diff --git a/binarycpython/utils/distribution_functions.py b/binarycpython/utils/distribution_functions.py
index bc0eb313eeba67a94227cabd5ec025352a6b467d..caf505f5951662ce579fe771e694c48bd3f88dbe 100644
--- a/binarycpython/utils/distribution_functions.py
+++ b/binarycpython/utils/distribution_functions.py
@@ -20,6 +20,7 @@ Tasks:
- TODO: make an n-part power law that's general enough to fix the three part and the 4 part
"""
+import functools
import math
import json
@@ -134,7 +135,7 @@ def const(
prob = 1.0 / (max_bound - min_bound)
return prob
-
+@functools.lru_cache(maxsize=16)
def powerlaw_constant(
min_val: Union[int, float], max_val: Union[int, float], k: Union[int, float]
) -> Union[int, float]:
@@ -202,7 +203,7 @@ def powerlaw(
# )
return prob
-
+@functools.lru_cache(maxsize=16)
def calculate_constants_three_part_powerlaw(
m0: Union[int, float],
m1: Union[int, float],
@@ -322,7 +323,7 @@ def three_part_powerlaw(
return prob
-
+@functools.lru_cache(maxsize=16)
def gaussian_normalizing_const(
mean: Union[int, float],
sigma: Union[int, float],
@@ -718,7 +719,7 @@ def sana12(
"""
res = 0
- if (M1 < 15) or (M2 / M1 < 0.1):
+ if (M1 < 15.0) or (M2 / M1 < 0.1):
res = 1.0 / (math.log(amax) - math.log(amin))
else:
p1 = 1.0 + p
diff --git a/binarycpython/utils/grid.py b/binarycpython/utils/grid.py
index 81ae2cae7534198a9f8cbeaf123b4f2a905b0b57..37e0bf0b9bf197e491472883b612fa5030f87a0b 100644
--- a/binarycpython/utils/grid.py
+++ b/binarycpython/utils/grid.py
@@ -340,10 +340,10 @@ class Population:
parameter, type(value), type(old_value)
),
self.grid_options["verbosity"],
- 1,
+ 2,
)
value = type(old_value)(value)
- verbose_print("Success!", self.grid_options["verbosity"], 1)
+ verbose_print("Success!", self.grid_options["verbosity"], 2)
except ValueError:
verbose_print(
@@ -1109,7 +1109,7 @@ class Population:
verbose_print(
"Queue produced system {}".format(system_number),
self.grid_options["verbosity"],
- 2,
+ 3,
)
# Print current size
@@ -1279,6 +1279,10 @@ class Population:
persistent_data_memaddr = self.persistent_data_memory_dict[self.process_ID]
# print("thread {}: persistent_data_memaddr: ".format(self.process_ID), persistent_data_memaddr)
+ # vb2 logging
+ if self.grid_options['verbosity'] >= 2:
+ self.vb2print(full_system_dict,binary_cmdline_string)
+
# Get results binary_c
# print("running: {}".format(binary_cmdline_string))
out = _binary_c_bindings.run_system(
@@ -1511,16 +1515,17 @@ class Population:
# In some cases, the whole run crashes. To be able to figure out which system
# that was on, we log each current system to a file (each thread has one).
# Each new system overrides the previous
- with open(
- os.path.join(
- self.grid_options["tmp_dir"],
- "current_system",
- "process_{}.txt".format(self.process_ID),
- ),
- "w",
- ) as f:
- binary_cmdline_string = self._return_argline(full_system_dict)
- f.write(binary_cmdline_string)
+ if self.grid_options["log_args"]:
+ with open(
+ os.path.join(
+ self.grid_options["log_args_dir"],
+ "current_system",
+ "process_{}.txt".format(self.process_ID),
+ ),
+ "w",
+ ) as f:
+ binary_cmdline_string = self._return_argline(full_system_dict)
+ f.write(binary_cmdline_string)
##############
# Running the system
@@ -1613,7 +1618,7 @@ class Population:
ID, self.persistent_data_memory_dict[self.process_ID]
),
self.grid_options["verbosity"],
- 2,
+ 3,
)
ensemble_raw_output = (
@@ -1633,7 +1638,7 @@ class Population:
verbose_print(
"Process {}: Extracting ensemble info from raw string".format(ID),
self.grid_options["verbosity"],
- 2,
+ 3,
)
ensemble_json["ensemble"] = extract_ensemble_json_from_string(
@@ -2160,7 +2165,10 @@ class Population:
key=lambda x: x[1]["grid_variable_number"],
)
):
- print("Constructing/adding: {}".format(grid_variable_el[0]))
+ verbose_print(
+ "Constructing/adding: {}".format(grid_variable_el[0]),
+ self.grid_options['verbosity'],
+ 2)
grid_variable = grid_variable_el[1]
#########################
@@ -2357,16 +2365,21 @@ class Population:
)
# Add condition failed action:
- self._add_code(
- 'print("Grid generator: Condition for {} not met!")'.format(
- grid_variable["parameter_name"]
+ if self.grid_options['verbosity'] >= 3:
+ self._add_code(
+ 'print("Grid generator: Condition for {} not met!")'.format(
+ grid_variable["parameter_name"]
+ )
+ + "\n",
+ "continue" + "\n",
+ mindent=1,
)
- + "\n",
- "continue" + "\n",
- mindent=1,
- )
-
- # Add some white line
+ else:
+ self._add_code(
+ "continue" + "\n",
+ mindent=1,
+ )
+ # Add some whitespace
self._add_code("\n")
# # Add debugging:
@@ -2533,8 +2546,7 @@ class Population:
self._increment_indent_depth(+1)
self._add_code("\n", "#" * 40 + "\n", "if print_results:\n")
self._add_code(
- "print('Grid has handled {} stars'.format(_total_starcount))\n",
- "print('with a total probability of {}'.format(self.grid_options['_probtot']))\n",
+ "print('Grid has handled {} stars with a total probability of {}'.format(_total_starcount,self.grid_options['_probtot']))\n",
mindent=1,
)
@@ -3567,9 +3579,9 @@ class Population:
f.write(argstring + "\n")
else:
verbose_print(
- "binary_c had 0 output. Which is strange. Make sure you mean to do this. If there is actually ensemble output being generated then its fine.",
+ "binary_c output nothing - this is strange. If there is ensemble output being generated then this is fine.",
self.grid_options["verbosity"],
- 2,
+ 3,
)
def set_moe_di_stefano_settings(self, options=None):
@@ -4348,7 +4360,7 @@ eccentricity3=0
verbose_print(
"_calculate_multiplicity_fraction: Chosen not to use any multiplicity fraction.",
self.grid_options["verbosity"],
- 2,
+ 3,
)
return 1
@@ -4364,7 +4376,7 @@ eccentricity3=0
verbose_print(
"_calculate_multiplicity_fraction: Using Arenou 2010 to calculate multiplicity fractions",
self.grid_options["verbosity"],
- 2,
+ 3,
)
binary_fraction = Arenou2010_binary_fraction(system_dict["M_1"])
@@ -4380,7 +4392,7 @@ eccentricity3=0
verbose_print(
"_calculate_multiplicity_fraction: Using Rhagavan 2010 to calculate multiplicity fractions",
self.grid_options["verbosity"],
- 2,
+ 3,
)
binary_fraction = raghavan2010_binary_fraction(system_dict["M_1"])
@@ -4406,7 +4418,7 @@ eccentricity3=0
verbose_print(
"_calculate_multiplicity_fraction: Moecache is empty. It needs to be filled with the data for the interpolators. Loading the data now",
self.grid_options["verbosity"],
- 2,
+ 3,
)
# Load the data
@@ -4443,7 +4455,7 @@ eccentricity3=0
multiplicity_fraction_dict[system_dict["multiplicity"]],
),
self.grid_options["verbosity"],
- 2,
+ 3,
)
return multiplicity_fraction_dict[system_dict["multiplicity"]]
@@ -4553,3 +4565,10 @@ eccentricity3=0
self.grid_options["verbosity"],
1,
)
+
+ def vb2print(self, system_dict, cmdline_string):
+ print("Running this system now on thread {ID}\n{blue}{cmdline}{reset}\n".format(
+ ID=self.process_ID,
+ blue=self.ANSI_colours["blue"],
+ cmdline=cmdline_string,
+ reset=self.ANSI_colours["reset"]))
diff --git a/binarycpython/utils/spacing_functions.py b/binarycpython/utils/spacing_functions.py
index 3eae711f1317b9bd95f1d55f9cea4d33720c550e..4ef7271526c0cd48eecb52ce38e60d5948acd7ac 100644
--- a/binarycpython/utils/spacing_functions.py
+++ b/binarycpython/utils/spacing_functions.py
@@ -14,7 +14,7 @@ import sys
from binarycpython.utils.grid import Population
-@functools.lru_cache(maxsize=128)
+@functools.lru_cache(maxsize=16)
def const(
min_bound: Union[int, float], max_bound: Union[int, float], steps: int
) -> list:
@@ -29,12 +29,38 @@ def const(
Returns:
np.linspace(min_bound, max_bound, steps+1)
"""
-
return np.linspace(min_bound, max_bound, steps + 1)
+############################################################
+@functools.lru_cache(maxsize=16)
+def const_ranges(ranges) -> list:
+ """
+ Samples a series of ranges linearly.
+
+ Args:
+ ranges: a tuple of tuples passed to the const() spacing function.
+
+ Returns:
+ numpy array of masses
+
+ Example:
+ The following allocates 10 stars between 0.1 and 0.65, 20 stars between 0.65
+ and 0.85, and 10 stars between 0.85 and 10.0 Msun.
+
+ spacingfunc="const_ranges((({},{},{}),({},{},{}),({},{},{})))".format(
+ 0.1,0.65,10,
+ 0.65,0.85,20,
+ 0.85,10.0,10
+ ),
+
+ """
+
+ masses = np.empty(0)
+ for range in ranges:
+ masses = np.append(masses,const(*range))
+ return np.unique(masses)
############################################################
-@functools.lru_cache(maxsize=128)
def peak_normalized_gaussian_func(
x: Union[int, float], mean: Union[int, float], sigma: Union[int, float]
) -> Union[int, float]:
@@ -59,7 +85,7 @@ def peak_normalized_gaussian_func(
############################################################
-@functools.lru_cache(maxsize=128)
+@functools.lru_cache(maxsize=16)
def gaussian_zoom(
min_bound: Union[int, float],
max_bound: Union[int, float],
@@ -102,9 +128,9 @@ def gaussian_zoom(
if array[-1] != max_bound:
array[-1] = max_bound
- return array
+ return np.unique(array)
-@functools.lru_cache(maxsize=128)
+@functools.lru_cache(maxsize=16)
def const_dt(self,
dt=1000.0,
dlogt=0.1,
@@ -226,7 +252,6 @@ def const_dt(self,
time = lifetime_population.grid_results['interpolation table m->t'][mass]
data_table_mass_time.append( [ mass, time ] )
-
# set up interpolators
interpolator_time_mass = py_rinterpolate.Rinterpolate(
table = data_table_time_mass,
@@ -329,4 +354,4 @@ def const_dt(self,
logtwas = logt
# return the mass list as a numpy array
- return np.array(mass_list)
+ return np.unique(np.array(mass_list))