Update merge_function.py
Fixed the normalization, changed the structure so we can merge duplicates without merging two dictionaries.
This commit is contained in:
JakHolzer
GitHub
parent
1761003d8a
commit
d0b67b8565
@ -12,24 +12,19 @@ def create_tuples(x, y, y_err):
|
||||
return t
|
||||
|
||||
|
||||
def normalize(scan, monitor):
|
||||
"""Normalizes the measurement to monitor, checks if sigma exists, otherwise creates it
|
||||
:arg dict : dictionary to from which to tkae the scan
|
||||
:arg key : which scan to normalize from dict1
|
||||
:arg monitor : final monitor
|
||||
:return counts - normalized counts
|
||||
:return sigma - normalized sigma"""
|
||||
|
||||
def normalize_all(dictionary, monitor=100000):
|
||||
for keys in dictionary["scan"]:
|
||||
scan = dictionary["scan"][keys]
|
||||
counts = np.array(scan["Counts"])
|
||||
sigma = np.sqrt(counts) if "sigma" not in scan else scan["sigma"]
|
||||
monitor_ratio = scan["monitor"] / monitor
|
||||
scaled_counts = counts * monitor_ratio
|
||||
scaled_sigma = np.array(sigma) * monitor_ratio
|
||||
|
||||
return scaled_counts, scaled_sigma
|
||||
monitor_ratio = monitor / scan["monitor"]
|
||||
scan["Counts"] = counts * monitor_ratio
|
||||
scan["sigma"] = np.array(sigma) * monitor_ratio
|
||||
scan["monitor"] = monitor
|
||||
print("Normalized %d scans to monitor %d" % (len(dictionary["scan"]), monitor))
|
||||
|
||||
|
||||
def merge(scan1, scan2, keep=True, monitor=100000):
|
||||
def merge(scan1, scan2):
|
||||
"""merges the two tuples and sorts them, if om value is same, Counts value is average
|
||||
averaging is propagated into sigma if dict1 == dict2, key[1] is deleted after merging
|
||||
:arg dict1 : dictionary to which measurement will be merged
|
||||
@ -41,14 +36,13 @@ def merge(scan1, scan2, keep=True, monitor=100000):
|
||||
note: dict1 and dict2 can be same dict
|
||||
:return dict1 with merged scan"""
|
||||
|
||||
if keep:
|
||||
if scan1["monitor"] == scan2["monitor"]:
|
||||
monitor = scan1["monitor"]
|
||||
|
||||
# load om and Counts
|
||||
x1, x2 = scan1["om"], scan2["om"]
|
||||
cor_y1, y_err1 = normalize(scan1, monitor=monitor)
|
||||
cor_y2, y_err2 = normalize(scan2, monitor=monitor)
|
||||
# print(scan1["om"])
|
||||
# print(scan2["om"])
|
||||
cor_y1, y_err1 = scan1["Counts"], scan1["sigma"]
|
||||
cor_y2, y_err2 = scan2["Counts"], scan2["sigma"]
|
||||
# creates touples (om, Counts, sigma) for sorting and further processing
|
||||
tuple_list = create_tuples(x1, cor_y1, y_err1) + create_tuples(x2, cor_y2, y_err2)
|
||||
# Sort the list on om and add 0 0 0 tuple to the last position
|
||||
@ -68,7 +62,7 @@ def merge(scan1, scan2, keep=True, monitor=100000):
|
||||
sigma1, sigma2 = sorted_t[i][2], sorted_t[i + 1][2]
|
||||
count_err1 = u.ufloat(counts1, sigma1)
|
||||
count_err2 = u.ufloat(counts2, sigma2)
|
||||
avg = (count_err1 + count_err2) / ((scan1["monitor"] + scan2["monitor"])/monitor)
|
||||
avg = (count_err1 + count_err2) / 2
|
||||
Counts = np.append(Counts, avg.n)
|
||||
sigma = np.append(sigma, avg.s)
|
||||
seen.append(sorted_t[i][0])
|
||||
@ -77,7 +71,10 @@ def merge(scan1, scan2, keep=True, monitor=100000):
|
||||
scan1["om"] = om
|
||||
scan1["Counts"] = Counts
|
||||
scan1["sigma"] = sigma
|
||||
scan1["monitor"] = monitor
|
||||
if "history" not in scan1:
|
||||
scan1["history"] = str("Merged with scan %d" % scan2["scan_number"])
|
||||
else:
|
||||
scan1["history"] = scan1["history"] + str(", merged with scan %d" % scan2["scan_number"])
|
||||
print("merging done")
|
||||
|
||||
|
||||
@ -138,19 +135,29 @@ def check_temp_mag(scan1, scan2):
|
||||
except KeyError:
|
||||
print("temperature missing")
|
||||
|
||||
|
||||
if all(truth_list):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
def merge_dups(dictionary, angles):
|
||||
def merge_dups(dictionary):
|
||||
|
||||
if dictionary["meta"]["data_type"] == "dat":
|
||||
return
|
||||
|
||||
if dictionary["meta"]["zebra_mode"] == "bi":
|
||||
angles = ["twotheta_angle", "omega_angle", "chi_angle", "phi_angle"]
|
||||
elif dictionary["meta"]["zebra_mode"] == "nb":
|
||||
angles = ["gamma_angle", "omega_angle", "nu_angle"]
|
||||
|
||||
precision = {
|
||||
"twotheta_angle": 0.1,
|
||||
"chi_angle": 0.1,
|
||||
"nu_angle": 0.1,
|
||||
"phi_angle": 0.05,
|
||||
"omega_angle": 0.05,
|
||||
"omega_angle": 5,
|
||||
"gamma_angle": 0.05,
|
||||
}
|
||||
|
||||
@ -160,12 +167,13 @@ def merge_dups(dictionary, angles):
|
||||
continue
|
||||
else:
|
||||
# print(i, j)
|
||||
if check_angles(dictionary["scan"][i], dictionary["scan"][j], angles, precision):
|
||||
if check_angles(dictionary["scan"][i], dictionary["scan"][j], angles, precision) \
|
||||
and check_temp_mag(dictionary["scan"][i], dictionary["scan"][j]):
|
||||
merge(dictionary["scan"][i], dictionary["scan"][j])
|
||||
print("merged %d with %d" % (i, j))
|
||||
print("merged %d with %d within the dictionary" % (i, j))
|
||||
|
||||
del dictionary["scan"][j]
|
||||
merge_dups(dictionary, angles)
|
||||
merge_dups(dictionary)
|
||||
break
|
||||
else:
|
||||
continue
|
||||
@ -175,9 +183,6 @@ def merge_dups(dictionary, angles):
|
||||
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]
|
||||
if dict1.get("extra_meta") is None:
|
||||
dict1["extra_meta"] = {}
|
||||
dict1["extra_meta"][max_scan + 1] = dict2["meta"]
|
||||
del dict2["scan"][scan_to_add]
|
||||
|
||||
|
||||
@ -185,7 +190,6 @@ def process(dict1, dict2, angles, precision):
|
||||
# stop when the second dict is empty
|
||||
# print(dict2["scan"])
|
||||
if dict2["scan"]:
|
||||
print("doing something")
|
||||
# check UB matrixes
|
||||
if check_UB(dict1, dict2):
|
||||
# iterate over second dict and check for matches
|
||||
@ -195,18 +199,18 @@ def process(dict1, dict2, angles, precision):
|
||||
# angles good, see the mag and temp
|
||||
if check_temp_mag(dict1["scan"][j], dict2["scan"][i]):
|
||||
merge(dict1["scan"][j], dict2["scan"][i])
|
||||
print("merged")
|
||||
print("merged %d with %d from different dictionaries" % (i, j))
|
||||
del dict2["scan"][i]
|
||||
process(dict1, dict2, angles, precision)
|
||||
break
|
||||
else:
|
||||
add_scan(dict1, dict2, i)
|
||||
print("scan added r")
|
||||
print("Diffrent T or M, scan added")
|
||||
process(dict1, dict2, angles, precision)
|
||||
break
|
||||
else:
|
||||
add_scan(dict1, dict2, i)
|
||||
print("scan added l")
|
||||
print("Mismatch in angles, scan added")
|
||||
process(dict1, dict2, angles, precision)
|
||||
break
|
||||
else:
|
||||
@ -245,18 +249,11 @@ def unified_merge(dict1, dict2):
|
||||
"nu_angle": 0.1,
|
||||
"phi_angle": 0.05,
|
||||
"omega_angle": 5,
|
||||
"gamma_angle": 0.05,
|
||||
"gamma_angle": 0.1,
|
||||
}
|
||||
if (dict1["meta"]["data_type"] == "ccl") and (dict2["meta"]["data_type"] == "ccl"):
|
||||
precision["omega_angle"] = 0.05
|
||||
|
||||
# check for duplicates in original files
|
||||
for d in dict1, dict2:
|
||||
# no duplicates in dats
|
||||
if d["meta"]["data_type"] == "dat":
|
||||
continue
|
||||
else:
|
||||
merge_dups(d, angles)
|
||||
|
||||
process(dict1, dict2, angles, precision)
|
||||
|
||||
@ -280,16 +277,11 @@ def add_dict(dict1, dict2):
|
||||
new_filenames = np.arange(
|
||||
max_measurement_dict1 + 1, max_measurement_dict1 + 1 + len(dict2["scan"])
|
||||
)
|
||||
|
||||
if dict1.get("extra_meta") is None:
|
||||
dict1["extra_meta"] = {}
|
||||
|
||||
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):
|
||||
dict2["scan"][keys]["file_of_origin"] = str(dict2["meta"]["original_filename"])
|
||||
dict1["scan"][name] = dict2["scan"][keys]
|
||||
dict1["extra_meta"][name] = dict2["meta"]
|
||||
|
||||
dict1[new_meta_name] = dict2["meta"]
|
||||
else:
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user