testing Gaussian field on cluster

TurTLE/test/test_Gaussian_field.py

@@ -5,7 +5,7 @@ from scipy import trapz
 from scipy.stats import norm
 from scipy.integrate import quad
 import h5py
-import sys
+import sys, os
 import time
 
 import TurTLE
@@ -17,7 +17,6 @@ except:
     plt = None
 
 def main():
-    c = TEST()
     # size of grid
     n = 1024
     slope = -5./3.
@@ -29,23 +28,27 @@ def main():
     rseed = int(time.time())
     simname = 'Gaussianity_test'
 
-    opt = c.launch(
-        ['Gauss_field_test',
-         '--nx', str(n),
-         '--ny', str(n),
-         '--nz', str(n),
-         '--simname', simname,
-         '--np', '4',
-         '--ntpp', '1',
-         '--wd', './',
-         '--histogram_bins', str(bin_no),
-         '--max_velocity_estimate', '8.',
-         '--spectrum_slope', str(slope),
-         '--spectrum_k_cutoff', str(k_cutoff),
-         '--spectrum_coefficient', str(coeff),
-         '--field_random_seed', str(rseed)] +
-         sys.argv[1:])
-    plot_stuff(c.simname, total_energy = total_energy)
+    if not os.path.exists(simname+'.h5'):
+        c = TEST()
+        opt = c.launch(
+            ['Gauss_field_test',
+             '--nx', str(n),
+             '--ny', str(n),
+             '--nz', str(n),
+             '--simname', simname,
+             '--np', '4',
+             '--environment', 'short',
+             '--minutes', '60',
+             '--ntpp', '1',
+             '--wd', './',
+             '--histogram_bins', str(bin_no),
+             '--max_velocity_estimate', '8.',
+             '--spectrum_slope', str(slope),
+             '--spectrum_k_cutoff', str(k_cutoff),
+             '--spectrum_coefficient', str(coeff),
+             '--field_random_seed', str(rseed)] +
+             sys.argv[1:])
+    plot_stuff(simname, total_energy = total_energy)
     return None
 
 def plot_stuff(simname, total_energy = 1.):
@@ -107,12 +110,12 @@ def plot_stuff(simname, total_energy = 1.):
     print('----------- k2-premultiplied spectrum -----------')
     k2func = lambda k, k_c=k_cutoff, s=slope : k**(2+s)*np.exp(-k/k_c)
     k2sum_analytic = quad(k2func, 0, k_cutoff*20)[0]
-    print('Analytically: {}'.format(k2sum_analytic))
+    print('Analytically: {}'.format(coeff*k2sum_analytic))
     k2spec_trace = (
             df['statistics/spectra/k*velocity_k*velocity'][..., 0, 0]
             + df['statistics/spectra/k*velocity_k*velocity'][..., 1, 1]
             + df['statistics/spectra/k*velocity_k*velocity'][..., 2, 2])
-    print('Energy sum: {}'.format(np.sum(k2spec_trace*df['kspace/dk'][()])))
+    print('Energy sum: {}'.format(np.sum(k2spec_trace*df['kspace/dk'][()])/2.))
 
     df.close()
     return None