functions to merge, scan, subtract measurements
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JakHolzer
GitHub
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418
ccl_dict_operation_v1.py
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418
ccl_dict_operation_v1.py
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import numpy as np
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import uncertainties as u
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from fitvol2 import create_uncertanities
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def scan_dict(dict):
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"""scans dictionary for duplicate hkl indexes
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:arg dict : dictionary to scan
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:return dictionary with matching scans, if there are none, the dict is empty
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note: can be checked by "not d", true if empty
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"""
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d = {}
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dupl = 0
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for i in dict["Measurements"]:
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for j in dict["Measurements"]:
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if dict["Measurements"][str(i)] != dict["Measurements"][str(j)]:
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itup = (
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dict["Measurements"][str(i)]["h_index"],
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dict["Measurements"][str(i)]["k_index"],
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dict["Measurements"][str(i)]["l_index"],
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)
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jtup = (
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dict["Measurements"][str(j)]["h_index"],
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dict["Measurements"][str(j)]["k_index"],
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dict["Measurements"][str(j)]["l_index"],
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)
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if itup != jtup:
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pass
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else:
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if str(itup) not in d:
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d[str(itup)] = (i, j)
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else:
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dupl = dupl + 1
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d[str(itup) + "_" + str(dupl)] = (i, j)
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else:
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continue
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return d
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def compare_hkl(dict1, dict2):
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"""Compares two dictionaries based on hkl indexes and return dictionary with str(h k l) as key and tuple with
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keys to same measurement in dict1 and dict2
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:arg dict1 : first dictionary
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:arg dict2 : second dictionary
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:return d : dict with matches
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example of one key: '0.0 0.0 -1.0 : ('M1', 'M9')' meaning that 001 hkl measurement is M1 in first dict and M9 in second"""
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d = {}
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dupl = 0
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for keys in dict1["Measurements"]:
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for key in dict2["Measurements"]:
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if (
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dict1["Measurements"][str(keys)]["h_index"]
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== dict2["Measurements"][str(key)]["h_index"]
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and dict1["Measurements"][str(keys)]["k_index"]
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== dict2["Measurements"][str(key)]["k_index"]
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and dict1["Measurements"][str(keys)]["l_index"]
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== dict2["Measurements"][str(key)]["l_index"]
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):
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if (
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str(
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(
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str(dict1["Measurements"][str(keys)]["h_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["k_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["l_index"])
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)
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)
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not in d
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):
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d[
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str(
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str(dict1["Measurements"][str(keys)]["h_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["k_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["l_index"])
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)
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] = (str(keys), str(key))
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else:
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dupl = dupl + 1
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d[
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str(
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str(dict1["Measurements"][str(keys)]["h_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["k_index"])
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+ " "
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+ str(dict1["Measurements"][str(keys)]["l_index"])
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+ "_dupl"
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+ str(dupl)
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)
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] = (str(keys), str(key))
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else:
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continue
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return d
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def create_tuples(x, y, y_err):
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"""creates tuples for sorting and merginng of the data
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Counts need to be normalized to monitor before"""
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t = list()
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for i in range(len(x)):
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tup = (x[i], y[i], y_err)
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t.append(tup)
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return t
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def merge(dict1, dict2, keys, auto=True, monitor=100000):
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"""merges the two tuples and sorts them, if om value is same, Counts value is average
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averaging is propagated into sigma if dict1 == dict2, key[1] is deleted after merging
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:arg dict1 : dictionary to which measurement will be merged
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:arg dict2 : dictionary from which measurement will be merged
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:arg keys : tuple with key to dict1 and dict2
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:arg auto : if true, when monitors are same, does not change it, if flase, takes monitor always
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:arg monitor : final monitor after merging
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note: dict1 and dict2 can be same dict
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:return dict1 with merged scan"""
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if auto:
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if dict1["Measurements"][keys[0]]["monitor"] == dict2["Measurements"][keys[1]]["monitor"]:
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monitor = dict1["Measurements"][keys[0]]["monitor"]
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# load om and Counts
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x1, x2 = dict1["Measurements"][keys[0]]["om"], dict2["Measurements"][keys[1]]["om"]
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y1, y2 = np.array(dict1["Measurements"][keys[0]]["Counts"]), np.array(
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dict2["Measurements"][keys[1]]["Counts"]
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)
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# normalize y to monitors
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cor_y1 = (y1 / dict1["Measurements"][keys[0]]["monitor"]) * monitor
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cor_y2 = (y2 / dict2["Measurements"][keys[0]]["monitor"]) * monitor
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# check if sigma errors for y exist, otherwise create them as sqrt(y)
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y_err1 = (
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np.sqrt(cor_y1)
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if "sigma" not in dict1["Measurements"][keys[0]]
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else np.array(dict1["Measurements"][keys[0]]["sigma"])
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* np.sqrt(monitor / dict1["Measurements"][keys[0]]["monitor"])
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)
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y_err2 = (
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np.sqrt(cor_y2)
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if "sigma" not in dict2["Measurements"][keys[1]]
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else np.array(dict2["Measurements"][keys[1]]["sigma"])
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* np.sqrt(monitor / dict2["Measurements"][keys[1]]["monitor"])
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)
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# creates touples (om, Counts, sigma) for sorting and further processing
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tuple_list = create_tuples(x1, cor_y1, y_err1) + create_tuples(x2, cor_y2, y_err2)
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# Sort the list on om and add 0 0 0 tuple to the last postion
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sorted_t = sorted(tuple_list, key=lambda tup: tup[0])
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sorted_t.append((0, 0, 0))
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om, Counts, sigma = [], [], []
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seen = list()
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for i in range(len(sorted_t) - 1):
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if sorted_t[i][0] not in seen:
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if sorted_t[i][0] != sorted_t[i + 1][0]:
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om = np.append(om, sorted_t[i][0])
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Counts = np.append(Counts, sorted_t[i][1])
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sigma = np.append(sigma, sorted_t[i][2])
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else:
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om = np.append(om, sorted_t[i][0])
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counts1, counts2 = sorted_t[i][1], sorted_t[i + 1][1]
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sigma1, sigma2 = sorted_t[i][2], sorted_t[i + 1][2]
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count_err1 = u.ufloat(counts1, sigma1)
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count_err2 = u.ufloat(counts2, sigma2)
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avg = (count_err1 + count_err2) / 2
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Counts = np.append(Counts, avg.n)
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sigma = np.append(sigma, avg.s)
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seen.append(sorted_t[i][0])
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else:
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continue
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if dict1 == dict2:
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del dict1["Measurements"][keys[1]]
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dict1["Measurements"][keys[0]]["om"] = om
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dict1["Measurements"][keys[0]]["Counts"] = Counts
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dict1["Measurements"][keys[0]]["sigma"] = sigma
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return dict1
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def substract_measurement(dict1, dict2, keys, auto=True, monitor=100000):
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"""Substracts two measurement (measurement key2 from dict2 from measurent key1 in dict1), expects om to be same
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:arg dict1 : dictionary to which measurement will be merged
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:arg dict2 : dictionary from which measurement will be merged
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:arg keys : tuple with key to dict1 and dict2
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:arg auto : if true, when monitors are same, does not change it, if flase, takes monitor always
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:arg monitor : final monitor after merging
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:returns d : dict1 with substracted Counts from dict2 and sigma that comes from the substraction"""
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if len(dict1["Measurements"][keys[0]]["om"]) != len(dict2["Measurements"][keys[1]]["om"]):
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raise ValueError("Omegas have different lengths, cannot be substracted")
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if auto:
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if dict1["Measurements"][keys[0]]["monitor"] == dict2["Measurements"][keys[1]]["monitor"]:
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monitor = dict1["Measurements"][keys[0]]["monitor"]
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monitor_ratio_prim = monitor / dict1["Measurements"][str(keys[0])]["monitor"]
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monitor_ratio_sec = monitor / dict2["Measurements"][str(keys[1])]["monitor"]
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y1 = np.array(dict1["Measurements"][str(keys[0])]["Counts"]) * monitor_ratio_prim
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y2 = np.array(dict2["Measurements"][str(keys[1])]["Counts"]) * monitor_ratio_sec
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y_err1 = (
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np.sqrt(y1)
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if "sigma" not in dict1["Measurements"][keys[0]]
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else dict1["Measurements"][keys[0]]["sigma"]
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* np.sqrt(monitor / dict1["Measurements"][keys[0]]["monitor"])
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)
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y_err2 = (
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np.sqrt(y2)
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if "sigma" not in dict2["Measurements"][keys[1]]
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else dict2["Measurements"][keys[1]]["sigma"]
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* np.sqrt(monitor / dict2["Measurements"][keys[1]]["monitor"])
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)
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dict1_count_err = create_uncertanities(y1, y_err1)
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dict2_count_err = create_uncertanities(y2, y_err2)
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if np.average(y1) > np.average(y2):
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res = np.subtract(dict1_count_err, dict2_count_err)
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else:
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res = np.subtract(dict2_count_err, dict1_count_err)
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res_nom = []
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res_err = []
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for k in range(len(res)):
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res_nom = np.append(res_nom, res[k].n)
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res_err = np.append(res_err, res[k].s)
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dict1["Measurements"][str(keys[0])]["Counts"] = res_nom
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dict1["Measurements"][str(keys[0])]["sigma"] = res_err
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def compare_dict(dict1, dict2):
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"""takes two ccl dictionaries and compare different values for each key
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:arg dict1 : dictionary 1 (ccl)
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:arg dict2 : dictionary 2 (ccl)
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:returns warning : dictionary with keys from primary files (if they differ) with
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information of how many measurement differ and which ones differ
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:returns report_string string comparing all different values respecively of measurements"""
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if dict1["file_type"] != dict2["file_type"]:
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print("select two dicts")
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return
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S = []
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conflicts = {}
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warnings = {}
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comp = compare_hkl(dict1, dict2)
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d1 = scan_dict(dict1)
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d2 = scan_dict(dict2)
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if not d1:
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S.append("There are no duplicates in %s (dict1) \n" % dict1["meta"]["original_filename"])
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else:
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S.append(
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"There are %d duplicates in %s (dict1) \n"
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% (len(d1), dict1["meta"]["original_filename"])
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)
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warnings["Duplicates in dict1"] = list()
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for keys in d1:
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S.append("Measurements %s with hkl %s \n" % (d1[keys], keys))
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warnings["Duplicates in dict1"].append(d1[keys])
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if not d2:
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S.append("There are no duplicates in %s (dict2) \n" % dict2["meta"]["original_filename"])
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else:
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S.append(
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"There are %d duplicates in %s (dict2) \n"
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% (len(d2), dict2["meta"]["original_filename"])
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)
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warnings["Duplicates in dict2"] = list()
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for keys in d2:
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S.append("Measurements %s with hkl %s \n" % (d2[keys], keys))
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warnings["Duplicates in dict2"].append(d2[keys])
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# compare meta
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S.append("Different values in meta: \n")
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different_meta = {
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k: dict1["meta"][k]
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for k in dict1["meta"]
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if k in dict2["meta"] and dict1["meta"][k] != dict2["meta"][k]
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}
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for keys in different_meta:
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if keys not in conflicts:
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conflicts[keys] = 1
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else:
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conflicts[keys] = conflicts[keys] + 1
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S.append(" Different values in %s \n" % str(keys))
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S.append(" dict1: %s \n" % str(dict1["meta"][str(keys)]))
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S.append(" dict2: %s \n" % str(dict2["meta"][str(keys)]))
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# compare Measurements
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S.append(
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"Number of measurements in %s = %s \n"
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% (dict1["meta"]["original_filename"], len(dict1["Measurements"]))
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)
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S.append(
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"Number of measurements in %s = %s \n"
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% (dict2["meta"]["original_filename"], len(dict2["Measurements"]))
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)
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S.append("Different values in Measurements:\n")
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select_set = ["om", "Counts", "sigma"]
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exlude_set = ["time", "Counts"]
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for keys1 in comp:
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for key2 in dict1["Measurements"][str(comp[str(keys1)][0])]:
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if key2 in exlude_set:
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continue
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if key2 not in select_set:
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if (
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dict1["Measurements"][comp[str(keys1)][0]][str(key2)]
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!= dict2["Measurements"][str(comp[str(keys1)][0])][str(key2)]
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):
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S.append(
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"Measurement value "
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"%s"
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", with hkl %s differs in meausrements %s and %s \n"
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% (key2, keys1, comp[str(keys1)][0], comp[str(keys1)][1])
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)
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S.append(
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" dict1: %s \n"
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% str(dict1["Measurements"][comp[str(keys1)][0]][str(key2)])
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)
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S.append(
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" dict2: %s \n"
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% str(dict2["Measurements"][comp[str(keys1)][1]][str(key2)])
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)
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if key2 not in conflicts:
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conflicts[key2] = {}
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conflicts[key2]["amount"] = 1
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conflicts[key2]["measurements"] = str(comp[str(keys1)][0])
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else:
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conflicts[key2]["amount"] = conflicts[key2]["amount"] + 1
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conflicts[key2]["measurements"] = (
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conflicts[key2]["measurements"] + " " + (str(comp[str(keys1)][0]))
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)
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else:
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comparison = list(dict1["Measurements"][comp[str(keys1)][0]][str(key2)]) == list(
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dict2["Measurements"][comp[str(keys1)][1]][str(key2)]
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)
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if len(list(dict1["Measurements"][comp[str(keys1)][0]][str(key2)])) != len(
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list(dict2["Measurements"][comp[str(keys1)][1]][str(key2)])
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):
|
||||||
|
if str("different length of %s" % key2) not in warnings:
|
||||||
|
warnings[str("different length of %s" % key2)] = list()
|
||||||
|
warnings[str("different length of %s" % key2)].append(
|
||||||
|
(str(comp[keys1][0]), str(comp[keys1][1]))
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
warnings[str("different length of %s" % key2)].append(
|
||||||
|
(str(comp[keys1][0]), str(comp[keys1][1]))
|
||||||
|
)
|
||||||
|
if not comparison:
|
||||||
|
S.append(
|
||||||
|
"Measurement value "
|
||||||
|
"%s"
|
||||||
|
" differs in measurement %s and %s \n"
|
||||||
|
% (key2, comp[str(keys1)][0], comp[str(keys1)][1])
|
||||||
|
)
|
||||||
|
S.append(
|
||||||
|
" dict1: %s \n"
|
||||||
|
% str(list(dict1["Measurements"][comp[str(keys1)][0]][str(key2)]))
|
||||||
|
)
|
||||||
|
S.append(
|
||||||
|
" dict2: %s \n"
|
||||||
|
% str(list(dict2["Measurements"][comp[str(keys1)][1]][str(key2)]))
|
||||||
|
)
|
||||||
|
if key2 not in conflicts:
|
||||||
|
conflicts[key2] = {}
|
||||||
|
conflicts[key2]["amount"] = 1
|
||||||
|
conflicts[key2]["measurements"] = str(comp[str(keys1)][0])
|
||||||
|
else:
|
||||||
|
conflicts[key2]["amount"] = conflicts[key2]["amount"] + 1
|
||||||
|
conflicts[key2]["measurements"] = (
|
||||||
|
conflicts[key2]["measurements"] + " " + (str(comp[str(keys1)][1]))
|
||||||
|
)
|
||||||
|
|
||||||
|
for keys in conflicts:
|
||||||
|
try:
|
||||||
|
conflicts[str(keys)]["measurements"] = conflicts[str(keys)]["measurements"].split(" ")
|
||||||
|
except:
|
||||||
|
continue
|
||||||
|
report_string = "".join(S)
|
||||||
|
return warnings, conflicts, report_string
|
||||||
|
|
||||||
|
|
||||||
|
def guess_next(dict1, dict2, comp):
|
||||||
|
"""iterates thorough the scans and tries to decide if the scans should be substracted or merged"""
|
||||||
|
threshold = 0.05
|
||||||
|
for keys in comp:
|
||||||
|
if (
|
||||||
|
abs(
|
||||||
|
(
|
||||||
|
dict1["Measurements"][str(comp[keys][0])]["temperature"]
|
||||||
|
- dict2["Measurements"][str(comp[keys][1])]["temperature"]
|
||||||
|
)
|
||||||
|
/ dict2["Measurements"][str(comp[keys][1])]["temperature"]
|
||||||
|
)
|
||||||
|
< threshold
|
||||||
|
and abs(
|
||||||
|
(
|
||||||
|
dict1["Measurements"][str(comp[keys][0])]["mag_field"]
|
||||||
|
- dict2["Measurements"][str(comp[keys][1])]["mag_field"]
|
||||||
|
)
|
||||||
|
/ dict2["Measurements"][str(comp[keys][1])]["mag_field"]
|
||||||
|
)
|
||||||
|
< threshold
|
||||||
|
):
|
||||||
|
comp[keys] = comp[keys] + tuple("m")
|
||||||
|
else:
|
||||||
|
comp[keys] = comp[keys] + tuple("s")
|
||||||
|
|
||||||
|
return comp
|
||||||
|
|
||||||
|
|
||||||
|
def process_dict(dict1, dict2, comp):
|
||||||
|
"""substracts or merges scans, guess_next function must run first """
|
||||||
|
for keys in comp:
|
||||||
|
if comp[keys][2] == "s":
|
||||||
|
substract_measurement(dict1, dict2, comp[keys])
|
||||||
|
elif comp[keys][2] == "m":
|
||||||
|
merge(dict1, dict2, comp[keys])
|
||||||
|
|
||||||
|
return dict1
|
||||||
Loading…
x
Reference in New Issue
Block a user