From bb9d93322abf825368dedaafc2376ef8fdfc1e2f Mon Sep 17 00:00:00 2001
From: ziejd2
Date: Mon, 28 Jan 2019 16:31:54 -0600
Subject: Jan 28 2019 update

---
 sourcecodes/kfold_plotly.py | 151 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 151 insertions(+)
 create mode 100644 sourcecodes/kfold_plotly.py

(limited to 'sourcecodes/kfold_plotly.py')

diff --git a/sourcecodes/kfold_plotly.py b/sourcecodes/kfold_plotly.py
new file mode 100644
index 00000000..e038c796
--- /dev/null
+++ b/sourcecodes/kfold_plotly.py
@@ -0,0 +1,151 @@
+#!/home/jziebart/python/Python-2.7.15/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"
+ 
+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
+
+#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"))
+line=tf.readline()
+vartypes = map(string.strip,line.strip().split("\t"))
+varindex = varnames.index(varName)
+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()
+    #Read the data
+    x = []
+    y = []
+    line = f.readline()
+    while line:
+        line = map(string.strip,line.strip().split("\t"))
+        x.append(float(line[2]))
+        y.append(float(line[3]))
+        line=f.readline()
+
+    data = [go.Scatter(x=x,y=y,mode='markers')]
+    layout = go.Layout(
+        xaxis=dict(
+            autorange=True,
+            title='Actual values',
+            titlefont=dict(
+                family='Arial, sans-serif',
+                size=18,
+                color='black'
+                ),
+            ),
+        yaxis=dict(
+            autorange=True,
+            title='Predicted values',
+            titlefont=dict(
+                family='Arial, sans-serif',
+                size=18,
+                color='black'
+                ),
+            )
+        )
+    fig = go.Figure(data=data, layout = layout)
+    plotly.offline.plot(fig,filename=outfile)
+
+else:
+    #Make bar chart for discrete data
+    #Read introductory lines from file
+    for i in range(5):
+        line = f.readline()
+    #Get names of states
+    line = map(string.strip,line.strip().split("\t"))
+    states = line[3:]
+    #Read the data
+    actual = []
+    predicted = []
+    line = f.readline()
+    while line:
+        line = map(string.strip,line.strip().split("\t"))
+        actual.append(line[2])
+        predict_x = line[3:]
+        predict_x = [float(x) for x in predict_x]
+        max_value = max(predict_x)
+        max_index = predict_x.index(max_value)
+        predicted.append(states[max_index])
+        #check if multiple states are equally likely to be predicted states
+        #I am not going to count these as being predicted here
+        max_items = [x for x in predict_x if (abs(x-max_value) < 0.000001)]
+        if len(max_items) > 1:
+            predicted.pop()
+            actual.pop()
+        line=f.readline()
+    
+    #Go through states and get number of true positives, false positives, and false negatives
+    tp_all = []
+    fp_all = []
+    fn_all = []
+    for state in states:
+        tp = 0
+        fp = 0
+        fn = 0
+        for i in range(len(actual)):
+            actual_i = actual[i]
+            predicted_i = predicted[i]
+            if actual_i == state:
+                if predicted_i == state:
+                    tp = tp + 1
+                else:
+                    fn = fn + 1
+            elif predicted_i == state:
+                fp = fp + 1
+        tp_all.append(tp)
+        fn_all.append(fn)
+        fp_all.append(fp)
+    trace1 = go.Bar(x=states,y=tp_all,name="True Positives")
+    trace2 = go.Bar(x=states,y=fn_all,name="False Negatives")
+    trace3 = go.Bar(x=states,y=fp_all,name="False Positives")
+    data = [trace1,trace2,trace3]
+    layout = go.Layout(
+        barmode='group',
+        xaxis=dict(
+            autorange=True,
+            title='State',
+            titlefont=dict(
+                family='Arial, sans-serif',
+                size=18,
+                color='black'
+                ),
+            ),
+        yaxis=dict(
+            autorange=True,
+            title='Number of cases',
+            titlefont=dict(
+                family='Arial, sans-serif',
+                size=18,
+                color='black'
+                ),
+            )
+    )
+    fig = go.Figure(data=data, layout = layout)
+    plotly.offline.plot(fig,filename=outfile)
-- 
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