Add parse_1D function

This commit is contained in:
usov_i 2020-09-16 16:22:17 +02:00
parent 2f4e097a68
commit 321e3e83a4

View File

@ -1,3 +1,4 @@
import os
import re
from collections import defaultdict
from decimal import Decimal
@ -68,105 +69,113 @@ def load_1D(filepath):
Names of these dictionaries are M + measurement number. They include HKL indeces, angles,
monitors, stepsize and array of counts
"""
det_variables = {"file_type": str(filepath)[-3:], "meta": {}}
with open(filepath, "r") as infile:
# read metadata
for line in infile:
det_variables["Measurements"] = {}
if "=" in line:
variable, value = line.split("=")
variable = variable.strip()
if variable in META_VARS_FLOAT:
det_variables["meta"][variable] = float(value)
elif variable in META_VARS_STR:
det_variables["meta"][variable] = str(value)[:-1].strip()
elif variable in META_UB_MATRIX:
det_variables["meta"][variable] = re.findall(r"[-+]?\d*\.\d+|\d+", str(value))
if "#data" in line:
# this is the end of metadata and the start of data section
break
# read data
if det_variables["file_type"] == "ccl":
decimal = list()
data = infile.readlines()
position = -1
for lines in data:
position = position + 1
if (
bool(re.match("(\s\s\s\d)", lines[0:4])) == True
or bool(re.match("(\s\s\d\d)", lines[0:4])) == True
or bool(re.match("(\s\d\d\d)", lines[0:4])) == True
or bool(re.match("(\d\d\d\d)", lines[0:4])) == True
):
counts = []
measurement_number = int(lines.split()[0])
d = {}
d["h_index"] = float(lines.split()[1])
decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
d["k_index"] = float(lines.split()[2])
decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
d["l_index"] = float(lines.split()[3])
decimal.append(bool(Decimal(d["l_index"]) % 1 == 0))
if det_variables["meta"]["zebra_mode"] == "bi":
d["twotheta_angle"] = float(lines.split()[4]) # gamma
d["omega_angle"] = float(lines.split()[5]) # omega
d["chi_angle"] = float(lines.split()[6]) # nu
d["phi_angle"] = float(lines.split()[7]) # doesnt matter
elif det_variables["meta"]["zebra_mode"] == "nb":
d["gamma_angle"] = float(lines.split()[4]) # gamma
d["omega_angle"] = float(lines.split()[5]) # omega
d["nu_angle"] = float(lines.split()[6]) # nu
d["unkwn_angle"] = float(lines.split()[7])
next_line = data[position + 1]
d["number_of_measurements"] = int(next_line.split()[0])
d["angle_step"] = float(next_line.split()[1])
d["monitor"] = float(next_line.split()[2])
d["unkwn1"] = float(next_line.split()[3])
d["unkwn2"] = float(next_line.split()[4])
d["date"] = str(next_line.split()[5])
d["time"] = str(next_line.split()[6])
d["scan_type"] = str(next_line.split()[7])
for i in range(
int(int(next_line.split()[0]) / 10) + (int(next_line.split()[0]) % 10 > 0)
):
fileline = data[position + 2 + i].split()
numbers = [int(w) for w in fileline]
counts = counts + numbers
d["om"] = np.linspace(
float(lines.split()[5])
- (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
float(lines.split()[5])
+ (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
int(next_line.split()[0]),
)
d["Counts"] = counts
det_variables["Measurements"][str("M" + str(measurement_number))] = d
if all(decimal):
det_variables["meta"]["indices"] = "hkl"
else:
det_variables["meta"]["indices"] = "real"
elif det_variables["file_type"] == "dat":
# skip the first 2 rows, the third row contans the column names
next(infile)
next(infile)
row_names = next(infile).split()
data_cols = defaultdict(list)
for line in infile:
if "END-OF-DATA" in line:
# this is the end of data
break
for name, val in zip(row_names, line.split()):
data_cols[name].append(float(val))
det_variables["Measurements"] = dict(data_cols)
else:
print("Unknown file extention")
_, ext = os.path.splitext(filepath)
det_variables = parse_1D(infile, data_type=ext)
return det_variables
def parse_1D(fileobj, data_type):
# read metadata
metadata = {}
for line in fileobj:
if "=" in line:
variable, value = line.split("=")
variable = variable.strip()
if variable in META_VARS_FLOAT:
metadata[variable] = float(value)
elif variable in META_VARS_STR:
metadata[variable] = str(value)[:-1].strip()
elif variable in META_UB_MATRIX:
metadata[variable] = re.findall(r"[-+]?\d*\.\d+|\d+", str(value))
if "#data" in line:
# this is the end of metadata and the start of data section
break
# read data
if data_type == ".ccl":
measurements = {}
decimal = list()
data = fileobj.readlines()
position = -1
for lines in data:
position = position + 1
if (
bool(re.match("(\s\s\s\d)", lines[0:4])) == True
or bool(re.match("(\s\s\d\d)", lines[0:4])) == True
or bool(re.match("(\s\d\d\d)", lines[0:4])) == True
or bool(re.match("(\d\d\d\d)", lines[0:4])) == True
):
counts = []
measurement_number = int(lines.split()[0])
d = {}
d["h_index"] = float(lines.split()[1])
decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
d["k_index"] = float(lines.split()[2])
decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
d["l_index"] = float(lines.split()[3])
decimal.append(bool(Decimal(d["l_index"]) % 1 == 0))
if metadata["zebra_mode"] == "bi":
d["twotheta_angle"] = float(lines.split()[4]) # gamma
d["omega_angle"] = float(lines.split()[5]) # omega
d["chi_angle"] = float(lines.split()[6]) # nu
d["phi_angle"] = float(lines.split()[7]) # doesnt matter
elif metadata["zebra_mode"] == "nb":
d["gamma_angle"] = float(lines.split()[4]) # gamma
d["omega_angle"] = float(lines.split()[5]) # omega
d["nu_angle"] = float(lines.split()[6]) # nu
d["unkwn_angle"] = float(lines.split()[7])
next_line = data[position + 1]
d["number_of_measurements"] = int(next_line.split()[0])
d["angle_step"] = float(next_line.split()[1])
d["monitor"] = float(next_line.split()[2])
d["unkwn1"] = float(next_line.split()[3])
d["unkwn2"] = float(next_line.split()[4])
d["date"] = str(next_line.split()[5])
d["time"] = str(next_line.split()[6])
d["scan_type"] = str(next_line.split()[7])
for i in range(
int(int(next_line.split()[0]) / 10) + (int(next_line.split()[0]) % 10 > 0)
):
fileline = data[position + 2 + i].split()
numbers = [int(w) for w in fileline]
counts = counts + numbers
d["om"] = np.linspace(
float(lines.split()[5])
- (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
float(lines.split()[5])
+ (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
int(next_line.split()[0]),
)
d["Counts"] = counts
measurements[str("M" + str(measurement_number))] = d
if all(decimal):
metadata["indices"] = "hkl"
else:
metadata["indices"] = "real"
elif data_type == ".dat":
# skip the first 2 rows, the third row contans the column names
next(fileobj)
next(fileobj)
col_names = next(fileobj).split()
data_cols = defaultdict(list)
for line in fileobj:
if "END-OF-DATA" in line:
# this is the end of data
break
for name, val in zip(col_names, line.split()):
data_cols[name].append(float(val))
measurements = dict(data_cols)
else:
print("Unknown file extention")
return {"meta": metadata, "Measurements": measurements}