from brian2.core.preferences import brian_prefs, BrianPreference
# Preferences
brian_prefs.register_preferences(
'codegen',
'Code generation preferences',
target=BrianPreference(
default='numpy',
docs='''
Default target for code generation.
Can be a string, in which case it should be one of:
* `'numpy'` by default because this works on all platforms, but may not
be maximally efficient.
* `'weave`' uses ``scipy.weave`` to generate and compile C++ code,
should work anywhere where ``gcc`` is installed and available at the
command line.
Or it can be a ``CodeObject`` class.
''',
),
)
brian_prefs.register_preferences(
'logging',
'Logging system preferences',
delete_log_on_exit=BrianPreference(
default=True,
docs='''
Whether to delete the log and script file on exit.
If set to ``True`` (the default), log files (and the copy of the main
script) will be deleted after the brian process has exited, unless an
uncaught exception occured. If set to ``False``, all log files will be kept.
''',
),
file_log_level=BrianPreference(default='DEBUG',
docs='''
What log level to use for the log written to the log file.
In case file logging is activated (see `logging.file_log`), which log
level should be used for logging. Has to be one of CRITICAL, ERROR,
WARNING, INFO or DEBUG.
''',
validator=log_level_validator),
console_log_level=BrianPreference(default='WARNING',
docs='''
What log level to use for the log written to the console.
Has to be one of CRITICAL, ERROR, WARNING, INFO or DEBUG.
''',
validator=log_level_validator),
file_log=BrianPreference(default=True,
docs='''
Whether to log to a file or not.
If set to ``True`` (the default), logging information will be written
to a file. The log level can be set via the `logging.file_log_level`
preference.
'''),
save_script=BrianPreference(default=True,
docs='''
Whether to save a copy of the script that is run.
If set to ``True`` (the default), a copy of the currently run script
is saved to a temporary location. It is deleted after a successful
run (unless `logging.delete_log_on_exit` is ``False``) but is kept after
an uncaught exception occured. This can be helpful for debugging,
in particular when several simulations are running in parallel.
'''))
__all__ = ['WeaveCodeObject', 'WeaveCodeGenerator']
# Preferences
brian_prefs.register_preferences(
'codegen.runtime.weave',
'Weave runtime codegen preferences',
compiler = BrianPreference(
default='gcc',
validator=lambda pref: pref=='gcc',
docs='''
Compiler to use for weave.
'''
),
extra_compile_args = BrianPreference(
default=['-w', '-O3', '-ffast-math'],
docs='''
Extra compile arguments to pass to compiler
'''
),
include_dirs = BrianPreference(
default=[],
docs='''
Include directories to use.
'''
)
)
def weave_data_type(dtype):
'''
'''
Module declaring general code generation preferences.
'''
from .codeobject import CodeObject
from brian2.core.preferences import brian_prefs, BrianPreference
# Preferences
brian_prefs.register_preferences(
'codegen',
'Code generation preferences',
target = BrianPreference(
default='numpy',
docs='''
Default target for code generation.
Can be a string, in which case it should be one of:
* `'numpy'` by default because this works on all platforms, but may not
be maximally efficient.
* `'weave`' uses ``scipy.weave`` to generate and compile C++ code,
should work anywhere where ``gcc`` is installed and available at the
command line.
Or it can be a ``CodeObject`` class.
''',
validator=lambda target: isinstance(target, str) or issubclass(target, CodeObject),
),
)
from ..targets import runtime_targets
from brian2.core.preferences import brian_prefs, BrianPreference
__all__ = ['WeaveCodeObject']
# Preferences
brian_prefs.register_preferences(
'codegen.runtime.weave',
'Weave runtime codegen preferences',
compiler = BrianPreference(
default='gcc',
validator=lambda pref: pref=='gcc',
docs='''
Compiler to use for weave.
''',
),
extra_compile_args = BrianPreference(
default=['-w', '-O3', '-ffast-math'],
docs='''
Extra compile arguments to pass to compiler
''',
),
)
def weave_data_type(dtype):
'''
Gives the C language specifier for numpy data types using weave. For example,
``numpy.int32`` maps to ``long`` in C.
'''
brian_prefs.register_preferences('logging', 'Logging system preferences',
delete_log_on_exit=BrianPreference(
default=True,
docs= '''
Whether to delete the log and script file on exit.
If set to ``True`` (the default), log files (and the copy of the main
script) will be deleted after the brian process has exited, unless an
uncaught exception occured. If set to ``False``, all log files will be kept.
''',
),
file_log_level=BrianPreference(
default='DEBUG',
docs='''
What log level to use for the log written to the log file.
In case file logging is activated (see `logging.file_log`), which log
level should be used for logging. Has to be one of CRITICAL, ERROR,
WARNING, INFO or DEBUG.
''',
validator=log_level_validator),
console_log_level=BrianPreference(
default='WARNING',
docs='''
What log level to use for the log written to the console.
Has to be one of CRITICAL, ERROR, WARNING, INFO or DEBUG.
''',
validator=log_level_validator),
file_log=BrianPreference(
default=True,
docs= '''
Whether to log to a file or not.
If set to ``True`` (the default), logging information will be written
to a file. The log level can be set via the `logging.file_log_level`
preference.
'''),
save_script=BrianPreference(
default=True,
docs= '''
Whether to save a copy of the script that is run.
If set to ``True`` (the default), a copy of the currently run script
is saved to a temporary location. It is deleted after a successful
run (unless `logging.delete_log_on_exit` is ``False``) but is kept after
an uncaught exception occured. This can be helpful for debugging,
in particular when several simulations are running in parallel.
''')
)
from ...codeobject import CodeObject
from ...templates import Templater
from ...generators.numpy_generator import NumpyCodeGenerator
from ...targets import codegen_targets
__all__ = ['NumpyCodeObject']
# Preferences
brian_prefs.register_preferences(
'codegen.runtime.numpy',
'Numpy runtime codegen preferences',
discard_units = BrianPreference(
default=False,
docs='''
Whether to change the namespace of user-specifed functions to remove
units.
'''
)
)
class NumpyCodeObject(CodeObject):
'''
Execute code using Numpy
Default for Brian because it works on all platforms.
'''
templater = Templater('brian2.codegen.runtime.numpy_rt')
generator_class = NumpyCodeGenerator
# Preferences
brian_prefs.register_preferences(
'codegen.languages.cpp',
'C++ codegen preferences',
restrict_keyword = BrianPreference(
default='__restrict__',
docs='''
The keyword used for the given compiler to declare pointers as restricted.
This keyword is different on different compilers, the default is for gcc.
''',
),
flush_denormals = BrianPreference(
default=False,
docs='''
Adds code to flush denormals to zero.
The code is gcc and architecture specific, so may not compile on all
platforms. The code, for reference is::
#define CSR_FLUSH_TO_ZERO (1 << 15)
unsigned csr = __builtin_ia32_stmxcsr();
csr |= CSR_FLUSH_TO_ZERO;
__builtin_ia32_ldmxcsr(csr);
Found at `<http://stackoverflow.com/questions/2487653/avoiding-denormal-values-in-c>`_.
''',
),
)
# Preferences
brian_prefs.register_preferences(
'codegen.generators.cpp',
'C++ codegen preferences',
restrict_keyword = BrianPreference(
default='__restrict__',
docs='''
The keyword used for the given compiler to declare pointers as restricted.
This keyword is different on different compilers, the default is for gcc.
''',
),
flush_denormals = BrianPreference(
default=False,
docs='''
Adds code to flush denormals to zero.
The code is gcc and architecture specific, so may not compile on all
platforms. The code, for reference is::
#define CSR_FLUSH_TO_ZERO (1 << 15)
unsigned csr = __builtin_ia32_stmxcsr();
csr |= CSR_FLUSH_TO_ZERO;
__builtin_ia32_ldmxcsr(csr);
Found at `<http://stackoverflow.com/questions/2487653/avoiding-denormal-values-in-c>`_.
''',
),
)
'''
Definitions, documentation, default values and validation functions for core
Brian preferences.
'''
from numpy import float64, int32
from brian2.core.preferences import BrianPreference, brian_prefs
def dtype_repr(dtype):
return dtype.__name__
brian_prefs.register_preferences('core', 'Core Brian preferences',
default_float_dtype=BrianPreference(
default=float64,
docs='''
Default dtype for all arrays of scalars (state variables, weights, etc.).
''',
representor=dtype_repr,
),
default_integer_dtype=BrianPreference(
default=int32,
docs='''
Default dtype for all arrays of integer scalars'
''',
representor=dtype_repr,
)
)
'make_weave_function']
# Preferences
brian_prefs.register_preferences(
'codegen.runtime.weave',
'Weave runtime codegen preferences',
compiler = BrianPreference(
default='gcc',
validator=lambda pref: pref=='gcc',
docs='''
Compiler to use for weave.
'''
),
extra_compile_args = BrianPreference(
default=['-w', '-O3'],
docs='''
Extra compile arguments to pass to compiler
'''
),
include_dirs = BrianPreference(
default=[],
docs='''
Include directories to use. Note that ``$prefix/include`` will be
appended to the end automatically, where ``$prefix`` is Python's
site-specific directory prefix as returned by `sys.prefix`.
'''
)
)
def make_weave_function(code, namespace=None, discard_units=None):
'''
Definitions, documentation, default values and validation functions for core
Brian preferences.
'''
from numpy import float64
from brian2.core.preferences import BrianPreference, brian_prefs
def dtype_repr(dtype):
return dtype.__name__
brian_prefs.register_preferences('core', 'Core Brian preferences',
default_scalar_dtype=BrianPreference(
default=float64,
docs='''
Default dtype for all arrays of scalars (state variables, weights, etc.).'
''',
representor=dtype_repr,
)
)
AttributeVariable, AuxiliaryVariable,
Subexpression)
from ...codeobject import CodeObject
from ...templates import Templater
from ...generators.numpy_generator import NumpyCodeGenerator
from ...targets import codegen_targets
__all__ = ['NumpyCodeObject']
# Preferences
brian_prefs.register_preferences('codegen.runtime.numpy',
'Numpy runtime codegen preferences',
discard_units=BrianPreference(default=False,
docs='''
Whether to change the namespace of user-specifed functions to remove
units.
'''))
class NumpyCodeObject(CodeObject):
'''
Execute code using Numpy
Default for Brian because it works on all platforms.
'''
templater = Templater('brian2.codegen.runtime.numpy_rt')
generator_class = NumpyCodeGenerator
class_name = 'numpy'