def transform(self, direction_train, directions, X_speed, power_curve, Coord, Coord_turb, threshold_dir=180,compute_dict=1):
n, p = direction_train.shape
turbines_number = directions.shape[1]
X_turbines = np.zeros([n, p])
count = 0
dict_turbs = dict.fromkeys(np.arange(0, turbines_number), np.array([[]], dtype="int64"))
if compute_dict:
current_dict_values = np.zeros([n, 3])
current_dict_values[:, 0] = count
current_dict_values[:, 2] = np.arange(0, n)
for i in range(p):
selected_turbs = []
keys = []
current_level = i % 12
if compute_dict:
current_dict_values[:, 1] = current_level
if current_level == 0 and i != 0:
count += 1
print("punto", count)
if compute_dict:
current_dict_values[:, 0] = count
current_angles = direction_train[:, i].reshape([n, 1])
point_direction = np.array(directions[count, :]).reshape([1, turbines_number])
current_diff = np.abs(current_angles - point_direction)
min_turbs = np.min(current_diff, axis=1)
for s in range(n):
if min_turbs[s] < threshold_dir:
turb = np.where(current_diff[s, :] == min_turbs[s])[0]
if len(turb) > 1:
# chooose neareast turbine in that direction
tree = create_tree(Coord_turb[turb, :])
d, sel_turb = tree.query(Coord[count, :])
selected_turb = turb[sel_turb]
if compute_dict:
key = selected_turb
else:
selected_turb = turb
if compute_dict:
key = selected_turb[0]
if compute_dict:
keys.append(key)
else:
selected_turb = -1
selected_turbs.append(selected_turb)
if compute_dict:
for turb_key in np.unique(keys):
position_turb = np.where(keys == turb_key)[0]
if dict_turbs[turb_key].shape[1] == 0:
dict_turbs[turb_key] = current_dict_values[position_turb, :]
else:
dict_turbs[turb_key] = np.concatenate(
(dict_turbs[turb_key], current_dict_values[position_turb, :]), axis=0)
wind_speed = X_speed[:, i]
power_values = self.enel_transf_power_curve_multiple_key(selected_turbs, wind_speed, power_curve)
X_turbines[:, i] = power_values
return X_turbines, dict_turbs
def transform(self, direction_train, directions, XTrain, power_curve, Coord, Coord_turb, x_verso, dir_turbine,
x_verso_turbine, compute_dict):
n, p = direction_train.shape
turbines_number = directions.shape[1]
X_turbines = np.zeros([n, p])
count = 0
dict_turbs = dict.fromkeys(np.arange(0, turbines_number), np.array([[]], dtype="int64"))
for i in range(p):
selected_turbs = []
current_level = i % 12
if current_level == 0 and i != 0:
count += 1
current_angles = direction_train[:, i].reshape([n, 1])
x_verso_current = x_verso[:, i]
x_verso_turbine_current = x_verso_turbine[count, :].reshape(turbines_number, 1)
point_direction = np.array(directions[count, :]).reshape([1, turbines_number])
current_diff = np.abs(current_angles - point_direction)
# min_turbs = np.min(current_diff,axis = 1)
selected_turb_same_verso = np.any(x_verso_turbine_current == dir_turbine, axis=1)
if np.any(selected_turb_same_verso):
turb_same_verso = np.where(selected_turb_same_verso)[0]
if len(turb_same_verso) != 0:
for s in range(n):
if x_verso_current[s] == dir_turbine:
min_turbs = np.min(current_diff[s, turb_same_verso])
turb = np.intersect1d(turb_same_verso, np.where(current_diff[s, :] == min_turbs)[0])
if len(turb) > 1:
# chooose neareast turbine in that direction
tree = create_tree(Coord_turb[turb, :])
d, sel_turb = tree.query(Coord[count, :])
selected_turb = turb[sel_turb]
key = selected_turb
else:
selected_turb = turb
key = selected_turb[0]
else:
# print("overcome trehold angle")
selected_turb = -1
if compute_dict:
current_dict_values = np.array([count,current_level,s]).reshape([1,3])
if dict_turbs[key].shape[1]==0:
dict_turbs[key] = current_dict_values
else:
dict_turbs[key] = np.concatenate((dict_turbs[key],current_dict_values), axis = 0)
selected_turbs.append(selected_turb)
wind_speed = XTrain[:, i]
power_values = self.enel_transf_power_curve_multiple_key(selected_turbs, wind_speed, power_curve)
X_turbines[:, i] = power_values
return X_turbines, dict_turbs
def transform_verso_distance(self, XTrain, power_curve, Coord, Coord_turb, x_verso, dir_turbine, x_verso_turbine):
n, p = XTrain.shape
turbines_number = Coord_turb.shape[0]
X_turbines = np.zeros([n, p])
count = 0
dict_turbs = dict.fromkeys(np.arange(0, turbines_number), np.array([[]], dtype="int64"))
for i in range(p):
selected_turbs = []
current_level = i % 12
if current_level == 0 and i != 0:
count += 1
x_verso_current = x_verso[:, i]
x_verso_turbine_current = x_verso_turbine[count, :].reshape(turbines_number, 1)
# min_turbs = np.min(current_diff,axis = 1)
selected_turb_same_verso = np.any(x_verso_turbine_current == dir_turbine, axis=1)
if np.any(selected_turb_same_verso):
turb_same_verso = np.where(selected_turb_same_verso)[0]
if len(turb_same_verso) != 0:
for s in range(n):
if x_verso_current[s] == dir_turbine:
# chooose neareast turbine in that direction
tree = create_tree(Coord_turb)
d, selected_turb = tree.query(Coord[count, :], k=1)
key = selected_turb
else:
# print("overcome trehold angle")
selected_turb = -1
# current_dict_values = np.array([count,current_level,s]).reshape([1,3])
# if dict_turbs[key].shape[1]==0:
# dict_turbs[key] = current_dict_values
# else:
# dict_turbs[key] = np.concatenate((dict_turbs[key],current_dict_values), axis = 0)
selected_turbs.append(selected_turb)
wind_speed = XTrain[:, i]
power_values = self.enel_transf_power_curve(selected_turbs, wind_speed, power_curve)
X_turbines[:, i] = power_values
return X_turbines, dict_turbs
