Plot one or multiple jobs.

scripts/plot-single-job.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+
+import csv
+import sys
+from pandas import DataFrame
+from pandas import Grouper
+from matplotlib import pyplot
+
+jobs = sys.argv[1:]
+
+print("Analyzing the jobs: " + str(jobs))
+
+# Plot the timeseries
+def plot(header, row):
+  x = { h : d for (h, d) in zip(header, row)}
+  jobid = x["jobid"]
+  del x["jobid"]
+  del x["coding_abs"]
+  del x["coding_abs_aggzeros"]
+
+  result = []
+  for k in x:
+    timeseries = x[k].split(":")
+    timeseries = [ float(x) for x in timeseries]
+    if sum(timeseries) == 0:
+      continue
+    timeseries = [ [k, x, s] for (s,x) in zip(timeseries, range(1, len(timeseries))) ]
+    result.extend(timeseries)
+
+  data = DataFrame(result, columns=["metrics", "segment", "value"])
+  groups = data.groupby(["metrics"])
+  metrics = DataFrame()
+  labels = []
+  for name, group in groups:
+    metrics[name] = [x[2] for x in group.values]
+    labels.append(name)
+
+  ax = metrics.plot(subplots=True, legend=False, sharex=True, grid = True,  sharey=True, colormap='jet', marker='.', markersize=10)
+  for (i, l) in zip(range(0, len(labels)), labels):
+    ax[i].set_ylabel(l)
+
+  pyplot.xlabel("Segment number")
+  pyplot.savefig("timeseries" + jobid + ".png")
+
+  # Plot first 30 minutes
+
+  ax = metrics.plot(subplots=True, legend=False, sharex=True, grid = True,  sharey=True, colormap='jet', marker='.', markersize=10, xlim=(0,30))
+  for (i, l) in zip(range(0, len(labels)), labels):
+    ax[i].set_ylabel(l)
+
+  pyplot.xlabel("Segment number")
+  pyplot.savefig("timeseries" + jobid + "-30.png")
+
+
+
+
+with open('job-io-datasets/datasets/job_codings.csv') as csv_file:
+    csv_reader = csv.reader(csv_file, delimiter=',')
+    line_count = 0
+    for row in csv_reader:
+      if line_count == 0:
+        header = row
+        line_count += 1
+        continue
+
+      if not row[0].strip() in jobs:
+        continue
+      else:
+        plot(header, row)