more lint

ausankey/ausankey.py

@@ -67,42 +67,43 @@ def sankey(
 
     num_col = len(data.columns)
     data.columns = range(num_col)  # force numeric column headings
-    N = int(num_col/2)  # number of labels
+    num_side = int(num_col/2)  # number of labels
+    num_flow = num_side - 1
 
     # sizes
-    weight_sum = np.empty(N)
-    num_uniq = np.empty(N)
-    col_hgt = np.empty(N)
-    for ii in range(N):
+    weight_sum = np.empty(num_side)
+    num_uniq = np.empty(num_side)
+    col_hgt = np.empty(num_side)
+    for ii in range(num_side):
         weight_sum[ii] = sum(data[2*ii+1])
         num_uniq[ii] = len(pd.Series(data[2*ii]).unique())
 
-    for ii in range(N):
+    for ii in range(num_side):
         col_hgt[ii] = weight_sum[ii] + (num_uniq[ii]-1)*barGap*max(weight_sum)
 
     # overall dimensions
     plot_height = max(col_hgt)
     sub_width = plot_height/aspect
     plotWidth = (
-        (N-1)*sub_width
+        (num_side-1)*sub_width
         + 2*sub_width*labelWidth
-        + N*sub_width*barWidth
+        + num_side*sub_width*barWidth
       )
 
     # offsets for alignment
-    voffset = np.empty(N)
+    voffset = np.empty(num_side)
     if valign == "top":
         vscale = 1
     elif valign == "center":
         vscale = 0.5
     else: # bottom, or undefined
         vscale = 0
 
-    for ii in range(N):
+    for ii in range(num_side):
         voffset[ii] = vscale*(col_hgt[1] - col_hgt[ii])
 
     # labels
-    label_record = data[range(0, 2*N, 2)].to_records(index=False)
+    label_record = data[range(0, 2*num_side, 2)].to_records(index=False)
     flattened = [item for sublist in label_record for item in sublist]
     flatcat = pd.Series(flattened).unique()
 
@@ -118,10 +119,10 @@ def sankey(
     if ax is None:
         ax = plt.gca()
 
-    for ii in range(N-1):
+    for ii in range(num_flow):
 
         _sankey(
-            ii, N-1, data,
+            ii, num_flow, data,
             titles=titles,
             titleGap=titleGap,
             titleSide=titleSide,
@@ -167,7 +168,7 @@ def sankey(
 
 
 def _sankey(
-        ii, N, data,
+        ii, num_flow, data,
         colorDict=None,
         labelOrder=None,
         fontsize=None,
@@ -318,15 +319,15 @@ def _sankey(
           lw=0,
           snap=True,
         )
-        if ii < N-1:  # inside labels
+        if ii < num_flow-1:  # inside labels
             ax.text(
               xRight + (labelGap+barWidth)*xMax,
               rbot + 0.5*rrr,
               labelDict.get(rightLabel, rightLabel),
               {'ha': 'left', 'va': 'center'},
               fontsize=fontsize
             )
-        if ii == N-1:  # last time
+        if ii == num_flow-1:  # last time
             ax.text(
               xRight + (labelGap+barWidth)*xMax,
               rbot + 0.5*rrr,
@@ -446,7 +447,7 @@ def check_data_matches_labels(labels, data, side):
             raise LabelMismatchError(side, msg)
 
 
-def combineColours(c1, c2, N):
+def combineColours(c1, c2, num_col):
 
     colorArrayLen = 4
     # if not [r,g,b,a] assume a hex string like "#rrggbb":
@@ -463,10 +464,10 @@ def combineColours(c1, c2, N):
         b2 = int(c2[5:7], 16)/255
         c2 = [r2, g2, b2, 1]
 
-    rr = np.linspace(c1[0], c2[0], N)
-    gg = np.linspace(c1[1], c2[1], N)
-    bb = np.linspace(c1[2], c2[2], N)
-    aa = np.linspace(c1[3], c2[3], N)
+    rr = np.linspace(c1[0], c2[0], num_col)
+    gg = np.linspace(c1[1], c2[1], num_col)
+    bb = np.linspace(c1[2], c2[2], num_col)
+    aa = np.linspace(c1[3], c2[3], num_col)
 
     return np.array([rr, gg, bb, aa])
 

sankey_doc_examples.py

@@ -5,7 +5,6 @@
 import ausankey as sky
 
 data = pd.read_csv('tests/fruit.csv')
-print(data)
 
 plt.figure()
 sky.sankey(data)
@@ -25,7 +24,7 @@
 plt.show()
 plt.savefig("doc/fruits_jet.png")
 
-colorDict = {
+color_dict = {
     'apple':     '#f71b1b',
     'blueberry': '#1b7ef7',
     'banana':    '#f3f71b',
@@ -34,11 +33,11 @@
 }
 
 plt.figure()
-sky.sankey(data,colorDict=colorDict)
+sky.sankey(data,colorDict=color_dict)
 plt.show()
 plt.savefig("doc/fruits_colordict.png")
 
-labelDict = {
+label_dict = {
     'apple':     'Apple',
     'blueberry': "B'berry",
     'banana':    'Banana',
@@ -47,7 +46,7 @@
 }
 
 plt.figure()
-sky.sankey(data,labelDict=labelDict)
+sky.sankey(data,labelDict=label_dict)
 plt.show()
 plt.savefig("doc/fruits_labeldict.png")
 
@@ -127,7 +126,7 @@
 plt.savefig("doc/frame2_sort_n1.png")
 
 
-colorDict =  {
+color_dict =  {
    'a':'#f71b1b',
    'b':'#1b7ef7',
   'ab':'#8821aa',
@@ -153,7 +152,7 @@
 sky.sankey(
   data,
   sorting    = -1,
-  colorDict  = colorDict,
+  colorDict  = color_dict,
   labelWidth = 0.1,
   labelGap   = 0.02,
   barWidth   = 0.05,

tests/test_fruit_defaults.py

@@ -10,36 +10,36 @@ def test_fruits_default(self):
         sky.sankey(self.data)
 
     def test_fruits_sorting(self):
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, sorting=1)
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, sorting=-1)
 
     def test_fruits_colormap(self):
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, colormap="jet")
 
     def test_fruits_colordict(self):
-        
+
         plt.figure(dpi=150)
-        sky.sankey(self.data, colorDict=self.colorDict)
-        
+        sky.sankey(self.data, colorDict=self.color_dict)
+
     def test_fruits_titles(self):
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, titles=["Summer", "Winter"])
-    
+
     def test_fruits_valign(self):
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, valign="top")
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, valign="center")
-        
+
         plt.figure(dpi=150)
         sky.sankey(self.data, valign="bottom")
 

tests/test_fruit_setup.py

@@ -1,17 +1,18 @@
-import pandas as pd
+
 from .generic_test import GenericTest
 
+import pandas as pd
 
 class TestFruit(GenericTest):
     """ Setup sankey test with data in fruit.csv """
 
     def setUp(self):
-        
+
         self.figure_name = "fruit"
         self.data = pd.read_csv(
             'tests/fruit.csv', sep=','
         )
-        self.colorDict = {
+        self.color_dict = {
             'apple': '#f71b1b',
             'blueberry': '#1b7ef7',
             'banana': '#f3f71b',