def main():
if (len(_sys.argv) > 1 and _os.path.exists(_sys.argv[1]) and _os.path.isfile(_sys.argv[1])):
filename = _sys.argv[1]
else:
filename = _gui.get_path("*.csv",defaultFile="odmanalysis.csv")
commonPath = _os.path.abspath(_os.path.split(filename)[0])
measurementName = _os.path.split(_os.path.split(filename)[0])[1]
try:
settings = _odm.CurveFitSettings.loadFromFile(commonPath + '/odmSettings.ini')
print "settings loaded from local odmSettings.ini"
except:
settings = _gui.getSettingsFromUser(None)
settings.saveToFile(commonPath + '/odmSettings.ini')
print "settings saved to local odmSettings.ini"
df = _odm.readAnalysisData(filename)
makeDisplacementPlots(df,commonPath, measurementName = measurementName, nmPerPx = settings.pxToNm)
_plt.show()
def main():
if (len(sys.argv) > 1 and os.path.exists(sys.argv[1]) and os.path.isfile(sys.argv[1])):
filename = sys.argv[1]
else:
filename = gui.get_path("*.csv",defaultFile="data.csv")
commonPath = os.path.abspath(os.path.split(filename)[0])
measurementName = os.path.split(os.path.split(filename)[0])[1]
outputFilename = commonPath + "/odmanalysis.csv"
readerProcess, readerQueue = startReadAsync(filename)
dataProcessor = ChunkedODMDataProcessor(commonPath)
chunkWriter = ChunkWriter(outputFilename)
while True:
try:
rawChunk = readerQueue.get(timeout=10)
except:
#done
break
rawChunk = rawChunk[rawChunk.intensityProfile.map(len) > 0]
if len(rawChunk) is not 0:
processedChunk = dataProcessor.processDataFrame(rawChunk)
chunkWriter.writeDataFrame(processedChunk)
readerProcess.join()
#make plots
df = odm.readAnalysisData(outputFilename)
settings = odm.CurveFitSettings.loadFromFile(commonPath + '/odmSettings.ini')
makeDisplacementPlots(df,commonPath,measurementName,settings.pxToNm)
def convertOdmAnalysisFileToHDF5(path, keep_original = True):
print "reading odmanalysis.csv..."
df = odm.readAnalysisData(path + '/odmanalysis.csv')
print "saving to data.hdf5"
df.to_hdf(path + '/odmanalysis.hdf5','odmanalysis', mode="a", complib='zlib', complevel=9, format='table', data_columns=True)
if not keep_original:
print "delete odmanalysis.csv"
os.remove(path + '/odmanalysis.csv')
def main():
if (len(_sys.argv) > 1 and _os.path.exists(_sys.argv[1]) and _os.path.isfile(_sys.argv[1])):
filename = _sys.argv[1]
else:
filename = _gui.get_path("*.csv",defaultFile="odmanalysis.csv")
commonPath = _os.path.abspath(_os.path.split(filename)[0])
measurementName = _os.path.split(_os.path.split(filename)[0])[1]
print "loading settings from " + commonPath + "/odmSettings.ini"
settings = _odm.CurveFitSettings.loadFromFile(commonPath+"/odmSettings.ini")
df = _odm.readAnalysisData(filename)
df['displacement_nm'] = df.displacement * settings.pxToNm
app = qt.QApplication(_sys.argv)
cycleViewer = InteractiveCycleViewer(df)
cycleViewer.show()
app.exec_()
def main():
parser = argparse.ArgumentParser(description='Pivots the odmanalysis output file to produce and excel file with all cycles in different columns')
parser.add_argument('filename',
nargs='?',
default="",
help="The odmanalysis.csv file to tabulate",
type=str)
parser.add_argument('--split-direction','-d',
type=bool,
help='split the actuation directions into different columns',
metavar='')
args = parser.parse_args()
if not os.path.isfile(args.filename):
args.filename = gui.get_path("*.csv",defaultFile="odmanalysis.csv")
commonPath = os.path.abspath(os.path.split(args.filename)[0])
df = odm.readAnalysisData(args.filename)
cycleFrames = []
keys = ['cycleNumber']
if args.split_direction == True:
keys.append('direction')
grouped = df.groupby(keys)
for keys, group in grouped:
if not hasattr(keys, '__iter__'):
keys = tuple([keys])
dfTemp = group[['actuatorVoltage','displacement']]
dfTemp = dfTemp.reset_index().drop('timestamp',axis=1)
name = 'cycle_%i' % keys[0]
for k in keys[1:]:
name += "_%s" % k
cycleFrames.append(pd.concat({name: dfTemp}, axis=1))
dfCombined = pd.concat(cycleFrames,axis=1)
dfCombined.to_excel(os.path.join(commonPath,'odmanalysis_tabulated.xlsx'),index=False)
print os.path.join(commonPath,'odmanalysis_tabulated.xlsx')
def main():
if len(sys.argv) > 1 and os.path.exists(sys.argv[1]) and os.path.isfile(sys.argv[1]):
filename = sys.argv[1]
else:
filename = gui.get_path("*.csv", defaultFile="odmanalysis.csv")
commonPath = os.path.abspath(os.path.split(filename)[0])
try:
settings = odm.CurveFitSettings.loadFromFile(commonPath + "/odmSettings.ini")
print "settings loaded from local odmSettings.ini"
except:
settings = gui.getSettingsFromUser(None)
settings.saveToFile(commonPath + "/odmSettings.ini")
print "settings saved to local odmSettings.ini"
nmPerPx = settings.pxToNm
df = odm.readAnalysisData(filename)
plt.plot(np.arange(len(df.displacement)), df.displacement * nmPerPx)
plt.interactive(False)
coordinateGrabber = gui.InteractiveCoordinateGrabber(plt.gcf(), 2, "Select range for fitting a polynomial...")
coordinateGrabber.promptMessages = ["Select lower limit...", "Select upper limit..."]
coordinates = coordinateGrabber.getValuesFromUser()
xLimits = [int(c[0]) for c in coordinates]
dfs = df.iloc[slice(*xLimits)]
validInput = False
while validInput == False:
try:
deg = int(raw_input("Polynomial degree: "))
validInput = True
except:
pass
xValues = np.arange(len(dfs.displacement))
p = cp.polyfit(xValues, dfs.displacement, deg)
noise = (dfs.displacement - cp.polyval(p, xValues)) * nmPerPx
ax = plt.subplot(111)
ax.plot(xValues, dfs.displacement * nmPerPx)
ax.plot(xValues, cp.polyval(p, xValues) * nmPerPx, "r--")
ax.set_xlabel("Actuator Voltage (V)")
ax.set_ylabel("Displacement (nm)")
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, sharex=False, sharey=True, squeeze=True)
ax1.plot(np.arange(len(noise)), noise, "o")
ax2.hist(noise, bins=50, orientation="horizontal", facecolor="green", alpha=0.5)
sd = ODMStats.makeStatsDescriptionDict(nmPerPx * dfs.displacement)
peakDistanceToEdge = [abs(sd["mean"] - x * nmPerPx) for x in ax2.get_xlim()]
xtext = 0.1 if peakDistanceToEdge[0] > peakDistanceToEdge[1] else 0.7
ax2.text(xtext, 0.7, ODMStats.printStatsDescriptionDict(sd), transform=ax2.transAxes)
ax1.set_ylabel("Displacement (nm)")
ax2.set_xlabel("Count")
fig.savefig(os.path.join(commonPath, "Displacement noise.png"), dpi=150)
stats = noise.describe()
with open(os.path.join(commonPath, "position_noise_stats.txt"), "w") as f:
f.write(str(stats))
plt.show()
