Expose label-trimming logic as a separate module for reuse

GEODE/Visualisation/ConfusionMatrix.py

 import argparse
 from GEODE.Store import prepare, tabular
+from GEODE.Visualisation.Legend import trim
 import matplotlib.pyplot as plot
 import pandas
 import seaborn
 from sklearn.metrics import confusion_matrix
 
-def trim(name, maxSize):
-    if len(name) > maxSize:
-        components = name.split(' ')
-        return components[0] + ' […]'
-    else:
-        return name
-
-def trimLabels(labels, maxWidth):
-    return labels if maxWidth is None else [trim(l, maxWidth) for l in labels]
-
 def heatmap(matrix, filePath, labels, **kwargs):
     plot.figure(figsize=(16,13))
     ax = seaborn.heatmap(
@@ -46,7 +37,7 @@ def prepareData(data, labels=None):
 def drawConfusionMatrix(data, outputFile, labels=None, maxWidth=None, **kwargs):
     truth, answers, labels = prepareData(data, labels=labels)
     matrix = confusion_matrix(truth, answers, labels=labels, normalize='true')
-    heatmap(matrix, outputFile, trimLabels(labels, maxWidth), **kwargs)
+    heatmap(matrix, outputFile, trim(labels, maxWidth), **kwargs)
 
 def getArgs(arguments):
     cli = argparse.ArgumentParser(

GEODE/Visualisation/__init__.py

 from GEODE.Visualisation.ConfusionMatrix import drawConfusionMatrix, heatmap
 from GEODE.Visualisation.DensityProfile import densityProfile, drawDensityProfile, plotDensity
+from GEODE.Visualisation.Legend import trim as legend

GEODE/__init__.py

@@ -23,7 +23,7 @@ from GEODE.ENE import eneLabels
 from GEODE.Metadata import article, articleKey, paragraph, paragraphKey, \
         fromKey, relativePath, toKey, uid
 from GEODE.Store import corpus, Directory, SelfContained, tabular, toTSV
-from GEODE.Visualisation import densityProfile, heatmap
+from GEODE.Visualisation import densityProfile, heatmap, legend
 from GEODE.Visualisation.ConfusionMatrix import drawConfusionMatrixCLI
 from GEODE.Visualisation.DensityProfile import drawDensityProfileCLI