if det_data: if dataset:
pyzebra.normalize_dataset(det_data, new) pyzebra.normalize_dataset(dataset, new)
_update_plot() _update_plot()
monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145) monitor_spinner = Spinner(title="Monitor:", mode="int", value=100_000, low=1, width=145)
monitor_spinner.on_change("value", monitor_spinner_callback) monitor_spinner.on_change("value", monitor_spinner_callback)
def _update_table(): def _update_table():
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data] fit_ok = [(1 if "fit" in scan else 0) for scan in dataset]
export = [scan["export"] for scan in det_data] export = [scan["export"] for scan in dataset]
scan_table_source.data.update(fit=fit_ok, export=export) scan_table_source.data.update(fit=fit_ok, export=export)
def _update_plot(): def _update_plot():
@ -368,7 +368,7 @@ def create():
def scan_table_source_callback(_attr, _old, new): def scan_table_source_callback(_attr, _old, new):
# unfortunately, we don't know if the change comes from data update or user input # unfortunately, we don't know if the change comes from data update or user input
# also `old` and `new` are the same for non-scalars # also `old` and `new` are the same for non-scalars
for scan, export in zip(det_data, new["export"]): for scan, export in zip(dataset, new["export"]):
scan["export"] = export scan["export"] = export
_update_preview() _update_preview()
@ -410,13 +410,13 @@ def create():
) )
def _get_selected_scan(): def _get_selected_scan():
return det_data[scan_table_source.selected.indices[0]] return dataset[scan_table_source.selected.indices[0]]
merge_from_select = Select(title="scan:", width=145) merge_from_select = Select(title="scan:", width=145)
def merge_button_callback(): def merge_button_callback():
scan_into = _get_selected_scan() scan_into = _get_selected_scan()
scan_from = det_data[int(merge_from_select.value)] scan_from = dataset[int(merge_from_select.value)]
if scan_into is scan_from: if scan_into is scan_from:
print("WARNING: Selected scans for merging are identical") print("WARNING: Selected scans for merging are identical")
@ -557,7 +557,7 @@ def create():
fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200) fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
def proc_all_button_callback(): def proc_all_button_callback():
for scan in det_data: for scan in dataset:
if scan["export"]: if scan["export"]:
pyzebra.fit_scan( pyzebra.fit_scan(
scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@ -602,7 +602,7 @@ def create():
with tempfile.TemporaryDirectory() as temp_dir: with tempfile.TemporaryDirectory() as temp_dir:
temp_file = temp_dir + "/temp" temp_file = temp_dir + "/temp"
export_data = [] export_data = []
for scan in det_data: for scan in dataset:
if scan["export"]: if scan["export"]:
export_data.append(scan) export_data.append(scan)

60
pyzebra/app/panel_hdf_param_study.py
View File

@ -48,8 +48,7 @@ IMAGE_PLOT_H = int(IMAGE_H * 2) + 27
def create(): def create():
doc = curdoc() doc = curdoc()
zebra_data = [] dataset = []
det_data = {}
cami_meta = {} cami_meta = {}
num_formatter = NumberFormatter(format="0.00", nan_format="") num_formatter = NumberFormatter(format="0.00", nan_format="")
@ -108,15 +107,15 @@ def create():
def _init_datatable(): def _init_datatable():
file_list = [] file_list = []
for scan in zebra_data: for scan in dataset:
file_list.append(os.path.basename(scan["original_filename"])) file_list.append(os.path.basename(scan["original_filename"]))
scan_table_source.data.update( scan_table_source.data.update(
file=file_list, file=file_list,
param=[None] * len(zebra_data), param=[None] * len(dataset),
frame=[None] * len(zebra_data), frame=[None] * len(dataset),
x_pos=[None] * len(zebra_data), x_pos=[None] * len(dataset),
y_pos=[None] * len(zebra_data), y_pos=[None] * len(dataset),
) )
scan_table_source.selected.indices = [] scan_table_source.selected.indices = []
scan_table_source.selected.indices = [0] scan_table_source.selected.indices = [0]
@ -127,7 +126,7 @@ def create():
frame = [] frame = []
x_pos = [] x_pos = []
y_pos = [] y_pos = []
for scan in zebra_data: for scan in dataset:
if "fit" in scan: if "fit" in scan:
framei = scan["fit"]["frame"] framei = scan["fit"]["frame"]
x_posi = scan["fit"]["x_pos"] x_posi = scan["fit"]["x_pos"]
@ -150,13 +149,13 @@ def create():
print("Could not read data from the file.") print("Could not read data from the file.")
return return
zebra_data.extend(new_data) dataset.extend(new_data)
_init_datatable() _init_datatable()
def file_open_button_callback(): def file_open_button_callback():
nonlocal zebra_data nonlocal dataset
zebra_data = [] dataset = []
_file_open() _file_open()
file_open_button = Button(label="Open New", width=100) file_open_button = Button(label="Open New", width=100)
@ -170,8 +169,6 @@ def create():
# Scan select # Scan select
def scan_table_select_callback(_attr, old, new): def scan_table_select_callback(_attr, old, new):
nonlocal det_data
if not new: if not new:
# skip empty selections # skip empty selections
return return
@ -186,21 +183,21 @@ def create():
# skip unnecessary update caused by selection drop # skip unnecessary update caused by selection drop
return return
det_data = zebra_data[new[0]] scan = dataset[new[0]]
zebra_mode = det_data["zebra_mode"] zebra_mode = scan["zebra_mode"]
if zebra_mode == "nb": if zebra_mode == "nb":
metadata_table_source.data.update(geom=["normal beam"]) metadata_table_source.data.update(geom=["normal beam"])
else: # zebra_mode == "bi" else: # zebra_mode == "bi"
metadata_table_source.data.update(geom=["bisecting"]) metadata_table_source.data.update(geom=["bisecting"])
if "mf" in det_data: if "mf" in scan:
metadata_table_source.data.update(mf=[det_data["mf"][0]]) metadata_table_source.data.update(mf=[scan["mf"][0]])
else: else:
metadata_table_source.data.update(mf=[None]) metadata_table_source.data.update(mf=[None])
if "temp" in det_data: if "temp" in scan:
metadata_table_source.data.update(temp=[det_data["temp"][0]]) metadata_table_source.data.update(temp=[scan["temp"][0]])
else: else:
metadata_table_source.data.update(temp=[None]) metadata_table_source.data.update(temp=[None])
@ -240,12 +237,15 @@ def create():
autosize_mode="none", autosize_mode="none",
) )
def _get_selected_scan():
return dataset[scan_table_source.selected.indices[0]]
def param_select_callback(_attr, _old, new): def param_select_callback(_attr, _old, new):
if new == "user defined": if new == "user defined":
param = [None] * len(zebra_data) param = [None] * len(dataset)
else: else:
# TODO: which value to take? # TODO: which value to take?
param = [scan[new][0] for scan in zebra_data] param = [scan[new][0] for scan in dataset]
scan_table_source.data["param"] = param scan_table_source.data["param"] = param
_update_param_plot() _update_param_plot()
@ -259,7 +259,8 @@ def create():
param_select.on_change("value", param_select_callback) param_select.on_change("value", param_select_callback)
def update_overview_plot(): def update_overview_plot():
h5_data = det_data["data"] scan = _get_selected_scan()
h5_data = scan["data"]
n_im, n_y, n_x = h5_data.shape n_im, n_y, n_x = h5_data.shape
overview_x = np.mean(h5_data, axis=1) overview_x = np.mean(h5_data, axis=1)
overview_y = np.mean(h5_data, axis=2) overview_y = np.mean(h5_data, axis=2)
@ -290,10 +291,10 @@ def create():
frame_range.reset_end = n_im frame_range.reset_end = n_im
frame_range.bounds = (0, n_im) frame_range.bounds = (0, n_im)
scan_motor = det_data["scan_motor"] scan_motor = scan["scan_motor"]
overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}" overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}"
var = det_data[scan_motor] var = scan[scan_motor]
var_start = var[0] var_start = var[0]
var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1) var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1)
@ -470,7 +471,7 @@ def create():
x = [] x = []
y = [] y = []
fit_param = fit_param_select.value fit_param = fit_param_select.value
for s, p in zip(zebra_data, scan_table_source.data["param"]): for s, p in zip(dataset, scan_table_source.data["param"]):
if "fit" in s and fit_param: if "fit" in s and fit_param:
x.append(p) x.append(p)
y.append(s["fit"][fit_param]) y.append(s["fit"][fit_param])
@ -498,7 +499,7 @@ def create():
fit_param_select.on_change("value", fit_param_select_callback) fit_param_select.on_change("value", fit_param_select_callback)
def proc_all_button_callback(): def proc_all_button_callback():
for scan in zebra_data: for scan in dataset:
pyzebra.fit_event( pyzebra.fit_event(
scan, scan,
int(np.floor(frame_range.start)), int(np.floor(frame_range.start)),
@ -511,7 +512,7 @@ def create():
_update_table() _update_table()
for scan in zebra_data: for scan in dataset:
if "fit" in scan: if "fit" in scan:
options = list(scan["fit"].keys()) options = list(scan["fit"].keys())
fit_param_select.options = options fit_param_select.options = options
@ -524,8 +525,9 @@ def create():
proc_all_button.on_click(proc_all_button_callback) proc_all_button.on_click(proc_all_button_callback)
def proc_button_callback(): def proc_button_callback():
scan = _get_selected_scan()
pyzebra.fit_event( pyzebra.fit_event(
det_data, scan,
int(np.floor(frame_range.start)), int(np.floor(frame_range.start)),
int(np.ceil(frame_range.end)), int(np.ceil(frame_range.end)),
int(np.floor(det_y_range.start)), int(np.floor(det_y_range.start)),
@ -536,7 +538,7 @@ def create():
_update_table() _update_table()
for scan in zebra_data: for scan in dataset:
if "fit" in scan: if "fit" in scan:
options = list(scan["fit"].keys()) options = list(scan["fit"].keys())
fit_param_select.options = options fit_param_select.options = options

114
pyzebra/app/panel_hdf_viewer.py
View File

@ -52,7 +52,7 @@ IMAGE_PLOT_H = int(IMAGE_H * 2) + 27
def create(): def create():
doc = curdoc() doc = curdoc()
det_data = {} scan = {}
cami_meta = {} cami_meta = {}
num_formatter = NumberFormatter(format="0.00", nan_format="") num_formatter = NumberFormatter(format="0.00", nan_format="")
@ -108,14 +108,14 @@ def create():
upload_cami_button.on_change("value", upload_cami_button_callback) upload_cami_button.on_change("value", upload_cami_button_callback)
def _file_open(file, cami_meta): def _file_open(file, cami_meta):
nonlocal det_data nonlocal scan
try: try:
det_data = pyzebra.read_detector_data(file, cami_meta) scan = pyzebra.read_detector_data(file, cami_meta)
except KeyError: except KeyError:
print("Could not read data from the file.") print("Could not read data from the file.")
return return
last_im_index = det_data["data"].shape[0] - 1 last_im_index = scan["data"].shape[0] - 1
index_spinner.value = 0 index_spinner.value = 0
index_spinner.high = last_im_index index_spinner.high = last_im_index
@ -125,7 +125,7 @@ def create():
index_slider.disabled = False index_slider.disabled = False
index_slider.end = last_im_index index_slider.end = last_im_index
zebra_mode = det_data["zebra_mode"] zebra_mode = scan["zebra_mode"]
if zebra_mode == "nb": if zebra_mode == "nb":
metadata_table_source.data.update(geom=["normal beam"]) metadata_table_source.data.update(geom=["normal beam"])
else: # zebra_mode == "bi" else: # zebra_mode == "bi"
@ -157,7 +157,7 @@ def create():
if index is None: if index is None:
index = index_spinner.value index = index_spinner.value
current_image = det_data["data"][index] current_image = scan["data"][index]
proj_v_line_source.data.update( proj_v_line_source.data.update(
x=np.arange(0, IMAGE_W) + 0.5, y=np.mean(current_image, axis=0) x=np.arange(0, IMAGE_W) + 0.5, y=np.mean(current_image, axis=0)
) )
@ -180,24 +180,24 @@ def create():
image_glyph.color_mapper.low = im_min image_glyph.color_mapper.low = im_min
image_glyph.color_mapper.high = im_max image_glyph.color_mapper.high = im_max
if "mf" in det_data: if "mf" in scan:
metadata_table_source.data.update(mf=[det_data["mf"][index]]) metadata_table_source.data.update(mf=[scan["mf"][index]])
else: else:
metadata_table_source.data.update(mf=[None]) metadata_table_source.data.update(mf=[None])
if "temp" in det_data: if "temp" in scan:
metadata_table_source.data.update(temp=[det_data["temp"][index]]) metadata_table_source.data.update(temp=[scan["temp"][index]])
else: else:
metadata_table_source.data.update(temp=[None]) metadata_table_source.data.update(temp=[None])
gamma, nu = calculate_pol(det_data, index) gamma, nu = calculate_pol(scan, index)
omega = np.ones((IMAGE_H, IMAGE_W)) * det_data["omega"][index] omega = np.ones((IMAGE_H, IMAGE_W)) * scan["omega"][index]
image_source.data.update(gamma=[gamma], nu=[nu], omega=[omega]) image_source.data.update(gamma=[gamma], nu=[nu], omega=[omega])
# update detector center angles # update detector center angles
det_c_x = int(IMAGE_W / 2) det_c_x = int(IMAGE_W / 2)
det_c_y = int(IMAGE_H / 2) det_c_y = int(IMAGE_H / 2)
if det_data["zebra_mode"] == "nb": if scan["zebra_mode"] == "nb":
gamma_c = gamma[det_c_y, det_c_x] gamma_c = gamma[det_c_y, det_c_x]
nu_c = nu[det_c_y, det_c_x] nu_c = nu[det_c_y, det_c_x]
omega_c = omega[det_c_y, det_c_x] omega_c = omega[det_c_y, det_c_x]
@ -205,13 +205,13 @@ def create():
phi_c = None phi_c = None
else: # zebra_mode == "bi" else: # zebra_mode == "bi"
wave = det_data["wave"] wave = scan["wave"]
ddist = det_data["ddist"] ddist = scan["ddist"]
gammad = det_data["gamma"][index] gammad = scan["gamma"][index]
om = det_data["omega"][index] om = scan["omega"][index]
ch = det_data["chi"][index] ch = scan["chi"][index]
ph = det_data["phi"][index] ph = scan["phi"][index]
nud = det_data["nu"] nud = scan["nu"]
nu_c = 0 nu_c = 0
chi_c, phi_c, gamma_c, omega_c = pyzebra.ang_proc( chi_c, phi_c, gamma_c, omega_c = pyzebra.ang_proc(
@ -223,7 +223,7 @@ def create():
) )
def update_overview_plot(): def update_overview_plot():
h5_data = det_data["data"] h5_data = scan["data"]
n_im, n_y, n_x = h5_data.shape n_im, n_y, n_x = h5_data.shape
overview_x = np.mean(h5_data, axis=1) overview_x = np.mean(h5_data, axis=1)
overview_y = np.mean(h5_data, axis=2) overview_y = np.mean(h5_data, axis=2)
@ -254,10 +254,10 @@ def create():
frame_range.reset_end = n_im frame_range.reset_end = n_im
frame_range.bounds = (0, n_im) frame_range.bounds = (0, n_im)
scan_motor = det_data["scan_motor"] scan_motor = scan["scan_motor"]
overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}" overview_plot_y.axis[1].axis_label = f"Scanning motor, {scan_motor}"
var = det_data[scan_motor] var = scan[scan_motor]
var_start = var[0] var_start = var[0]
var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1) if n_im != 1 else var_start + 1 var_end = var[-1] + (var[-1] - var[0]) / (n_im - 1) if n_im != 1 else var_start + 1
@ -374,9 +374,9 @@ def create():
# calculate hkl-indices of first mouse entry # calculate hkl-indices of first mouse entry
def mouse_enter_callback(_event): def mouse_enter_callback(_event):
if det_data and np.array_equal(image_source.data["h"][0], np.zeros((1, 1))): if scan and np.array_equal(image_source.data["h"][0], np.zeros((1, 1))):
index = index_spinner.value index = index_spinner.value
h, k, l = calculate_hkl(det_data, index) h, k, l = calculate_hkl(scan, index)
image_source.data.update(h=[h], k=[k], l=[l]) image_source.data.update(h=[h], k=[k], l=[l])
plot.on_event(MouseEnter, mouse_enter_callback) plot.on_event(MouseEnter, mouse_enter_callback)
@ -438,7 +438,7 @@ def create():
def box_edit_callback(_attr, _old, new): def box_edit_callback(_attr, _old, new):
if new["x"]: if new["x"]:
h5_data = det_data["data"] h5_data = scan["data"]
x_val = np.arange(h5_data.shape[0]) x_val = np.arange(h5_data.shape[0])
left = int(np.floor(new["x"][0])) left = int(np.floor(new["x"][0]))
right = int(np.ceil(new["x"][0] + new["width"][0])) right = int(np.ceil(new["x"][0] + new["width"][0]))
@ -739,7 +739,7 @@ def create():
def add_event_button_callback(): def add_event_button_callback():
pyzebra.fit_event( pyzebra.fit_event(
det_data, scan,
int(np.floor(frame_range.start)), int(np.floor(frame_range.start)),
int(np.ceil(frame_range.end)), int(np.ceil(frame_range.end)),
int(np.floor(det_y_range.start)), int(np.floor(det_y_range.start)),
@ -748,21 +748,21 @@ def create():
int(np.ceil(det_x_range.end)), int(np.ceil(det_x_range.end)),
) )
wave = det_data["wave"] wave = scan["wave"]
ddist = det_data["ddist"] ddist = scan["ddist"]
cell = det_data["cell"] cell = scan["cell"]
gamma = det_data["gamma"][0] gamma = scan["gamma"][0]
omega = det_data["omega"][0] omega = scan["omega"][0]
nu = det_data["nu"][0] nu = scan["nu"][0]
chi = det_data["chi"][0] chi = scan["chi"][0]
phi = det_data["phi"][0] phi = scan["phi"][0]
scan_motor = det_data["scan_motor"] scan_motor = scan["scan_motor"]
var_angle = det_data[scan_motor] var_angle = scan[scan_motor]
snr_cnts = det_data["fit"]["snr"] snr_cnts = scan["fit"]["snr"]
frC = det_data["fit"]["frame"] frC = scan["fit"]["frame"]
var_F = var_angle[int(np.floor(frC))] var_F = var_angle[int(np.floor(frC))]
var_C = var_angle[int(np.ceil(frC))] var_C = var_angle[int(np.ceil(frC))]
@ -781,11 +781,11 @@ def create():
elif scan_motor == "phi": elif scan_motor == "phi":
phi = var_p phi = var_p
intensity = det_data["fit"]["intensity"] intensity = scan["fit"]["intensity"]
x_pos = det_data["fit"]["x_pos"] x_pos = scan["fit"]["x_pos"]
y_pos = det_data["fit"]["y_pos"] y_pos = scan["fit"]["y_pos"]
if det_data["zebra_mode"] == "nb": if scan["zebra_mode"] == "nb":
chi = None chi = None
phi = None phi = None
@ -883,22 +883,22 @@ def create():
return Panel(child=tab_layout, title="hdf viewer") return Panel(child=tab_layout, title="hdf viewer")
def calculate_hkl(det_data, index): def calculate_hkl(scan, index):
h = np.empty(shape=(IMAGE_H, IMAGE_W)) h = np.empty(shape=(IMAGE_H, IMAGE_W))
k = np.empty(shape=(IMAGE_H, IMAGE_W)) k = np.empty(shape=(IMAGE_H, IMAGE_W))
l = np.empty(shape=(IMAGE_H, IMAGE_W)) l = np.empty(shape=(IMAGE_H, IMAGE_W))
wave = det_data["wave"] wave = scan["wave"]
ddist = det_data["ddist"] ddist = scan["ddist"]
gammad = det_data["gamma"][index] gammad = scan["gamma"][index]
om = det_data["omega"][index] om = scan["omega"][index]
nud = det_data["nu"] nud = scan["nu"]
ub = det_data["ub"] ub = scan["ub"]
geometry = det_data["zebra_mode"] geometry = scan["zebra_mode"]
if geometry == "bi": if geometry == "bi":
chi = det_data["chi"][index] chi = scan["chi"][index]
phi = det_data["phi"][index] phi = scan["phi"][index]
elif geometry == "nb": elif geometry == "nb":
chi = 0 chi = 0
phi = 0 phi = 0
@ -914,10 +914,10 @@ def calculate_hkl(det_data, index):
return h, k, l return h, k, l
def calculate_pol(det_data, index): def calculate_pol(scan, index):
ddist = det_data["ddist"] ddist = scan["ddist"]
gammad = det_data["gamma"][index] gammad = scan["gamma"][index]
nud = det_data["nu"] nud = scan["nu"]
yi, xi = np.ogrid[:IMAGE_H, :IMAGE_W] yi, xi = np.ogrid[:IMAGE_H, :IMAGE_W]
gamma, nu = pyzebra.det2pol(ddist, gammad, nud, xi, yi) gamma, nu = pyzebra.det2pol(ddist, gammad, nud, xi, yi)

66
pyzebra/app/panel_param_study.py
View File

@ -83,7 +83,7 @@ def color_palette(n_colors):
def create(): def create():
doc = curdoc() doc = curdoc()
det_data = [] dataset = []
fit_params = {} fit_params = {}
js_data = ColumnDataSource(data=dict(content=[""], fname=[""], ext=[""])) js_data = ColumnDataSource(data=dict(content=[""], fname=[""], ext=[""]))
@ -111,15 +111,15 @@ def create():
proposal_textinput.on_change("name", proposal_textinput_callback) proposal_textinput.on_change("name", proposal_textinput_callback)
def _init_datatable(): def _init_datatable():
scan_list = [s["idx"] for s in det_data] scan_list = [s["idx"] for s in dataset]
export = [s["export"] for s in det_data] export = [s["export"] for s in dataset]
if param_select.value == "user defined": if param_select.value == "user defined":
param = [None] * len(det_data) param = [None] * len(dataset)
else: else:
param = [scan[param_select.value] for scan in det_data] param = [scan[param_select.value] for scan in dataset]
file_list = [] file_list = []
for scan in det_data: for scan in dataset:
file_list.append(os.path.basename(scan["original_filename"])) file_list.append(os.path.basename(scan["original_filename"]))
scan_table_source.data.update( scan_table_source.data.update(
@ -128,8 +128,8 @@ def create():
scan_table_source.selected.indices = [] scan_table_source.selected.indices = []
scan_table_source.selected.indices = [0] scan_table_source.selected.indices = [0]
scan_motor_select.options = det_data[0]["scan_motors"] scan_motor_select.options = dataset[0]["scan_motors"]
scan_motor_select.value = det_data[0]["scan_motor"] scan_motor_select.value = dataset[0]["scan_motor"]
merge_options = [(str(i), f"{i} ({idx})") for i, idx in enumerate(scan_list)] merge_options = [(str(i), f"{i} ({idx})") for i, idx in enumerate(scan_list)]
merge_from_select.options = merge_options merge_from_select.options = merge_options
@ -138,7 +138,7 @@ def create():
file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250) file_select = MultiSelect(title="Available .ccl/.dat files:", width=210, height=250)
def file_open_button_callback(): def file_open_button_callback():
nonlocal det_data nonlocal dataset
new_data = [] new_data = []
for f_path in file_select.value: for f_path in file_select.value:
with open(f_path) as file: with open(f_path) as file:
@ -160,7 +160,7 @@ def create():
pyzebra.merge_datasets(new_data, file_data) pyzebra.merge_datasets(new_data, file_data)
if new_data: if new_data:
det_data = new_data dataset = new_data
_init_datatable() _init_datatable()
append_upload_button.disabled = False append_upload_button.disabled = False
@ -180,7 +180,7 @@ def create():
continue continue
pyzebra.normalize_dataset(file_data, monitor_spinner.value) pyzebra.normalize_dataset(file_data, monitor_spinner.value)
pyzebra.merge_datasets(det_data, file_data) pyzebra.merge_datasets(dataset, file_data)
if file_data: if file_data:
_init_datatable() _init_datatable()
@ -189,7 +189,7 @@ def create():
file_append_button.on_click(file_append_button_callback) file_append_button.on_click(file_append_button_callback)
def upload_button_callback(_attr, _old, _new): def upload_button_callback(_attr, _old, _new):
nonlocal det_data nonlocal dataset
new_data = [] new_data = []
for f_str, f_name in zip(upload_button.value, upload_button.filename): for f_str, f_name in zip(upload_button.value, upload_button.filename):
with io.StringIO(base64.b64decode(f_str).decode()) as file: with io.StringIO(base64.b64decode(f_str).decode()) as file:
@ -210,7 +210,7 @@ def create():
pyzebra.merge_datasets(new_data, file_data) pyzebra.merge_datasets(new_data, file_data)
if new_data: if new_data:
det_data = new_data dataset = new_data
_init_datatable() _init_datatable()
append_upload_button.disabled = False append_upload_button.disabled = False
@ -232,7 +232,7 @@ def create():
continue continue
pyzebra.normalize_dataset(file_data, monitor_spinner.value) pyzebra.normalize_dataset(file_data, monitor_spinner.value)
pyzebra.merge_datasets(det_data, file_data) pyzebra.merge_datasets(dataset, file_data)
if file_data: if file_data:
_init_datatable() _init_datatable()
@ -244,8 +244,8 @@ def create():
append_upload_button.on_change("filename", append_upload_button_callback) append_upload_button.on_change("filename", append_upload_button_callback)
def monitor_spinner_callback(_attr, _old, new): def monitor_spinner_callback(_attr, _old, new):
if det_data: if dataset:
pyzebra.normalize_dataset(det_data, new) pyzebra.normalize_dataset(dataset, new)
_update_single_scan_plot() _update_single_scan_plot()
_update_overview() _update_overview()
@ -253,8 +253,8 @@ def create():
monitor_spinner.on_change("value", monitor_spinner_callback) monitor_spinner.on_change("value", monitor_spinner_callback)
def scan_motor_select_callback(_attr, _old, new): def scan_motor_select_callback(_attr, _old, new):
if det_data: if dataset:
for scan in det_data: for scan in dataset:
scan["scan_motor"] = new scan["scan_motor"] = new
_update_single_scan_plot() _update_single_scan_plot()
_update_overview() _update_overview()
@ -263,12 +263,12 @@ def create():
scan_motor_select.on_change("value", scan_motor_select_callback) scan_motor_select.on_change("value", scan_motor_select_callback)
def _update_table(): def _update_table():
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data] fit_ok = [(1 if "fit" in scan else 0) for scan in dataset]
export = [scan["export"] for scan in det_data] export = [scan["export"] for scan in dataset]
if param_select.value == "user defined": if param_select.value == "user defined":
param = [None] * len(det_data) param = [None] * len(dataset)
else: else:
param = [scan[param_select.value] for scan in det_data] param = [scan[param_select.value] for scan in dataset]
scan_table_source.data.update(fit=fit_ok, export=export, param=param) scan_table_source.data.update(fit=fit_ok, export=export, param=param)
@ -322,7 +322,7 @@ def create():
par = [] par = []
for s, p in enumerate(scan_table_source.data["param"]): for s, p in enumerate(scan_table_source.data["param"]):
if p is not None: if p is not None:
scan = det_data[s] scan = dataset[s]
scan_motor = scan["scan_motor"] scan_motor = scan["scan_motor"]
xs.append(scan[scan_motor]) xs.append(scan[scan_motor])
x.extend(scan[scan_motor]) x.extend(scan[scan_motor])
@ -331,8 +331,8 @@ def create():
param.append(float(p)) param.append(float(p))
par.extend(scan["counts"]) par.extend(scan["counts"])
if det_data: if dataset:
scan_motor = det_data[0]["scan_motor"] scan_motor = dataset[0]["scan_motor"]
ov_plot.axis[0].axis_label = scan_motor ov_plot.axis[0].axis_label = scan_motor
ov_param_plot.axis[0].axis_label = scan_motor ov_param_plot.axis[0].axis_label = scan_motor
@ -371,7 +371,7 @@ def create():
y_lower = [] y_lower = []
y_upper = [] y_upper = []
fit_param = fit_param_select.value fit_param = fit_param_select.value
for s, p in zip(det_data, scan_table_source.data["param"]): for s, p in zip(dataset, scan_table_source.data["param"]):
if "fit" in s and fit_param: if "fit" in s and fit_param:
x.append(p) x.append(p)
param_fit_val = s["fit"].params[fit_param].value param_fit_val = s["fit"].params[fit_param].value
@ -534,7 +534,7 @@ def create():
def scan_table_source_callback(_attr, _old, new): def scan_table_source_callback(_attr, _old, new):
# unfortunately, we don't know if the change comes from data update or user input # unfortunately, we don't know if the change comes from data update or user input
# also `old` and `new` are the same for non-scalars # also `old` and `new` are the same for non-scalars
for scan, export in zip(det_data, new["export"]): for scan, export in zip(dataset, new["export"]):
scan["export"] = export scan["export"] = export
_update_overview() _update_overview()
_update_param_plot() _update_param_plot()
@ -563,7 +563,7 @@ def create():
def merge_button_callback(): def merge_button_callback():
scan_into = _get_selected_scan() scan_into = _get_selected_scan()
scan_from = det_data[int(merge_from_select.value)] scan_from = dataset[int(merge_from_select.value)]
if scan_into is scan_from: if scan_into is scan_from:
print("WARNING: Selected scans for merging are identical") print("WARNING: Selected scans for merging are identical")
@ -587,7 +587,7 @@ def create():
restore_button.on_click(restore_button_callback) restore_button.on_click(restore_button_callback)
def _get_selected_scan(): def _get_selected_scan():
return det_data[scan_table_source.selected.indices[0]] return dataset[scan_table_source.selected.indices[0]]
def param_select_callback(_attr, _old, _new): def param_select_callback(_attr, _old, _new):
_update_table() _update_table()
@ -720,7 +720,7 @@ def create():
fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200) fit_output_textinput = TextAreaInput(title="Fit results:", width=750, height=200)
def proc_all_button_callback(): def proc_all_button_callback():
for scan in det_data: for scan in dataset:
if scan["export"]: if scan["export"]:
pyzebra.fit_scan( pyzebra.fit_scan(
scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value scan, fit_params, fit_from=fit_from_spinner.value, fit_to=fit_to_spinner.value
@ -735,7 +735,7 @@ def create():
_update_overview() _update_overview()
_update_table() _update_table()
for scan in det_data: for scan in dataset:
if "fit" in scan: if "fit" in scan:
options = list(scan["fit"].params.keys()) options = list(scan["fit"].params.keys())
fit_param_select.options = options fit_param_select.options = options
@ -760,7 +760,7 @@ def create():
_update_overview() _update_overview()
_update_table() _update_table()
for scan in det_data: for scan in dataset:
if "fit" in scan: if "fit" in scan:
options = list(scan["fit"].params.keys()) options = list(scan["fit"].params.keys())
fit_param_select.options = options fit_param_select.options = options
@ -782,7 +782,7 @@ def create():
temp_file = temp_dir + "/temp" temp_file = temp_dir + "/temp"
export_data = [] export_data = []
param_data = [] param_data = []
for scan, param in zip(det_data, scan_table_source.data["param"]): for scan, param in zip(dataset, scan_table_source.data["param"]):
if scan["export"] and param: if scan["export"] and param:
export_data.append(scan) export_data.append(scan)
param_data.append(param) param_data.append(param)

104
pyzebra/ccl_io.py
View File

@ -93,9 +93,9 @@ def load_1D(filepath):
""" """
with open(filepath, "r") as infile: with open(filepath, "r") as infile:
_, ext = os.path.splitext(filepath) _, ext = os.path.splitext(filepath)
det_variables = parse_1D(infile, data_type=ext) dataset = parse_1D(infile, data_type=ext)
return det_variables return dataset
def parse_1D(fileobj, data_type): def parse_1D(fileobj, data_type):
@ -133,7 +133,7 @@ def parse_1D(fileobj, data_type):
metadata["zebra_mode"] = "nb" metadata["zebra_mode"] = "nb"
# read data # read data
scan = [] dataset = []
if data_type == ".ccl": if data_type == ".ccl":
ccl_first_line = CCL_FIRST_LINE + CCL_ANGLES[metadata["zebra_mode"]] ccl_first_line = CCL_FIRST_LINE + CCL_ANGLES[metadata["zebra_mode"]]
ccl_second_line = CCL_SECOND_LINE ccl_second_line = CCL_SECOND_LINE
@ -143,47 +143,49 @@ def parse_1D(fileobj, data_type):
if not line or line.isspace(): if not line or line.isspace():
continue continue
s = {} scan = {}
s["export"] = True scan["export"] = True
# first line # first line
for param, (param_name, param_type) in zip(line.split(), ccl_first_line): for param, (param_name, param_type) in zip(line.split(), ccl_first_line):
s[param_name] = param_type(param) scan[param_name] = param_type(param)
# second line # second line
next_line = next(fileobj) next_line = next(fileobj)
for param, (param_name, param_type) in zip(next_line.split(), ccl_second_line): for param, (param_name, param_type) in zip(next_line.split(), ccl_second_line):
s[param_name] = param_type(param) scan[param_name] = param_type(param)
if s["scan_motor"] != "om": if scan["scan_motor"] != "om":
raise Exception("Unsupported variable name in ccl file.") raise Exception("Unsupported variable name in ccl file.")
# "om" -> "omega" # "om" -> "omega"
s["scan_motor"] = "omega" scan["scan_motor"] = "omega"
s["scan_motors"] = ["omega", ] scan["scan_motors"] = ["omega", ]
# overwrite metadata, because it only refers to the scan center # overwrite metadata, because it only refers to the scan center
half_dist = (s["n_points"] - 1) / 2 * s["angle_step"] half_dist = (scan["n_points"] - 1) / 2 * scan["angle_step"]
s["omega"] = np.linspace(s["omega"] - half_dist, s["omega"] + half_dist, s["n_points"]) scan["omega"] = np.linspace(
scan["omega"] - half_dist, scan["omega"] + half_dist, scan["n_points"]
)
# subsequent lines with counts # subsequent lines with counts
counts = [] counts = []
while len(counts) < s["n_points"]: while len(counts) < scan["n_points"]:
counts.extend(map(float, next(fileobj).split())) counts.extend(map(float, next(fileobj).split()))
s["counts"] = np.array(counts) scan["counts"] = np.array(counts)
s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1)) scan["counts_err"] = np.sqrt(np.maximum(scan["counts"], 1))
if s["h"].is_integer() and s["k"].is_integer() and s["l"].is_integer(): if scan["h"].is_integer() and scan["k"].is_integer() and scan["l"].is_integer():
s["h"], s["k"], s["l"] = map(int, (s["h"], s["k"], s["l"])) scan["h"], scan["k"], scan["l"] = map(int, (scan["h"], scan["k"], scan["l"]))
scan.append({**metadata, **s}) dataset.append({**metadata, **scan})
elif data_type == ".dat": elif data_type == ".dat":
# TODO: this might need to be adapted in the future, when "gamma" will be added to dat files # TODO: this might need to be adapted in the future, when "gamma" will be added to dat files
if metadata["zebra_mode"] == "nb": if metadata["zebra_mode"] == "nb":
metadata["gamma"] = metadata["twotheta"] metadata["gamma"] = metadata["twotheta"]
s = defaultdict(list) scan = defaultdict(list)
s["export"] = True scan["export"] = True
match = re.search("Scanning Variables: (.*), Steps: (.*)", next(fileobj)) match = re.search("Scanning Variables: (.*), Steps: (.*)", next(fileobj))
motors = [motor.lower() for motor in match.group(1).split(", ")] motors = [motor.lower() for motor in match.group(1).split(", ")]
@ -192,8 +194,8 @@ def parse_1D(fileobj, data_type):
match = re.search("(.*) Points, Mode: (.*), Preset (.*)", next(fileobj)) match = re.search("(.*) Points, Mode: (.*), Preset (.*)", next(fileobj))
if match.group(2) != "Monitor": if match.group(2) != "Monitor":
raise Exception("Unknown mode in dat file.") raise Exception("Unknown mode in dat file.")
s["n_points"] = int(match.group(1)) scan["n_points"] = int(match.group(1))
s["monitor"] = float(match.group(3)) scan["monitor"] = float(match.group(3))
col_names = list(map(str.lower, next(fileobj).split())) col_names = list(map(str.lower, next(fileobj).split()))
@ -203,56 +205,56 @@ def parse_1D(fileobj, data_type):
break break
for name, val in zip(col_names, line.split()): for name, val in zip(col_names, line.split()):
s[name].append(float(val)) scan[name].append(float(val))
for name in col_names: for name in col_names:
s[name] = np.array(s[name]) scan[name] = np.array(scan[name])
s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1)) scan["counts_err"] = np.sqrt(np.maximum(scan["counts"], 1))
s["scan_motors"] = [] scan["scan_motors"] = []
for motor, step in zip(motors, steps): for motor, step in zip(motors, steps):
if step == 0: if step == 0:
# it's not a scan motor, so keep only the median value # it's not a scan motor, so keep only the median value
s[motor] = np.median(s[motor]) scan[motor] = np.median(scan[motor])
else: else:
s["scan_motors"].append(motor) scan["scan_motors"].append(motor)
# "om" -> "omega" # "om" -> "omega"
if "om" in s["scan_motors"]: if "om" in scan["scan_motors"]:
s["scan_motors"][s["scan_motors"].index("om")] = "omega" scan["scan_motors"][scan["scan_motors"].index("om")] = "omega"
s["omega"] = s["om"] scan["omega"] = scan["om"]
del s["om"] del scan["om"]
# "tt" -> "temp" # "tt" -> "temp"
if "tt" in s["scan_motors"]: if "tt" in scan["scan_motors"]:
s["scan_motors"][s["scan_motors"].index("tt")] = "temp" scan["scan_motors"][scan["scan_motors"].index("tt")] = "temp"
s["temp"] = s["tt"] scan["temp"] = scan["tt"]
del s["tt"] del scan["tt"]
# "mf" stays "mf" # "mf" stays "mf"
# "phi" stays "phi" # "phi" stays "phi"
s["scan_motor"] = s["scan_motors"][0] scan["scan_motor"] = scan["scan_motors"][0]
if "h" not in s: if "h" not in scan:
s["h"] = s["k"] = s["l"] = float("nan") scan["h"] = scan["k"] = scan["l"] = float("nan")
for param in ("mf", "temp"): for param in ("mf", "temp"):
if param not in metadata: if param not in metadata:
s[param] = 0 scan[param] = 0
s["idx"] = 1 scan["idx"] = 1
scan.append({**metadata, **s}) dataset.append({**metadata, **scan})
else: else:
print("Unknown file extention") print("Unknown file extention")
return scan return dataset
def export_1D(data, path, export_target, hkl_precision=2): def export_1D(dataset, path, export_target, hkl_precision=2):
"""Exports data in the .comm/.incomm format for fullprof or .col/.incol format for jana. """Exports data in the .comm/.incomm format for fullprof or .col/.incol format for jana.
Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files
@ -262,11 +264,11 @@ def export_1D(data, path, export_target, hkl_precision=2):
if export_target not in EXPORT_TARGETS: if export_target not in EXPORT_TARGETS:
raise ValueError(f"Unknown export target: {export_target}.") raise ValueError(f"Unknown export target: {export_target}.")
zebra_mode = data[0]["zebra_mode"] zebra_mode = dataset[0]["zebra_mode"]
exts = EXPORT_TARGETS[export_target] exts = EXPORT_TARGETS[export_target]
file_content = {ext: [] for ext in exts} file_content = {ext: [] for ext in exts}
for scan in data: for scan in dataset:
if "fit" not in scan: if "fit" not in scan:
continue continue
@ -306,7 +308,7 @@ def export_1D(data, path, export_target, hkl_precision=2):
out_file.writelines(content) out_file.writelines(content)
def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2): def export_ccl_compare(dataset1, dataset2, path, export_target, hkl_precision=2):
"""Exports compare data in the .comm/.incomm format for fullprof or .col/.incol format for jana. """Exports compare data in the .comm/.incomm format for fullprof or .col/.incol format for jana.
Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files Scans with integer/real hkl values are saved in .comm/.incomm or .col/.incol files
@ -316,11 +318,11 @@ def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2):
if export_target not in EXPORT_TARGETS: if export_target not in EXPORT_TARGETS:
raise ValueError(f"Unknown export target: {export_target}.") raise ValueError(f"Unknown export target: {export_target}.")
zebra_mode = data1[0]["zebra_mode"] zebra_mode = dataset1[0]["zebra_mode"]
exts = EXPORT_TARGETS[export_target] exts = EXPORT_TARGETS[export_target]
file_content = {ext: [] for ext in exts} file_content = {ext: [] for ext in exts}
for scan1, scan2 in zip(data1, data2): for scan1, scan2 in zip(dataset1, dataset2):
if "fit" not in scan1: if "fit" not in scan1:
continue continue
@ -363,9 +365,9 @@ def export_ccl_compare(data1, data2, path, export_target, hkl_precision=2):
out_file.writelines(content) out_file.writelines(content)
def export_param_study(data, param_data, path): def export_param_study(dataset, param_data, path):
file_content = [] file_content = []
for scan, param in zip(data, param_data): for scan, param in zip(dataset, param_data):
if "fit" not in scan: if "fit" not in scan:
continue continue

30
pyzebra/ccl_process.py
View File

@ -1,7 +1,7 @@
import os import os
import numpy as np import numpy as np
from lmfit.models import Gaussian2dModel, GaussianModel, LinearModel, PseudoVoigtModel, VoigtModel from lmfit.models import GaussianModel, LinearModel, PseudoVoigtModel, VoigtModel
from scipy.integrate import simpson, trapezoid from scipy.integrate import simpson, trapezoid
from .ccl_io import CCL_ANGLES from .ccl_io import CCL_ANGLES
@ -259,31 +259,3 @@ def get_area(scan, area_method, lorentz):
area_s = np.abs(area_s * corr_factor) area_s = np.abs(area_s * corr_factor)
scan["area"] = (area_v, area_s) scan["area"] = (area_v, area_s)
def fit_event(scan, fr_from, fr_to, y_from, y_to, x_from, x_to):
data_roi = scan["data"][fr_from:fr_to, y_from:y_to, x_from:x_to]
model = GaussianModel()
fr = np.arange(fr_from, fr_to)
counts_per_fr = np.sum(data_roi, axis=(1, 2))
params = model.guess(counts_per_fr, fr)
result = model.fit(counts_per_fr, x=fr, params=params)
frC = result.params["center"].value
intensity = result.params["height"].value
counts_std = counts_per_fr.std()
counts_mean = counts_per_fr.mean()
snr = 0 if counts_std == 0 else counts_mean / counts_std
model = Gaussian2dModel()
xs, ys = np.meshgrid(np.arange(x_from, x_to), np.arange(y_from, y_to))
xs = xs.flatten()
ys = ys.flatten()
counts = np.sum(data_roi, axis=0).flatten()
params = model.guess(counts, xs, ys)
result = model.fit(counts, x=xs, y=ys, params=params)
xC = result.params["centerx"].value
yC = result.params["centery"].value
scan["fit"] = {"frame": frC, "x_pos": xC, "y_pos": yC, "intensity": intensity, "snr": snr}

86
pyzebra/h5.py
View File

@ -1,6 +1,6 @@
import h5py import h5py
import numpy as np import numpy as np
from lmfit.models import Gaussian2dModel, GaussianModel
META_MATRIX = ("UB") META_MATRIX = ("UB")
META_CELL = ("cell") META_CELL = ("cell")
@ -74,69 +74,97 @@ def read_detector_data(filepath, cami_meta=None):
n, cols, rows = data.shape n, cols, rows = data.shape
data = data.reshape(n, rows, cols) data = data.reshape(n, rows, cols)
det_data = {"data": data} scan = {"data": data}
det_data["original_filename"] = filepath scan["original_filename"] = filepath
if "/entry1/zebra_mode" in h5f: if "/entry1/zebra_mode" in h5f:
det_data["zebra_mode"] = h5f["/entry1/zebra_mode"][0].decode() scan["zebra_mode"] = h5f["/entry1/zebra_mode"][0].decode()
else: else:
det_data["zebra_mode"] = "nb" scan["zebra_mode"] = "nb"
# overwrite zebra_mode from cami # overwrite zebra_mode from cami
if cami_meta is not None: if cami_meta is not None:
if "zebra_mode" in cami_meta: if "zebra_mode" in cami_meta:
det_data["zebra_mode"] = cami_meta["zebra_mode"][0] scan["zebra_mode"] = cami_meta["zebra_mode"][0]
# om, sometimes ph # om, sometimes ph
if det_data["zebra_mode"] == "nb": if scan["zebra_mode"] == "nb":
det_data["omega"] = h5f["/entry1/area_detector2/rotation_angle"][:] scan["omega"] = h5f["/entry1/area_detector2/rotation_angle"][:]
else: # bi else: # bi
det_data["omega"] = h5f["/entry1/sample/rotation_angle"][:] scan["omega"] = h5f["/entry1/sample/rotation_angle"][:]
det_data["gamma"] = h5f["/entry1/ZEBRA/area_detector2/polar_angle"][:] # gammad scan["gamma"] = h5f["/entry1/ZEBRA/area_detector2/polar_angle"][:] # gammad
det_data["nu"] = h5f["/entry1/ZEBRA/area_detector2/tilt_angle"][:] # nud scan["nu"] = h5f["/entry1/ZEBRA/area_detector2/tilt_angle"][:] # nud
det_data["ddist"] = h5f["/entry1/ZEBRA/area_detector2/distance"][:] scan["ddist"] = h5f["/entry1/ZEBRA/area_detector2/distance"][:]
det_data["wave"] = h5f["/entry1/ZEBRA/monochromator/wavelength"][:] scan["wave"] = h5f["/entry1/ZEBRA/monochromator/wavelength"][:]
det_data["chi"] = h5f["/entry1/sample/chi"][:] # ch scan["chi"] = h5f["/entry1/sample/chi"][:] # ch
det_data["phi"] = h5f["/entry1/sample/phi"][:] # ph scan["phi"] = h5f["/entry1/sample/phi"][:] # ph
det_data["ub"] = h5f["/entry1/sample/UB"][:].reshape(3, 3) scan["ub"] = h5f["/entry1/sample/UB"][:].reshape(3, 3)
det_data["name"] = h5f["/entry1/sample/name"][0].decode() scan["name"] = h5f["/entry1/sample/name"][0].decode()
det_data["cell"] = h5f["/entry1/sample/cell"][:] scan["cell"] = h5f["/entry1/sample/cell"][:]
if n == 1: if n == 1:
# a default motor for a single frame file # a default motor for a single frame file
det_data["scan_motor"] = "omega" scan["scan_motor"] = "omega"
else: else:
for var in ("omega", "gamma", "nu", "chi", "phi"): for var in ("omega", "gamma", "nu", "chi", "phi"):
if abs(det_data[var][0] - det_data[var][-1]) > 0.1: if abs(scan[var][0] - scan[var][-1]) > 0.1:
det_data["scan_motor"] = var scan["scan_motor"] = var
break break
else: else:
raise ValueError("No angles that vary") raise ValueError("No angles that vary")
# optional parameters # optional parameters
if "/entry1/sample/magnetic_field" in h5f: if "/entry1/sample/magnetic_field" in h5f:
det_data["mf"] = h5f["/entry1/sample/magnetic_field"][:] scan["mf"] = h5f["/entry1/sample/magnetic_field"][:]
if "/entry1/sample/temperature" in h5f: if "/entry1/sample/temperature" in h5f:
det_data["temp"] = h5f["/entry1/sample/temperature"][:] scan["temp"] = h5f["/entry1/sample/temperature"][:]
# overwrite metadata from .cami # overwrite metadata from .cami
if cami_meta is not None: if cami_meta is not None:
if "crystal" in cami_meta: if "crystal" in cami_meta:
cami_meta_crystal = cami_meta["crystal"] cami_meta_crystal = cami_meta["crystal"]
if "name" in cami_meta_crystal: if "name" in cami_meta_crystal:
det_data["name"] = cami_meta_crystal["name"] scan["name"] = cami_meta_crystal["name"]
if "UB" in cami_meta_crystal: if "UB" in cami_meta_crystal:
det_data["ub"] = cami_meta_crystal["UB"] scan["ub"] = cami_meta_crystal["UB"]
if "cell" in cami_meta_crystal: if "cell" in cami_meta_crystal:
det_data["cell"] = cami_meta_crystal["cell"] scan["cell"] = cami_meta_crystal["cell"]
if "lambda" in cami_meta_crystal: if "lambda" in cami_meta_crystal:
det_data["wave"] = cami_meta_crystal["lambda"] scan["wave"] = cami_meta_crystal["lambda"]
if "detector parameters" in cami_meta: if "detector parameters" in cami_meta:
cami_meta_detparam = cami_meta["detector parameters"] cami_meta_detparam = cami_meta["detector parameters"]
if "dist2" in cami_meta_detparam: if "dist2" in cami_meta_detparam:
det_data["ddist"] = cami_meta_detparam["dist2"] scan["ddist"] = cami_meta_detparam["dist2"]
return det_data return scan
def fit_event(scan, fr_from, fr_to, y_from, y_to, x_from, x_to):
data_roi = scan["data"][fr_from:fr_to, y_from:y_to, x_from:x_to]
model = GaussianModel()
fr = np.arange(fr_from, fr_to)
counts_per_fr = np.sum(data_roi, axis=(1, 2))
params = model.guess(counts_per_fr, fr)
result = model.fit(counts_per_fr, x=fr, params=params)
frC = result.params["center"].value
intensity = result.params["height"].value
counts_std = counts_per_fr.std()
counts_mean = counts_per_fr.mean()
snr = 0 if counts_std == 0 else counts_mean / counts_std
model = Gaussian2dModel()
xs, ys = np.meshgrid(np.arange(x_from, x_to), np.arange(y_from, y_to))
xs = xs.flatten()
ys = ys.flatten()
counts = np.sum(data_roi, axis=0).flatten()
params = model.guess(counts, xs, ys)
result = model.fit(counts, x=xs, y=ys, params=params)
xC = result.params["centerx"].value
yC = result.params["centery"].value
scan["fit"] = {"frame": frC, "x_pos": xC, "y_pos": yC, "intensity": intensity, "snr": snr}