Refactor parsing of the first lines in each meas
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@ -57,6 +57,40 @@ META_VARS_FLOAT = (
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)
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META_UB_MATRIX = ("ub1j", "ub2j", "ub3j")
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CCL_FIRST_LINE = (
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# the first element is `measurement_number`, which we don't save to metadata
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("h_index", float),
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("k_index", float),
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("l_index", float),
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)
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CCL_FIRST_LINE_BI = (
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*CCL_FIRST_LINE,
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("twotheta_angle", float),
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("omega_angle", float),
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("chi_angle", float),
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("phi_angle", float),
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)
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CCL_FIRST_LINE_NB = (
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*CCL_FIRST_LINE,
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("gamma_angle", float),
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("omega_angle", float),
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("nu_angle", float),
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("unkwn_angle", float),
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)
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CCL_SECOND_LINE = (
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("number_of_measurements", int),
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("angle_step", float),
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("monitor", float),
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("temperature", float),
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("mag_field", float),
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("date", str),
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("time", str),
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("scan_type", str),
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)
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def load_1D(filepath):
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"""
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@ -99,42 +133,31 @@ def parse_1D(fileobj, data_type):
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measurements = {}
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if data_type == ".ccl":
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decimal = list()
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for line in fileobj:
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counts = []
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measurement_number = int(line.split()[0])
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d = {}
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d["h_index"] = float(line.split()[1])
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decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
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d["k_index"] = float(line.split()[2])
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decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
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d["l_index"] = float(line.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(line.split()[4]) # gamma
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d["omega_angle"] = float(line.split()[5]) # omega
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d["chi_angle"] = float(line.split()[6]) # nu
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d["phi_angle"] = float(line.split()[7]) # doesnt matter
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elif metadata["zebra_mode"] == "nb":
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d["gamma_angle"] = float(line.split()[4]) # gamma
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d["omega_angle"] = float(line.split()[5]) # omega
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d["nu_angle"] = float(line.split()[6]) # nu
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d["unkwn_angle"] = float(line.split()[7])
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if metadata["zebra_mode"] == "bi":
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ccl_first_line = CCL_FIRST_LINE_BI
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elif metadata["zebra_mode"] == "nb":
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ccl_first_line = CCL_FIRST_LINE_NB
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ccl_second_line = CCL_SECOND_LINE
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for line in fileobj:
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d = {}
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# first line
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measurement_number, *params = line.split()
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for param, (param_name, param_type) in zip(params, ccl_first_line):
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d[param_name] = param_type(param)
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decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
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decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
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decimal.append(bool(Decimal(d["l_index"]) % 1 == 0))
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# second line
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next_line = next(fileobj)
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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["temperature"] = float(next_line.split()[3])
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d["mag_field"] = 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 = next(fileobj).split()
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numbers = [int(w) for w in fileline]
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counts = counts + numbers
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params = next_line.split()
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for param, (param_name, param_type) in zip(params, ccl_second_line):
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d[param_name] = param_type(param)
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d["om"] = np.linspace(
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float(line.split()[5])
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- (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
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@ -142,8 +165,19 @@ def parse_1D(fileobj, data_type):
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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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# subsequent lines with counts
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counts = []
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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 = next(fileobj).split()
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numbers = [int(w) for w in fileline]
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counts = counts + numbers
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d["Counts"] = counts
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measurements[measurement_number] = d
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measurements[int(measurement_number)] = d
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if all(decimal):
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metadata["indices"] = "hkl"
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