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 = []