99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
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from stimuli.AbstractStimulus import AbstractStimulus
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from warnings import warn
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class AbstractModel:
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# TODO what information about the model does the ModelParser need to be able to simulate the right kind of data
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# for further analysis in cell_data/fi_curve etc.
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DEFAULT_VALUES = {}
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def __init__(self, params: dict = None):
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self.parameters = {}
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if params is None:
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self._set_default_parameters()
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else:
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self.set_parameters(params)
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def simulates_voltage_trace(self) -> bool:
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raise NotImplementedError("NOT IMPLEMENTED")
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def simulates_frequency(self) -> bool:
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raise NotImplementedError("NOT IMPLEMENTED")
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def simulates_spiketimes(self) -> bool:
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raise NotImplementedError("NOT IMPLEMENTED")
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def simulate(self, stimulus: AbstractStimulus, total_time_s):
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"""
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Simulate the given stimulus in the model
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and simulate up to the given total time
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and saves the simulated data in the model.
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:param stimulus: given stimulus
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:param total_time_s: time to simulate
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:return: depending on availability: [voltage, spiketimes, frequency]
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"""
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raise NotImplementedError("NOT IMPLEMENTED")
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def get_voltage_trace(self):
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raise NotImplementedError("NOT IMPLEMENTED")
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def get_spiketimes(self):
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raise NotImplementedError("NOT IMPLEMENTED")
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def get_frequency(self):
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raise NotImplementedError("NOT IMPLEMENTED")
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def min_stimulus_strength_to_spike(self):
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"""
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return the minimal stimulus strength needed for the model to spike
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:return: min stimulus strength to spike
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"""
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raise NotImplementedError("NOT IMPLEMENTED")
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def get_sampling_interval(self):
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"""
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return the "sampling" interval of the model: the time step the model simulates by
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:return: the sampling interval
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"""
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raise NotImplementedError("NOT IMPLEMENTED")
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def set_parameters(self, params):
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self._test_given_parameters(params)
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for k in params.keys():
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self.parameters[k] = params[k]
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for key in self.DEFAULT_VALUES.keys():
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if key not in self.parameters.keys():
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self.parameters[key] = self.DEFAULT_VALUES[key]
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def get_parameters(self):
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return self.parameters
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def set_variable(self, key, value):
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if key not in self.DEFAULT_VALUES.keys():
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raise ValueError("Given key is unknown!\n"
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"Please check spelling and refer to list LIFAC.KEYS.")
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if "tau" in key and value < 0:
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warn("Time constants cannot be negative! Setting it to 0.5ms")
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self.parameters[key] = 0.00005
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return
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self.parameters[key] = value
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def _set_default_parameters(self):
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self.parameters = self.DEFAULT_VALUES
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def _test_given_parameters(self, params):
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for k in params.keys():
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if k not in self.DEFAULT_VALUES.keys():
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err_msg = "Unknown key in the given parameters:" + str(k)
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raise ValueError(err_msg)
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if "tau" in k and params[k] < 0:
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warn("Time constants cannot be negative setting" + str(k) + "0.5ms")
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params[k] = 0.00005
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