Replace analysistool.py

analysistool.py

@@ -2,6 +2,7 @@ import numpy as np
 import pandas as pd
 import seaborn as sns
 import matplotlib.pyplot as plt
+from matplotlib.ticker import MultipleLocator
 from datetime import datetime
 
 class AnalysisTool:
@@ -18,9 +19,9 @@ class AnalysisTool:
         
         
     def boxplot(self, croptype, save=False):
-        """Plot relative deltas of different cropsites for a give croptype"""
+        """Plot log deltas of different cropsites for a give croptype"""
         
-        colors = ['#134e6f', '#ffa822', '#ff6150', '#1ac0c6']
+        colors = ['#134e6f', '#ffa822', '#ff6150', '#1ac0c6', '#9e416b']
         
         data = pd.DataFrame(columns=['Date', 'Month', 'Cropsite', 'Delta'])
         
@@ -31,7 +32,7 @@ class AnalysisTool:
             if croptype in self.data[cropsite]['cropwise'].keys():
                 for season in self.data[cropsite]['cropwise'][croptype]:
                     dates = self.data[cropsite]['cropwise'][croptype][season]['dates']
-                    deltas = self.data[cropsite]['cropwise'][croptype][season]['deltas_rel']['MODIS']
+                    deltas = self.data[cropsite]['cropwise'][croptype][season]['deltas_log']['MODIS']
                     months = []
                     cropsites = []
 
@@ -43,24 +44,32 @@ class AnalysisTool:
                         months.append(date.strftime('%b'))
                         cropsites.append(cropsite)
 
-                    df = pd.DataFrame(list(zip(dates, months, cropsites, np.array(deltas)*100)), columns=['Date', 'Month', 'Cropsite', 'Delta'])
+                    df = pd.DataFrame(list(zip(dates, months, cropsites, deltas)), columns=['Date', 'Month', 'Cropsite', 'Delta'])
                     data = pd.concat([data, df])
         
         months = []
+        hold = []
         
         for i in range(start_month, start_month + 12):
             if i > 12:
                 i = i - 12
             month = datetime.strptime(str(i), '%m').strftime('%b')
-            if month in data.values:
+            if month not in data.values:
+                hold.append(month)
+            else:
+                months += hold
+                hold = []
                 months.append(month)
         
-        plt.figure(figsize=(10,20))
+        plt.figure(figsize=(20,10))
         axs = sns.boxplot(x='Month', y='Delta', hue='Cropsite', palette=colors, data=data, order=months)
         axs.set_title(croptype)
-        axs.set_ylabel('Relative Difference in Latent Heat Flux [%]')
+        axs.yaxis.set_major_locator(MultipleLocator(1))
+        axs.set_ylabel('Sign-adjusted Natural Logarithm of Difference in Latent Heat Flux [sign(W m-2) * ln(|W m-2|)]')
+        for i in range(int(len(months)/2)):
+            axs.axvline((i*2)+1, color='black', linestyle='-', linewidth=1120/len(months), alpha=0.05)
         try:
-            axs.axvline(months.index('Jan'), color='lightgrey', linestyle='--')
+            axs.axvline(months.index('Jan')-0.5, color='lightgrey', linestyle='--')
         except ValueError:
             pass
         axs.axhline(0, color='black', linestyle='-')
@@ -74,7 +83,7 @@ class AnalysisTool:
     def scatterplot(self, croptype, cropsite='all', combine=True, save=False):
         """Plot latent heat values: MODIS vs FLUXNET"""
         
-        colors = ['#134e6f', '#ffa822', '#ff6150', '#1ac0c6']
+        colors = ['#134e6f', '#ffa822', '#ff6150', '#1ac0c6', '#9e416b']
         
         fig, axs = plt.subplots(figsize=(10, 10))