Tune size + output
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@ -28,6 +28,10 @@ def plot(prefix, header, row):
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timeseries = [ [k, x, s] for (s,x) in zip(timeseries, range(1, len(timeseries))) ]
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result.extend(timeseries)
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if len(result) == 0:
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print("Empty job! Cannot plot!")
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return
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data = DataFrame(result, columns=["metrics", "segment", "value"])
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groups = data.groupby(["metrics"])
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metrics = DataFrame()
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@ -36,14 +40,16 @@ def plot(prefix, header, row):
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metrics[name] = [x[2] for x in group.values]
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labels.append(name)
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ax = metrics.plot(subplots=True, legend=False, sharex=True, grid = True, sharey=True, colormap='jet', marker='.', markersize=10)
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ax = metrics.plot(subplots=True, legend=False, sharex=True, grid = True, sharey=True, colormap='jet', marker='.', markersize=10, figsize=(8, 2 + 2 * len(labels)))
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for (i, l) in zip(range(0, len(labels)), labels):
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ax[i].set_ylabel(l)
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pyplot.xlabel("Segment number")
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pyplot.savefig(prefix + "timeseries" + jobid + ".png")
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# Plot first 30 minutes
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# Plot first 30 segments
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if len(timeseries) <= 50:
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return
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ax = metrics.plot(subplots=True, legend=False, sharex=True, grid = True, sharey=True, colormap='jet', marker='.', markersize=10, xlim=(0,30))
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for (i, l) in zip(range(0, len(labels)), labels):
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@ -54,7 +54,7 @@ plotJobs = function(jobs){
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# print the job timeline
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r = e[ordered, ]
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for (row in 1:length(jobs)) {
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prefix = sprintf("%s-%f-%.0f", level, r[row, "similarity"], row)
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prefix = sprintf("%s-%f-%.0f-", level, r[row, "similarity"], row)
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job = r[row, "jobid"]
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system(sprintf("scripts/plot-single-job.py %s %s", job, prefix))
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}
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