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Commit 490e28b9 authored by David Hendriks's avatar David Hendriks
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More detailed test output

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binarycpython/tests/test_distributions.py
+ 46
− 12
View file @ 490e28b9
...@@ -93,12 +93,15 @@ class TestDistributions(unittest.TestCase): ...@@ -93,12 +93,15 @@ class TestDistributions(unittest.TestCase):
0.000161214690242696, 0.000161214690242696,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append(powerlaw(1, 100, -2.3, mass)) python_results.append(powerlaw(1, 100, -2.3, mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
msg = "Error: Value perl: {} Value python: {} for mass, per: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance)
# extra test for k = -1 # extra test for k = -1
...@@ -118,15 +121,18 @@ class TestDistributions(unittest.TestCase): ...@@ -118,15 +121,18 @@ class TestDistributions(unittest.TestCase):
6.19974072148769e-06, 6.19974072148769e-06,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append( python_results.append(
three_part_powerlaw(mass, 0.08, 0.1, 1, 300, -1.3, -2.3, -2.3) three_part_powerlaw(mass, 0.08, 0.1, 1, 300, -1.3, -2.3, -2.3)
) )
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass, per: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
# Extra test: # Extra test:
# M < M0 # M < M0
...@@ -149,13 +155,17 @@ class TestDistributions(unittest.TestCase): ...@@ -149,13 +155,17 @@ class TestDistributions(unittest.TestCase):
1.77061658757533e-05, 1.77061658757533e-05,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append(Kroupa2001(mass)) python_results.append(Kroupa2001(mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
# Extra tests: # Extra tests:
self.assertEqual( self.assertEqual(
Kroupa2001(10, newopts={"mmax": 300}), Kroupa2001(10, newopts={"mmax": 300}),
...@@ -176,13 +186,17 @@ class TestDistributions(unittest.TestCase): ...@@ -176,13 +186,17 @@ class TestDistributions(unittest.TestCase):
4.02817276824841e-06, 4.02817276824841e-06,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append(ktg93(mass)) python_results.append(ktg93(mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
# extra test: # extra test:
self.assertEqual( self.assertEqual(
ktg93(10, newopts={"mmax": 300}), ktg93(10, newopts={"mmax": 300}),
...@@ -235,7 +249,7 @@ class TestDistributions(unittest.TestCase): ...@@ -235,7 +249,7 @@ class TestDistributions(unittest.TestCase):
self.assertLess( self.assertLess(
np.abs(imf_chabrier2003(m) - 0.581457346702825), np.abs(imf_chabrier2003(m) - 0.581457346702825),
self.tolerance, self.tolerance,
msg="Difference is bigger than the tolerance", msg="Difference is bigger than the tolerance. Input mass = {}".format(m),
) )
# For m = 2 # For m = 2
...@@ -243,7 +257,7 @@ class TestDistributions(unittest.TestCase): ...@@ -243,7 +257,7 @@ class TestDistributions(unittest.TestCase):
self.assertLess( self.assertLess(
np.abs(imf_chabrier2003(m) - 0.581457346702825), np.abs(imf_chabrier2003(m) - 0.581457346702825),
self.tolerance, self.tolerance,
msg="Difference is bigger than the tolerance", msg="Difference is bigger than the tolerance. Input mass = {}".format(m),
) )
def test_duquennoy1991(self): def test_duquennoy1991(self):
...@@ -267,13 +281,16 @@ class TestDistributions(unittest.TestCase): ...@@ -267,13 +281,16 @@ class TestDistributions(unittest.TestCase):
0.0134332780385336, 0.0134332780385336,
] ]
python_results = [] python_results = []
input_lists = []
for logper in self.logper_list: for logper in self.logper_list:
input_lists.append(logper)
python_results.append(gaussian(logper, 4.8, 2.3, -2.0, 12.0)) python_results.append(gaussian(logper, 4.8, 2.3, -2.0, 12.0))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for logper: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
# Extra test: # Extra test:
self.assertTrue( self.assertTrue(
...@@ -295,13 +312,16 @@ class TestDistributions(unittest.TestCase): ...@@ -295,13 +312,16 @@ class TestDistributions(unittest.TestCase):
0.8388, 0.8388,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append(Arenou2010_binary_fraction(mass)) python_results.append(Arenou2010_binary_fraction(mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
def test_raghavan2010_binary_fraction(self): def test_raghavan2010_binary_fraction(self):
""" """
...@@ -310,13 +330,16 @@ class TestDistributions(unittest.TestCase): ...@@ -310,13 +330,16 @@ class TestDistributions(unittest.TestCase):
perl_results = [0.304872297931597, 0.334079955706623, 0.41024, 1, 1, 1] perl_results = [0.304872297931597, 0.334079955706623, 0.41024, 1, 1, 1]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
input_lists.append(mass)
python_results.append(raghavan2010_binary_fraction(mass)) python_results.append(raghavan2010_binary_fraction(mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
def test_Izzard2012_period_distribution(self): def test_Izzard2012_period_distribution(self):
""" """
...@@ -362,14 +385,18 @@ class TestDistributions(unittest.TestCase): ...@@ -362,14 +385,18 @@ class TestDistributions(unittest.TestCase):
0.0221093965810181, 0.0221093965810181,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
for per in self.per_list: for per in self.per_list:
input_lists.append([mass, per])
python_results.append(Izzard2012_period_distribution(per, mass)) python_results.append(Izzard2012_period_distribution(per, mass))
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass, per: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
def test_flatsections(self): def test_flatsections(self):
""" """
...@@ -385,15 +412,18 @@ class TestDistributions(unittest.TestCase): ...@@ -385,15 +412,18 @@ class TestDistributions(unittest.TestCase):
1.01010101010101, 1.01010101010101,
] ]
python_results = [] python_results = []
input_lists = []
for q in self.q_list: for q in self.q_list:
input_lists.append(q)
python_results.append( python_results.append(
flatsections(q, [{"min": 0.01, "max": 1.0, "height": 1.0}]) flatsections(q, [{"min": 0.01, "max": 1.0, "height": 1.0}])
) )
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for q: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
def test_sana12(self): def test_sana12(self):
""" """
...@@ -619,6 +649,7 @@ class TestDistributions(unittest.TestCase): ...@@ -619,6 +649,7 @@ class TestDistributions(unittest.TestCase):
0.066436408359805, 0.066436408359805,
] ]
python_results = [] python_results = []
input_lists = []
for mass in self.mass_list: for mass in self.mass_list:
for q in self.q_list: for q in self.q_list:
...@@ -628,6 +659,9 @@ class TestDistributions(unittest.TestCase): ...@@ -628,6 +659,9 @@ class TestDistributions(unittest.TestCase):
sep = calc_sep_from_period(mass, mass_2, per) sep = calc_sep_from_period(mass, mass_2, per)
sep_min = calc_sep_from_period(mass, mass_2, 10 ** 0.15) sep_min = calc_sep_from_period(mass, mass_2, 10 ** 0.15)
sep_max = calc_sep_from_period(mass, mass_2, 10 ** 5.5) sep_max = calc_sep_from_period(mass, mass_2, 10 ** 5.5)
input_lists.append([mass, mass_2, per])
python_results.append( python_results.append(
sana12( sana12(
mass, mass_2, sep, per, sep_min, sep_max, 0.15, 5.5, -0.55 mass, mass_2, sep, per, sep_min, sep_max, 0.15, 5.5, -0.55
...@@ -636,8 +670,8 @@ class TestDistributions(unittest.TestCase): ...@@ -636,8 +670,8 @@ class TestDistributions(unittest.TestCase):
# GO over the results and check whether they are equal (within tolerance) # GO over the results and check whether they are equal (within tolerance)
for i in range(len(python_results)): for i in range(len(python_results)):
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance) msg = "Error: Value perl: {} Value python: {} for mass, mass2, per: {}".format(python_results[i], perl_results[i], str(input_lists[i]))
self.assertLess(np.abs(python_results[i] - perl_results[i]), self.tolerance, msg=msg)
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()
binarycpython/utils/grid.py
+ 41
− 29
View file @ 490e28b9
...@@ -843,6 +843,7 @@ class Population: ...@@ -843,6 +843,7 @@ class Population:
""" """
binary_cmdline_string = self._return_argline(full_system_dict) binary_cmdline_string = self._return_argline(full_system_dict)
print(binary_cmdline_string)
persistent_data_memaddr = -1 persistent_data_memaddr = -1
if self.bse_options.get("ensemble", 0) == 1: if self.bse_options.get("ensemble", 0) == 1:
...@@ -884,17 +885,27 @@ class Population: ...@@ -884,17 +885,27 @@ class Population:
ID # Store the ID as a object property again, lets see if that works. ID # Store the ID as a object property again, lets see if that works.
) )
# lets try out making stores for all the grids:
self.grid_options["_store_memaddr"] = _binary_c_bindings.return_store_memaddr()
verbose_print(
"Process {} started at {}.\tUsing store memaddr {}".format(ID, datetime.datetime.now().isoformat(), self.grid_options["_store_memaddr"]), self.grid_options["verbosity"], 0
)
# Set the ensemble memaddr
if self.bse_options.get("ensemble", 0) == 1: if self.bse_options.get("ensemble", 0) == 1:
# set persistent data memaddr if necessary. # set persistent data memaddr if necessary.
persistent_data_memaddr = ( persistent_data_memaddr = (
_binary_c_bindings.return_persistent_data_memaddr() _binary_c_bindings.return_persistent_data_memaddr()
) )
self.persistent_data_memory_dict = { self.persistent_data_memory_dict = {
self.process_ID: persistent_data_memaddr self.process_ID: persistent_data_memaddr
} }
# lets try out making stores for all the grids: verbose_print(
self.grid_options["_store_memaddr"] = _binary_c_bindings.return_store_memaddr() "\tUsing persistent_data memaddr: {}".format(persistent_data_memaddr), self.grid_options["verbosity"], 0
)
# apparently we have to re-load this for every process, otherwise NameErrors arise (seems like a bug but I'm not sure) # apparently we have to re-load this for every process, otherwise NameErrors arise (seems like a bug but I'm not sure)
self._load_grid_function() self._load_grid_function()
...@@ -914,10 +925,6 @@ class Population: ...@@ -914,10 +925,6 @@ class Population:
0 # counter for the actual amt of systems this thread ran 0 # counter for the actual amt of systems this thread ran
) )
verbose_print(
"Process {} started at {}. Using store memaddr {}".format(ID, datetime.datetime.now().isoformat(), self.grid_options["_store_memaddr"]), self.grid_options["verbosity"], 0
)
round_number_mod = 0 # rotating modulo round_number_mod = 0 # rotating modulo
total_time_calling_binary_c = 0 total_time_calling_binary_c = 0
...@@ -931,7 +938,7 @@ class Population: ...@@ -931,7 +938,7 @@ class Population:
system = next(generator) system = next(generator)
# Check if the ID is the correct one for this process # Check if the ID is the correct one for this process
if (localcounter + (ID+round_number_mod)) % self.grid_options["amt_cores"] == 0: if (localcounter + (ID + round_number_mod)) % self.grid_options["amt_cores"] == 0:
# Combine that with the other settings # Combine that with the other settings
full_system_dict = self.bse_options.copy() full_system_dict = self.bse_options.copy()
...@@ -975,7 +982,7 @@ class Population: ...@@ -975,7 +982,7 @@ class Population:
if (localcounter+1)%self.grid_options["amt_cores"]==0: if (localcounter+1)%self.grid_options["amt_cores"]==0:
round_number_mod += 1 round_number_mod += 1
# round_number_mod = (localcounter+1)%self.grid_options["amt_cores"]
# print("thread {} round_nr_mod {}. localcounter {}".format(ID, round_number_mod, localcounter)) # print("thread {} round_nr_mod {}. localcounter {}".format(ID, round_number_mod, localcounter))
# Has to be here because this one is used for the (localcounter+ID) % (self..) # Has to be here because this one is used for the (localcounter+ID) % (self..)
...@@ -984,14 +991,26 @@ class Population: ...@@ -984,14 +991,26 @@ class Population:
# Handle ensemble output: is ensemble==1, then either directly write that data to a file, or combine everything into 1 file. # Handle ensemble output: is ensemble==1, then either directly write that data to a file, or combine everything into 1 file.
ensemble_json = {} # Make sure it exists already ensemble_json = {} # Make sure it exists already
if self.bse_options.get("ensemble", 0) == 1: if self.bse_options.get("ensemble", 0) == 1:
verbose_print(
"Process {}: is freeing ensemble output (using persisten_data memaddr {})".format(ID, self.persistent_data_memory_dict[self.process_ID]), self.grid_options["verbosity"], 2
)
ensemble_raw_output = ( ensemble_raw_output = (
_binary_c_bindings.free_persistent_data_memaddr_and_return_json_output( _binary_c_bindings.free_persistent_data_memaddr_and_return_json_output(
self.persistent_data_memory_dict[self.process_ID] self.persistent_data_memory_dict[self.process_ID]
) )
) )
if ensemble_raw_output == None:
verbose_print(
"Process {}: Warning! Ensemble output is empty. ".format(ID), self.grid_options["verbosity"], 2
)
# #
if self.grid_options["combine_ensemble_with_thread_joining"] == True: if self.grid_options["combine_ensemble_with_thread_joining"] == True:
verbose_print(
"Process {}: Extracting ensemble info from raw string".format(ID), self.grid_options["verbosity"], 2
)
ensemble_json = extract_ensemble_json_from_string( ensemble_json = extract_ensemble_json_from_string(
ensemble_raw_output ensemble_raw_output
) # Load this into a dict so that we can combine it later ) # Load this into a dict so that we can combine it later
...@@ -1004,16 +1023,17 @@ class Population: ...@@ -1004,16 +1023,17 @@ class Population:
self.grid_options["_population_id"], self.process_ID self.grid_options["_population_id"], self.process_ID
), ),
) )
print(
"Thread {}: Chosen to output the ensemble results directly to file: {}".format(
self.process_ID, output_file
)
)
# Write to file # Write to file
with open(output_file, "w") as f: with open(output_file, "w") as f:
f.write(ensemble_raw_output) f.write(ensemble_raw_output)
print(
"Thread {}: Wrote ensemble results directly to file: {}".format(
self.process_ID, output_file
)
)
# free store mem: # free store mem:
_binary_c_bindings.free_store_memaddr(self.grid_options["_store_memaddr"]) _binary_c_bindings.free_store_memaddr(self.grid_options["_store_memaddr"])
...@@ -1124,7 +1144,7 @@ class Population: ...@@ -1124,7 +1144,7 @@ class Population:
### ensemble: make some checks for this ### ensemble: make some checks for this
## check the settings and set all the warnings. ## check the settings and set all the warnings.
if self.bse_options.get("ensemble", None): if self.bse_options.get("ensemble", None):
if not self.bse_options["ensemble_defer"] == 1: if not self.bse_options.get("ensemble_defer", 0) == 1:
verbose_print( verbose_print(
"Error, if you want to run an ensemble in a population, the output needs to be deferred. Please set 'ensemble_defer' to 1", "Error, if you want to run an ensemble in a population, the output needs to be deferred. Please set 'ensemble_defer' to 1",
self.grid_options["verbosity"], self.grid_options["verbosity"],
...@@ -1132,31 +1152,22 @@ class Population: ...@@ -1132,31 +1152,22 @@ class Population:
) )
raise ValueError raise ValueError
if not self.custom_options["ensemble_output_name"]: if not any(
[key.startswith("ensemble_filter_") for key in self.bse_options]
):
verbose_print( verbose_print(
"Error: if you want to run an ensemble in a population, please set set 'ensemble_output_name'. It will be combined with 'data_dir' to write the output of the ensembles to", "Warning: Running the ensemble without any filter requires alot of available RAM",
self.grid_options["verbosity"], self.grid_options["verbosity"],
0, 0,
) )
raise ValueError
if not any( if self.bse_options.get("ensemble_filters_off", 0) != 1:
[key.startswith("ensemble_filter_") for key in self.bse_options]
):
verbose_print( verbose_print(
"Warning: Running the ensemble without any filter requires alot of available RAM", "Warning: Running the ensemble without any filter requires alot of available RAM",
self.grid_options["verbosity"], self.grid_options["verbosity"],
0, 0,
) )
if self.bse_options.get("ensemble_filters_off", None):
if self.bse_options["ensemble_filters_off"] == 0:
verbose_print(
"Warning: Running the ensemble without any filter requires alot of available RAM",
self.grid_options["verbosity"],
0,
)
if self.grid_options["combine_ensemble_with_thread_joining"] == False: if self.grid_options["combine_ensemble_with_thread_joining"] == False:
if not self.custom_options.get("data_dir", None): if not self.custom_options.get("data_dir", None):
verbose_print( verbose_print(
...@@ -1164,6 +1175,7 @@ class Population: ...@@ -1164,6 +1175,7 @@ class Population:
self.grid_options["verbosity"], self.grid_options["verbosity"],
0, 0,
) )
raise ValueError
# Check which type of population generation # Check which type of population generation
if self.grid_options["evolution_type"] == "grid": if self.grid_options["evolution_type"] == "grid":
...@@ -2383,7 +2395,7 @@ class Population: ...@@ -2383,7 +2395,7 @@ class Population:
## check the settings: ## check the settings:
if self.bse_options.get("ensemble", None): if self.bse_options.get("ensemble", None):
if self.bse_options["ensemble"] == 1: if self.bse_options["ensemble"] == 1:
if not self.bse_options["ensemble_defer"] == 1: if not self.bse_options.get("ensemble_defer", 0) == 1:
verbose_print( verbose_print(
"Error, if you want to run an ensemble in a population, the output needs to be deferred", "Error, if you want to run an ensemble in a population, the output needs to be deferred",
self.grid_options["verbosity"], self.grid_options["verbosity"],
......
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