diff --git a/demos/critical_filtering.py b/demos/critical_filtering.py index bcc6b4ad4c0a20f4251e39d291c2b53919279b19..87494f655fb556226d032b16ed91080e842f9b64 100644 --- a/demos/critical_filtering.py +++ b/demos/critical_filtering.py @@ -10,7 +10,7 @@ def plot_parameters(m, t, p, p_d): t = t.val.real p = p.val.real p_d = p_d.val.real - ift.plotting.plot(m.real, name='map.pdf') + ift.plotting.plot(m.real, name='map.png') class AdjointFFTResponse(ift.LinearOperator): @@ -88,7 +88,7 @@ if __name__ == "__main__": data_power = ift.log(ift.power_analyze(fft(d), binbounds=p_space.binbounds)) d_data = d.val.real - ift.plotting.plot(d.real, name="data.pdf") + ift.plotting.plot(d.real, name="data.png") IC1 = ift.GradientNormController(verbose=True, iteration_limit=100, tol_abs_gradnorm=0.1) diff --git a/demos/log_normal_wiener_filter.py b/demos/log_normal_wiener_filter.py index 3f7a4c6a7e55aa0a67e212da4a5529e90847dde7..865938e798b16ca2fa40bb5cd569ace4099cc685 100644 --- a/demos/log_normal_wiener_filter.py +++ b/demos/log_normal_wiener_filter.py @@ -66,19 +66,19 @@ if __name__ == "__main__": # m3 = fft(me3[0].position) # Plotting - ift.plotting.plot(mock_signal.real, name='mock_signal.pdf', + ift.plotting.plot(mock_signal.real, name='mock_signal.png', colormap="plasma", xlabel="Pixel Index", ylabel="Pixel Index") logdata = np.log(ift.dobj.to_global_data(data.val.real)).reshape(signal_space.shape) ift.plotting.plot(ift.Field(signal_space, val=ift.dobj.from_global_data(logdata)), - name="log_of_data.pdf", colormap="plasma", + name="log_of_data.png", colormap="plasma", xlabel="Pixel Index", ylabel="Pixel Index") - # ift.plotting.plot(m1.real,name='m_LBFGS.pdf', colormap="plasma", + # ift.plotting.plot(m1.real,name='m_LBFGS.png', colormap="plasma", # xlabel="Pixel Index", ylabel="Pixel Index") - ift.plotting.plot(m2.real, name='m_Newton.pdf', colormap="plasma", + ift.plotting.plot(m2.real, name='m_Newton.png', colormap="plasma", xlabel="Pixel Index", ylabel="Pixel Index") - # ift.plotting.plot(m3.real, name='m_SteepestDescent.pdf', + # ift.plotting.plot(m3.real, name='m_SteepestDescent.png', # colormap="plasma", xlabel="Pixel Index", # ylabel="Pixel Index") @@ -90,4 +90,4 @@ if __name__ == "__main__": sm = ift.FFTSmoothingOperator(signal_space, sigma=0.02) variance = sm(proby.diagonal.weight(-1)) - ift.plotting.plot(variance, name='variance.pdf') + ift.plotting.plot(variance, name='variance.png') diff --git a/demos/paper_demos/cartesian_wiener_filter.py b/demos/paper_demos/cartesian_wiener_filter.py index d67eac56c8985c3b1917e26eb9aa57d84ad42284..a4dcfda4436e611fddeb34430421642077ab0d89 100644 --- a/demos/paper_demos/cartesian_wiener_filter.py +++ b/demos/paper_demos/cartesian_wiener_filter.py @@ -111,7 +111,7 @@ if __name__ == "__main__": plot_space = ift.RGSpace((N_pixels_1, N_pixels_2)) sm = ift.FFTSmoothingOperator(plot_space, sigma=0.03) - ift.plotting.plot(ift.log(ift.sqrt(sm(ift.Field(plot_space, val=variance.val.real)))), name='uncertainty.pdf',zmin=0.,zmax=3.,title="Uncertainty map",colormap="Planck-like") - ift.plotting.plot(ift.Field(plot_space, val=mock_signal.val.real), name='mock_signal.pdf',colormap="Planck-like") - ift.plotting.plot(ift.Field(plot_space, val=data.val.real), name='data.pdf',colormap="Planck-like") - ift.plotting.plot(ift.Field(plot_space, val=m.val.real), name='map.pdf',colormap="Planck-like") + ift.plotting.plot(ift.log(ift.sqrt(sm(ift.Field(plot_space, val=variance.val.real)))), name='uncertainty.png',zmin=0.,zmax=3.,title="Uncertainty map",colormap="Planck-like") + ift.plotting.plot(ift.Field(plot_space, val=mock_signal.val.real), name='mock_signal.png',colormap="Planck-like") + ift.plotting.plot(ift.Field(plot_space, val=data.val.real), name='data.png',colormap="Planck-like") + ift.plotting.plot(ift.Field(plot_space, val=m.val.real), name='map.png',colormap="Planck-like") diff --git a/demos/paper_demos/wiener_filter.py b/demos/paper_demos/wiener_filter.py index 16de178476b9fbd1a618a3145562ea595478d97c..9f414b9eb545b31ecb99c99d038bde81f8c21e26 100644 --- a/demos/paper_demos/wiener_filter.py +++ b/demos/paper_demos/wiener_filter.py @@ -65,7 +65,7 @@ if __name__ == "__main__": variance = ift.sqrt(sm(proby.diagonal.weight(-1))) # Plotting - ift.plotting.plot(variance,name="uncertainty.pdf",xlabel='Pixel index', ylabel='Pixel index') - ift.plotting.plot(mock_signal,name="mock_signal.pdf",xlabel='Pixel index', ylabel='Pixel index') - ift.plotting.plot(ift.Field(signal_space, val=data.val),name="data.pdf",xlabel='Pixel index', ylabel='Pixel index') - ift.plotting.plot(m,name="map.pdf",xlabel='Pixel index', ylabel='Pixel index') + ift.plotting.plot(variance,name="uncertainty.png",xlabel='Pixel index', ylabel='Pixel index') + ift.plotting.plot(mock_signal,name="mock_signal.png",xlabel='Pixel index', ylabel='Pixel index') + ift.plotting.plot(ift.Field(signal_space, val=data.val),name="data.png",xlabel='Pixel index', ylabel='Pixel index') + ift.plotting.plot(m,name="map.png",xlabel='Pixel index', ylabel='Pixel index') diff --git a/demos/wiener_filter_via_curvature.py b/demos/wiener_filter_via_curvature.py index 7d4f41593e6a68b17ef9668b0a95ea6c75a11e44..fb2340e7f001a079d6188f4b12953dc8d6996e8f 100644 --- a/demos/wiener_filter_via_curvature.py +++ b/demos/wiener_filter_via_curvature.py @@ -80,8 +80,8 @@ if __name__ == "__main__": sspace2 = ift.RGSpace(shape, distances=L/N_pixels/nu.m) ift.plotting.plot(ift.Field(sspace2, mock_signal.real.val)/nu.K, - name="mock_signal.pdf") + name="mock_signal.png") data = ift.dobj.to_global_data(data.val.real).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.pdf") - ift.plotting.plot(ift.Field(sspace2, m_s.real.val)/nu.K, name="map.pdf") + ift.plotting.plot(ift.Field(sspace2, val=data), name="data.png") + ift.plotting.plot(ift.Field(sspace2, m_s.real.val)/nu.K, name="map.png") diff --git a/demos/wiener_filter_via_hamiltonian.py b/demos/wiener_filter_via_hamiltonian.py index 87a33dac01d6c0d9be7af841d008a37c600f0fc2..ee2a18c80219ee34a5cb5cc0b6642f73fd644203 100644 --- a/demos/wiener_filter_via_hamiltonian.py +++ b/demos/wiener_filter_via_hamiltonian.py @@ -89,8 +89,8 @@ if __name__ == "__main__": energy, convergence = minimizer(energy) m = energy.position D = energy.curvature - ift.plotting.plot(ss, name="signal.pdf", colormap="Planck-like") - ift.plotting.plot(fft.inverse_times(m), name="m.pdf", + ift.plotting.plot(ss, name="signal.png", colormap="Planck-like") + ift.plotting.plot(fft.inverse_times(m), name="m.png", colormap="Planck-like") # sampling the uncertainty map @@ -105,4 +105,4 @@ if __name__ == "__main__": sample_mean /= n_samples sample_variance /= n_samples variance = sample_variance - sample_mean**2 - ift.plotting.plot(variance, name="variance.pdf", colormap="Planck-like") + ift.plotting.plot(variance, name="variance.png", colormap="Planck-like")