def check1():
#### python core_test_encoder.py check1
#############################################################
from source.prepro import pd_col_genetic_transform as pd_prepro
pars = {'path_pipeline_export': ''}
############################################################
for name in ['boston']:
df, col = get_test_data(name)
dfnew, col_pars = pd_prepro(df, col, pars)
print(pd_prepro, name)
print(dfnew[col].head(3).T, col)
print(dfnew.head(3).T, col_pars)
def check1():
#### python core_test_encoder.py check1
#############################################################
from source.prepro import pd_col_genetic_transform as pd_prepro
pars = {'path_pipeline_export': ''}
############################################################
for name in ['boston']:
## condition for gplearn.SymbolicTransformer:
## len(col) < population_size
## for boston dataset, the number of features is 13, so pupulation_size should be greater than 13
df, col = get_test_data(name)
print(len(col))
pars = {'coly': 'price', 'pars_genetic': {'population_size': 14}}
dfnew, col_pars = pd_prepro(df, col, pars)
print(pd_prepro, name)
print(dfnew.head(3).T)