raise ValueError("x and y signals must have same size")
except ValueError, err_msg:
raise ValueError(err_msg)
return
' Initialize default values if not given '
if self._tau_max == 0:
self._tau_max = lx / 10
if self._window == 0:
self._window = lx / 10
' Initialize lag array'
lag_array = np.arange(-self._tau_max, self._tau_max + 1, self._tau_inc)
' Initialize Mutual information instance once '
mi = MutualInformation(self._n_neighbours, self._type, self._var_resc,
self._noise)
' Initialize results '
window_MI = {}
i = self._tau_max
while i <= lx - self._window:
curr_coef_lag = []
for k in lag_array:
if k <= 0: # For negative tau
curr_x = x[i:i + self._window].values
curr_y = y[i + k:i + k + self._window].values
else: # For positive tau
curr_x = x[i - k:i - k + self._window].values
curr_y = y[i:i + self._window].values
raise ValueError("x and y signals must have same size")
except ValueError, err_msg:
raise ValueError(err_msg)
return
' Initialize default values if not given '
if self._tau_max == 0 :
self._tau_max = lx / 10
if self._window == 0 :
self._window = lx / 10
' Initialize lag array'
lag_array = np.arange(-self._tau_max, self._tau_max +1, self._tau_inc)
' Initialize Mutual information instance once '
mi = MutualInformation(self._n_neighbours, self._type, self._var_resc, self._noise)
' Initialize results '
window_MI = {}
i = self._tau_max
while i <= lx - self._window :
curr_coef_lag = []
for k in lag_array :
if k <= 0 : # For negative tau
curr_x = x[i : i + self._window].values
curr_y = y[i + k : i + k + self._window].values
else : # For positive tau
curr_x = x[i - k : i - k + self._window].values
curr_y = y[i : i + self._window].values
raise ValueError("x and y signals must have same size")
except ValueError, err_msg:
raise ValueError(err_msg)
return
' Initialize default values if not given '
if self._tau_max == 0 :
self._tau_max = lx / 10
if self._window == 0 :
self._window = lx / 10
' Initialize lag array'
lag_array = np.arange(-self._tau_max, self._tau_max +1, self._tau_inc)
' Initialize Mutual information instance once '
mi = MutualInformation(self._n_neighbours, self._type, self._var_resc, self._noise)
' Initialize results '
window_MI = {}
i = self._tau_max
while i <= lx - self._window:
curr_coef_lag = []
fixed_x = pd.DataFrame(x[i: i + self._window].values)
fixed_y = pd.DataFrame(y[i: i + self._window].values)
# For negative tau
for k in lag_array[lag_array <= 0]:
curr_y = y[i + k: i + k + self._window].values