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