GENENET8 update

1 files changed, 59 insertions, 27 deletions

diff --git a/sourcecodes/kfold_plotly.py b/sourcecodes/kfold_plotly.py
index e038c796..102d01d2 100644
--- a/sourcecodes/kfold_plotly.py
+++ b/sourcecodes/kfold_plotly.py
@@ -1,15 +1,13 @@
-#!/home/jziebart/python/Python-2.7.15/python
+#!/var/www/html/compbio/BNW_1.3/bnw-env/bin/python
 import os
 import sys
 
-#sys.path.append('/home/jziebart/.local/bin')
-#sys.path.append('/home/jziebart/.local/lib')
-
 import plotly
 import plotly.graph_objs as go
 import csv
 import string
 
+
 netID = sys.argv[-1]
 
 outfile = netID+"kfold_plotly.html"
@@ -17,19 +15,26 @@ outfile = netID+"kfold_plotly.html"
 filename=netID+"kfoldCV.txt"
 f=open(filename,"r")
 #Read the first line to get the variable name
-line=f.readline()
-line = map(string.strip,line.strip().split(" "))
-print line
-varName = line[-1]
-print varName
+lines=f.readlines()
+line = lines.pop()
+#line = map(string.strip,line.strip().split(" "))
+line = line.strip().split(" ")
+#print line
+varName = line[3][:-1]
+#print varName
+plot_title = varName+' k-fold validation'
+#print plot_title
+header = lines.pop(0)
 
 #Read type file to determine if it is continuous or discrete
 typefile = netID+"type.txt"
 tf=open(typefile,"r")
 line=tf.readline()
-varnames = map(string.strip,line.strip().split("\t"))
+#varnames = map(string.strip,line.strip().split("\t"))
+varnames = line.strip().split("\t")
 line=tf.readline()
-vartypes = map(string.strip,line.strip().split("\t"))
+#vartypes = map(string.strip,line.strip().split("\t"))
+vartypes = line.strip().split("\t")
 varindex = varnames.index(varName)
 cd_type = int(vartypes[varindex])
 
@@ -37,20 +42,32 @@ cd_type = int(vartypes[varindex])
 if cd_type == 1:
     #Make scatterplot for continuous_data
     #Read introductory lines from file
-    for i in range(6):
-        line = f.readline()
+#    for i in range(6):
+#        line = f.readline()
     #Read the data
     x = []
     y = []
-    line = f.readline()
-    while line:
-        line = map(string.strip,line.strip().split("\t"))
+#    line = f.readline()
+#    while line:
+    for line in lines:
+        #line = map(string.strip,line.strip().split("\t"))
+        line = line.strip().split("\t")
         x.append(float(line[2]))
         y.append(float(line[3]))
-        line=f.readline()
+#        line=f.readline()
 
     data = [go.Scatter(x=x,y=y,mode='markers')]
     layout = go.Layout(
+        title=plot_title,
+        titlefont=dict(
+            family='Arial, sans-serif',
+            size=24,
+            color='black'
+            ),
+	title_xref="paper",
+	title_x=0.5,
+	title_xanchor="center",
+	title_yanchor="middle",
         xaxis=dict(
             autorange=True,
             title='Actual values',
@@ -68,7 +85,8 @@ if cd_type == 1:
                 size=18,
                 color='black'
                 ),
-            )
+            ),
+        margin=dict(t=30,l=50,b=40)
         )
     fig = go.Figure(data=data, layout = layout)
     plotly.offline.plot(fig,filename=outfile)
@@ -76,17 +94,20 @@ if cd_type == 1:
 else:
     #Make bar chart for discrete data
     #Read introductory lines from file
-    for i in range(5):
-        line = f.readline()
+#    for i in range(5):
+#        line = f.readline()
     #Get names of states
-    line = map(string.strip,line.strip().split("\t"))
-    states = line[3:]
+    #header = map(string.strip,header.strip().split("\t"))
+    header = header.strip().split("\t")
+    states = header[3:]
     #Read the data
     actual = []
     predicted = []
-    line = f.readline()
-    while line:
-        line = map(string.strip,line.strip().split("\t"))
+#    line = f.readline()
+#    while line:
+    for line in lines:
+        #line = map(string.strip,line.strip().split("\t"))
+        line = line.strip().split("\t")
         actual.append(line[2])
         predict_x = line[3:]
         predict_x = [float(x) for x in predict_x]
@@ -99,7 +120,7 @@ else:
         if len(max_items) > 1:
             predicted.pop()
             actual.pop()
-        line=f.readline()
+#        line=f.readline()
     
     #Go through states and get number of true positives, false positives, and false negatives
     tp_all = []
@@ -128,6 +149,16 @@ else:
     data = [trace1,trace2,trace3]
     layout = go.Layout(
         barmode='group',
+        title=plot_title,
+        titlefont=dict(
+            family='Arial, sans-serif',
+            size=24,
+            color='black'
+            ),
+	title_xref="paper",	
+	title_x=0.5,
+	title_xanchor="center",
+	title_yanchor="middle",
         xaxis=dict(
             autorange=True,
             title='State',
@@ -145,7 +176,8 @@ else:
                 size=18,
                 color='black'
                 ),
-            )
+            ),
+        margin=dict(t=30,l=50,b=40),
     )
     fig = go.Figure(data=data, layout = layout)
     plotly.offline.plot(fig,filename=outfile)