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Commit c48d8f23 authored by Theo Steininger's avatar Theo Steininger
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First running version of HammurapyBase.

parent 31330874
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Showing with 268 additions and 162 deletions
imagine/__init__.py
View file @ c48d8f23
......@@ -7,3 +7,6 @@ from observers import *
from priors import *
from pipeline import Pipeline
import nifty
nifty.nifty_configuration['default_distribution_strategy'] = 'equal'
imagine/observers/hammurapy/__init__.py
View file @ c48d8f23
# -*- coding: utf-8 -*-
from mixins import *
from hammurapy_base import HammurapyBase
imagine/observers/hammurapy/hammurapy_base.py
View file @ c48d8f23
......@@ -3,31 +3,25 @@
import abc
import os
import tempfile
import subprocess
import healpy
import numpy as np
from nifty import Field, FieldArray, HPSpace
from d2o import distributed_data_object
from imagine.magnetic_fields.magnetic_field import MagneticField
from imagine.observers.observer import Observer
class HammurapyBase(Observer):
def __init__(self, hammurabi_executable, conf_directory='./confs',
working_directory='.'):
working_directory_base='.'):
self.hammurabi_executable = os.path.abspath(hammurabi_executable)
self.conf_directory = os.path.abspath(conf_directory)
self.working_directory = os.path.abspath(working_directory)
self.working_directory_base = os.path.abspath(working_directory_base)
self.last_call_log = ""
self.do_sync_emission = True
self.do_rm = True
self.do_dm = False
self.do_dust = False
self.do_tau = False
self.do_ff = False
self.basic_parameters = {'obs_shell_index_numb': '1',
'total_shell_numb': '1',
'obs_NSIDE': '128',
......@@ -41,6 +35,12 @@ class HammurapyBase(Observer):
'TE_nz': '80',
'B_field_do_random': 'T',
'B_ran_mem_lim': '4',
'do_sync_emission': 'F',
'do_rm': 'F',
'do_dm': 'F',
'do_dust': 'F',
'do_tau': 'F',
'do_ff': 'F',
}
@abc.abstractproperty
......@@ -48,145 +48,23 @@ class HammurapyBase(Observer):
return object
def _make_temp_folder(self):
prefix = os.path.join(self.working_directory, 'temp_hammurabi_')
prefix = os.path.join(self.working_directory_base, 'temp_hammurabi_')
return tempfile.mkdtemp(prefix=prefix)
def __call__(self, magnetic_field):
ensemble_number = magnetic_field.shape[0]
ensemble_space = magnetic_field.domain[0]
hp128 = HPSpace(nside=128)
result_observable = {}
if self.do_sync_emission:
result_observable['sync_emission'] = \
Field(domain=(ensemble_space, hp128, FieldArray((3,))))
if self.do_rm:
result_observable['rm'] = Field(domain=(ensemble_space, hp128))
if self.do_dm:
result_observable['dm'] = Field(domain=(hp128,))
if self.do_dust:
result_observable['dust'] = \
Field(domain=(ensemble_space, hp128, FieldArray((3,))))
if self.do_tau:
result_observable['tau'] = Field(domain=(ensemble_space, hp128,))
if self.do_ff:
result_observable['ff'] = Field(domain=(ensemble_space, hp128,))
# create dictionary for parameter file
# iterate over ensemble and put result into result_observable
###########
def _make_parameter_file(self, working_directory, resolution, dimensions,
custom_parameters={}):
# setup the default parameters
parameters_dict = {'B_field_lx': dimensions[0],
'B_field_ly': dimensions[1],
'B_field_lz': dimensions[2],
'B_field_nx': int(resolution[0]),
'B_field_ny': int(resolution[1]),
'B_field_nz': int(resolution[2]),
}
{
'do_sync_emission': 'T',
'do_rm': 'T',
'do_dm': 'F',
'do_dust': 'F',
'do_tau': 'F',
'do_ff': 'F'}
if self.parameters_dict['do_sync_emission'] == 'T':
obs_sync_file_name = os.path.join(working_directory,
'IQU_sync.fits')
parameters_dict['obs_file_name'] = obs_sync_file_name
if self.parameters_dict['do_rm'] == 'T':
obs_RM_file_name = os.path.join(working_directory, 'rm.fits')
parameters_dict['obs_RM_file_name'] = obs_RM_file_name
if self.parameters_dict['do_dm'] == 'T':
obs_DM_file_name = os.path.join(working_directory,
'dm.fits')
parameters_dict['obs_DM_file_name'] = obs_DM_file_name
if self.parameters_dict['do_dust'] == 'T':
obs_dust_file_name = os.path.join(working_directory,
'IQU_dust.fits')
parameters_dict['obs_dust_file_name'] = obs_dust_file_name
if self.parameters_dict['do_tau'] == 'T':
obs_tau_file_name = os.path.join(working_directory,
'tau.fits')
parameters_dict['obs_tau_file_name'] = obs_tau_file_name
if self.parameters_dict['do_ff'] == 'T':
obs_ff_file_name = os.path.join(working_directory,
'free.fits')
parameters_dict['obs_ff_file_name'] = obs_ff_file_name
# ammend the parameters_dict
parameters_dict.update(self.parameters_dict)
# add custom parameters
parameters_dict.update(custom_parameters)
parameters_string = ''
for item in parameters_dict:
parameters_string += item + '=' + str(parameters_dict[item]) + '\n'
parameters_file_path = os.path.join(working_directory,
'parameters.txt')
with open(parameters_file_path, 'wb') as config_file:
config_file.write(parameters_string)
def _build_observables(self, temp_folder):
observables = {}
if self.parameters_dict['do_sync_emission'] == 'T':
[sync_I, sync_Q, sync_U] = self._read_fits_file(temp_folder,
'IQU_sync.fits')
logger.debug('Read the sync_map')
observables['sync_observable'] = {'sync_I': sync_I,
'sync_Q': sync_Q,
'sync_U': sync_U}
if self.parameters_dict['do_rm'] == 'T':
[rm_map] = self._read_fits_file(temp_folder, 'rm.fits')
logger.debug('Read the rm_map')
observables['rm_observable'] = {'rm_map': rm_map}
if self.parameters_dict['do_dm'] == 'T':
[dm_map] = self._read_fits_file(temp_folder, 'dm.fits')
logger.debug('Read the dm_map')
observables['dm_observable'] = {'dm_map': dm_map}
if self.parameters_dict['do_dust'] == 'T':
[dust_I, dust_Q, dust_U] = self._read_fits_file(temp_folder,
'IQU_dust.fits')
logger.debug('Read the dust_map')
observables['dust_observable'] = {'dust_I': dust_I,
'dust_Q': dust_Q,
'dust_U': dust_U}
if self.parameters_dict['do_tau'] == 'T':
[tau_map] = self._read_fits_file(temp_folder, 'tau.fits')
logger.debug('Read the tau_map')
observables['tau_observable'] = {'tau_map': tau_map}
if self.parameters_dict['do_ff'] == 'T':
[ff_map] = self._read_fits_file(temp_folder, 'free.fits')
logger.debug('Read the ff_map')
observables['ff_observable'] = {'ff_map': ff_map}
return observables
def _remove_folder(self, path):
# Try multiple times in order to overcome 'Directory not empty' errors
# Hopefully open file handles get closed in the meantime
n = 0
while n < 10:
temp_process = subprocess.Popen(['rm', '-rf', path],
stderr=subprocess.PIPE)
# wait until process is finished
errlog = temp_process.communicate()[1]
# check if there were some errors
if errlog == '':
break
else:
self.logger.warning('Could not delete %s' % path)
def _read_fits_file(self, path, name):
map_path = os.path.join(path, name)
......@@ -211,18 +89,196 @@ class HammurapyBase(Observer):
cwd=self.conf_directory)
self.last_call_log = temp_process.communicate()[0]
def _initialize_observable_dict(self, observable_dict, magnetic_field):
pass
def _remove_folder(self, path):
# Try multiple times in order to overcome 'Directory not empty' errors
# Hopefully open file handles get closed in the meantime
n = 0
while n < 10:
temp_process = subprocess.Popen(['rm', '-rf', path],
stderr=subprocess.PIPE)
# wait until process is finished
errlog = temp_process.communicate()[1]
# check if there were some errors
if errlog == '':
break
else:
logger.warning('Could not delete %s', path)
\ No newline at end of file
def _build_parameter_dict(self, parameter_dict, magnetic_field,
working_directory, local_ensemble_index):
grid_space = magnetic_field.domain[1]
lx, ly, lz = np.array(grid_space.shape)*np.array(grid_space.distances)
nx, ny, nz = grid_space.shape
parameter_dict.update({'B_field_lx': lx,
'B_field_ly': ly,
'B_field_lz': lz,
'B_field_nx': nx,
'B_field_ny': ny,
'B_field_nz': nz,
})
def _write_parameter_dict(self, parameter_dict, working_directory):
parameters_string = ''
for item in parameter_dict:
parameters_string += item + '=' + str(parameter_dict[item]) + '\n'
parameters_file_path = os.path.join(working_directory,
'parameters.txt')
with open(parameters_file_path, 'wb') as config_file:
config_file.write(parameters_string)
def _fill_observable_dict(self, observable_dict, working_directory,
ensemble_index):
return observable_dict
def __call__(self, magnetic_field):
observable_dict = {}
self._initialize_observable_dict(observable_dict=observable_dict,
magnetic_field=magnetic_field)
# iterate over ensemble and put result into result_observable
# get the local shape by creating a dummy d2o
ensemble_number = magnetic_field.shape[0]
dummy = distributed_data_object(global_shape=(ensemble_number,),
distribution_strategy='equal')
local_length = dummy.distributor.local_length
for local_ensemble_index in xrange(local_length):
# create a temporary folder
working_directory = self._make_temp_folder()
# create dictionary for parameter file
parameter_dict = self.basic_parameters.copy()
self._build_parameter_dict(
parameter_dict=parameter_dict,
magnetic_field=magnetic_field,
working_directory=working_directory,
local_ensemble_index=local_ensemble_index)
self._write_parameter_dict(parameter_dict=parameter_dict,
working_directory=working_directory)
self._call_hammurabi(working_directory)
self._fill_observable_dict(observable_dict,
working_directory,
local_ensemble_index)
self._remove_folder(working_directory)
return observable_dict
###########
# def _make_parameter_file(self, working_directory, resolution, dimensions,
# custom_parameters={}):
#
# # setup the default parameters
# parameters_dict = {'B_field_lx': dimensions[0],
# 'B_field_ly': dimensions[1],
# 'B_field_lz': dimensions[2],
# 'B_field_nx': int(resolution[0]),
# 'B_field_ny': int(resolution[1]),
# 'B_field_nz': int(resolution[2]),
# }
#
# {
# 'do_sync_emission': 'T',
# 'do_rm': 'T',
# 'do_dm': 'F',
# 'do_dust': 'F',
# 'do_tau': 'F',
# 'do_ff': 'F'}
#
# if self.parameters_dict['do_sync_emission'] == 'T':
# obs_sync_file_name = os.path.join(working_directory,
# 'IQU_sync.fits')
# parameters_dict['obs_file_name'] = obs_sync_file_name
#
# if self.parameters_dict['do_rm'] == 'T':
# obs_RM_file_name = os.path.join(working_directory, 'rm.fits')
# parameters_dict['obs_RM_file_name'] = obs_RM_file_name
#
# if self.parameters_dict['do_dm'] == 'T':
# obs_DM_file_name = os.path.join(working_directory,
# 'dm.fits')
# parameters_dict['obs_DM_file_name'] = obs_DM_file_name
#
# if self.parameters_dict['do_dust'] == 'T':
# obs_dust_file_name = os.path.join(working_directory,
# 'IQU_dust.fits')
# parameters_dict['obs_dust_file_name'] = obs_dust_file_name
#
# if self.parameters_dict['do_tau'] == 'T':
# obs_tau_file_name = os.path.join(working_directory,
# 'tau.fits')
# parameters_dict['obs_tau_file_name'] = obs_tau_file_name
#
# if self.parameters_dict['do_ff'] == 'T':
# obs_ff_file_name = os.path.join(working_directory,
# 'free.fits')
# parameters_dict['obs_ff_file_name'] = obs_ff_file_name
#
# # ammend the parameters_dict
# parameters_dict.update(self.parameters_dict)
#
# # add custom parameters
# parameters_dict.update(custom_parameters)
#
# parameters_string = ''
# for item in parameters_dict:
# parameters_string += item + '=' + str(parameters_dict[item]) + '\n'
#
# parameters_file_path = os.path.join(working_directory,
# 'parameters.txt')
# with open(parameters_file_path, 'wb') as config_file:
# config_file.write(parameters_string)
#
#
#
#
# def _build_observables(self, temp_folder):
# observables = {}
# if self.parameters_dict['do_sync_emission'] == 'T':
# [sync_I, sync_Q, sync_U] = self._read_fits_file(temp_folder,
# 'IQU_sync.fits')
# logger.debug('Read the sync_map')
# observables['sync_observable'] = {'sync_I': sync_I,
# 'sync_Q': sync_Q,
# 'sync_U': sync_U}
#
# if self.parameters_dict['do_rm'] == 'T':
# [rm_map] = self._read_fits_file(temp_folder, 'rm.fits')
# logger.debug('Read the rm_map')
# observables['rm_observable'] = {'rm_map': rm_map}
#
# if self.parameters_dict['do_dm'] == 'T':
# [dm_map] = self._read_fits_file(temp_folder, 'dm.fits')
# logger.debug('Read the dm_map')
# observables['dm_observable'] = {'dm_map': dm_map}
#
# if self.parameters_dict['do_dust'] == 'T':
# [dust_I, dust_Q, dust_U] = self._read_fits_file(temp_folder,
# 'IQU_dust.fits')
# logger.debug('Read the dust_map')
# observables['dust_observable'] = {'dust_I': dust_I,
# 'dust_Q': dust_Q,
# 'dust_U': dust_U}
#
# if self.parameters_dict['do_tau'] == 'T':
# [tau_map] = self._read_fits_file(temp_folder, 'tau.fits')
# logger.debug('Read the tau_map')
# observables['tau_observable'] = {'tau_map': tau_map}
#
# if self.parameters_dict['do_ff'] == 'T':
# [ff_map] = self._read_fits_file(temp_folder, 'free.fits')
# logger.debug('Read the ff_map')
# observables['ff_observable'] = {'ff_map': ff_map}
#
# return observables
#
#############
#
# if self.do_sync_emission:
# result_observable['sync_emission'] = \
# Field(domain=(ensemble_space, hp128, FieldArray((3,))))
# if self.do_rm:
# result_observable['rm'] = Field(domain=(ensemble_space, hp128))
# if self.do_dm:
# result_observable['dm'] = Field(domain=(ensemble_space, hp128,))
# if self.do_dust:
# result_observable['dust'] = \
# Field(domain=(ensemble_space, hp128, FieldArray((3,))))
# if self.do_tau:
# result_observable['tau'] = Field(domain=(ensemble_space, hp128,))
# if self.do_ff:
# result_observable['ff'] = Field(domain=(ensemble_space, hp128,))
imagine/observers/hammurapy/mixins/__init__.py 0 → 100644
View file @ c48d8f23
# -*- coding: utf-8 -*-
from hammurapy_rm_mixin import HammurapyRMMixin
imagine/observers/hammurapy/mixins/hammurapy_rm_mixin.py 0 → 100644
View file @ c48d8f23
# -*- coding: utf-8 -*-
import os
from nifty import Field, HPSpace
class HammurapyRMMixin(object):
def _initialize_observable_dict(self, observable_dict, magnetic_field):
ensemble_space = magnetic_field.domain[0]
hp128 = HPSpace(nside=128)
observable_dict['rm'] = Field(domain=(ensemble_space, hp128),
distribution_strategy='equal')
super(HammurapyRMMixin, self)._initialize_observable_dict(
observable_dict,
magnetic_field)
def _build_parameter_dict(self, parameter_dict, magnetic_field,
working_directory, local_ensemble_index):
obs_RM_file_name = os.path.join(working_directory, 'rm.fits')
parameter_dict['do_rm'] = 'T'
parameter_dict['obs_RM_file_name'] = obs_RM_file_name
super(HammurapyRMMixin, self)._build_parameter_dict(
parameter_dict,
magnetic_field,
working_directory,
local_ensemble_index)
def _fill_observable_dict(self, observable_dict, working_directory,
local_ensemble_index):
self.logger.debug('Reading RM-map.')
[rm_map] = self._read_fits_file(working_directory, 'rm.fits')
rm_field = observable_dict['rm']
rm_field.val.data[local_ensemble_index] = rm_map
super(HammurapyRMMixin, self)._fill_observable_dict(
observable_dict,
working_directory,
local_ensemble_index)
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