from stimuli.AbstractStimulus import AbstractStimulus
import numpy as np


class LIFACModel:
    # all times in milliseconds
    KEYS = ["mem_res", "mem_tau", "v_base", "v_zero", "threshold", "step_size", "delta_a", "tau_a"]
    VALUES = [100 * 1000000, 0.1 * 200, 0, 0, 10, 0.01, 1, 200]

    # membrane time constant tau = mem_cap*mem_res
    def __init__(self, params: dict = None):
        self.parameters = {}
        if params is None:
            self._set_default_parameters()
        else:
            self._test_given_parameters(params)
            self.set_parameters(params)

        self.last_v = []
        self.last_adaption = []
        self.last_spiketimes = []

    def __call__(self, stimulus: AbstractStimulus, total_time_s):
        output_voltage = []
        adaption = []
        spiketimes = []
        current_v = self.parameters["v_zero"]
        current_a = 0

        for time_point in np.arange(0, total_time_s*1000, self.parameters["step_size"]):
            v_next = self._calculate_voltage_step(current_v, stimulus.value_at_time_in_ms(time_point) - current_a)
            a_next = self._calculate_adaption_step(current_a)

            if v_next > self.parameters["threshold"]:
                v_next = self.parameters["v_base"]
                spiketimes.append(time_point/1000)
                a_next += self.parameters["delta_a"]

            output_voltage.append(v_next)
            adaption.append(a_next)

            current_v = v_next
            current_a = a_next

        self.last_v = output_voltage
        self.last_adaption = adaption
        self.last_spiketimes = spiketimes

        return output_voltage, spiketimes

    def _calculate_voltage_step(self, current_v, input_v):
        v_base = self.parameters["v_base"]
        step_size = self.parameters["step_size"]
        # mem_res = self.parameters["mem_res"]
        mem_tau = self.parameters["mem_tau"]
        return current_v + (step_size * (v_base - current_v + input_v)) / mem_tau

    def _calculate_adaption_step(self, current_a):
        step_size = self.parameters["step_size"]
        return current_a + (step_size * (-current_a)) / self.parameters["tau_a"]

    def set_parameters(self, params):
        for k in params.keys():
            self.parameters[k] = params[k]

        for i in range(len(self.KEYS)):
            if self.KEYS[i] not in self.parameters.keys():
                self.parameters[self.KEYS[i]] = self.VALUES[i]

    def get_parameters(self):
        return self.parameters

    def set_variable(self, key, value):
        if key not in self.KEYS:
            raise ValueError("Given key is unknown!\n"
                             "Please check spelling and refer to list LIFAC.KEYS.")
        self.parameters[key] = value

    def _set_default_parameters(self):
        for i in range(len(self.KEYS)):
            self.parameters[self.KEYS[i]] = self.VALUES[i]

    def _test_given_parameters(self, params):
        for k in params.keys():
            if k not in self.KEYS:
                err_msg = "Unknown key in the given parameters:" + str(k)
                raise ValueError(err_msg)