Population class extension: sampling variables functions module

Main script to provide the sampling variable class extension. Here the sampling variable codebase is defined.

class binarycpython.utils.population_extensions.sampling_variables.sampling_variables(**kwargs)

Bases: object

Extension for the Population class containing the code for the sampling variable.

add_grid_variable(name, parameter_name, longname, valuerange, samplerfunc, probdist, dphasevol=- 1, gridtype='centred', branchpoint=0, branchcode=None, precode=None, postcode=None, topcode=None, bottomcode=None, condition=None, dry_parallel=False)

NOTE: this function exists for backward compatability with older scripts. Please use add_sampling_variable from now on.

Function to add sampling variables to the population_options. Calls add_sampling_variable().

The execution of the sampling generation will be through a nested for loop. Each of the grid variables will get create a deeper for loop.

The real function that generates the numbers will get written to a new file in the TMP_DIR, and then loaded imported and evaluated. beware that if you insert some destructive piece of code, it will be executed anyway. Use at own risk.

Parameters

• name (str) –

  name of parameter used in the grid Python code. This is evaluated as a parameter and you can use it throughout the rest of the function

  Examples:

  name = 'lnM_1'
  

• parameter_name (str) –

  name of the parameter in binary_c

  This name must correspond to a Python variable of the same name, which is automatic if parameter_name == name.

  Note: if parameter_name != name, you must set a

  variable in “precode” or “postcode” to define a Python variable called parameter_name

• longname (str) –

  Long name of parameter

  Examples:

  longname = 'Primary mass'
  

• range –

  Range of values to take. Does not get used really, the samplerfunc is used to get the values from

  Examples:

  range = [math.log(m_min), math.log(m_max)]
  

• samplerfunc (str) –

  Function returning a list or numpy array of samples spaced appropriately. You can either use a real function, or a string representation of a function call.

  Examples:

  samplerfunc = "self.const_linear(math.log(m_min), math.log(m_max), {})".format(resolution['M_1'])
  

• precode (Optional[str]) –

  Extra room for some code. This code will be evaluated within the loop of the sampling function (i.e. a value for lnM_1 is chosen already)

  Examples:

  precode = 'M_1=math.exp(lnM_1);'
  

• postcode (Optional[str]) – Code executed after the probability is calculated.

• probdist (str) –

  Function determining the probability that gets assigned to the sampled parameter

  Examples:

  probdist = 'self.Kroupa2001(M_1)*M_1'
  

• dphasevol (Union[str, int]) –

  part of the parameter space that the total probability is calculated with. Put to -1 if you want to ignore any dphasevol calculations and set the value to 1

  Examples:

  dphasevol = 'dlnM_1'
  

• condition (Optional[str]) –

  condition that has to be met in order for the grid generation to continue

  Examples:

  condition = "self.population_options['binary']==1"
  

• gridtype (str) – Method on how the value range is sampled. Can be either ‘edge’ (steps starting at the lower edge of the value range) or ‘centred’ (steps starting at lower edge + 0.5 * stepsize).

• dry_parallel (Optional[bool]) – If True, try to parallelize this variable in dry runs.

• topcode (Optional[str]) – Code added at the very top of the block.

• bottomcode (Optional[str]) – Code added at the very bottom of the block.

Return type

None

add_sampling_variable(name, parameter_name, longname, valuerange, samplerfunc, probdist, dphasevol=- 1, gridtype='centred', branchpoint=0, branchcode=None, precode=None, postcode=None, topcode=None, bottomcode=None, condition=None, dry_parallel=False, dependency_variables=None)

Function to add sampling variables to the population_options.

The execution of the sampling generation will be through a nested for loop. Each of the grid variables will get create a deeper for loop.

The real function that generates the numbers will get written to a new file in the TMP_DIR, and then loaded imported and evaluated. beware that if you insert some destructive piece of code, it will be executed anyway. Use at own risk.

Parameters

• name (str) –

  name of parameter used in the grid Python code. This is evaluated as a parameter and you can use it throughout the rest of the function

  Examples:

  name = 'lnM_1'
  

• parameter_name (str) –

  name of the parameter in binary_c

  This name must correspond to a Python variable of the same name, which is automatic if parameter_name == name.

  Note: if parameter_name != name, you must set a

  variable in “precode” or “postcode” to define a Python variable called parameter_name

• longname (str) –

  Long name of parameter

  Examples:

  longname = 'Primary mass'
  

• range –

  Range of values to take. Does not get used really, the samplerfunc is used to get the values from

  Examples:

  range = [math.log(m_min), math.log(m_max)]
  

• samplerfunc (str) –

  Function returning a list or numpy array of samples spaced appropriately. You can either use a real function, or a string representation of a function call.

  Examples:

  samplerfunc = "self.const_linear(math.log(m_min), math.log(m_max), {})".format(resolution['M_1'])
  

• precode (Optional[str]) –

  Extra room for some code. This code will be evaluated within the loop of the sampling function (i.e. a value for lnM_1 is chosen already)

  Examples:

  precode = 'M_1=math.exp(lnM_1);'
  

• postcode (Optional[str]) – Code executed after the probability is calculated.

• probdist (str) –

  Function determining the probability that gets assigned to the sampled parameter

  Examples:

  probdist = 'self.Kroupa2001(M_1)*M_1'
  

• dphasevol (Union[str, int]) –

  part of the parameter space that the total probability is calculated with. Put to -1 if you want to ignore any dphasevol calculations and set the value to 1

  Examples:

  dphasevol = 'dlnM_1'
  

• condition (Optional[str]) –

  condition that has to be met in order for the grid generation to continue

  Examples:

  condition = "self.population_options['binary']==1"
  

• gridtype (str) – Method on how the value range is sampled. Can be either ‘edge’ (steps starting at the lower edge of the value range) or ‘centred’ (steps starting at lower edge + 0.5 * stepsize).

• dry_parallel (Optional[bool]) – If True, try to parallelize this variable in dry runs.

• topcode (Optional[str]) – Code added at the very top of the block.

• bottomcode (Optional[str]) – Code added at the very bottom of the block.

• dependency_variables (Optional[list]) – TODO: describe

Return type

None

delete_grid_variable(name)

NOTE: this function exists for backward compatability with older scripts. Please use delete_sampling_variable from now on.

Function to delete a sampling variable with the given name. Calls delete_sampling_variable()

Parameters

name (str) – name of the sampling variable to be deleted.

Return type

None

delete_sampling_variable(name)

Function to delete a sampling variable with the given name.

Parameters

name (str) – name of the sampling variable to be deleted.

Return type

None

rename_grid_variable(oldname, newname)

NOTE: this function exists for backward compatability with older scripts. Please use rename_sampling_variable from now on.

Function to rename a sampling variable. Calls rename_sampling_variable()

note: this does NOT alter the order of the self.population_options[“_sampling_variables”] dictionary.

The order in which the sampling variables are loaded into the grid is based on their sampling_variable_number property

Parameters

• oldname (str) – old name of the sampling variable

• newname (str) – new name of the sampling variable

Return type

None

rename_sampling_variable(oldname, newname)

Function to rename a sampling variable.

note: this does NOT alter the order of the self.population_options[“_sampling_variables”] dictionary.

The order in which the sampling variables are loaded into the grid is based on their sampling_variable_number property

Parameters

• oldname (str) – old name of the sampling variable

• newname (str) – new name of the sampling variable

Return type

None

update_grid_variable(name, **kwargs)

NOTE: this function exists for backward compatability with older scripts. Please use update_sampling_variable from now on.

Function to update the values of a sampling variable. Calls update_sampling_variable().

Parameters

• name (str) – name of the grid variable to be changed.

• **kwargs – key-value pairs to override the existing grid variable data. See add_sampling_variable for these names.

Return type

None

update_sampling_variable(name, **kwargs)

Function to update the values of a sampling variable.

Parameters

• name (str) – name of the grid variable to be changed.

• **kwargs – key-value pairs to override the existing grid variable data. See add_sampling_variable for these names.

Return type

None