def __init__(self,
history_steps=None,
n_bins=None,
t_max=None,
track_type=None):
"""
Constructor for the OnTheFlyMSD.
:param history_steps: The number of steps per atom to store in the
history buffer.
:type history_steps: int
:param n_bins: The nuber of bins in the histogram.
:type n_bins: int
:param t_max: The starting value of the last bin.
:type t_max: float
:param track_type: The atom type to track during the simulation.
:type track_type: str
"""
# Check and set the history steps input.
self.__history_steps = checkPositiveInteger(history_steps, 5, "history_step")
# Check and set the number of bins.
self.__n_bins = checkPositiveInteger(n_bins, 100, "n_bins")
# Check and set the time maximum.
self.__t_max = checkPositiveFloat(t_max, 100.0, "t_max")
# Check that the track type.
if not isinstance(track_type, str):
raise Error("The 'track_type' parameter must be a string.")
self.__track_type = track_type
# Calculate and store the binsize.
self.__binsize = self.__t_max / self.__n_bins
# Set the step counter to zero.
self.__n_steps = 0
# Set the blocksize to zero.
self.__blocksize = 0
def __init__(self,
number_of_steps=None,
dump_interval=None,
analysis_interval=None,
seed=None):
"""
Constructuor for the KMCControlParameters object that
holds all parameters controlling the flow of the KMC simulation.
:param number_of_steps: The number of KMC steps to take. If not provided
the default value 0 will be used.
:type number_of_steps: int
:param dump_interval: The number of steps between subsequent trajectory
dumps. The default value is 1, i.e. dump every step.
:type dump_interval: int
:param analysis_interval: The number of steps between subsequent calls to
the custom analysis 'registerStep' functions.
The default value is 1, i.e. analysis every step.
:type analysis_interval: int
:param seed: The seed value to use for the backend random number generator.
If no seed value is given the random numnber generator will be
seeded based on the wall-clock time.
:type seed: int
"""
# Check and set the number of steps.
self.__number_of_steps = checkPositiveInteger(number_of_steps, 0,
"number_of_steps")
self.__dump_interval = checkPositiveInteger(dump_interval, 1,
"dump_interval")
self.__analysis_interval = checkPositiveInteger(
analysis_interval, 1, "analysis_interval")
self.__time_seed = (seed is None)
self.__seed = checkPositiveInteger(seed, 1, "seed")
def __init__(self,
processes=None,
time_interval=None,
spatially_resolved=None,
anal_Interval=None,
resultsPlace=None,
processesObject=None):
"""
Constructor for the process statistics analysis.
:param processes: List of process numbers to collect statistics from.
:param time_interval: Time interval for binning results. Defaults to
1.0 if not specified.
:type time_interval: float
:param spatially_resolved: True if spatially resolved information about
the total number of events per site should
be collected. Defaults to False.
:type spatially_resovled: bool
"""
# Check and set the input.
msg = "The 'processes' parameter must be given as a list of process numbers."
self.__processes = checkSequenceOfPositiveIntegers(processes, msg)
self.__time_interval = checkPositiveFloat(time_interval, 1.0,
'time_interval')
self.__analInterval = checkPositiveInteger(anal_Interval, 1,
'anal_Interval')
self.__resultsPlace = resultsPlace
self.__processesObject = processesObject
if (self.__resultsPlace is not None):
if (self.__processesObject is None):
raise Error(
"If this is the trajRecord-keeping processStatistics analysis instance, you need to specify what the processes are!"
)
self.__trajRecord = open(self.__resultsPlace + '/trajRecord.tr',
'w')
self.__floatAnalInterval = float(self.__analInterval)
if (spatially_resolved is None):
spatially_resolved = False
elif not isinstance(spatially_resolved, bool):
raise Error(
"The 'spatially_resolved' parameter to the ProcessStatistics analysis must be given as a bool."
)
# Done checking.
self.__spatially_resolved = spatially_resolved
self.__last_time = 0.0
self.__data = []
self.__spatial_data = None
self.__current_count = 0
def __init__(self,
number_of_steps=None,
dump_interval=None):
"""
Constructuor for the KMCControlParameters object that
holds all parameters controlling the flow of the KMC simulation.
:param number_of_steps: The number of KMC steps to take. If not provided
the default value 0 will be used.
:type number_of_steps: int
:param dump_interval: The number of steps between subsequent trajectory
dumps. The default value is 1, i.e. dump every step.
:type dump_interval: int
"""
# Check and set the number of steps.
self.__number_of_steps = checkPositiveInteger(number_of_steps,
0,
"number_of_steps")
self.__dump_interval = checkPositiveInteger(dump_interval,
1,
"dump_interval")
def __init__(self,
processes=None,
time_interval=None,
spatially_resolved=None,
anal_Interval=None,
resultsPlace=None,
processesObject=None):
"""
Constructor for the process statistics analysis.
:param processes: List of process numbers to collect statistics from.
:param time_interval: Time interval for binning results. Defaults to
1.0 if not specified.
:type time_interval: float
:param spatially_resolved: True if spatially resolved information about
the total number of events per site should
be collected. Defaults to False.
:type spatially_resovled: bool
"""
# Check and set the input.
msg = "The 'processes' parameter must be given as a list of process numbers."
self.__processes = checkSequenceOfPositiveIntegers(processes, msg)
self.__time_interval = checkPositiveFloat(time_interval, 1.0, 'time_interval')
self.__analInterval = checkPositiveInteger(anal_Interval, 1, 'anal_Interval')
self.__resultsPlace = resultsPlace
self.__processesObject = processesObject
if (self.__resultsPlace is not None):
if(self.__processesObject is None):
raise Error("If this is the trajRecord-keeping processStatistics analysis instance, you need to specify what the processes are!")
self.__trajRecord = open(self.__resultsPlace+'/trajRecord.tr', 'w')
self.__floatAnalInterval = float(self.__analInterval)
if (spatially_resolved is None):
spatially_resolved = False
elif not isinstance(spatially_resolved, bool):
raise Error("The 'spatially_resolved' parameter to the ProcessStatistics analysis must be given as a bool.")
# Done checking.
self.__spatially_resolved = spatially_resolved
self.__last_time = 0.0
self.__data = []
self.__spatial_data = None
self.__current_count = 0
def testCheckPositiveInteger(self):
""" Test that the positive integer checking works. """
# Test pass.
integer0 = checkPositiveInteger(21, 1234, "integer0")
self.assertEqual(integer0, 21)
integer0 = checkPositiveInteger(0, 1234, "integer0")
self.assertEqual(integer0, 0)
# Test default.
integer0 = checkPositiveInteger(None, 1234, "integer0")
self.assertEqual(integer0, 1234)
# Test fail negative.
self.assertRaises(Error, lambda: checkPositiveInteger(-1, 12, "fail"))
# Test fail wrong type.
self.assertRaises(Error, lambda: checkPositiveInteger(1.1, 12, "fail"))
# Test fail wrong type.
self.assertRaises(Error, lambda: checkPositiveInteger("1", 12, "fail"))
def testCheckPositiveInteger(self):
""" Test that the positive integer checking works. """
# Test pass.
integer0 = checkPositiveInteger(21, 1234, "integer0")
self.assertEqual(integer0, 21)
integer0 = checkPositiveInteger(0, 1234, "integer0")
self.assertEqual(integer0, 0)
# Test default.
integer0 = checkPositiveInteger(None, 1234, "integer0")
self.assertEqual(integer0, 1234)
# Test fail negative.
self.assertRaises( Error,
lambda: checkPositiveInteger(-1, 12, "fail") )
# Test fail wrong type.
self.assertRaises( Error,
lambda: checkPositiveInteger(1.1, 12, "fail") )
# Test fail wrong type.
self.assertRaises( Error,
lambda: checkPositiveInteger("1", 12, "fail") )
def __init__(self,
number_of_steps=None,
dump_interval=None,
analysis_interval=None,
seed=None,
dump_time_interval=None,
rng_type=None):
"""
Constructuor for the KMCControlParameters object that
holds all parameters controlling the flow of the KMC simulation.
:param number_of_steps: The number of KMC steps to take. If not provided
the default value 0 will be used.
:type number_of_steps: int
:param dump_interval: The number of steps between subsequent trajectory
dumps. The default value is 1, i.e. dump every step.
:type dump_interval: int
:param analysis_interval: The number of steps between subsequent calls to
the custom analysis 'registerStep' functions.
The default value is 1, i.e. analysis every step.
:type analysis_interval: int
:param seed: The seed value to use for the backend random number generator.
If no seed value is given the random numnber generator will be
seeded based on the wall-clock time.
:type seed: int
:param dump_time_interval: The simulation time between subsequent trajectory
dumps. The default value is None, causing the dump_interval parameter to determine the behavior.
:type dump_interval: int
:param rng_type: The type of pseudo random number generator to use. The random
number generators are the once in the standard C++ library and
the supported types maps directly to the given C++ construction
as indicated here:
'MT' for Mersenne-Twister (Default) [rng = std::mt19937],
'MINSTD' for the 'minimum standard' rng [rng = std::minstd_rand],
'RANLUX24' for the 24-bit version of the ranlux rng [rng = std::ranlux24],
'RANLUX48' for the 48-bit version of the ranlux rng [rng = std::ranlux48].
The sequence of pseudo-random numbers is generated by repeated calls to
std::generate_canonical<double, 32>(rng);
See: http://en.cppreference.com/w/cpp/numeric/random for further details on
C++ random number generators.
There is also the option 'DEVICE' for using a random device
installed on the macine through [rng = std::random_device] in C++. Note
however that you should spend some time evaluating this option to make
sure it works as you expect if you have a random device installed, since this
has not been tested with a random device by the KMCLib developers.
:type rng_type: str
"""
# Check and set the number of steps.
self.__number_of_steps = checkPositiveInteger(number_of_steps, 0,
"number_of_steps")
self.__dump_interval = None
if dump_interval is not None:
self.__dump_interval = checkPositiveInteger(
dump_interval, 1, "dump_interval")
self.__analysis_interval = checkPositiveInteger(
analysis_interval, 1, "analysis_interval")
self.__time_seed = (seed is None)
self.__seed = checkPositiveInteger(seed, 1, "seed")
if dump_time_interval is not None:
if not isinstance(dump_time_interval, float):
raise Error(
"The 'dump_time_interval' parameter must be of type float."
)
if dump_time_interval <= 0:
raise Error(
"The 'dump_time_interval' parameter must be greater than zero."
)
self.__dump_time_interval = dump_time_interval
# Check that dump_time_interval and dump_interval not both are different from None.
if (self.__dump_time_interval is not None) and (self.__dump_interval
is not None):
raise Error(
"The 'dump_time_interval' and the 'dump_interval' parameters can not both be used."
)
# If both are None, set the dump_interval to 1.
if (self.__dump_interval is None) and (self.__dump_time_interval is
None):
self.__dump_interval = 1
# Check and set the random number generator type.
self.__rng_type = self.__checkRngType(rng_type, "MT")
def __init__(self,
number_of_steps=None,
dump_interval=None,
analysis_interval=None,
seed=None,
dump_time_interval=None,
rng_type=None):
"""
Constructuor for the KMCControlParameters object that
holds all parameters controlling the flow of the KMC simulation.
:param number_of_steps: The number of KMC steps to take. If not provided
the default value 0 will be used.
:type number_of_steps: int
:param dump_interval: The number of steps between subsequent trajectory
dumps. The default value is 1, i.e. dump every step.
:type dump_interval: int
:param analysis_interval: The number of steps between subsequent calls to
the custom analysis 'registerStep' functions.
The default value is 1, i.e. analysis every step.
:type analysis_interval: int
:param seed: The seed value to use for the backend random number generator.
If no seed value is given the random numnber generator will be
seeded based on the wall-clock time.
:type seed: int
:param dump_time_interval: The simulation time between subsequent trajectory
dumps. The default value is None, causing the dump_interval parameter to determine the behavior.
:type dump_interval: int
:param rng_type: The type of pseudo random number generator to use. The random
number generators are the once in the standard C++ library and
the supported types maps directly to the given C++ construction
as indicated here:
'MT' for Mersenne-Twister (Default) [rng = std::mt19937],
'MINSTD' for the 'minimum standard' rng [rng = std::minstd_rand],
'RANLUX24' for the 24-bit version of the ranlux rng [rng = std::ranlux24],
'RANLUX48' for the 48-bit version of the ranlux rng [rng = std::ranlux48].
The sequence of pseudo-random numbers is generated by repeated calls to
std::generate_canonical<double, 32>(rng);
See: http://en.cppreference.com/w/cpp/numeric/random for further details on
C++ random number generators.
There is also the option 'DEVICE' for using a random device
installed on the macine through [rng = std::random_device] in C++. Note
however that you should spend some time evaluating this option to make
sure it works as you expect if you have a random device installed, since this
has not been tested with a random device by the KMCLib developers.
:type rng_type: str
"""
# Check and set the number of steps.
self.__number_of_steps = checkPositiveInteger(number_of_steps,
0,
"number_of_steps")
self.__dump_interval = None
if dump_interval is not None:
self.__dump_interval = checkPositiveInteger(dump_interval,
1,
"dump_interval")
self.__analysis_interval = checkPositiveInteger(analysis_interval,
1,
"analysis_interval")
self.__time_seed = (seed is None)
self.__seed = checkPositiveInteger(seed,
1,
"seed")
if dump_time_interval is not None:
if not isinstance(dump_time_interval, float):
raise Error("The 'dump_time_interval' parameter must be of type float.")
if dump_time_interval <= 0:
raise Error("The 'dump_time_interval' parameter must be greater than zero.")
self.__dump_time_interval = dump_time_interval
# Check that dump_time_interval and dump_interval not both are different from None.
if (self.__dump_time_interval is not None) and (self.__dump_interval is not None):
raise Error("The 'dump_time_interval' and the 'dump_interval' parameters can not both be used.")
# If both are None, set the dump_interval to 1.
if (self.__dump_interval is None) and (self.__dump_time_interval is None):
self.__dump_interval = 1
# Check and set the random number generator type.
self.__rng_type = self.__checkRngType(rng_type, "MT")
