From 82ff4a871d674fe8605814c1ec33eddcf4e4afc8 Mon Sep 17 00:00:00 2001
From: robertsilen <robert.silen@iki.fi>
Date: Thu, 23 Nov 2017 12:58:41 +0200
Subject: [PATCH] testing

---
 groupanalysis.py   | 25 +++++++++++++++++++++++++
 timeseries_plot.py | 39 +++++++++++++++++++++++++++++++++++++++
 2 files changed, 64 insertions(+)
 create mode 100644 timeseries_plot.py

diff --git a/groupanalysis.py b/groupanalysis.py
index 28e3016..c3e0d05 100644
--- a/groupanalysis.py
+++ b/groupanalysis.py
@@ -57,8 +57,11 @@ def stop(self):
 # Read data from file
 inputfiles = []
 
+<<<<<<< HEAD
 timeseries = True
 
+=======
+>>>>>>> parent of 040a575... removed timeseries_plt.py and updated plotting to groupanalysis.py
 if len(sys.argv) < 2: 
 	sys.argv.append('example.csv')
 
@@ -73,6 +76,7 @@ def stop(self):
 timeseries_medians = pd.DataFrame()
 timeseries_results = pd.DataFrame()	
 
+<<<<<<< HEAD
 
 
 df_timeseries
@@ -84,15 +88,23 @@ def stop(self):
 # Loop through all files
 for j, element in enumerate(inputfiles):
 	progress_bar = ProgressBar()
+=======
+# Loop through all files
+for j, element in enumerate(inputfiles):
+>>>>>>> parent of 040a575... removed timeseries_plt.py and updated plotting to groupanalysis.py
 	try: 
 		input = element
 
 		print("\nReading: "+str(input))
+<<<<<<< HEAD
 		
 		if timeseries==False: 
 			df = pd.read_csv(input)
 		else: 
 			df = df_timeseries
+=======
+		df = pd.read_csv(input)
+>>>>>>> parent of 040a575... removed timeseries_plt.py and updated plotting to groupanalysis.py
 
 		if input.endswith('.csv'):
 			input = input[:-4]
@@ -117,6 +129,10 @@ def stop(self):
 		else: 
 			print ('Groups are NOT equal size: '+str(a))
 	
+<<<<<<< HEAD
+=======
+		progress_bar = ProgressBar()
+>>>>>>> parent of 040a575... removed timeseries_plt.py and updated plotting to groupanalysis.py
 		progress_bar.start()
 
 		# Prepare to capture results
@@ -227,12 +243,21 @@ def stop(self):
 		
 	except: 
 		progress_bar.stop()
+<<<<<<< HEAD
+
+		print "\nUnexpected error:", sys.exc_info()[0]
 
+timeseries_results = pd.concat([timeseries_medians, timeseries_values], axis=1)
+timeseries_results = pd.concat([timeseries_results.loc[['Group'],:], timeseries_results.drop('Group', axis=0)], axis=0)
+
+=======
+		progress_bar.join()
 		print "\nUnexpected error:", sys.exc_info()[0]
 
 timeseries_results = pd.concat([timeseries_medians, timeseries_values], axis=1)
 timeseries_results = pd.concat([timeseries_results.loc[['Group'],:], timeseries_results.drop('Group', axis=0)], axis=0)
 
+>>>>>>> parent of 040a575... removed timeseries_plt.py and updated plotting to groupanalysis.py
 output = 'medians'+time.strftime("-%d-%m-%Y")+".csv"
 print "\nWriting summary of median values: "+str(output)+"\n"
 timeseries_results.to_csv(output)
diff --git a/timeseries_plot.py b/timeseries_plot.py
new file mode 100644
index 0000000..a679eeb
--- /dev/null
+++ b/timeseries_plot.py
@@ -0,0 +1,39 @@
+import sys
+import pandas as pd   
+import matplotlib.pyplot as plt  
+
+# load all input files into array of dataframes
+data = []
+for j, element in enumerate(sys.argv[1:]):
+	data.append(pd.read_csv(element))
+	data[j].set_index('Person',inplace=True)
+	input = element
+	if input.endswith('.csv'):
+		input = input[:-4]
+	data[j] = data[j].T
+	data[j].insert(loc=1, column='TimeSeries', value=input)
+
+# merge dataframes, change cells to numeric, not objects
+df = pd.concat(data, axis=0, join='inner')
+df = pd.concat([df.ix[:,:2], df.ix[:,2:].apply(pd.to_numeric)], axis=1)
+df['Group'] = df['Group'].astype(int)
+
+# move groups and timeseries to first columns
+cols = list(df)
+cols.insert(0, cols.pop(cols.index('Group')))
+cols.insert(0, cols.pop(cols.index('TimeSeries')))
+df = df.ix[:, cols]
+
+# plotting
+for column in df.ix[:,2:]:
+	fig, ax = plt.subplots()
+	labels = []
+	for key, grp in df.groupby(['TimeSeries', 'Group'])[[column]].median().groupby(['TimeSeries']):
+		ax = grp.reset_index().plot(ax=ax, x='Group', y=column, xticks=grp.reset_index()['Group'], kind='line', title=column)
+		labels.append(key)
+	lines, _ = ax.get_legend_handles_labels()
+	ax.legend(lines, labels, loc='best')
+	plt.savefig('fig/'+column+'.png')
+	plt.clf()
+	
+df.to_csv('test.csv')