Commit 18a419e6 authored by Martin Reinecke's avatar Martin Reinecke
Browse files

make 'plot' directly available

parent 1a867445
Pipeline #23896 passed with stage
in 4 minutes and 41 seconds
......@@ -51,7 +51,7 @@ if __name__ == "__main__":
data_power = ift.log(ift.power_analyze(fft.adjoint_times(d),
binbounds=p_space.binbounds))
d_data = d.val
ift.plotting.plot(d, name="data.png")
ift.plot(d, name="data.png")
IC1 = ift.GradientNormController(verbose=True, iteration_limit=100,
tol_abs_gradnorm=0.1)
......@@ -90,5 +90,5 @@ if __name__ == "__main__":
# Plot current estimate
ift.dobj.mprint(i)
if i % 5 == 0:
ift.plotting.plot(fft(m0), name='map.png')
if i % 50 == 0:
ift.plot(fft(m0), name='map.png')
......@@ -68,14 +68,13 @@ if __name__ == "__main__":
# Plotting
plotdict = {"xlabel": "Pixel index", "ylabel": "Pixel index",
"colormap": "Planck-like"}
ift.plotting.plot(mock_signal, name="mock_signal.png", **plotdict)
ift.plot(mock_signal, name="mock_signal.png", **plotdict)
logdata = np.log(ift.dobj.to_global_data(data.val)).reshape(signal_space.shape)
ift.plotting.plot(ift.Field(signal_space,
val=ift.dobj.from_global_data(logdata)),
name="log_of_data.png", **plotdict)
# ift.plotting.plot(m1,name='m_LBFGS.png', **plotdict)
ift.plotting.plot(m2, name='m_Newton.png', **plotdict)
# ift.plotting.plot(m3, name='m_SteepestDescent.png', **plotdict)
ift.plot(ift.Field(signal_space, val=ift.dobj.from_global_data(logdata)),
name="log_of_data.png", **plotdict)
# ift.plot(m1,name='m_LBFGS.png', **plotdict)
ift.plot(m2, name='m_Newton.png', **plotdict)
# ift.plot(m3, name='m_SteepestDescent.png', **plotdict)
# Probing the variance
class Proby(ift.DiagonalProberMixin, ift.Prober):
......@@ -85,4 +84,4 @@ if __name__ == "__main__":
sm = ift.FFTSmoothingOperator(signal_space, sigma=0.02)
variance = sm(proby.diagonal.weight(-1))
ift.plotting.plot(variance, name='variance.png', **plotdict)
ift.plot(variance, name='variance.png', **plotdict)
......@@ -110,7 +110,7 @@ if __name__ == "__main__":
# excitation monopole to 1
m0, t0 = adjust_zero_mode(m0, t0)
ift.plotting.plot(true_sky)
ift.plotting.plot(nonlinearity(FFT.adjoint_times(power0*m0)),
title='reconstructed_sky')
ift.plotting.plot(MeasurementOperator.adjoint_times(d))
ift.plot(true_sky)
ift.plot(nonlinearity(FFT.adjoint_times(power0*m0)),
title='reconstructed_sky')
ift.plot(MeasurementOperator.adjoint_times(d))
......@@ -107,13 +107,12 @@ if __name__ == "__main__":
sm = ift.FFTSmoothingOperator(plot_space, sigma=0.03)
plotdict = {"xlabel": "Pixel index", "ylabel": "Pixel index",
"colormap": "Planck-like"}
ift.plotting.plot(
ift.plot(
ift.log(ift.sqrt(sm(ift.Field(plot_space, val=variance.val.real)))),
name='uncertainty.png', zmin=0., zmax=3., title="Uncertainty map",
**plotdict)
ift.plotting.plot(ift.Field(plot_space, val=mock_signal.val.real),
name='mock_signal.png', **plotdict)
ift.plotting.plot(ift.Field(plot_space, val=data.val.real),
name='data.png', **plotdict)
ift.plotting.plot(ift.Field(plot_space, val=m.val.real),
name='map.png', **plotdict)
ift.plot(ift.Field(plot_space, val=mock_signal.val.real),
name='mock_signal.png', **plotdict)
ift.plot(ift.Field(plot_space, val=data.val.real),
name='data.png', **plotdict)
ift.plot(ift.Field(plot_space, val=m.val.real), name='map.png', **plotdict)
......@@ -69,8 +69,8 @@ if __name__ == "__main__":
# Plotting
plotdict = {"xlabel": "Pixel index", "ylabel": "Pixel index",
"colormap": "Planck-like"}
ift.plotting.plot(variance, name="uncertainty.png", **plotdict)
ift.plotting.plot(mock_signal, name="mock_signal.png", **plotdict)
ift.plotting.plot(ift.Field(signal_space, val=data.val),
name="data.png", **plotdict)
ift.plotting.plot(m, name="map.png", **plotdict)
ift.plot(variance, name="uncertainty.png", **plotdict)
ift.plot(mock_signal, name="mock_signal.png", **plotdict)
ift.plot(ift.Field(signal_space, val=data.val),
name="data.png", **plotdict)
ift.plot(m, name="map.png", **plotdict)
......@@ -77,9 +77,8 @@ if __name__ == "__main__":
sspace2 = ift.RGSpace(shape, distances=L/N_pixels/nu.m)
ift.plotting.plot(ift.Field(sspace2, mock_signal.val)/nu.K,
name="mock_signal.png")
ift.plot(ift.Field(sspace2, mock_signal.val)/nu.K, name="mock_signal.png")
data = ift.dobj.to_global_data(data.val).reshape(sspace2.shape)/nu.K
data = ift.Field(sspace2, val=ift.dobj.from_global_data(data))/nu.K
ift.plotting.plot(ift.Field(sspace2, val=data), name="data.png")
ift.plotting.plot(ift.Field(sspace2, m_s.val)/nu.K, name="map.png")
ift.plot(ift.Field(sspace2, val=data), name="data.png")
ift.plot(ift.Field(sspace2, m_s.val)/nu.K, name="map.png")
......@@ -62,8 +62,8 @@ if __name__ == "__main__":
energy, convergence = minimizer(energy)
m = energy.position
D = energy.curvature
ift.plotting.plot(ss, name="signal.png", colormap="Planck-like")
ift.plotting.plot(fft(m), name="m.png", colormap="Planck-like")
ift.plot(ss, name="signal.png", colormap="Planck-like")
ift.plot(fft(m), name="m.png", colormap="Planck-like")
# sampling the uncertainty map
sample_variance = ift.Field.zeros(s_space)
......@@ -77,4 +77,4 @@ if __name__ == "__main__":
sample_mean /= n_samples
sample_variance /= n_samples
variance = sample_variance - sample_mean**2
ift.plotting.plot(variance, name="variance.png", colormap="Planck-like")
ift.plot(variance, name="variance.png", colormap="Planck-like")
......@@ -9,6 +9,6 @@ from .spaces import *
from .operators import *
from .probing import *
from .sugar import *
from . import plotting
from .plotting import plot
from . import library
from . import dobj
......@@ -114,7 +114,4 @@ class DomainObject(with_metaclass(
@property
def total_volume(self):
tmp = self.dvol()
if np.isscalar(tmp):
return self.dim * tmp
else:
return np.sum(tmp)
return self.dim * tmp if np.isscalar(tmp) else np.sum(tmp)
......@@ -541,7 +541,7 @@ class Field(object):
minmax = [self.min(), self.max()]
mean = self.mean()
return "nifty4.Field instance\n- domain = " + \
repr(self._domain) + \
self._domain.__str__() + \
"\n- val = " + repr(self.val) + \
"\n - min.,max. = " + str(minmax) + \
"\n - mean = " + str(mean)
......
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