New "statistics" command line to print or export to html stats of computed nodes

meshroom/statistics.py

@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+import argparse
+import os
+from pprint import pprint
+from collections import Iterable
+
+from meshroom.processGraph import graph as pg
+
+parser = argparse.ArgumentParser(description='Query the status of nodes in a Graph of processes.')
+parser.add_argument('graphFile', metavar='GRAPHFILE.mg', type=str,
+                    help='Filepath to a graph file.')
+parser.add_argument('--node', metavar='NODE_NAME', type=str,
+                    help='Process the node alone.')
+parser.add_argument('--graph', metavar='NODE_NAME', type=str,
+                    help='Process the node and all previous nodes needed.')
+parser.add_argument('--exportHtml', metavar='FILE', type=str,
+                    help='Filepath to the output html file.')
+parser.add_argument("--verbose", help="Print full status information",
+                    action="store_true")
+
+args = parser.parse_args()
+
+if not os.path.exists(args.graphFile):
+    print('ERROR: No graph file "{}".'.format(args.node, args.graphFile))
+    exit(-1)
+
+graph = pg.loadGraph(args.graphFile)
+
+graph.update()
+graph.updateStatisticsFromCache()
+
+nodes = []
+if args.node:
+    if args.node not in graph.nodes:
+        print('ERROR: node "{}" does not exist in file "{}".'.format(args.node, args.graphFile))
+        exit(-1)
+    nodes = [graph.nodes[args.node]]
+else:
+    startNodes = None
+    if args.graph:
+        startNodes = [graph.nodes[args.graph]]
+    nodes = graph.dfsNodesOnFinish(startNodes=startNodes)
+
+for node in nodes:
+    print('{}: {}'.format(node.name, node.statistics.toDict()))
+
+if args.exportHtml:
+    import matplotlib.pyplot as plt, mpld3
+    import numpy as np
+
+    with open(args.exportHtml, 'w') as fileObj:
+        for node in nodes:
+            plt.title(node.name)
+            s = node.statistics
+            for k in ('cpuUsage', 'ramUsage', 'swapUsage', 'vramUsage'):
+                allData = s.__dict__[k]
+                fig = plt.figure()
+                ax = fig.add_subplot(111, axisbg='#EEEEEE')
+                ax.grid(color='white', linestyle='solid')
+
+                # if multiple values per time
+                if allData and isinstance(allData[0], Iterable):
+                    # transpose the list of list
+                    allData = list(map(list, zip(*allData)))
+                else:
+                    allData = [allData]
+
+                for data in allData:
+                    y = data
+                    x = np.arange(len(y))
+                    ax.plot(x, y)
+                plt.ylim(0, 100)
+                plt.title(k)
+
+                mpld3.save_html(fig, fileObj)