Wrap all scripts in functions

This is best practise in python scripts in order no to clutter the global
namespace.

demos/bench_gridder.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2019 Max-Planck-Society
+# Copyright(C) 2019-2020 Max-Planck-Society
 # Author: Martin Reinecke
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
@@ -23,16 +23,18 @@ import numpy as np
 
 import nifty7 as ift
 
-N0s, a0s, b0s, c0s = [], [], [], []
 
-for ii in range(10, 26):
+def main():
+    N0s, a0s, b0s, c0s = [], [], [], []
+
+    for ii in range(10, 26):
         nu = 1024
         nv = 1024
         N = int(2**ii)
         print('N = {}'.format(N))
 
         rng = ift.random.current_rng()
-    uv = rng.uniform(-.5, .5, (N,2))
+        uv = rng.uniform(-.5, .5, (N, 2))
         vis = rng.normal(0., 1., N) + 1j*rng.normal(0., 1., N)
 
         uvspace = ift.RGSpace((nu, nv))
@@ -57,34 +59,37 @@ for ii in range(10, 26):
         b0s.append(t2 - t1)
         c0s.append(t3 - t2)
 
-print('Measure rest operator')
-sc = ift.StatCalculator()
-op = GM.getRest().adjoint
-for _ in range(10):
+    print('Measure rest operator')
+    sc = ift.StatCalculator()
+    op = GM.getRest().adjoint
+    for _ in range(10):
         t0 = time()
         res = op(img)
         sc.add(time() - t0)
-t_fft = sc.mean
-print('FFT shape', res.shape)
-
-plt.scatter(N0s, a0s, label='Gridder mr')
-plt.legend()
-# no idea why this is necessary, but if it is omitted, the range is wrong
-plt.ylim(min(a0s), max(a0s))
-plt.ylabel('time [s]')
-plt.title('Initialization')
-plt.loglog()
-plt.savefig('bench0.png')
-plt.close()
-
-plt.scatter(N0s, b0s, color='k', marker='^', label='Gridder mr times')
-plt.scatter(N0s, c0s, color='k', label='Gridder mr adjoint times')
-plt.axhline(sc.mean, label='FFT')
-plt.axhline(sc.mean + np.sqrt(sc.var))
-plt.axhline(sc.mean - np.sqrt(sc.var))
-plt.legend()
-plt.ylabel('time [s]')
-plt.title('Apply')
-plt.loglog()
-plt.savefig('bench1.png')
-plt.close()
+    print('FFT shape', res.shape)
+
+    plt.scatter(N0s, a0s, label='Gridder mr')
+    plt.legend()
+    # no idea why this is necessary, but if it is omitted, the range is wrong
+    plt.ylim(min(a0s), max(a0s))
+    plt.ylabel('time [s]')
+    plt.title('Initialization')
+    plt.loglog()
+    plt.savefig('bench0.png')
+    plt.close()
+
+    plt.scatter(N0s, b0s, color='k', marker='^', label='Gridder mr times')
+    plt.scatter(N0s, c0s, color='k', label='Gridder mr adjoint times')
+    plt.axhline(sc.mean, label='FFT')
+    plt.axhline(sc.mean + np.sqrt(sc.var))
+    plt.axhline(sc.mean - np.sqrt(sc.var))
+    plt.legend()
+    plt.ylabel('time [s]')
+    plt.title('Apply')
+    plt.loglog()
+    plt.savefig('bench1.png')
+    plt.close()
+
+
+if __name__ == '__main__':
+    main()

demos/bernoulli_demo.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -26,7 +26,8 @@ import numpy as np
 
 import nifty7 as ift
 
-if __name__ == '__main__':
+
+def main():
     # Set up the position space of the signal
     mode = 2
     if mode == 0:
@@ -84,3 +85,7 @@ if __name__ == '__main__':
     plot.add(GR.adjoint_times(data), title='data')
     plot.add(sky(mock_position), title='truth')
     plot.output(nx=3, xsize=16, ysize=9, title="results", name="bernoulli.png")
+
+
+if __name__ == '__main__':
+    main()

demos/getting_started_1.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -38,14 +38,14 @@ def make_checkerboard_mask(position_space):
     return mask
 
 
-def make_random_mask():
+def make_random_mask(domain):
     # Random mask for spherical mode
-    mask = ift.from_random(position_space, 'pm1')
+    mask = ift.from_random(domain, 'pm1')
     mask = (mask + 1)/2
     return mask.val
 
 
-if __name__ == '__main__':
+def main():
     # Choose space on which the signal field is defined
     if len(sys.argv) == 2:
         mode = int(sys.argv[1])
@@ -63,7 +63,7 @@ if __name__ == '__main__':
     else:
         # Sphere with half of its pixels randomly masked
         position_space = ift.HPSpace(128)
-        mask = make_random_mask()
+        mask = make_random_mask(position_space)
 
     # Specify harmonic space corresponding to signal
     harmonic_space = position_space.get_default_codomain()
@@ -148,3 +148,7 @@ if __name__ == '__main__':
                  title='Residuals')
         plot.output(nx=2, ny=2, xsize=10, ysize=10, name=filename)
     print("Saved results as '{}'.".format(filename))
+
+
+if __name__ == '__main__':
+    main()

demos/getting_started_2.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -28,22 +28,20 @@ import numpy as np
 import nifty7 as ift
 
 
-def exposure_2d():
+def exposure_2d(domain):
     # Structured exposure for 2D mode
-    x_shape, y_shape = position_space.shape
-
-    exposure = np.ones(position_space.shape)
+    x_shape, y_shape = domain.shape
+    exposure = np.ones(domain.shape)
     exposure[x_shape//3:x_shape//2, :] *= 2.
     exposure[x_shape*4//5:x_shape, :] *= .1
     exposure[x_shape//2:x_shape*3//2, :] *= 3.
     exposure[:, x_shape//3:x_shape//2] *= 2.
     exposure[:, x_shape*4//5:x_shape] *= .1
     exposure[:, x_shape//2:x_shape*3//2] *= 3.
-
-    return ift.Field.from_raw(position_space, exposure)
+    return ift.Field.from_raw(domain, exposure)
 
 
-if __name__ == '__main__':
+def main():
     # Choose space on which the signal field is defined
     if len(sys.argv) == 2:
         mode = int(sys.argv[1])
@@ -57,7 +55,7 @@ if __name__ == '__main__':
     elif mode == 1:
         # Two-dimensional regular grid with inhomogeneous exposure
         position_space = ift.RGSpace([512, 512])
-        exposure = exposure_2d()
+        exposure = exposure_2d(position_space)
     else:
         # Sphere with uniform exposure of 100
         position_space = ift.HPSpace(128)
@@ -118,3 +116,7 @@ if __name__ == '__main__':
     plot.add(reconst - signal, title='Residuals')
     plot.output(xsize=12, ysize=10, name=filename)
     print("Saved results as '{}'.".format(filename))
+
+
+if __name__ == '__main__':
+    main()

demos/getting_started_3.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -44,7 +44,7 @@ def radial_los(n_los):
     return starts, ends
 
 
-if __name__ == '__main__':
+def main():
     # Choose between random line-of-sight response (mode=0) and radial lines
     # of sight (mode=1)
     if len(sys.argv) == 2:
@@ -60,10 +60,10 @@ if __name__ == '__main__':
     #  see 'getting_started_4_CorrelatedFields.ipynb'.
 
     cfmaker = ift.CorrelatedFieldMaker.make(
-        offset_mean =      0.0,  # 0.
-        offset_std_mean = 1e-3,  # 1e-3
-        offset_std_std =  1e-6,  # 1e-6
-        prefix = '')
+        offset_mean=      0.0,
+        offset_std_mean= 1e-3,
+        offset_std_std=  1e-6,
+        prefix='')
 
     fluctuations_dict = {
         # Amplitude of field fluctuations
@@ -163,3 +163,7 @@ if __name__ == '__main__':
         linewidth=[1.]*len(powers) + [3., 3.])
     plot.output(ny=1, nx=3, xsize=24, ysize=6, name=filename_res)
     print("Saved results as '{}'.".format(filename_res))
+
+
+if __name__ == '__main__':
+    main()

demos/getting_started_5_mf.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -55,7 +55,7 @@ def radial_los(n_los):
     return starts, ends
 
 
-if __name__ == '__main__':
+def main():
     # Choose between random line-of-sight response (mode=0) and radial lines
     # of sight (mode=1)
     if len(sys.argv) == 2:
@@ -83,7 +83,7 @@ if __name__ == '__main__':
     A2 = cfmaker.normalized_amplitudes[1]
     DC = SingleDomain(correlated_field.target, position_space)
 
-    ## Apply a nonlinearity
+    # Apply a nonlinearity
     signal = DC @ ift.sigmoid(correlated_field)
 
     # Build the line-of-sight response and define signal response
@@ -118,7 +118,7 @@ if __name__ == '__main__':
     ic_newton.enable_logging()
     minimizer = ift.NewtonCG(ic_newton, enable_logging=True)
 
-    ## number of samples used to estimate the KL
+    # number of samples used to estimate the KL
     N_samples = 20
 
     # Set up likelihood and information Hamiltonian
@@ -157,7 +157,6 @@ if __name__ == '__main__':
                     name=filename.format("loop_{:02d}".format(i)))
 
     # Done, draw posterior samples
-    Nsamples = 20
     KL = ift.MetricGaussianKL(mean, H, N_samples)
     sc = ift.StatCalculator()
     scA1 = ift.StatCalculator()
@@ -189,3 +188,7 @@ if __name__ == '__main__':
              linewidth=[1.]*len(powers2) + [3., 3.])
     plot.output(ny=2, nx=2, xsize=15, ysize=15, name=filename_res)
     print("Saved results as '{}'.".format(filename_res))
+
+
+if __name__ == '__main__':
+    main()

demos/mgvi_visualized.py

@@ -34,7 +34,7 @@ from matplotlib.colors import LogNorm
 
 import nifty7 as ift
 
-if __name__ == '__main__':
+def main():
     dom = ift.UnstructuredDomain(1)
     scale = 10
 
@@ -119,3 +119,7 @@ if __name__ == '__main__':
     ift.logger.info('Finished')
     # Uncomment the following line in order to leave the plots open
     # plt.show()
+
+
+if __name__ == '__main__':
+    main()

demos/misc/convolution.py

@@ -11,7 +11,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2019 Max-Planck-Society
+# Copyright(C) 2019-2020 Max-Planck-Society
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -37,55 +37,52 @@ def convtest(test_signal, delta, func):
 
     # Plot results
     plot = ift.Plot()
-    plot.add(signal, title='Signal')
+    plot.add(test_signal, title='Signal')
     plot.add(conv_signal, title='Signal Convolved')
     plot.add(cac_signal, title='Signal, Conv, Adj-Conv')
     plot.add(conv_delta, title='Kernel')
     plot.output()
 
 
-# Healpix test
-nside = 64
-npix = 12 * nside * nside
+def main():
+    # Healpix test
+    nside = 64
+    npix = 12 * nside * nside
 
-domain = ift.HPSpace(nside)
+    domain = ift.HPSpace(nside)
 
-# Define test signal (some point sources)
-signal_vals = np.zeros(npix, dtype=np.float64)
-for i in range(0, npix, npix//12 + 27):
+    # Define test signal (some point sources)
+    signal_vals = np.zeros(npix, dtype=np.float64)
+    for i in range(0, npix, npix//12 + 27):
         signal_vals[i] = 500.
 
-signal = ift.makeField(domain, signal_vals)
+    signal = ift.makeField(domain, signal_vals)
 
-delta_vals = np.zeros(npix, dtype=np.float64)
-delta_vals[0] = 1.0
-delta = ift.makeField(domain, delta_vals)
+    delta_vals = np.zeros(npix, dtype=np.float64)
+    delta_vals[0] = 1.0
+    delta = ift.makeField(domain, delta_vals)
 
-
-# Define kernel function
-def func(theta):
+    # Define kernel function
+    def func(theta):
         ct = np.cos(theta)
         return 1. * np.logical_and(ct > 0.7, ct <= 0.8)
 
+    convtest(signal, delta, func)
 
-convtest(signal, delta, func)
-
-domain = ift.RGSpace((100, 100))
-# Define test signal (some point sources)
-signal_vals = np.zeros(domain.shape, dtype=np.float64)
-signal_vals[35, 70] = 5000.
-signal_vals[45, 8] = 5000.
-signal = ift.makeField(domain, signal_vals)
-
-# Define delta signal, generate kernel image
-delta_vals = np.zeros(domain.shape, dtype=np.float64)
-delta_vals[0, 0] = 1.0
-delta = ift.makeField(domain, delta_vals)
+    domain = ift.RGSpace((100, 100))
+    # Define test signal (some point sources)
+    signal_vals = np.zeros(domain.shape, dtype=np.float64)
+    signal_vals[35, 70] = 5000.
+    signal_vals[45, 8] = 5000.
+    signal = ift.makeField(domain, signal_vals)
 
+    # Define delta signal, generate kernel image
+    delta_vals = np.zeros(domain.shape, dtype=np.float64)
+    delta_vals[0, 0] = 1.0
+    delta = ift.makeField(domain, delta_vals)
 
-# Define kernel function
-def func(dist):
-    return 1. * np.logical_and(dist > 0.1, dist <= 0.2)
+    convtest(signal, delta, lambda d: 1. * np.logical_and(d > 0.1, d <= 0.2))
 
 
-convtest(signal, delta, func)
+if __name__ == '__main__':
+    main()

demos/polynomial_fit.py

@@ -11,7 +11,8 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
-# Copyright(C) 2013-2019 Max-Planck-Society
+# Copyright(C) 2013-2020 Max-Planck-Society
+# Author: Philipp Arras
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
@@ -56,7 +57,7 @@ class PolynomialResponse(ift.LinearOperator):
 
     def __init__(self, domain, sampling_points):
         if not (isinstance(domain, ift.UnstructuredDomain)
-                and isinstance(x, np.ndarray)):
+                and isinstance(sampling_points, np.ndarray)):
             raise TypeError
         self._domain = ift.DomainTuple.make(domain)
         tgt = ift.UnstructuredDomain(sampling_points.shape)
@@ -80,7 +81,7 @@ class PolynomialResponse(ift.LinearOperator):
         return ift.makeField(self._tgt(mode), out)
 
 
-if __name__ == '__main__':
+def main():
     # Generate some mock data
     N_params = 10
     N_samples = 100
@@ -140,3 +141,7 @@ if __name__ == '__main__':
     sigma = np.sqrt(sc.var.val)
     for ii in range(len(mean)):
         print('Coefficient x**{}: {:.2E} +/- {:.2E}'.format(ii, mean[ii], sigma[ii]))
+
+
+if __name__ == '__main__':
+    main()