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ice_data_comparison.py
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ice_data_comparison.py
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# -*- coding: utf-8 -*-
"""
Created on Mon Mar 22 18:57:56 2021
@author: siirias
"""
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
fig_dpi = 300
for data_set in ['A001', 'B001', 'D001']:
output_dir = "D:\\Data\\Figures\\SmartSea\\new_run\\ice\\"
new_dat=pd.read_csv("E:\\SmartSea\\derived_data\\ice_extent_{}.csv".format(data_set),parse_dates=['time'])
old_dat=pd.read_csv("E:\\SmartSea\\derived_data_old\\ice_extent_{}.csv".format(data_set),parse_dates=['time'])
l = len(new_dat.time)
fig,ax1 = plt.subplots(figsize=[20,10])
plt.plot(old_dat.time[:l], old_dat.ice_extent[:l],'r',label='old')
plt.plot(new_dat.time[:l], new_dat.ice_extent[:l],'b',label='new')
plt.title(data_set)
plt.legend(loc='upper left')
ax2 = ax1.twinx()
#plt.figure()
plt.plot(old_dat.time[:l], old_dat.ice_extent[:l]-new_dat.ice_extent[:l],
'k',label='old - new', alpha=0.4)
plt.legend(loc='upper right')
print("{} difference in averages: {}, ({}%)".format(
data_set,
np.mean(old_dat.ice_extent[:l]-new_dat.ice_extent[:l]),
100.0*(1.0-np.mean(old_dat.ice_extent[:l])/np.mean(new_dat.ice_extent[:l]))
))
# print("{} difference in averages: {}, ({}%)".format(
# data_set,
# np.mean(np.abs(old_dat.ice_extent[:l]-new_dat.ice_extent[:l])),
# 100.0*(np.mean(np.abs(old_dat.ice_extent[:l]-new_dat.ice_extent[:l]))/np.mean(old_dat.ice_extent[:l]))
# ))
filename = "{}_ice_concentration.png".format(data_set)
plt.savefig(output_dir+filename,\
facecolor='w',dpi=fig_dpi,bbox_inches='tight')
print("Saved: {}".format(\
output_dir+filename))