diff --git a/CMakeLists.txt b/CMakeLists.txt
index a2a18ce081039e32df522b993c3a60e9e5e78514..a9d0425fdbed5c8b4f5c7dab2dae54afdad2256b 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -415,6 +415,10 @@ if (BUILD_TESTING)
NAME test_Parseval
COMMAND turtle.test_Parseval
WORKING_DIRECTORY ${TEST_OUTPUT_DIRECTORY})
+ add_test(
+ NAME test_statistics
+ COMMAND turtle.test_statistics
+ WORKING_DIRECTORY ${TEST_OUTPUT_DIRECTORY})
### basic particle functionality
add_test(
NAME test_particles
diff --git a/TurTLE/DNS.py b/TurTLE/DNS.py
index b3e7c76a96cd9afabfc25f0118f5d23ee81802dc..9b1bff221ee57e977a617869706b50dffb82ad52 100644
--- a/TurTLE/DNS.py
+++ b/TurTLE/DNS.py
@@ -350,7 +350,9 @@ class DNS(_code):
'R_ij(t)',
'vel_max(t)',
'renergy(t)',
- 'renstrophy(t)']:
+ 'renstrophy(t)',
+ 'iter0',
+ 'iter1']:
if k in pp_file.keys():
self.statistics[k] = pp_file[k][...]
# sanity check --- Parseval theorem check
@@ -452,6 +454,60 @@ class DNS(_code):
self.statistics['D'] = self.statistics['Lint'] * self.statistics['diss'] / self.statistics['Uint']**3
self.statistics['Taylor_microscale'] = self.statistics['lambda']
return None
+ def read_moments(
+ self,
+ quantity = 'velocity',
+ base_group = 'statistics',
+ pp_file = None,
+ iteration_range = None):
+ assert(len(self.statistics.keys()) > 0)
+ if type(pp_file) == type(None):
+ pp_file = self.get_data_file()
+ if type(iteration_range) == type(None):
+ iteration_range = [self.statistics['iter0'], self.statistics['iter1']]
+ mm = pp_file[base_group + '/moments/' + quantity][
+ iteration_range[0]//self.parameters['niter_stat']:iteration_range[1]//self.parameters['niter_stat']]
+ mm = np.mean(mm, axis = 0)
+ return mm
+ def read_histogram(
+ self,
+ quantity = 'velocity',
+ base_group = 'statistics',
+ pp_file = None,
+ iteration_range = None,
+ max_estimate = None):
+ assert(len(self.statistics.keys()) > 0)
+ if type(pp_file) == type(None):
+ pp_file = self.get_data_file()
+ if type(iteration_range) == type(None):
+ iteration_range = [self.statistics['iter0'], self.statistics['iter1']]
+ if type(max_estimate) == type(None):
+ max_estimate = self.parameters['max_' + quantity + '_estimate']
+ hh = pp_file[base_group + '/histograms/' + quantity][
+ iteration_range[0]//self.parameters['niter_stat']:iteration_range[1]//self.parameters['niter_stat']]
+ hh = np.mean(hh, axis = 0)
+ if (hh.shape[-1] == 4):
+ hh = hh[..., :3]
+ max_estimate /= 3**0.5
+ bb0 = np.linspace(-max_estimate, max_estimate, self.parameters['histogram_bins']+1)
+ bb = (bb0[1:] + bb0[:-1])*0.5
+ npoints = np.round(np.mean(np.sum(hh, axis = 0)))
+ if (int(npoints) != self.parameters['nx']*self.parameters['ny']*self.parameters['nz']):
+ print('Warning: maximum estimates were wrong, histogram does not capture all values of ' + quantity + '.')
+ print('Total number of points is {0}, histogram captures {1} points.'.format(
+ self.parameters['nx']*self.parameters['ny']*self.parameters['nz'],
+ npoints))
+ pdf = hh / (npoints * (bb[1] - bb[0]))
+ return bb, hh, pdf
+ def compute_statistics_error(
+ self,
+ **kwargs):
+ mm = self.read_moments(**kwargs)
+ bb, hh, pdf = self.read_histogram(**kwargs)
+ alt_mm2 = np.sum(pdf*(bb[:, None]**2)*(bb[1] - bb[0]), axis = 0)
+ relative_error = np.abs(mm[2, :3] - alt_mm2) / (mm[2, :3])
+ assert(relative_error.max() < 0.01)
+ return relative_error.max()
def set_plt_style(
self,
style = {'dashes' : (None, None)}):
diff --git a/TurTLE/PP.py b/TurTLE/PP.py
index f653f5dbd9b9cb05fdad85529bf625a90f674b5a..d77d550fab534e8337f1a28da3cf170bb747957b 100644
--- a/TurTLE/PP.py
+++ b/TurTLE/PP.py
@@ -125,7 +125,7 @@ class PP(_code):
self.parameters['fk1'] = float(4.0)
self.parameters['forcing_type'] = 'linear'
self.pp_parameters = {}
- self.pp_parameters['iteration_list'] = np.zeros(1).astype(np.int)
+ self.pp_parameters['iteration_list'] = np.zeros(1).astype(int)
return None
def extra_postprocessing_parameters(
self,
@@ -205,7 +205,7 @@ class PP(_code):
pp_file['ii1'] = ii1
pp_file['t'] = (self.parameters['dt']*
self.parameters['niter_stat']*
- (np.arange(ii0, ii1+1).astype(np.float)))
+ (np.arange(ii0, ii1+1).astype(float)))
pp_file['energy(t, k)'] = (
data_file['statistics/spectra/velocity_velocity'][ii0:ii1+1, :, 0, 0] +
data_file['statistics/spectra/velocity_velocity'][ii0:ii1+1, :, 1, 1] +
@@ -468,7 +468,7 @@ class PP(_code):
niter_out = self.get_data_file()['parameters/niter_out'][...]
assert(opt.iter0 % niter_out == 0)
self.pp_parameters['iteration_list'] = np.arange(
- opt.iter0, opt.iter1+niter_out, niter_out, dtype = np.int)
+ opt.iter0, opt.iter1+niter_out, niter_out, dtype = int)
return opt
def launch(
self,
diff --git a/TurTLE/TEST.py b/TurTLE/TEST.py
index 72fc9609ea962787550a6082d3b1e65f0bb0f69e..7095f59ac74c978aae3c54f611fedcee85519f35 100644
--- a/TurTLE/TEST.py
+++ b/TurTLE/TEST.py
@@ -460,13 +460,13 @@ class TEST(_code):
(self.parameters['tracers{0}_integration_steps'.format(s)],) +
pbase_shape +
(ncomponents,)),
- dtype = np.float)
+ dtype = np.float64)
ofile['tracers{0}/state'.format(s)].create_dataset(
'0',
shape = (
pbase_shape +
(ncomponents,)),
- dtype = np.float)
+ dtype = np.float64)
if type(particle_initial_condition) == type(None):
ofile['tracers0/state/0'][:] = np.random.random(pbase_shape + (ncomponents,))*2*np.pi
else:
diff --git a/TurTLE/_base.py b/TurTLE/_base.py
index da1c91fc8a44b3270d77e6c30c4c9124d9d0cc8b..e445e8d05f25236d7514be1b1b96d855f8f21f22 100644
--- a/TurTLE/_base.py
+++ b/TurTLE/_base.py
@@ -78,7 +78,7 @@ class _base(object):
src_txt += 'std::vector<'
if parameters[key[i]].dtype == np.float64:
src_txt += 'double'
- elif parameters[key[i]].dtype == np.int:
+ elif parameters[key[i]].dtype == int:
src_txt += 'int'
src_txt += '> ' + key[i] + ';\n'
else:
@@ -137,7 +137,7 @@ class _base(object):
'}\n' +
'else printf({0}, "NULL");\n'.format(key_prefix + key[i]))
elif type(parameters[key[i]]) == np.ndarray:
- if parameters[key[i]].dtype in [np.int, np.int64, np.int32]:
+ if parameters[key[i]].dtype in [int, np.int64, np.int32]:
template_par = 'int'
elif parameters[key[i]].dtype == np.float64:
template_par = 'double'
@@ -164,7 +164,7 @@ class _base(object):
'.size(); array_counter++)\n' +
'{\n' +
'DEBUG_MSG("' + key[i] + '[%d] = %')
- if self.parameters[key[i]].dtype == np.int:
+ if self.parameters[key[i]].dtype == int:
src_txt += 'd'
elif self.parameters[key[i]].dtype == np.float64:
src_txt += 'g'
diff --git a/TurTLE/_code.py b/TurTLE/_code.py
index fcd6ac5b4181fdf75b27ba920aa43caa28c5ec57..a26e564af1d74da484c27d383bc4fead55fc4709 100644
--- a/TurTLE/_code.py
+++ b/TurTLE/_code.py
@@ -47,151 +47,10 @@ class _code(_base):
work_dir = './',
simname = 'test'):
_base.__init__(self, work_dir = work_dir, simname = simname)
- self.version_message = (
- '/***********************************************************************\n' +
- '* this code automatically generated by TurTLE\n' +
- '* version {0}\n'.format(TurTLE.__version__) +
- '***********************************************************************/\n\n\n')
- self.includes = """
- //begincpp
- #include "base.hpp"
- #include "fluid_solver.hpp"
- #include "scope_timer.hpp"
- #include "fftw_interface.hpp"
- #include <iostream>
- #include <hdf5.h>
- #include <string>
- #include <cstring>
- #include <fftw3-mpi.h>
- #include <omp.h>
- #include <fenv.h>
- #include <cstdlib>
- //endcpp
- """
- self.variables = 'int myrank, nprocs;\n'
- self.variables += 'int iteration;\n'
- self.variables += 'char simname[256], fname[256];\n'
- self.variables += ('hid_t parameter_file, stat_file, Cdset;\n')
- self.definitions = ''
- self.main_start = """
- //begincpp
- int main(int argc, char *argv[])
- {
- if(getenv("TURTLE_FPE_OFF") == nullptr || getenv("TURTLE_FPE_OFF") != std::string("TRUE")){
- feenableexcept(FE_INVALID | FE_OVERFLOW);
- }
- else{
- std::cout << "FPE have been turned OFF" << std::endl;
- }
- if (argc != 2)
- {
- std::cerr << "Wrong number of command line arguments. Stopping." << std::endl;
- MPI_Finalize();
- return EXIT_SUCCESS;
- }
- #ifdef NO_FFTWOMP
- MPI_Init(&argc, &argv);
- MPI_Comm_rank(MPI_COMM_WORLD, &myrank);
- MPI_Comm_size(MPI_COMM_WORLD, &nprocs);
- fftw_mpi_init();
- fftwf_mpi_init();
- DEBUG_MSG("There are %d processes\\n", nprocs);
- #else
- int mpiprovided;
- MPI_Init_thread(&argc, &argv, MPI_THREAD_FUNNELED, &mpiprovided);
- assert(mpiprovided >= MPI_THREAD_FUNNELED);
- MPI_Comm_rank(MPI_COMM_WORLD, &myrank);
- MPI_Comm_size(MPI_COMM_WORLD, &nprocs);
- const int nbThreads = omp_get_max_threads();
- DEBUG_MSG("Number of threads for the FFTW = %d\\n", nbThreads);
- if (nbThreads > 1){
- fftw_init_threads();
- fftwf_init_threads();
- }
- fftw_mpi_init();
- fftwf_mpi_init();
- DEBUG_MSG("There are %d processes and %d threads\\n", nprocs, nbThreads);
- if (nbThreads > 1){
- fftw_plan_with_nthreads(nbThreads);
- fftwf_plan_with_nthreads(nbThreads);
- }
- #endif
- strcpy(simname, argv[1]);
- snprintf(fname, 255, "%s.h5", simname);
- parameter_file = H5Fopen(fname, H5F_ACC_RDONLY, H5P_DEFAULT);
- Cdset = H5Dopen(parameter_file, "iteration", H5P_DEFAULT);
- H5Dread(
- Cdset,
- H5T_NATIVE_INT,
- H5S_ALL,
- H5S_ALL,
- H5P_DEFAULT,
- &iteration);
- DEBUG_MSG("simname is %s and iteration is %d\\n",
- simname, iteration);
- H5Dclose(Cdset);
- H5Fclose(parameter_file);
- read_parameters();
- if (myrank == 0)
- {
- // set caching parameters
- hid_t fapl = H5Pcreate(H5P_FILE_ACCESS);
- herr_t cache_err = H5Pset_cache(fapl, 0, 521, 134217728, 1.0);
- DEBUG_MSG("when setting stat_file cache I got %d\\n", cache_err);
- stat_file = H5Fopen(fname, H5F_ACC_RDWR, fapl);
- }
- {
- TIMEZONE("code::main_start");
- //endcpp
- """
- for ostream in ['cout', 'cerr']:
- self.main_start += 'if (myrank == 0) std::{1} << "{0}" << std::endl;'.format(
- self.version_message, ostream).replace('\n', '\\n') + '\n'
- self.main_end = """
- //begincpp
- }
- // clean up
- if (myrank == 0)
- {
- Cdset = H5Dopen(stat_file, "iteration", H5P_DEFAULT);
- H5Dwrite(Cdset, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, &iteration);
- H5Dclose(Cdset);
- H5Fclose(stat_file);
- }
- fftwf_mpi_cleanup();
- fftw_mpi_cleanup();
- #ifndef NO_FFTWOMP
- if (nbThreads > 1){
- fftw_cleanup_threads();
- fftwf_cleanup_threads();
- }
- #endif
- #ifdef USE_TIMINGOUTPUT
- global_timer_manager.show(MPI_COMM_WORLD);
- global_timer_manager.showHtml(MPI_COMM_WORLD);
- #endif
- MPI_Finalize();
- return EXIT_SUCCESS;
- }
- //endcpp
- """
self.host_info = host_info
- self.main = ''
self.check_current_vorticity_exists = True
self.check_current_velocity_exists = False
return None
- def write_src(self):
- with open(self.name + '.cpp', 'w') as outfile:
- outfile.write(self.version_message)
- outfile.write(self.includes)
- outfile.write(self.cdef_pars())
- outfile.write(self.variables)
- outfile.write(self.cread_pars())
- outfile.write(self.definitions)
- outfile.write(self.main_start)
- outfile.write(self.main)
- outfile.write(self.main_end)
- return None
def compile_code(
self,
no_debug = True):
diff --git a/TurTLE/test/test_Heun_p2p.py b/TurTLE/test/test_Heun_p2p.py
index 7947ded4da7e908e6db037bedbd719518786ddd7..170144723d405d95baaca2687ddbc496b1808375 100644
--- a/TurTLE/test/test_Heun_p2p.py
+++ b/TurTLE/test/test_Heun_p2p.py
@@ -59,7 +59,7 @@ class ADNS(TurTLE.DNS):
for hh in self.include_list])
self.name = 'NSVEparticle_set'
self.dns_type = 'NSVEparticle_set'
- self.definitions += open(
+ self.definitions = open(
os.path.join(
cpp_location, 'NSVEparticle_set.hpp'), 'r').read()
self.definitions += open(
diff --git a/TurTLE/test/test_collisions.py b/TurTLE/test/test_collisions.py
index cf3afd9c608e7b24a9cf7e498be209e387fcba52..ae82a5f015e6c0895c83c392edf61d5222ed3371 100644
--- a/TurTLE/test/test_collisions.py
+++ b/TurTLE/test/test_collisions.py
@@ -74,7 +74,7 @@ class ADNS_Stokes_test(TurTLE.DNS):
for hh in self.include_list])
self.name = 'NSVEparticles_stokes_set'
self.dns_type = 'NSVE_Stokes_growing_subset'
- self.definitions += open(
+ self.definitions = open(
os.path.join(
cpp_location, 'p2p_stokes_collisions_growing_subset.hpp'), 'r').read()
self.definitions += open(
@@ -150,11 +150,11 @@ class ADNS_Stokes_test(TurTLE.DNS):
data_file['tracers{0}/rhs'.format(species)].create_dataset(
'0',
shape = (integration_steps, nn, ncomponents,),
- dtype = np.float)
+ dtype = float)
dset = data_file['tracers{0}/state'.format(species)].create_dataset(
'0',
shape = (nn, ncomponents,),
- dtype = np.float)
+ dtype = float)
if not type(rseed) == type(None):
np.random.seed(rseed)
cc = int(0)
diff --git a/TurTLE/test/test_interpolation_methods.py b/TurTLE/test/test_interpolation_methods.py
index 50a58328ae3037b053a69a851bac3c6de2b6d428..9c900813cc10aef8f33ee04fa407bfe3a2662302 100644
--- a/TurTLE/test/test_interpolation_methods.py
+++ b/TurTLE/test/test_interpolation_methods.py
@@ -59,11 +59,11 @@ def main():
err = np.abs(phi0 - phi1)
err_mean_2.append(err.mean())
err_max_2.append(err.max())
- neighbour_list = np.array([1, 2, 3, 4]).astype(np.float)
+ neighbour_list = np.array([1, 2, 3, 4]).astype(float)
a.plot(neighbour_list, err_mean_1, marker = '.', label = 'm=1, mean')
a.plot(neighbour_list, err_max_1, marker = '.', label = 'm=1, max')
a.plot(neighbour_list, 1e-4*neighbour_list**(-4), color = 'black', dashes = (2, 2))
- neighbour_list = np.array([2, 3, 4]).astype(np.float)
+ neighbour_list = np.array([2, 3, 4]).astype(float)
a.plot(neighbour_list, err_mean_2, marker = '.', label = 'm=2, mean')
a.plot(neighbour_list, err_max_2, marker = '.', label = 'm=2, max')
diff --git a/TurTLE/test/test_particle_deleter.py b/TurTLE/test/test_particle_deleter.py
index af8fb85170bb6ca76aa856ab09dc1ff7a22c59a8..551a0756c5e3b4eba11372f91c8fd0f11ae921f8 100644
--- a/TurTLE/test/test_particle_deleter.py
+++ b/TurTLE/test/test_particle_deleter.py
@@ -66,7 +66,7 @@ class ADNS(TurTLE.DNS):
for hh in self.include_list])
self.name = 'particle_deleter'
self.dns_type = 'particle_deleter'
- self.definitions += open(
+ self.definitions = open(
os.path.join(
cpp_location, self.dns_type + '.hpp'), 'r').read()
self.definitions += open(
diff --git a/TurTLE/test/test_particle_integration.py b/TurTLE/test/test_particle_integration.py
index def55e5bde50af678b758e49aef7c21d027678b0..644c00a4ab355a58add373bec3c8e59a92d18935 100644
--- a/TurTLE/test/test_particle_integration.py
+++ b/TurTLE/test/test_particle_integration.py
@@ -100,11 +100,11 @@ def main():
# err = np.abs(phi0 - phi1)
# err_mean_2.append(err.mean())
# err_max_2.append(err.max())
- #neighbour_list = np.array([1, 2, 3, 4]).astype(np.float)
+ #neighbour_list = np.array([1, 2, 3, 4]).astype(float)
#a.plot(neighbour_list, err_mean_1, marker = '.', label = 'm=1, mean')
#a.plot(neighbour_list, err_max_1, marker = '.', label = 'm=1, max')
#a.plot(neighbour_list, 1e-4*neighbour_list**(-4), color = 'black', dashes = (2, 2))
- #neighbour_list = np.array([2, 3, 4]).astype(np.float)
+ #neighbour_list = np.array([2, 3, 4]).astype(float)
#a.plot(neighbour_list, err_mean_2, marker = '.', label = 'm=2, mean')
#a.plot(neighbour_list, err_max_2, marker = '.', label = 'm=2, max')
diff --git a/TurTLE/test/test_particles.py b/TurTLE/test/test_particles.py
index f3afb7f7cbd659311845a6d0c32f00fa9653b022..7c1baa2a521f7c4b1e329094647f221603d28a84 100644
--- a/TurTLE/test/test_particles.py
+++ b/TurTLE/test/test_particles.py
@@ -59,7 +59,7 @@ def main():
np.sum(x**2, axis = -1).flatten()**.5,
bins = np.linspace(0, 2, 40))
bb = (bins[:-1] + bins[1:])/2
- pp = hist.astype(np.float) / (np.sum(hist) * (bb[1] - bb[0]))
+ pp = hist.astype(float) / (np.sum(hist) * (bb[1] - bb[0]))
a.plot(bb, pp, label = '{0}'.format(iteration))
a.legend(loc = 'best')
f.tight_layout()
@@ -74,7 +74,7 @@ def main():
np.sum(x**2, axis = -1).flatten()**.5,
bins = 40)
bb = (bins[:-1] + bins[1:])/2
- pp = hist.astype(np.float) / (np.sum(hist) * (bb[1] - bb[0]))
+ pp = hist.astype(float) / (np.sum(hist) * (bb[1] - bb[0]))
a.plot(bb, pp, label = '{0}'.format(iteration))
a.legend(loc = 'best')
f.tight_layout()
@@ -89,7 +89,7 @@ def main():
np.sum(x**2, axis = -1).flatten()**.5,
bins = np.linspace(0, 2, 40))
bb = (bins[:-1] + bins[1:])/2
- pp = hist.astype(np.float) / (np.sum(hist) * (bb[1] - bb[0]))
+ pp = hist.astype(float) / (np.sum(hist) * (bb[1] - bb[0]))
a.plot(bb, pp, label = '{0}'.format(iteration))
a.legend(loc = 'best')
f.tight_layout()
@@ -121,7 +121,7 @@ def main():
x.flatten(),
bins = 100)
bb = (bins[:-1] + bins[1:])/2
- pp = hist.astype(np.float) / (np.sum(hist) * (bb[1] - bb[0]))
+ pp = hist.astype(float) / (np.sum(hist) * (bb[1] - bb[0]))
a.plot(bb, pp, label = '{0}'.format(iteration))
a.legend(loc = 'best')
f.tight_layout()
diff --git a/TurTLE/test/test_statistics.py b/TurTLE/test/test_statistics.py
new file mode 100644
index 0000000000000000000000000000000000000000..7094a5f657766dc17db86a392eb137079ed54287
--- /dev/null
+++ b/TurTLE/test/test_statistics.py
@@ -0,0 +1,32 @@
+import TurTLE
+from TurTLE import DNS
+import numpy as np
+
+def main():
+ c = DNS()
+ c.launch([
+ 'NSVE',
+ '--simname', 'test_statistics',
+ '--src-simname', 'B32p1e4',
+ '--src-wd', TurTLE.data_dir,
+ '--niter_todo', '32',
+ '--niter_stat', '1',
+ '--max_velocity_estimate', '10',
+ '--max_vorticity_estimate', '20'])
+ c.compute_statistics()
+
+ # velocity
+ mm = c.read_moments()
+ bb, hh, pdf = c.read_histogram()
+ print(c.compute_statistics_error())
+ print(mm[2, 3]*0.5, c.statistics['energy'])
+
+ # vorticity
+ mm = c.read_moments(quantity = 'vorticity')
+ bb, hh, pdf = c.read_histogram(quantity = 'vorticity')
+ print(c.compute_statistics_error(quantity = 'vorticity'))
+ print(mm[2, 3]*0.5, c.statistics['enstrophy'])
+ return None
+
+if __name__ == '__main__':
+ main()
diff --git a/TurTLE/test/test_turtle_NSVE_Stokes_particles.py b/TurTLE/test/test_turtle_NSVE_Stokes_particles.py
index 400a0cdb12ba0790343489a8570f9383a16daa80..acc67272843995bbe64dec0bbdf6a060d8d64d5b 100644
--- a/TurTLE/test/test_turtle_NSVE_Stokes_particles.py
+++ b/TurTLE/test/test_turtle_NSVE_Stokes_particles.py
@@ -83,7 +83,7 @@ def main():
time_values = np.arange(0, niterations*dt, dt)
numerics, = plt.plot(time_values, particle_momentum, alpha = 1, lw=2)
plt.plot(time_values,
- theory_exponential(time_values, f2['parameters/initial_particle_vel'],np.float(drag_coeff)),
+ theory_exponential(time_values, f2['parameters/initial_particle_vel'],float(drag_coeff)),
color='black', ls = '--')
plt.plot(0,0,color=numerics.get_color(),label=r'drag coefficient '+drag_coeff)
j+=1
diff --git a/TurTLE/tools.py b/TurTLE/tools.py
index 6d3869854a9070eaeca2c1bc8149e38637730df7..1fab1c18a6329a05826ce6e19ffca2e05dfcf60e 100644
--- a/TurTLE/tools.py
+++ b/TurTLE/tools.py
@@ -258,7 +258,7 @@ def get_fornberg_coeffs(
coeffs.append([])
for j in range(len(d)):
coeffs[-1].append(d[m][N][j])
- return np.array(coeffs).astype(np.float)
+ return np.array(coeffs).astype(float)
def particle_finite_diff_test(
c,
diff --git a/examples/convergence/fields_temporal.py b/examples/convergence/fields_temporal.py
index d5e271be336b70303c6e2845a438293930834a6e..eb20cef121fba83b7c300cff2ef64639754c1b72 100644
--- a/examples/convergence/fields_temporal.py
+++ b/examples/convergence/fields_temporal.py
@@ -161,7 +161,7 @@ def plot_error_field(err_vs_t = False):
error_list[2],
marker = '.',
label = 'NSVE vs NSE')
- fl = np.array(factor_list).astype(np.float)
+ fl = np.array(factor_list).astype(float)
for ee in [2, 3]:
a.plot(fl[:2], error_list[0][0] * fl[:2]**(-ee),
dashes = (ee, ee),
diff --git a/examples/convergence/particles_temporal.py b/examples/convergence/particles_temporal.py
index c7b0ac15573a97031bd9a72e706674d03f6d8a8f..190bfa89f8a6990754ccc495401fa493fcf075bf 100644
--- a/examples/convergence/particles_temporal.py
+++ b/examples/convergence/particles_temporal.py
@@ -166,7 +166,7 @@ def plot_error_particles():
f = plt.figure()
a = f.add_subplot(111)
factor_list = [1, 2]
- factor_list = np.array(factor_list).astype(np.float)
+ factor_list = np.array(factor_list).astype(float)
for neighbours, smoothness in neighbours_smoothness_list:
interp_name = 'I{0}O{1}'.format(2*neighbours+2, 2*smoothness+1)
err_max_list = []
diff --git a/meta/count_nmodes.py b/meta/count_nmodes.py
index 19af4ab332067ba72758bbc5244b33c8ea569dc0..d3b55587850f4ee2d137074d0dd5e46eadff7fb9 100644
--- a/meta/count_nmodes.py
+++ b/meta/count_nmodes.py
@@ -1,7 +1,7 @@
import numpy as np
def count_expensive(fk0, fk1):
- kcomponent = np.arange(-np.floor(fk1)-1, np.floor(fk1)+2, 1).astype(np.float)
+ kcomponent = np.arange(-np.floor(fk1)-1, np.floor(fk1)+2, 1).astype(float)
ksize = (kcomponent[:, None, None]**2 +
kcomponent[None, :, None]**2 +
kcomponent[None, None, :]**2)**.5
diff --git a/projects/sedimenting_rods/GCDNS.py b/projects/sedimenting_rods/GCDNS.py
index 670c910d270d3b5fb60aaf255b1b8f438cd0c77a..e7232dfcfc866b921f0693776d1e22cd572dfac9 100644
--- a/projects/sedimenting_rods/GCDNS.py
+++ b/projects/sedimenting_rods/GCDNS.py
@@ -47,7 +47,7 @@ class GCDNS(TurTLE.DNS):
'tracers0_u_sed' : np.array([1.0],dtype='float64'),
'l_factor' : float(1.0),
't_factor' : float(1.0),
- 'many_integration_steps' : np.array([2]).astype(np.int),
+ 'many_integration_steps' : np.array([2]).astype(int),
}
return None
def write_src(
@@ -127,11 +127,11 @@ class GCDNS(TurTLE.DNS):
data_file['tracers{0}/rhs'.format(species)].create_dataset(
'0',
shape = (integration_steps, nn, ncomponents,),
- dtype = np.float)
+ dtype = np.float64)
dset = data_file['tracers{0}/state'.format(species)].create_dataset(
'0',
shape = (nn, ncomponents,),
- dtype = np.float)
+ dtype = np.float64)
if not type(rseed) == type(None):
np.random.seed(rseed)
cc = int(0)
diff --git a/setup.py.in b/setup.py.in
index 87261d3275b2fe97190e7268771ddd8660f3b3b5..984a8993a1aedbbcae15267b7dcd24fb87012fe8 100644
--- a/setup.py.in
+++ b/setup.py.in
@@ -47,6 +47,7 @@ setup(
'turtle.test_NSVEparticles = TurTLE.test.test_turtle_NSVEparticles:main',
'turtle.test_particles = TurTLE.test.test_particles:main',
'turtle.test_Parseval = TurTLE.test.test_Parseval:main',
+ 'turtle.test_statistics = TurTLE.test.test_statistics:main',
'turtle.test_fftw = TurTLE.test.test_fftw:main',
'turtle.test_Heun_p2p = TurTLE.test.test_Heun_p2p:main',
'turtle.test_particle_deleter = TurTLE.test.test_particle_deleter:main',
diff --git a/tests/test_field_class.py b/tests/test_field_class.py
index ef0cc8513c3bb289c018afb9f4a4e726a5e8a728..7bd9e7ab38cd41b336fd065a4aa96ddbcf74de1c 100644
--- a/tests/test_field_class.py
+++ b/tests/test_field_class.py
@@ -129,8 +129,8 @@ def main():
f['scal/real/0'] = rdata
f['vec/complex/0'] = np.array([cdata, cdata, cdata]).reshape(cdata.shape + (3,))
f['vec/real/0'] = np.array([rdata, rdata, rdata]).reshape(rdata.shape + (3,))
- f['moments/scal'] = np.zeros(shape = (1, 10)).astype(np.float)
- f['histograms/scal'] = np.zeros(shape = (1, 64)).astype(np.float)
+ f['moments/scal'] = np.zeros(shape = (1, 10)).astype(float)
+ f['histograms/scal'] = np.zeros(shape = (1, 64)).astype(float)
kspace = tf.get_kspace()
nshells = kspace['nshell'].shape[0]
f['spectra/scal'] = np.zeros(shape = (1, nshells)).astype(np.float64)