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Merge based on variable parameter range overlap

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This commit is contained in:
usov_i 2021-02-09 18:06:51 +01:00
parent 3b1a2b1a0b
commit 12077dd5f3
7 changed files with 45 additions and 22 deletions
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10
pyzebra/app/panel_ccl_integrate.py
View File

@ -172,7 +172,7 @@ def create():
peak_pos_textinput_lock = True
y = scan["Counts"]
x = scan["om"]
x = scan["omega"]
plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
@ -180,11 +180,11 @@ def create():
if num_of_peaks is not None and num_of_peaks > 0:
peak_indexes = scan["peak_indexes"]
if len(peak_indexes) == 1:
peak_pos_textinput.value = str(scan["om"][peak_indexes[0]])
peak_pos_textinput.value = str(scan["omega"][peak_indexes[0]])
else:
peak_pos_textinput.value = str([scan["om"][ind] for ind in peak_indexes])
peak_pos_textinput.value = str([scan["omega"][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=scan["omega"][peak_indexes], y=scan["peak_heights"])
plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"])
else:
peak_pos_textinput.value = None
@ -314,7 +314,7 @@ def create():
if new is not None and not peak_pos_textinput_lock:
scan = _get_selected_scan()
peak_ind = (np.abs(scan["om"] - float(new))).argmin()
peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
_update_table()

10
pyzebra/app/panel_param_study.py
View File

@ -194,7 +194,7 @@ def create():
peak_pos_textinput_lock = True
y = scan["Counts"]
x = scan["om"]
x = scan["omega"]
plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
@ -267,10 +267,10 @@ def create():
par = []
for s, p in enumerate(scan_table_source.data["param"]):
if p:
xs.append(np.array(det_data[s]["om"]))
x.extend(det_data[s]["om"])
xs.append(np.array(det_data[s]["omega"]))
x.extend(det_data[s]["omega"])
ys.append(np.array(det_data[s]["Counts"]))
y.extend([float(p)] * len(det_data[s]["om"]))
y.extend([float(p)] * len(det_data[s]["omega"]))
param.append(float(p))
par.extend(det_data[s]["Counts"])
@ -412,7 +412,7 @@ def create():
if new is not None and not peak_pos_textinput_lock:
scan = _get_selected_scan()
peak_ind = (np.abs(scan["om"] - float(new))).argmin()
peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
_update_table()

2
pyzebra/ccl_findpeaks.py
View File

@ -11,7 +11,7 @@ def ccl_findpeaks(
smooth=False,
window_size=7,
poly_order=3,
variable="om",
variable="omega",
):
"""function iterates through the dictionary created by load_cclv2 and locates peaks for each scan

18
pyzebra/ccl_io.py
View File

@ -144,11 +144,18 @@ def parse_1D(fileobj, data_type):
for param, (param_name, param_type) in zip(next_line.split(), ccl_second_line):
s[param_name] = param_type(param)
s["om"] = np.linspace(
if s["variable_name"] != "om":
raise Exception("Unsupported variable name in ccl file.")
# "om" -> "omega"
s["variable_name"] = "omega"
s["variable"] = np.linspace(
s["omega"] - (s["n_points"] / 2) * s["angle_step"],
s["omega"] + (s["n_points"] / 2) * s["angle_step"],
s["n_points"],
)
# overwrite metadata, because it only refers to the scan center
s["omega"] = s["variable"]
# subsequent lines with counts
counts = []
@ -182,6 +189,15 @@ def parse_1D(fileobj, data_type):
for name in col_names:
s[name] = np.array(s[name])
# "om" -> "omega"
if s["variable_name"] == "om":
s["variable_name"] = "omega"
s["variable"] = s["om"]
s["omega"] = s["om"]
del s["om"]
else:
s["variable"] = s[s["variable_name"]]
s["h"] = s["k"] = s["l"] = float("nan")
for param in ("mf", "temp"):

17
pyzebra/ccl_process.py
View File

@ -9,7 +9,7 @@ PARAM_PRECISIONS = {
"chi": 0.1,
"nu": 0.1,
"phi": 0.05,
"omega": 5,
"omega": 0.05,
"gamma": 0.05,
"temp": 1,
"mf": 0.001,
@ -36,7 +36,14 @@ def _parameters_match(scan1, scan2):
return False
for param in ("ub", "temp", "mf", *(vars[0] for vars in CCL_ANGLES[zebra_mode])):
if np.max(np.abs(scan1[param] - scan2[param])) > PARAM_PRECISIONS[param]:
if param == scan1["variable_name"] == scan2["variable_name"]:
# check if ranges of variable parameter overlap
range1 = scan1["variable"]
range2 = scan2["variable"]
if range1[0] > range2[-1] or range2[0] > range1[-1]:
return False
elif np.max(np.abs(scan1[param] - scan2[param])) > PARAM_PRECISIONS[param]:
return False
return True
@ -53,12 +60,12 @@ def merge_datasets(dataset1, dataset2):
def _merge_scans(scan1, scan2):
om = np.concatenate((scan1["om"], scan2["om"]))
omega = np.concatenate((scan1["omega"], scan2["omega"]))
counts = np.concatenate((scan1["Counts"], scan2["Counts"]))
index = np.argsort(om)
index = np.argsort(omega)
scan1["om"] = om[index]
scan1["omega"] = omega[index]
scan1["Counts"] = counts[index]
print(f'Scan {scan2["idx"]} merged into {scan1["idx"]}')

4
pyzebra/fit2.py
View File

@ -67,7 +67,7 @@ def fitccl(
return
if binning is None or binning == 0 or binning == 1:
x = list(scan["om"])
x = list(scan["omega"])
y = list(scan["Counts"])
y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"])
if not scan["peak_indexes"]:
@ -75,7 +75,7 @@ def fitccl(
else:
centre = x[int(scan["peak_indexes"])]
else:
x = list(scan["om"])
x = list(scan["omega"])
if not scan["peak_indexes"]:
centre = np.mean(x)
else:

6
pyzebra/fitvol3.py
View File

@ -39,13 +39,13 @@ def find_nearest(array, value):
# peaks = [6.2, 8.1, 9.9, 11.5]
peaks = [23.5, 24.5]
# peaks = [24]
def fitccl(scan, variable="om", peak_type="gauss", binning=None):
def fitccl(scan, variable="omega", peak_type="gauss", binning=None):
x = list(scan[variable])
y = list(scan["Counts"])
peak_centre = np.mean(x)
if binning is None or binning == 0 or binning == 1:
x = list(scan["om"])
x = list(scan[variable])
y = list(scan["Counts"])
y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"])
print(scan["peak_indexes"])
@ -54,7 +54,7 @@ def fitccl(scan, variable="om", peak_type="gauss", binning=None):
else:
centre = x[int(scan["peak_indexes"])]
else:
x = list(scan["om"])
x = list(scan[variable])
if not scan["peak_indexes"]:
peak_centre = np.mean(x)
else: