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Adapt param study to work with a set of dat files

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This commit is contained in:
usov_i 2020-11-23 16:07:31 +01:00
parent b19b70caae
commit c602a3df2e
2 changed files with 58 additions and 57 deletions
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113
pyzebra/app/panel_param_study.py
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@ -76,29 +76,24 @@ def create():
for file in os.listdir(ccl_path): for file in os.listdir(ccl_path):
if file.endswith(".ccl"): if file.endswith(".ccl"):
ccl_file_list.append((os.path.join(ccl_path, file), file)) ccl_file_list.append((os.path.join(ccl_path, file), file))
ccl_file_select.options = ccl_file_list file_select.options = ccl_file_list
ccl_file_select.value = ccl_file_list[0][0] file_select.value = ccl_file_list[0][0]
proposal_textinput = TextInput(title="Enter proposal number:", default_size=145) proposal_textinput = TextInput(title="Enter proposal number:", default_size=145, disabled=True)
proposal_textinput.on_change("value", proposal_textinput_callback) proposal_textinput.on_change("value", proposal_textinput_callback)
def _init_datatable(): def _init_datatable():
scan_list = list(det_data["scan"].keys())
hkl = [
f'{int(m["h_index"])} {int(m["k_index"])} {int(m["l_index"])}'
for m in det_data["scan"].values()
]
scan_table_source.data.update( scan_table_source.data.update(
scan=scan_list, file=list(det_data.keys()),
hkl=hkl, param=[""] * len(det_data),
peaks=[0] * len(scan_list), peaks=[0] * len(det_data),
fit=[0] * len(scan_list), fit=[0] * len(det_data),
export=[True] * len(scan_list), export=[True] * len(det_data),
) )
scan_table_source.selected.indices = [] scan_table_source.selected.indices = []
scan_table_source.selected.indices = [0] scan_table_source.selected.indices = [0]
def ccl_file_select_callback(_attr, _old, new): def file_select_callback(_attr, _old, new):
nonlocal det_data nonlocal det_data
with open(new) as file: with open(new) as file:
_, ext = os.path.splitext(new) _, ext = os.path.splitext(new)
@ -106,38 +101,37 @@ def create():
_init_datatable() _init_datatable()
ccl_file_select = Select(title="Available .ccl files") file_select = Select(title="Available .dat files", disabled=True)
ccl_file_select.on_change("value", ccl_file_select_callback) file_select.on_change("value", file_select_callback)
def upload_button_callback(_attr, _old, new): def upload_button_callback(_attr, _old, new):
nonlocal det_data nonlocal det_data
with io.StringIO(base64.b64decode(new).decode()) as file: det_data = {}
_, ext = os.path.splitext(upload_button.filename) for f_str, f_name in zip(new, upload_button.filename):
det_data = pyzebra.parse_1D(file, ext) with io.StringIO(base64.b64decode(f_str).decode()) as file:
_, ext = os.path.splitext(f_name)
det_data[f_name] = pyzebra.parse_1D(file, ext)
_init_datatable() _init_datatable()
upload_button = FileInput(accept=".ccl") upload_button = FileInput(accept=".dat", multiple=True)
upload_button.on_change("value", upload_button_callback) upload_button.on_change("value", upload_button_callback)
def append_upload_button_callback(_attr, _old, new): def append_upload_button_callback(_attr, _old, new):
nonlocal det_data nonlocal det_data
with io.StringIO(base64.b64decode(new).decode()) as file: for f_str, f_name in zip(new, append_upload_button.filename):
_, ext = os.path.splitext(append_upload_button.filename) with io.StringIO(base64.b64decode(f_str).decode()) as file:
append_data = pyzebra.parse_1D(file, ext) _, ext = os.path.splitext(f_name)
det_data[f_name] = pyzebra.parse_1D(file, ext)
added = pyzebra.add_dict(det_data, append_data)
scan_result = pyzebra.auto(pyzebra.scan_dict(added))
det_data = pyzebra.merge(added, added, scan_result)
_init_datatable() _init_datatable()
append_upload_button = FileInput(accept=".ccl,.dat") append_upload_button = FileInput(accept=".dat", multiple=True)
append_upload_button.on_change("value", append_upload_button_callback) append_upload_button.on_change("value", append_upload_button_callback)
def _update_table(): def _update_table():
num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"].values()] num_of_peaks = [len(scan["scan"][1].get("peak_indexes", [])) for scan in det_data.values()]
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"].values()] fit_ok = [(1 if "fit" in scan["scan"][1] else 0) for scan in det_data.values()]
scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok) scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
def _update_plot(scan): def _update_plot(scan):
@ -153,11 +147,11 @@ def create():
if num_of_peaks is not None and num_of_peaks > 0: if num_of_peaks is not None and num_of_peaks > 0:
peak_indexes = scan["peak_indexes"] peak_indexes = scan["peak_indexes"]
if len(peak_indexes) == 1: if len(peak_indexes) == 1:
peak_pos_textinput.value = str(scan["om"][peak_indexes[0]]) peak_pos_textinput.value = str(x[peak_indexes[0]])
else: else:
peak_pos_textinput.value = str([scan["om"][ind] for ind in peak_indexes]) peak_pos_textinput.value = str([x[ind] for ind in peak_indexes])
plot_peak_source.data.update(x=scan["om"][peak_indexes], y=scan["peak_heights"]) plot_peak_source.data.update(x=x[peak_indexes], y=scan["peak_heights"])
plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"]) plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"])
else: else:
peak_pos_textinput.value = None peak_pos_textinput.value = None
@ -261,29 +255,31 @@ def create():
# skip unnecessary update caused by selection drop # skip unnecessary update caused by selection drop
return return
_update_plot(det_data["scan"][scan_table_source.data["scan"][new[0]]]) f_name = scan_table_source.data["file"][new[0]]
_update_plot(det_data[f_name]["scan"][1])
scan_table_source = ColumnDataSource(dict(scan=[], hkl=[], peaks=[], fit=[], export=[])) scan_table_source = ColumnDataSource(dict(file=[], param=[], peaks=[], fit=[], export=[]))
scan_table = DataTable( scan_table = DataTable(
source=scan_table_source, source=scan_table_source,
columns=[ columns=[
TableColumn(field="scan", title="scan"), TableColumn(field="file", title="file", width=150),
TableColumn(field="hkl", title="hkl"), TableColumn(field="param", title="param", width=50),
TableColumn(field="peaks", title="Peaks"), TableColumn(field="peaks", title="Peaks", width=50),
TableColumn(field="fit", title="Fit"), TableColumn(field="fit", title="Fit", width=50),
TableColumn(field="export", title="Export", editor=CheckboxEditor()), TableColumn(field="export", title="Export", editor=CheckboxEditor(), width=50),
], ],
width=250, width=350,
index_position=None, index_position=None,
editable=True, editable=True,
fit_columns=False,
) )
scan_table_source.selected.on_change("indices", scan_table_select_callback) scan_table_source.selected.on_change("indices", scan_table_select_callback)
def _get_selected_scan(): def _get_selected_scan():
selected_index = scan_table_source.selected.indices[0] selected_index = scan_table_source.selected.indices[0]
selected_scan_id = scan_table_source.data["scan"][selected_index] selected_file_name = scan_table_source.data["file"][selected_index]
return det_data["scan"][selected_scan_id] return det_data[selected_file_name]["scan"][1]
def peak_pos_textinput_callback(_attr, _old, new): def peak_pos_textinput_callback(_attr, _old, new):
if new is not None and not peak_pos_textinput_lock: if new is not None and not peak_pos_textinput_lock:
@ -331,7 +327,6 @@ def create():
("Pseudo Voigt1", "pseudovoigt1"), ("Pseudo Voigt1", "pseudovoigt1"),
], ],
default_size=145, default_size=145,
disabled=True,
) )
fitparams_add_dropdown.on_click(fitparams_add_dropdown_callback) fitparams_add_dropdown.on_click(fitparams_add_dropdown_callback)
@ -366,7 +361,7 @@ def create():
fitparams_select.value = [] fitparams_select.value = []
fitparams_remove_button = Button(label="Remove fit function", default_size=145, disabled=True) fitparams_remove_button = Button(label="Remove fit function", default_size=145)
fitparams_remove_button.on_click(fitparams_remove_button_callback) fitparams_remove_button.on_click(fitparams_remove_button_callback)
def fitparams_factory(function): def fitparams_factory(function):
@ -424,8 +419,8 @@ def create():
def peakfind_all_button_callback(): def peakfind_all_button_callback():
peakfind_params = _get_peakfind_params() peakfind_params = _get_peakfind_params()
for scan in det_data["scan"].values(): for dat_file in det_data.values():
pyzebra.ccl_findpeaks(scan, **peakfind_params) pyzebra.ccl_findpeaks(dat_file["scan"][1], **peakfind_params)
_update_table() _update_table()
_update_plot(_get_selected_scan()) _update_plot(_get_selected_scan())
@ -456,9 +451,9 @@ def create():
def fit_all_button_callback(): def fit_all_button_callback():
fit_params = _get_fit_params() fit_params = _get_fit_params()
for scan in det_data["scan"].values(): for dat_file in det_data.values():
# fit_params are updated inplace within `fitccl` # fit_params are updated inplace within `fitccl`
pyzebra.fitccl(scan, **deepcopy(fit_params)) pyzebra.fitccl(dat_file["scan"][1], **deepcopy(fit_params))
_update_plot(_get_selected_scan()) _update_plot(_get_selected_scan())
_update_table() _update_table()
@ -480,15 +475,17 @@ def create():
det_data["meta"]["area_method"] = AREA_METHODS[new] det_data["meta"]["area_method"] = AREA_METHODS[new]
area_method_radiobutton = RadioButtonGroup( area_method_radiobutton = RadioButtonGroup(
labels=["Fit area", "Int area"], active=0, default_size=145 labels=["Fit area", "Int area"], active=0, default_size=145, disabled=True
) )
area_method_radiobutton.on_change("active", area_method_radiobutton_callback) area_method_radiobutton.on_change("active", area_method_radiobutton_callback)
bin_size_spinner = Spinner(title="Bin size:", value=1, low=1, step=1, default_size=145) bin_size_spinner = Spinner(title="Bin size:", value=1, low=1, step=1, default_size=145)
lorentz_toggle = Toggle(label="Lorentz Correction", default_size=145) lorentz_toggle = Toggle(label="Lorentz Correction", default_size=145, disabled=True)
preview_output_textinput = TextAreaInput(title="Export file preview:", width=450, height=400) preview_output_textinput = TextAreaInput(
title="Export file preview:", width=450, height=400, disabled=True
)
def preview_output_button_callback(): def preview_output_button_callback():
if det_data["meta"]["indices"] == "hkl": if det_data["meta"]["indices"] == "hkl":
@ -507,7 +504,7 @@ def create():
with open(f"{temp_file}{ext}") as f: with open(f"{temp_file}{ext}") as f:
preview_output_textinput.value = f.read() preview_output_textinput.value = f.read()
preview_output_button = Button(label="Preview file", default_size=220) preview_output_button = Button(label="Preview file", default_size=220, disabled=True)
preview_output_button.on_click(preview_output_button_callback) preview_output_button.on_click(preview_output_button_callback)
def export_results(det_data): def export_results(det_data):
@ -533,7 +530,9 @@ def create():
cont, ext = export_results(det_data) cont, ext = export_results(det_data)
js_data.data.update(cont=[cont], ext=[ext]) js_data.data.update(cont=[cont], ext=[ext])
save_button = Button(label="Download file", button_type="success", default_size=220) save_button = Button(
label="Download file", button_type="success", default_size=220, disabled=True
)
save_button.on_click(save_button_callback) save_button.on_click(save_button_callback)
save_button.js_on_click(CustomJS(args={"js_data": js_data}, code=javaScript)) save_button.js_on_click(CustomJS(args={"js_data": js_data}, code=javaScript))
@ -558,10 +557,10 @@ def create():
export_layout = column(preview_output_textinput, row(preview_output_button, save_button)) export_layout = column(preview_output_textinput, row(preview_output_button, save_button))
upload_div = Div(text="Or upload .ccl file:") upload_div = Div(text="Or upload .dat files:")
append_upload_div = Div(text="append extra .ccl/.dat files:") append_upload_div = Div(text="append extra .dat files:")
tab_layout = column( tab_layout = column(
row(proposal_textinput, ccl_file_select), row(proposal_textinput, file_select),
row( row(
column(Spacer(height=5), upload_div), column(Spacer(height=5), upload_div),
upload_button, upload_button,

2
pyzebra/ccl_io.py
View File

@ -185,6 +185,8 @@ def parse_1D(fileobj, data_type):
except (ValueError, IndexError): except (ValueError, IndexError):
print("seems hkl is not in title") print("seems hkl is not in title")
data_cols["om"] = np.array(data_cols["om"])
data_cols["temperature"] = metadata["temp"] data_cols["temperature"] = metadata["temp"]
try: try:
data_cols["mag_field"] = metadata["mf"] data_cols["mag_field"] = metadata["mf"]