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Commit 8910a536 authored by Wuttke, Joachim's avatar Wuttke, Joachim
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mv fit monitors to separate Py module

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Wrap/Python/fit_monitor.py 0 → 100644
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View file @ 8910a536
# ************************************************************************** #
"""
# BornAgain: simulate and fit scattering at grazing incidence
#
# @file Wrap/Python/fit_monitor.py
# @brief Plotter classes for monitoring fit progress.
#
# @homepage http://apps.jcns.fz-juelich.de/BornAgain
# @license GNU General Public License v3 or higher (see COPYING)
# @copyright Forschungszentrum Juelich GmbH 2019
# @authors Scientific Computing Group at MLZ (see CITATION, AUTHORS)
"""
# ************************************************************************** #
import plot_utils
class Plotter:
"""
Draws fit progress. Base class for simulation-specific classes (PlotterGISAS etc).
"""
def __init__(self,
zmin=None,
zmax=None,
xlabel=None,
ylabel=None,
units=ba.Axes.DEFAULT,
aspect=None):
self._fig = plt.figure(figsize=(10.25, 7.69))
self._fig.canvas.draw()
self._zmin = zmin
self._zmax = zmax
self._xlabel = xlabel
self._ylabel = ylabel
self._units = units
self._aspect = aspect
def reset(self):
self._fig.clf()
def plot(self):
self._fig.tight_layout()
plt.pause(0.03)
class PlotterGISAS(Plotter):
"""
Draws fit progress, for GISAS simulation.
"""
def __init__(self,
zmin=None,
zmax=None,
xlabel=None,
ylabel=None,
units=ba.Axes.DEFAULT,
aspect=None):
Plotter.__init__(self, zmin, zmax, xlabel, ylabel, units, aspect)
@staticmethod
def make_subplot(nplot):
plt.subplot(2, 2, nplot)
plt.subplots_adjust(wspace=0.2, hspace=0.2)
def plot(self, fit_objective):
Plotter.reset(self)
real_data = fit_objective.experimentalData()
sim_data = fit_objective.simulationResult()
diff = fit_objective.absoluteDifference()
self.make_subplot(1)
# same limits for both plots
arr = real_data.array()
zmax = np.amax(arr) if self._zmax is None else self._zmax
zmin = zmax*1e-6 if self._zmin is None else self._zmin
ba.plot_colormap(real_data,
title="Experimental data",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(2)
ba.plot_colormap(sim_data,
title="Simulated data",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(3)
ba.plot_colormap(diff,
title="Difference",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(4)
plt.title('Parameters')
plt.axis('off')
iteration_info = fit_objective.iterationInfo()
plt.text(
0.01, 0.85,
"Iterations " + '{:d}'.format(iteration_info.iterationCount()))
plt.text(0.01, 0.75,
"Chi2 " + '{:8.4f}'.format(iteration_info.chi2()))
index = 0
params = iteration_info.parameterMap()
for key in params:
plt.text(0.01, 0.55 - index*0.1,
'{:30.30s}: {:6.3f}'.format(key, params[key]))
index = index + 1
Plotter.plot(self)
class PlotterSpecular(Plotter):
"""
Draws fit progress, for specular simulation.
"""
def __init__(self, units=ba.Axes.DEFAULT):
Plotter.__init__(self)
self.gs = gridspec.GridSpec(1, 2, width_ratios=[2.5, 1], wspace=0)
self.units = units
def __call__(self, fit_objective):
self.plot(fit_objective)
@staticmethod
def as_si(val, ndp):
"""
Fancy print of scientific-formatted values
:param val: numeric value
:param ndp: number of decimal digits to print
:return: a string corresponding to the _val_
"""
s = '{x:0.{ndp:d}e}'.format(x=val, ndp=ndp)
m, e = s.split('e')
return r'{m:s}\times 10^{{{e:d}}}'.format(m=m, e=int(e))
@staticmethod
def trunc_str(token, length):
"""
Truncates token if it is longer than length.
Example:
trunc_str("123456789", 8) returns "123456.."
trunc_str("123456789", 9) returns "123456789"
:param token: input string
:param length: max non-truncated length
:return:
"""
return (token[:length - 2] + '..') if len(token) > length else token
def plot_table(self, fit_objective):
iteration_info = fit_objective.iterationInfo()
trunc_length = 9 # max string field width in the table
n_digits = 1 # number of decimal digits to print
n_iterations = iteration_info.iterationCount(
) # current number of iterations passed
rel_dif = fit_objective.relativeDifference().array().max(
) # maximum relative difference
fitted_parameters = iteration_info.parameterMap()
# creating table content
labels = ("Parameter", "Value")
table_data = [["Iteration", '${:d}$'.format(n_iterations)],
[
"$d_{r, max}$",
'${:s}$'.format(self.as_si(rel_dif, n_digits))
]]
for key, value in fitted_parameters.iteritems():
table_data.append([
'{:s}'.format(self.trunc_str(key, trunc_length)),
'${:s}$'.format(self.as_si(value, n_digits))
])
# creating table
axs = plt.subplot(self.gs[1])
axs.axis('tight')
axs.axis('off')
table = plt.table(cellText=table_data,
colLabels=labels,
cellLoc='center',
loc='bottom left',
bbox=[0.0, 0.0, 1.0, 1.0])
def plot_graph(self, fit_objective):
# retrieving data from fit suite
real_data = fit_objective.experimentalData()
sim_data = fit_objective.simulationResult()
unc_data = fit_objective.uncertaintyData()
# data values
sim_values = sim_data.array(self.units)
real_values = real_data.array(self.units)
unc_values = None if unc_data is None else unc_data.array(self.units)
# default font properties dictionary to use
font = {'family': 'serif', 'weight': 'normal', 'size': label_fontsize}
plt.subplot(self.gs[0])
plt.semilogy(sim_data.axis(), sim_values, 'b', real_data.axis(),
real_values, 'k--')
if unc_values is not None:
plt.semilogy(real_data.axis(),
real_values - unc_values,
'xkcd:grey',
alpha=0.6)
plt.semilogy(real_data.axis(),
real_values + unc_values,
'xkcd:grey',
alpha=0.6)
plt.ylim((0.5*np.min(real_values), 5*np.max(real_values)))
xlabel = get_axes_labels(real_data, self.units)[0]
legend = ['BornAgain', 'Data']
if unc_values is not None:
legend = ['BornAgain', 'Data', r'Data $\pm \sigma$']
plt.legend(legend, loc='upper right', prop=font)
plt.xlabel(xlabel, fontdict=font)
plt.ylabel("Intensity", fontdict=font)
plt.title("Specular data fitting", fontdict=font)
def plot(self, fit_objective):
Plotter.reset(self)
self.plot_graph(fit_objective)
self.plot_table(fit_objective)
Plotter.plot(self)
Wrap/Python/plot_utils.py
+ 8
− 240
View file @ 8910a536
...@@ -2,14 +2,13 @@ ...@@ -2,14 +2,13 @@
""" """
# BornAgain: simulate and fit scattering at grazing incidence # BornAgain: simulate and fit scattering at grazing incidence
# #
# @file Wrap/Python.plot_utils # @file Wrap/Python/plot_utils.py
# @brief Python extensions of the SWIG-generated Python module bornagain. # @brief Python extensions of the SWIG-generated Python module bornagain.
# #
# @homepage http://apps.jcns.fz-juelich.de/BornAgain # @homepage http://apps.jcns.fz-juelich.de/BornAgain
# @license GNU General Public License v3 or higher (see COPYING) # @license GNU General Public License v3 or higher (see COPYING)
# @copyright Forschungszentrum Juelich GmbH 2016 # @copyright Forschungszentrum Juelich GmbH 2016
# @authors Scientific Computing Group at MLZ Garching # @authors Scientific Computing Group at MLZ (see CITATION, AUTHORS)
# @authors J. Fisher, M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke
""" """
# ************************************************************************** # # ************************************************************************** #
...@@ -48,19 +47,19 @@ def translate_axis_label(label): ...@@ -48,19 +47,19 @@ def translate_axis_label(label):
""" """
label_dict = { label_dict = {
'X [nbins]': r'$X \; $(bins)', 'X [nbins]': r'$X \; $(bins)',
'X [mm]': r'$X \; $(mm)',
'Y [nbins]': r'$Y \; $(bins)',
'Y [mm]': r'$Y \; $(mm)',
'phi_f [rad]': r'$\varphi_f \; $(rad)', 'phi_f [rad]': r'$\varphi_f \; $(rad)',
'phi_f [deg]': r'$\varphi_f \; $(deg)', 'phi_f [deg]': r'$\varphi_f \; $(deg)',
'alpha_i [rad]': r'$\alpha_i \; $(rad)', 'alpha_i [rad]': r'$\alpha_i \; $(rad)',
'alpha_i [deg]': r'$\alpha_i \; $(deg)', 'alpha_i [deg]': r'$\alpha_i \; $(deg)',
'X [mm]': r'$X \; $(mm)',
'Qx [1/nm]': r'$Q_x \; $(nm$^{-1}$)',
'Qy [1/nm]': r'$Q_y \; $(nm$^{-1}$)',
'Q [1/nm]': r'$Q \; $(nm$^{-1}$)',
'Y [nbins]': r'$Y \; $(bins)',
'alpha_f [rad]': r'$\alpha_f \; $(rad)', 'alpha_f [rad]': r'$\alpha_f \; $(rad)',
'alpha_f [deg]': r'$\alpha_f \; $(deg)', 'alpha_f [deg]': r'$\alpha_f \; $(deg)',
'Y [mm]': r'$Y \; $(mm)', 'Qx [1/nm]': r'$Q_x \; $(nm$^{-1}$)',
'Qy [1/nm]': r'$Q_y \; $(nm$^{-1}$)',
'Qz [1/nm]': r'$Q_z \; $(nm$^{-1}$)', 'Qz [1/nm]': r'$Q_z \; $(nm$^{-1}$)',
'Q [1/nm]': r'$Q \; $(nm$^{-1}$)',
'Position [nm]': r'$Position \; $(nm)' 'Position [nm]': r'$Position \; $(nm)'
} }
if label in label_dict.keys(): if label in label_dict.keys():
...@@ -265,234 +264,3 @@ def plot_simulation_result(result, ...@@ -265,234 +264,3 @@ def plot_simulation_result(result,
plt.tight_layout() plt.tight_layout()
if not postpone_show: if not postpone_show:
plt.show() plt.show()
class Plotter:
def __init__(self,
zmin=None,
zmax=None,
xlabel=None,
ylabel=None,
units=ba.Axes.DEFAULT,
aspect=None):
self._fig = plt.figure(figsize=(10.25, 7.69))
self._fig.canvas.draw()
self._zmin = zmin
self._zmax = zmax
self._xlabel = xlabel
self._ylabel = ylabel
self._units = units
self._aspect = aspect
def reset(self):
self._fig.clf()
def plot(self):
self._fig.tight_layout()
plt.pause(0.03)
class PlotterGISAS(Plotter):
def __init__(self,
zmin=None,
zmax=None,
xlabel=None,
ylabel=None,
units=ba.Axes.DEFAULT,
aspect=None):
Plotter.__init__(self, zmin, zmax, xlabel, ylabel, units, aspect)
@staticmethod
def make_subplot(nplot):
plt.subplot(2, 2, nplot)
plt.subplots_adjust(wspace=0.2, hspace=0.2)
def plot(self, fit_objective):
Plotter.reset(self)
real_data = fit_objective.experimentalData()
sim_data = fit_objective.simulationResult()
diff = fit_objective.absoluteDifference()
self.make_subplot(1)
# same limits for both plots
arr = real_data.array()
zmax = np.amax(arr) if self._zmax is None else self._zmax
zmin = zmax*1e-6 if self._zmin is None else self._zmin
ba.plot_colormap(real_data,
title="Experimental data",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(2)
ba.plot_colormap(sim_data,
title="Simulated data",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(3)
ba.plot_colormap(diff,
title="Difference",
zmin=zmin,
zmax=zmax,
units=self._units,
xlabel=self._xlabel,
ylabel=self._ylabel,
zlabel='',
aspect=self._aspect)
self.make_subplot(4)
plt.title('Parameters')
plt.axis('off')
iteration_info = fit_objective.iterationInfo()
plt.text(
0.01, 0.85,
"Iterations " + '{:d}'.format(iteration_info.iterationCount()))
plt.text(0.01, 0.75,
"Chi2 " + '{:8.4f}'.format(iteration_info.chi2()))
index = 0
params = iteration_info.parameterMap()
for key in params:
plt.text(0.01, 0.55 - index*0.1,
'{:30.30s}: {:6.3f}'.format(key, params[key]))
index = index + 1
Plotter.plot(self)
class PlotterSpecular(Plotter):
"""
Draws fit progress. Intended specifically for observing
specular data fit.
"""
def __init__(self, units=ba.Axes.DEFAULT):
Plotter.__init__(self)
self.gs = gridspec.GridSpec(1, 2, width_ratios=[2.5, 1], wspace=0)
self.units = units
def __call__(self, fit_objective):
self.plot(fit_objective)
@staticmethod
def as_si(val, ndp):
"""
Fancy print of scientific-formatted values
:param val: numeric value
:param ndp: number of decimal digits to print
:return: a string corresponding to the _val_
"""
s = '{x:0.{ndp:d}e}'.format(x=val, ndp=ndp)
m, e = s.split('e')
return r'{m:s}\times 10^{{{e:d}}}'.format(m=m, e=int(e))
@staticmethod
def trunc_str(token, length):
"""
Truncates token if it is longer than length.
Example:
trunc_str("123456789", 8) returns "123456.."
trunc_str("123456789", 9) returns "123456789"
:param token: input string
:param length: max non-truncated length
:return:
"""
return (token[:length - 2] + '..') if len(token) > length else token
def plot_table(self, fit_objective):
iteration_info = fit_objective.iterationInfo()
trunc_length = 9 # max string field width in the table
n_digits = 1 # number of decimal digits to print
n_iterations = iteration_info.iterationCount(
) # current number of iterations passed
rel_dif = fit_objective.relativeDifference().array().max(
) # maximum relative difference
fitted_parameters = iteration_info.parameterMap()
# creating table content
labels = ("Parameter", "Value")
table_data = [["Iteration", '${:d}$'.format(n_iterations)],
[
"$d_{r, max}$",
'${:s}$'.format(self.as_si(rel_dif, n_digits))
]]
for key, value in fitted_parameters.iteritems():
table_data.append([
'{:s}'.format(self.trunc_str(key, trunc_length)),
'${:s}$'.format(self.as_si(value, n_digits))
])
# creating table
axs = plt.subplot(self.gs[1])
axs.axis('tight')
axs.axis('off')
table = plt.table(cellText=table_data,
colLabels=labels,
cellLoc='center',
loc='bottom left',
bbox=[0.0, 0.0, 1.0, 1.0])
def plot_graph(self, fit_objective):
# retrieving data from fit suite
real_data = fit_objective.experimentalData()
sim_data = fit_objective.simulationResult()
unc_data = fit_objective.uncertaintyData()
# data values
sim_values = sim_data.array(self.units)
real_values = real_data.array(self.units)
unc_values = None if unc_data is None else unc_data.array(self.units)
# default font properties dictionary to use
font = {'family': 'serif', 'weight': 'normal', 'size': label_fontsize}
plt.subplot(self.gs[0])
plt.semilogy(sim_data.axis(), sim_values, 'b', real_data.axis(),
real_values, 'k--')
if unc_values is not None:
plt.semilogy(real_data.axis(),
real_values - unc_values,
'xkcd:grey',
alpha=0.6)
plt.semilogy(real_data.axis(),
real_values + unc_values,
'xkcd:grey',
alpha=0.6)
plt.ylim((0.5*np.min(real_values), 5*np.max(real_values)))
xlabel = get_axes_labels(real_data, self.units)[0]
legend = ['BornAgain', 'Data']
if unc_values is not None:
legend = ['BornAgain', 'Data', r'Data $\pm \sigma$']
plt.legend(legend, loc='upper right', prop=font)
plt.xlabel(xlabel, fontdict=font)
plt.ylabel("Intensity", fontdict=font)
plt.title("Specular data fitting", fontdict=font)
def plot(self, fit_objective):
Plotter.reset(self)
self.plot_graph(fit_objective)
self.plot_table(fit_objective)
Plotter.plot(self)
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