import MOS_reader as mr import os path = "../Data/wacl_data/Raw_data_files/" f_date = '201610' cal_file = os.listdir(path + f_date + '/MOS') # The name of the MOS file to be analysed data_concat = mr.readin(path, f_date, cal_file, 1, 5)
import matplotlib.pyplot as plt import MOS_reader as mr import pylab import voc_reader from pylab import * from sklearn import linear_model from scipy import stats from matplotlib.offsetbox import AnchoredText # The path to where the raw files are stored path = "../Data/wacl_data/Raw_data_files/" f_date = '201610' cal_file = os.listdir(path + f_date + '/MOS') # The name of the MOS file to be analysed Time_avg = '300S' data_concat = mr.readin(path, f_date, cal_file, 1, 5, Time_avg) data_voc = voc_reader.extract_voc('../Data/', 'Detailed Compound Concentrations', 'Analyte vs Time', Time_avg) data_merge = data_concat.merge(data_voc, how='inner', on=['Time']) sub = 'vocs6' voc6 = ['C3H3+ (1,3-butadiene;O2+) (ppb)', 'MOS1c_Av'] VOCs6fig = plt.figure("vocs6") ax1 = VOCs6fig.add_subplot(111) ax2 = ax1.twinx() colors = [ "black", "firebrick", "lightgreen", "c", "darkblue", "purple", "orange", "forestgreen", "lightskyblue", "indigo", "dimgrey", "fuchsia" ] ax = []