def run(self, postResults):
# create tree with relevant datas
source = sortTree(postResults, ['modules', 'controller', 'type'])
# create plot
fig = Figure()
fig.subplots_adjust(wspace=0.5, hspace=0.25)
# plot for L1NormAbs
axes = fig.add_subplot(111)
self.plotVariousController(source, axes, \
xPath=['modules', 'disturbance', 'sigma'], \
yPath=['metrics', 'L1NormAbs'], \
typ='line')
self.plotSettings(axes, \
titel=r'Fehlerintegral w(t) und y(t) \"uber Sigma', \
grid=True, \
xlabel=r'$\sigma \, \lbrack m\rbrack$', \
ylabel=r'$E \, \lbrack ms \rbrack$', \
)
# extract controllerNames
controllerNames = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
# write output files
fileName = self.name[len('eval_'):] \
+ '_Controller_(' + ''.join(controllerNames) + ')'
self.writeOutputFiles(fileName, fig)
return [{'figure': canvas, 'name': self.name}]
def run(self, postResults):
#create tree with relevant datas
source = sortTree(postResults, ['modules', 'controller', 'type'])
#create plot
fig = Figure()
fig.subplots_adjust(wspace=0.5, hspace=0.25)
#plot for L1NormAbs
axes = fig.add_subplot(111)
self.plotVariousController(source, axes,\
xPath=['modules', 'disturbance', 'sigma'],\
yPath=['metrics', 'L1NormAbs'],\
typ='line')
self.plotSettings(axes,\
titel=r'Fehlerintegral w(t) und y(t) \"uber Sigma',\
grid=True,\
xlabel=r'$\sigma \, \lbrack m\rbrack$',\
ylabel=r'$E \, \lbrack ms \rbrack$',\
)
#extract controllerNames
controllerNames = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
#write output files
fileName = self.name[len('eval_'):]\
+ '_Controller_(' + ''.join(controllerNames) + ')'
self.writeOutputFiles(fileName, fig)
return [{'figure': canvas, 'name': self.name}]
def run(self, postResults):
# create tree with relevant datas
source = sortTree(postResults, ["modules", "controller", "type"])
# create plot
fig = Figure()
# plot for L1NormAbs
axes = fig.add_subplot(111)
self.plotVariousController(
source, axes, xPath=["modules", "trajectory", "delta t"], yPath=["metrics", "L1NormAbs"], typ="bar"
)
self.plotSettings(
axes,
titel=r"Fehlerintegral w(t) und y(t) \"uber $\Delta t$",
grid=True,
xlabel=r"$\Delta t \, \lbrack s\rbrack$",
ylabel=r"$E \, \lbrack m \cdot s\rbrack$",
typ="bar",
)
# extract controllerNames
controllerNames = [x[: -len("Controller")] for x in source.keys()]
canvas = FigureCanvas(fig)
# write output files
fileName = self.name[len("eval_") :] + "_Controller_(" + "".join(controllerNames) + ")"
self.writeOutputFiles(fileName, fig)
return [{"figure": canvas, "name": self.name}]
def run(self, post_results):
# create tree with all relevant data
source = sortTree(post_results, ['modules', 'controller', 'type'])
# Get the Poles for the Minimum
for controller in source:
x_path = ['modules', 'controller', 'poles']
y_path = ['metrics', 'L1NormITAE']
x_list = getSubValue(source[controller], x_path)
y_list = getSubValue(source[controller], y_path)
x_list[:] = [x for x, y in zip(x_list, y_list) if y]
y_list[:] = [i for i in y_list if i]
self._logger.info("processing controller '{}'".format(controller))
self._logger.info("min ITAE {}".format(min(y_list)))
self._logger.info("opt poles {}".format(x_list[y_list.index(min(y_list))][0]))
# create plot
fig = Figure()
# fig.subplots_adjust(wspace=20, hspace=10, h_pad=50)
fig.subplots_adjust(wspace=0.6, hspace=0.6)
# plot for L1NormITAE over poles
axes = fig.add_subplot(111)
self.plotVariousController(source, axes,
xPath=['modules', 'controller', 'poles'],
yPath=['metrics', 'L1NormITAE'],
typ='line',
xIndex=0)
self.plotSettings(axes,
titel=r'Fehlerintegral ITAE \"uber Polplatzierung',
grid=True,
xlabel=r'$Poles \, \lbrack s\rbrack$',
ylabel=r'$E \, \lbrack ms^{2} \rbrack$',
)
# error minimum
for controllerName in source.keys():
error_list = getSubValue(source[controllerName], ['metrics', 'L1NormITAE'])
error_min = min(x for x in error_list if x is not None)
error_min_index = error_list.index(error_min)
poles = getSubValue(source[controllerName], ['modules', 'controller', 'poles'])[error_min_index][0]
self._logger.info("minimum error of {} for {} with poles at {}".format(error_min, controllerName, poles))
# extract controllerNames
controller_names = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
# write output files
file_name = self.name[len('eval_'):] \
+ '_Controller_(' + ''.join(controller_names) + ')'
self.writeOutputFiles(file_name, fig)
return [{'figure': canvas, 'name': self.name}]
def run(self, postResults):
#create tree with relevant datas
source = sortTree(postResults, ['modules', 'controller', 'type'])
#create plot
fig = Figure()
#plot for L1NormAbs
axes = fig.add_subplot(211)
self.plotVariousController(source, axes,\
xPath=['modules','trajectory', 'delta t'],\
yPath=['metrics','L1NormAbs'],\
typ='line')
self.plotSettings(axes,\
titel=r'Fehlerintegral w(t) und y(t) \"uber $\Delta t$',\
grid=True,\
xlabel=r'$\Delta t \, \lbrack s\rbrack$',\
ylabel=r'$E \, \lbrack ms\rbrack$',\
)
#plot for time-difference
axes1 = fig.add_subplot(212)
self.plotVariousController(source, axes1,\
xPath=['modules','trajectory', 'delta t'],\
yPath=['metrics','t_diff'],\
typ='line')
self.plotSettings(axes1,\
titel=r'\"Ubergangszeitfehler \"uber $\Delta t$',\
grid=True,\
xlabel=r'$\Delta t \, \lbrack s\rbrack$',\
ylabel=r'$e_{t} \, \lbrack s\rbrack$',\
)
# spacing
fig.subplots_adjust(wspace=0.5, hspace=0.5)
#extract controllerNames
controllerNames = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
#write output files
fileName = self.name[len('eval_'):]\
+ '_Controller_(' + ''.join(controllerNames) + ')'
self.writeOutputFiles(fileName, fig)
return [{'figure': canvas, 'name': self.name}]
def run(self, postResults):
#create tree with relevant datas
source = sortTree(postResults, ['modules', 'controller', 'type'])
#create plot
fig = Figure()
#plot for L1NormAbs
axes = fig.add_subplot(211)
self.plotVariousController(source, axes,\
xPath=['modules','trajectory', 'delta t'],\
yPath=['metrics','L1NormAbs'],\
typ='line')
self.plotSettings(axes,\
titel=r'Fehlerintegral w(t) und y(t) \"uber $\Delta t$',\
grid=True,\
xlabel=r'$\Delta t \, \lbrack s\rbrack$',\
ylabel=r'$E \, \lbrack ms\rbrack$',\
)
#plot for time-difference
axes1 = fig.add_subplot(212)
self.plotVariousController(source, axes1,\
xPath=['modules','trajectory', 'delta t'],\
yPath=['metrics','t_diff'],\
typ='line')
self.plotSettings(axes1,\
titel=r'\"Ubergangszeitfehler \"uber $\Delta t$',\
grid=True,\
xlabel=r'$\Delta t \, \lbrack s\rbrack$',\
ylabel=r'$e_{t} \, \lbrack s\rbrack$',\
)
# spacing
fig.subplots_adjust(wspace=0.5, hspace=0.5)
#extract controllerNames
controllerNames = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
#write output files
fileName = self.name[len('eval_'):]\
+ '_Controller_(' + ''.join(controllerNames) + ')'
self.writeOutputFiles(fileName, fig)
return [{'figure': canvas, 'name': self.name}]
def run(self, post_results):
# create tree with all relevant data
source = sortTree(post_results, ['modules', 'controller', 'type'])
# Get the Poles for the Minimum
for controller in source:
x_path = ['modules', 'controller', 'poles']
y_path = ['metrics', 'L1NormITAE']
x_list = getSubValue(source[controller], x_path)
y_list = getSubValue(source[controller], y_path)
x_list[:] = [x for x, y in zip(x_list, y_list) if y]
y_list[:] = [i for i in y_list if i]
self._logger.info("processing controller '{}'".format(controller))
self._logger.info("min ITAE {}".format(min(y_list)))
self._logger.info("opt poles {}".format(x_list[y_list.index(
min(y_list))][0]))
# create plot
fig = Figure()
# fig.subplots_adjust(wspace=20, hspace=10, h_pad=50)
fig.subplots_adjust(wspace=0.6, hspace=0.6)
# plot for L1NormITAE over poles
axes = fig.add_subplot(111)
self.plotVariousController(source,
axes,
xPath=['modules', 'controller', 'poles'],
yPath=['metrics', 'L1NormITAE'],
typ='line',
xIndex=0)
self.plotSettings(
axes,
titel=r'Fehlerintegral ITAE \"uber Polplatzierung',
grid=True,
xlabel=r'$Poles \, \lbrack s\rbrack$',
ylabel=r'$E \, \lbrack ms^{2} \rbrack$',
)
# error minimum
for controllerName in source.keys():
error_list = getSubValue(source[controllerName],
['metrics', 'L1NormITAE'])
error_min = min(x for x in error_list if x is not None)
error_min_index = error_list.index(error_min)
poles = getSubValue(
source[controllerName],
['modules', 'controller', 'poles'])[error_min_index][0]
self._logger.info(
"minimum error of {} for {} with poles at {}".format(
error_min, controllerName, poles))
# extract controllerNames
controller_names = [x[:-len('Controller')] for x in source.keys()]
canvas = FigureCanvas(fig)
# write output files
file_name = self.name[len('eval_'):] \
+ '_Controller_(' + ''.join(controller_names) + ')'
self.writeOutputFiles(file_name, fig)
return [{'figure': canvas, 'name': self.name}]