def WHEREDataTransformation(filename):
from Utilities.where import where
# The Data has to be access using this attribute table._rows.cells
import pandas as pd
df = pd.read_csv(filename)
headers = [h for h in df.columns if '$<' not in h]
data = df[headers]
clusters = where(data)
return clusters
def WHEREDataTransformation(filename):
from Utilities.where import where
# The Data has to be access using this attribute table._rows.cells
import pandas as pd
df = pd.read_csv(filename)
headers = [h for h in df.columns if '$<' not in h]
data = df[headers]
clusters = where(data)
return clusters
def gale_8_WHERE(problem, population, configuration, values_to_be_passed):
"The Core method behind GALE"
from Utilities.where import where
import numpy as np
decisions = np.array([pop.decisionValues for pop in population])
leaves = where(decisions)
filled_leaves = []
for leaf in leaves:
temp_list = [jmoo_individual(problem, list(member), None) for member in leaf]
filled_leaves.append(temp_list)
return filled_leaves, 0
def gale_8_WHERE(problem, population, configuration, values_to_be_passed):
"The Core method behind GALE"
from Utilities.where import where
import numpy as np
decisions = np.array([pop.decisionValues for pop in population])
leaves = where(decisions)
filled_leaves = []
for leaf in leaves:
temp_list = [
jmoo_individual(problem, list(member), None) for member in leaf
]
filled_leaves.append(temp_list)
return filled_leaves, 0