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Make file Flake8 compatible

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This commit is contained in:
th0rntwig 2022-08-21 18:34:06 +02:00
parent 6855727f5c
commit 353512899d
1 changed files with 17 additions and 12 deletions
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25
freqtrade/freqai/data_kitchen.py
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@ -601,7 +601,7 @@ class FreqaiDataKitchen:
is an outlier.
"""
from math import sin, cos
from math import cos, sin
if predict:
train_ft_df = self.data_dictionary['train_features']
@ -622,13 +622,17 @@ class FreqaiDataKitchen:
else:
def normalise_distances(distances):
normalised_distances = (distances - distances.min()) / (distances.max() - distances.min())
normalised_distances = (distances - distances.min()) / \
(distances.max() - distances.min())
return normalised_distances
def rotate_point(origin,point,angle):
# rotate a point counterclockwise by a given angle (in radians) around a given origin
x = origin[0] + cos(angle) * (point[0] - origin[0]) - sin(angle) * (point[1] - origin[1])
y = origin[1] + sin(angle) * (point[0] - origin[0]) + cos(angle) * (point[1] - origin[1])
def rotate_point(origin, point, angle):
# rotate a point counterclockwise by a given angle (in radians)
# around a given origin
x = origin[0] + cos(angle) * (point[0] - origin[0]) - \
sin(angle) * (point[1] - origin[1])
y = origin[1] + sin(angle) * (point[0] - origin[0]) + \
cos(angle) * (point[1] - origin[1])
return (x, y)
MinPts = len(self.data_dictionary['train_features'].columns) * 2
@ -641,12 +645,13 @@ class FreqaiDataKitchen:
normalised_distances = normalise_distances(distances)
x_range = np.linspace(0, 1, len(distances))
line = np.linspace(normalise_distances[0], normalise_distances[-1], len(normalise_distances))
deflection = np.abs(normalise_distances - line)
max_deflection_loc = np.where(deflection==deflection.max())[0][0]
line = np.linspace(normalised_distances[0],
normalised_distances[-1], len(normalised_distances))
deflection = np.abs(normalised_distances - line)
max_deflection_loc = np.where(deflection == deflection.max())[0][0]
origin = x_range[max_deflection_loc], line[max_deflection_loc]
point = x_range[max_deflection_loc], normalised_distances[max_deflection_loc]
rot_angle = np.pi/4
rot_angle = np.pi / 4
elbow_loc = rotate_point(origin, point, rot_angle)
epsilon = elbow_loc[1] * (distances[-1] - distances[0]) + distances[0]