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Keep scans in a list instead of a dict

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This commit is contained in:
usov_i
2021-02-04 17:11:18 +01:00
parent 6bf401aba8
commit e38993e69d
5 changed files with 41 additions and 41 deletions
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15
pyzebra/app/panel_ccl_integrate.py
View File

@ -87,8 +87,8 @@ def create():
proposal_textinput.on_change("value", proposal_textinput_callback)
def _init_datatable():
scan_list = list(det_data["scan"].keys())
hkl = [f'{m["h_index"]} {m["k_index"]} {m["l_index"]}' for m in det_data["scan"].values()]
scan_list = list(range(len(det_data["scan"])))
hkl = [f'{m["h_index"]} {m["k_index"]} {m["l_index"]}' for m in det_data["scan"]]
scan_table_source.data.update(
scan=scan_list,
hkl=hkl,
@ -159,8 +159,8 @@ def create():
append_upload_button.on_change("value", append_upload_button_callback)
def _update_table():
num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"].values()]
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"].values()]
num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"]]
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"]]
scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
def _update_plot(scan):
@ -447,7 +447,7 @@ def create():
def peakfind_all_button_callback():
peakfind_params = _get_peakfind_params()
for scan in det_data["scan"].values():
for scan in det_data["scan"]:
pyzebra.ccl_findpeaks(scan, **peakfind_params)
_update_table()
@ -479,7 +479,7 @@ def create():
def fit_all_button_callback():
fit_params = _get_fit_params()
for scan in det_data["scan"].values():
for scan in det_data["scan"]:
# fit_params are updated inplace within `fitccl`
pyzebra.fitccl(scan, **deepcopy(fit_params))
@ -515,7 +515,8 @@ def create():
export_data = deepcopy(det_data)
for s, export in zip(scan_table_source.data["scan"], scan_table_source.data["export"]):
if not export:
del export_data["scan"][s]
if "fit" in export_data["scan"][s]:
del export_data["scan"][s]["fit"]
pyzebra.export_1D(
export_data,

13
pyzebra/app/panel_param_study.py
View File

@ -96,7 +96,7 @@ def create():
proposal_textinput.on_change("value", proposal_textinput_callback)
def _init_datatable():
scan_list = list(det_data["scan"].keys())
scan_list = list(range(len(det_data["scan"])))
file_list = []
extra_meta = det_data.get("extra_meta", {})
for scan_id in scan_list:
@ -184,8 +184,8 @@ def create():
append_upload_button.on_change("value", append_upload_button_callback)
def _update_table():
num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"].values()]
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"].values()]
num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"]]
fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"]]
scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
def _update_plot():
@ -554,7 +554,7 @@ def create():
def peakfind_all_button_callback():
peakfind_params = _get_peakfind_params()
for scan in det_data["scan"].values():
for scan in det_data["scan"]:
pyzebra.ccl_findpeaks(scan, **peakfind_params)
_update_table()
@ -586,7 +586,7 @@ def create():
def fit_all_button_callback():
fit_params = _get_fit_params()
for scan in det_data["scan"].values():
for scan in det_data["scan"]:
# fit_params are updated inplace within `fitccl`
pyzebra.fitccl(scan, **deepcopy(fit_params))
@ -649,7 +649,8 @@ def create():
export_data = deepcopy(det_data)
for s, export in zip(scan_table_source.data["scan"], scan_table_source.data["export"]):
if not export:
del export_data["scan"][s]
if "fit" in export_data["scan"][s]:
del export_data["scan"][s]["fit"]
pyzebra.export_1D(
export_data,

15
pyzebra/ccl_io.py
View File

@ -133,7 +133,7 @@ def parse_1D(fileobj, data_type):
break
# read data
scan = {}
scan = []
if data_type == ".ccl":
ccl_first_line = (*CCL_FIRST_LINE, *CCL_ANGLES[metadata["zebra_mode"]])
ccl_second_line = CCL_SECOND_LINE
@ -162,7 +162,7 @@ def parse_1D(fileobj, data_type):
counts.extend(map(int, next(fileobj).split()))
s["Counts"] = counts
scan[s["scan_number"]] = s
scan.append(s)
elif data_type == ".dat":
# skip the first 2 rows, the third row contans the column names
@ -203,12 +203,12 @@ def parse_1D(fileobj, data_type):
s["nu_angle"] = metadata["nu"]
s["scan_number"] = 1
scan[s["scan_number"]] = dict(s)
scan.append(dict(s))
else:
print("Unknown file extention")
for s in scan.values():
for s in scan:
if s["h_index"].is_integer() and s["k_index"].is_integer() and s["l_index"].is_integer():
s["h_index"] = int(s["h_index"])
s["k_index"] = int(s["k_index"])
@ -231,12 +231,11 @@ def export_1D(data, path, area_method=AREA_METHODS[0], lorentz=False, hkl_precis
zebra_mode = data["meta"]["zebra_mode"]
file_content = {".comm": [], ".incomm": []}
for key, scan in data["scan"].items():
for ind, scan in enumerate(data["scan"]):
if "fit" not in scan:
print("Scan skipped - no fit value for:", key)
continue
scan_str = f"{key:6}"
ind_str = f"{ind:6}"
h, k, l = scan["h_index"], scan["k_index"], scan["l_index"]
if scan["indices"] == "hkl":
@ -267,7 +266,7 @@ def export_1D(data, path, area_method=AREA_METHODS[0], lorentz=False, hkl_precis
ang_str = ang_str + f"{scan[angle]:8}"
ref = file_content[".comm"] if scan["indices"] == "hkl" else file_content[".incomm"]
ref.append(scan_str + hkl_str + area_str + ang_str + "\n")
ref.append(ind_str + hkl_str + area_str + ang_str + "\n")
for ext, content in file_content.items():
if content:

21
pyzebra/merge_function.py
View File

@ -13,8 +13,7 @@ def create_tuples(x, y, y_err):
def normalize_all(dictionary, monitor=100000):
for keys in dictionary["scan"]:
scan = dictionary["scan"][keys]
for scan in dictionary["scan"]:
counts = np.array(scan["Counts"])
sigma = np.sqrt(counts) if "sigma" not in scan else scan["sigma"]
monitor_ratio = monitor / scan["monitor"]
@ -161,8 +160,8 @@ def merge_dups(dictionary):
"gamma_angle": 0.05,
}
for i in list(dictionary["scan"]):
for j in list(dictionary["scan"]):
for i in range(len(dictionary["scan"])):
for j in range(len(dictionary["scan"])):
if i == j:
continue
else:
@ -181,8 +180,8 @@ def merge_dups(dictionary):
def add_scan(dict1, dict2, scan_to_add):
max_scan = np.max(list(dict1["scan"]))
dict1["scan"][max_scan + 1] = dict2["scan"][scan_to_add]
max_scan = len(dict1["scan"])
dict1["scan"].append(dict2["scan"][scan_to_add])
if dict1.get("extra_meta") is None:
dict1["extra_meta"] = {}
dict1["extra_meta"][max_scan + 1] = dict2["meta"]
@ -196,8 +195,8 @@ def process(dict1, dict2, angles, precision):
# check UB matrixes
if check_UB(dict1, dict2):
# iterate over second dict and check for matches
for i in list(dict2["scan"]):
for j in list(dict1["scan"]):
for i in range(len(dict2["scan"])):
for j in range(len(dict1["scan"])):
if check_angles(dict1["scan"][j], dict2["scan"][i], angles, precision):
# angles good, see the mag and temp
if check_temp_mag(dict1["scan"][j], dict2["scan"][i]):
@ -276,7 +275,7 @@ def add_dict(dict1, dict2):
# this is for the qscan case
except KeyError:
print("Zebra mode not specified")
max_measurement_dict1 = max([keys for keys in dict1["scan"]])
max_measurement_dict1 = len(dict1["scan"])
new_filenames = np.arange(
max_measurement_dict1 + 1, max_measurement_dict1 + 1 + len(dict2["scan"])
)
@ -286,9 +285,9 @@ def add_dict(dict1, dict2):
new_meta_name = "meta" + str(dict2["meta"]["original_filename"])
if new_meta_name not in dict1:
for keys, name in zip(dict2["scan"], new_filenames):
for keys, name in zip(range(len(dict2["scan"])), new_filenames):
dict2["scan"][keys]["file_of_origin"] = str(dict2["meta"]["original_filename"])
dict1["scan"][name] = dict2["scan"][keys]
dict1["scan"].append(dict2["scan"][keys])
dict1["extra_meta"][name] = dict2["meta"]
dict1[new_meta_name] = dict2["meta"]

18
pyzebra/param_study_moduls.py
View File

@ -51,7 +51,7 @@ def load_dats(filepath):
else:
dict1 = add_dict(dict1, load_1D(file_list[i]))
dict1["scan"][i + 1]["params"] = {}
dict1["scan"].append({})
if data_type == "txt":
for x in range(len(col_names) - 1):
dict1["scan"][i + 1]["params"][col_names[x + 1]] = float(file_list[i][x + 1])
@ -76,7 +76,7 @@ def create_dataframe(dict1, variables):
print(keys)
# populate the dict
for keys in dict1["scan"]:
for keys in range(len(dict1["scan"])):
if "file_of_origin" in dict1["scan"][keys]:
pull_dict["filenames"].append(dict1["scan"][keys]["file_of_origin"].split("/")[-1])
else:
@ -298,7 +298,7 @@ def add_dict(dict1, dict2):
# this is for the qscan case
except KeyError:
print("Zebra mode not specified")
max_measurement_dict1 = max([keys for keys in dict1["scan"]])
max_measurement_dict1 = len(dict1["scan"])
new_filenames = np.arange(
max_measurement_dict1 + 1, max_measurement_dict1 + 1 + len(dict2["scan"])
)
@ -352,8 +352,8 @@ def scan_dict(dict, precision=0.5):
return
d = {}
for i in dict["scan"]:
for j in dict["scan"]:
for i in range(len(dict["scan"])):
for j in range(len(dict["scan"])):
if dict["scan"][i] != dict["scan"][j]:
itup = list()
for k in angles:
@ -399,7 +399,7 @@ def variables(dictionary):
# find all variables that are in all scans
stdev_precision = 0.05
all_vars = list()
for keys in dictionary["scan"]:
for keys in range(len(dictionary["scan"])):
all_vars.append([key for key in dictionary["scan"][keys] if key != "params"])
if dictionary["scan"][keys]["params"]:
all_vars.append(key for key in dictionary["scan"][keys]["params"])
@ -432,7 +432,7 @@ def variables(dictionary):
# check for primary variable, needs to be list, we dont suspect the
# primary variable be as a parameter (be in scan[params])
primary_candidates = list()
for key in dictionary["scan"]:
for key in range(len(dictionary["scan"])):
for i in inall_red:
if isinstance(_finditem(dictionary["scan"][key], i), list):
if np.std(_finditem(dictionary["scan"][key], i)) > stdev_precision:
@ -454,7 +454,7 @@ def variables(dictionary):
# print("secondary candidates", secondary_candidates)
# select arrays and floats and ints
second_round_secondary_candidates = list()
for key in dictionary["scan"]:
for key in range(len(dictionary["scan"])):
for i in secondary_candidates:
if isinstance(_finditem(dictionary["scan"][key], i), float):
second_round_secondary_candidates.append(i)
@ -475,7 +475,7 @@ def variables(dictionary):
third_round_sec_candidates = list()
for i in second_round_secondary_candidates:
check_array = list()
for keys in dictionary["scan"]:
for keys in range(len(dictionary["scan"])):
check_array.append(np.average(_finditem(dictionary["scan"][keys], i)))
# print(i, check_array, np.std(check_array))
if np.std(check_array) > stdev_precision: