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functions.py
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functions.py
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import numpy as np
import pandas as pd
from netCDF4 import Dataset
def build_df(fname, time_as_column=False):
'''
Parse a ANDI netCDF file to a pandas dataframe
fname -- full file name path
time_as_column -- use time values as column
'''
dataset = Dataset(fname, 'r')
SCAN_INDEX = 'scan_index'
POINT_COUNT = 'point_count'
MASS_VALUES = 'mass_values'
INTENSITY_VALUES = 'intensity_values'
SCAN_ACQ_TIME = 'scan_acquisition_time'
scan_indexes = dataset.variables[SCAN_INDEX]
mz_values = np.asarray(dataset.variables[MASS_VALUES])
mz_values = np.rint(mz_values).astype(int)
point_counts = dataset.variables[POINT_COUNT]
intensity_values = dataset.variables[INTENSITY_VALUES]
time_val = np.array([t.data for t in dataset.variables[SCAN_ACQ_TIME]])
mz_max = int(round(np.max(mz_values), 0))
mz_min = int(round(np.min(mz_values), 0))
num_mz = mz_max - mz_min + 1
point_upper_bound = len(intensity_values) - 1
scan_list = []
time_list = []
for i in range(len(scan_indexes)):
num_point = point_counts[i]
if num_point == 0:
continue
start_i = scan_indexes[i]
row_intensity = intensity_values[start_i:start_i+ num_point]
row_mz = mz_values[start_i:start_i+ num_point]
np_fill_index = row_mz - mz_min
time_row = np.zeros(num_mz)
np.put(time_row, np_fill_index, row_intensity)
scan_list.append(time_row)
time_list.append(time_val[i])
if time_as_column:
df = pd.DataFrame(np.transpose(scan_list), columns=time_list, index=range(mz_min, mz_max+1))
else:
df = pd.DataFrame(scan_list, columns=range(mz_min, mz_max+1), index=time_list)
return df