def plotNetworkState(experiment, plotVerbosity, trainingPasses, phase=""):
if plotVerbosity >= 1:
rcParams["figure.figsize"] = _PLOT_WIDTH, _PLOT_HEIGHT
# Plot Union SDR trace
dataTrace = experiment.up._mmTraces["activeCells"].data
unionSizeTrace = [len(datum) for datum in dataTrace]
x = [i for i in xrange(len(unionSizeTrace))]
stdDevs = None
title = "Union Size; {0} training passses vs. Time".format(trainingPasses)
data_utils.getErrorbarFigure(title, x, unionSizeTrace, stdDevs, "Time",
"Union Size")
if plotVerbosity >= 2:
title = "training passes: {0}, phase: {1}".format(trainingPasses, phase)
experiment.up.mmGetPlotConnectionsPerColumn(title=title)
experiment.tm.mmGetCellActivityPlot(title=title,
activityType="activeCells",
showReset=True,
resetShading=_PLOT_RESET_SHADING)
experiment.tm.mmGetCellActivityPlot(title=title,
activityType="predictedActiveCells",
showReset=True,
resetShading=_PLOT_RESET_SHADING)
experiment.up.mmGetCellActivityPlot(title=title,
showReset=True,
resetShading=_PLOT_RESET_SHADING)
def main(inputPath, csvOutputPath, imgOutputPath):
# remove existing /overlaps.csv if present
if os.path.exists(csvOutputPath + _OVERLAPS_FILE_NAME):
os.remove(csvOutputPath + _OVERLAPS_FILE_NAME)
if not os.path.exists(csvOutputPath):
os.makedirs(csvOutputPath)
if not os.path.exists(imgOutputPath):
os.makedirs(imgOutputPath)
print "Computing Union SDR overlap between SDR traces in following dir:"
print inputPath + "\n"
filesAll = os.listdir(inputPath)
files = []
for _ in xrange(len(filesAll)):
if filesAll[_].find('unionSdrTrace') != -1:
files.append(filesAll[_])
if len(files) != 2:
print "Found {0} files at input path {1} - Requires exactly 2.".format(
len(files), inputPath)
sys.exit(1)
pathNoLearn = inputPath + "/" + files[0]
pathLearn = inputPath + "/" + files[1]
print "Comparing files..."
print pathLearn
print pathNoLearn + "\n"
# Load source A
with open(pathLearn, "rU") as fileA:
csvReader = csv.reader(fileA)
dataA = [line for line in csvReader]
unionSizeA = [len(datum) for datum in dataA]
# Load source B
with open(pathNoLearn, "rU") as fileB:
csvReader = csv.reader(fileB)
dataB = [line for line in csvReader]
unionSizeB = [len(datum) for datum in dataB]
assert len(dataA) == len(dataB)
# To display all plots on the same y scale
yRangeMax = 1.05 * max(max(unionSizeA), max(unionSizeB))
# Plot union size for data A
x = [i for i in xrange(len(dataA))]
stdDevs = None
title = "Union Size with Learning vs. Time"
data_utils.getErrorbarFigure(title, x, unionSizeA, stdDevs, "Time",
"Union Size", yRangeMax=yRangeMax)
figPath = "{0}/{1}.png".format(imgOutputPath, title)
plt.savefig(figPath, bbox_inches="tight")
# Plot union size for data B and save image
title = "Union Size without Learning vs. Time"
data_utils.getErrorbarFigure(title, x, unionSizeB, stdDevs, "Time",
"Union Size", yRangeMax=yRangeMax)
figPath = "{0}/{1}.png".format(imgOutputPath, title)
plt.savefig(figPath, bbox_inches="tight")
with open(csvOutputPath + _OVERLAPS_FILE_NAME, "wb") as outputFile:
csvWriter = csv.writer(outputFile)
overlaps = [getOverlap(dataA[i], dataB[i]) for i in xrange(len(dataA))]
csvWriter.writerow(overlaps)
outputFile.flush()
# Plot overlap and save image
title = "Learn-NoLearn Union SDR Overlap vs. Time"
data_utils.getErrorbarFigure(title, x, overlaps, stdDevs, "Time","Overlap",
yRangeMax=yRangeMax)
figPath = "{0}/{1}.png".format(imgOutputPath, title)
plt.savefig(figPath, bbox_inches="tight")
raw_input("Press any key to exit...")
