Add a script to draw graphs

GEODE/Visualisation/Graph.py

+import argparse
+from GEODE.Store import prepare
+from GEODE.Visualisation.ConfusionMatrix import getConfusionMatrix
+from GEODE.Visualisation.Legend import trim
+from graphviz import Digraph
+from matplotlib.cm import ScalarMappable
+from matplotlib.colors import Normalize
+from seaborn import color_palette
+
+def hexColorRange(vmin, vmax, cmap):
+    mapper = ScalarMappable(
+            norm=Normalize(vmin=vmin, vmax=vmax, clip=True),
+            cmap=color_palette(cmap, as_cmap=True)
+        )
+    def toHexRGB(color):
+        (r, g, b, _) = mapper.to_rgba(color)
+        return f"#{int(r*255):02x}{int(g*255):02x}{int(b*255):02x}"
+    return toHexRGB
+
+def withBorder(color):
+    border = ["#3b3b3b"]
+    return ':'.join(border + 3*[color] + border)
+
+def drawGraph(data, outputFile, cmap='Blues', maxWidth=None):
+    matrix = data['matrix']
+    labels = trim(data['labels'], maxWidth)
+    edgeValues = [c for row in matrix for c in row if c is not None]
+    colorize = hexColorRange(min(edgeValues), max(edgeValues), cmap)
+    g = Digraph()
+    g.graph_attr['rankdir'] = 'LR'
+    g.node_attr['fontsize'] = g.edge_attr['fontsize'] = '22'
+    g.edge_attr['arrowsize'] = g.edge_attr['penwidth'] = '2'
+    dimension = len(matrix)
+    for i in range(0, dimension):
+        g.node(str(i), label=labels[i])
+    for i in range(0, dimension):
+        for j in range(0, len(matrix[i])):
+            link = matrix[i][j]
+            if link is not None and link > 0:
+                label = f"{link}" if type(link) == int else f"{link:.2f}"
+                color=withBorder(colorize(link))
+                g.edge(str(i), str(j), color=color, label=label)
+    return g.render(prepare(outputFile[:-4]), format=outputFile[-3:])
+
+def getArgs(arguments):
+    cli = argparse.ArgumentParser(
+            prog='graph',
+            description="Draw a graph from its weighted adjacency matrix")
+    cli.add_argument('inputJSON')
+    cli.add_argument('outputPNG')
+    cli.add_argument('-w', '--maxWidth', type=int,
+                     help="length from which labels will be truncated")
+    cli.add_argument('-c', '--cmap', help="color map to use")
+    return cli.parse_args(arguments)
+
+def drawGraphCLI(arguments):
+    args = getArgs(arguments)
+    data = getConfusionMatrix(args.inputJSON)
+    drawGraph(data,
+              args.outputPNG,
+              maxWidth=args.maxWidth,
+              cmap=args.cmap)

GEODE/Visualisation/__init__.py

@@ -3,4 +3,5 @@ from GEODE.Visualisation.ConfusionMatrix import extractConfusionMatrix, \
 from GEODE.Visualisation.DensityProfile import densityProfile, \
         drawDensityProfile, plotDensity
 from GEODE.Visualisation.DrawMatrix import drawMatrix
+from GEODE.Visualisation.Graph import drawGraph
 from GEODE.Visualisation.Legend import trim as legend

GEODE/__init__.py

@@ -23,16 +23,18 @@ from GEODE.ENE import eneLabels
 from GEODE.Metadata import article, articleKey, paragraph, paragraphKey, \
         fromKey, relativePath, toKey, uid
 from GEODE.Store import corpus, Directory, JSON, SelfContained, tabular, toTSV
-from GEODE.Visualisation import densityProfile, drawMatrix, legend, \
+from GEODE.Visualisation import densityProfile, drawMatrix, drawGraph, legend, \
         maxConfusionMatrix
 from GEODE.Visualisation.ConfusionMatrix import extractConfusionMatrixCLI
 from GEODE.Visualisation.DensityProfile import drawDensityProfileCLI
 from GEODE.Visualisation.DrawMatrix import drawMatrixCLI
+from GEODE.Visualisation.Graph import drawGraphCLI
 
 commands = {
         'confusionMatrix': extractConfusionMatrixCLI,
         'densityProfile': drawDensityProfileCLI,
         'drawMatrix': drawMatrixCLI,
+        'graph': drawGraphCLI
         }
 
 def geopyckCLI():

guix.scm

-(use-modules ((gnu packages machine-learning) #:select (python-pytorch python-scikit-learn python-spacy))
+(use-modules ((gnu packages graphviz) #:select (python-graphviz))
+             ((gnu packages machine-learning) #:select (python-pytorch python-scikit-learn python-spacy))
              ((gnu packages python-science) #:select (python-pandas))
              ((gnu packages python-xyz) #:select (python-matplotlib
                                                   python-nltk
@@ -25,6 +26,7 @@
     (propagated-inputs
       (list nltk-data-corpora-stopwords
             python-frenchleffflemmatizer
+            python-graphviz
             python-matplotlib
             python-nltk
             python-pandas