Module ctsimu.evaluation.test2D_SW_4
Test 2D-SW-4: Scattering
No documentation yet.
To run this test, call:
from ctsimu.toolbox import Toolbox
Toolbox("2D-SW-4", "2D-SW-4_metadata.json")
Classes
class Test2D_SW_4 (resultFileDirectory='.', name=None, rawOutput=False)-
CTSimU test 2D-SW-4: scattering.
Expand source code
class Test2D_SW_4(generalTest): """ CTSimU test 2D-SW-4: scattering. """ def __init__(self, resultFileDirectory=".", name=None, rawOutput=False): generalTest.__init__( self, testName="2D-SW-4", name=name, resultFileDirectory=resultFileDirectory, rawOutput=rawOutput) # Profile Data: self.results = Test2D_SW_4_results() # Definitions of the central and right ROI for the vertical grey value profiles: self.steps = [ ImageROI(101, 0, 111, 200), ImageROI(190, 0, 200, 200) ] def prepare(self): """ Preparations before the test will be run with the images from the pipeline. """ if not self.prepared: # Load the nominal profile data: profilesText = pkgutil.get_data(__name__, "data/2D-SW-4_profiles_monte-carlo_reference.txt").decode() profilesIO = io.StringIO(profilesText) profilesData = numpy.loadtxt(profilesIO, delimiter='\t') for i in range(len(self.steps)): self.results.profiles_nominal.append(profilesData[:,(i+1)]) profilesIO.close() # Vertical profile positions: nP = len(self.results.profiles_nominal[0]) self.results.profiles_pos = numpy.linspace(0, nP, nP, endpoint=False) # Fit a fourth order polynomial to the MC data to smooth it: for i in range(len(self.steps)): popt, pcov = optimize.curve_fit(f=poly4, xdata=self.results.profiles_pos, ydata=self.results.profiles_nominal[i], p0=None) a = popt[0] b = popt[1] c = popt[2] d = popt[3] e = popt[4] self.results.profiles_nominalfit.append(poly4(x=self.results.profiles_pos, a=a, b=b, c=c, d=d, e=e)) self.prepared = True def writeProfiles(self, title, filename, pos, profiles): profilesText = "# {}\n".format(title) profilesText += "# Mean vertical grey value profiles\n" profilesText += "# pos [px]\tcentral [GV]\tmargin_right [GV]\n" for i in range(len(pos)): profilesText += "{}".format(int(pos[i])) for p in profiles: profilesText += "\t{}".format(p[i]) profilesText += "\n" with open(filename, 'w') as profilesFile: profilesFile.write(profilesText) profilesFile.close() def run(self, image): self.prepare() # Vertical profiles: for roi in self.steps: profile = image.verticalROIProfile(roi) self.results.profiles.append(profile) # Write profiles profileFileName = "{dir}/{name}_profiles_measured.txt".format(dir=self.resultFileDirectory, name=self.name) self.writeProfiles(title="Measured profiles", filename=profileFileName, pos=self.results.profiles_pos, profiles=self.results.profiles) profileFileName = "{dir}/{name}_profiles_monte-carlo.txt".format(dir=self.resultFileDirectory, name=self.name) self.writeProfiles(title="Monte Carlo results as basis for reference values", filename=profileFileName, pos=self.results.profiles_pos, profiles=self.results.profiles_nominal) profileFileName = "{dir}/{name}_profiles_reference.txt".format(dir=self.resultFileDirectory, name=self.name) self.writeProfiles(title="Reference values (fourth order polynomial fit to Monte-Carlo measurements)", filename=profileFileName, pos=self.results.profiles_pos, profiles=self.results.profiles_nominalfit) log("Evaluation data for test {name} written to {dir}.".format(name=self.name, dir=self.resultFileDirectory)) self.plotResults() self.currentRun += 1 return image def followUp(self): pass def plotResults(self): try: import matplotlib import matplotlib.pyplot from matplotlib.ticker import (MultipleLocator, FormatStrFormatter, AutoMinorLocator) xValues = self.results.profiles_pos tolerance = 50 matplotlib.use("agg") fig, ((ax1, ax2)) = matplotlib.pyplot.subplots(nrows=2, ncols=1, figsize=(6, 6)) # Grey Value Profiles: #ax1.fill_between(xValues, self.results.profiles_nominalfit[0]+tolerance, self.results.profiles_nominalfit[0]-tolerance, facecolor='#ffcc00') ax1.plot(xValues, self.results.profiles_nominal[0], linewidth=1.0, label="Monte-Carlo", color='#a0a0a0') ax1.plot(xValues, self.results.profiles_nominalfit[0], linewidth=5.0, linestyle="dotted", label="Reference profile", color='#c18100') ax1.plot(xValues, self.results.profiles[0], linewidth=2.0, label="Measurement", color='#1f77b4') ax1.set_xlabel("Vertical position in px") ax1.set_ylabel("Grey value") ax1.set_title("Central Profile") ax1.xaxis.set_major_locator(MultipleLocator(20)) ax1.xaxis.set_major_formatter(FormatStrFormatter('%d')) ax1.xaxis.set_minor_locator(MultipleLocator(10)) ax1.grid(visible=True, which='major', axis='both', color='#d9d9d9', linestyle='dashed') ax1.grid(visible=True, which='minor', axis='both', color='#e7e7e7', linestyle='dotted') ax1.legend(loc='best') #ax2.fill_between(xValues, self.results.profiles_nominalfit[1]+tolerance, self.results.profiles_nominalfit[1]-tolerance, facecolor='#ffcc00') ax2.plot(xValues, self.results.profiles_nominal[1], linewidth=1.0, label="Monte-Carlo", color='#a0a0a0') ax2.plot(xValues, self.results.profiles_nominalfit[1], linewidth=5.0, linestyle="dotted", label="Reference profile", color='#c18100') ax2.plot(xValues, self.results.profiles[1], linewidth=2.0, label="Measurement", color='#1f77b4') ax2.set_xlabel("Vertical position in px") ax2.set_ylabel("Grey value") ax2.set_title("Fringe Profile") ax2.xaxis.set_major_locator(MultipleLocator(20)) ax2.xaxis.set_major_formatter(FormatStrFormatter('%d')) ax2.xaxis.set_minor_locator(MultipleLocator(10)) ax2.grid(visible=True, which='major', axis='both', color='#d9d9d9', linestyle='dashed') ax2.grid(visible=True, which='minor', axis='both', color='#e7e7e7', linestyle='dotted') ax2.legend(loc='best') fig.tight_layout() plotFilename = "{dir}/{name}_profiles.png".format(dir=self.resultFileDirectory, name=self.name) matplotlib.pyplot.savefig(plotFilename) fig.clf() matplotlib.pyplot.close('all') except Exception as e: log(f"Warning: Error plotting results for test {self.name}, {subtestName} using matplotlib: {e}")Ancestors
Methods
def prepare(self)-
Preparations before the test will be run with the images from the pipeline.
def writeProfiles(self, title, filename, pos, profiles)
Inherited members
class Test2D_SW_4_results-
Results for one sub test of the scenario.
Expand source code
class Test2D_SW_4_results: """ Results for one sub test of the scenario. """ def __init__(self): self.profiles = [] self.profiles_nominal = [] self.profiles_fitpars = [] # fit parameters self.profiles_nominalfit = [] self.profiles_pos = None