### Imports ###
import qbiocode.data_generation.make_circles as circles
import qbiocode.data_generation.make_moons as moons
import qbiocode.data_generation.make_class as make_class
import qbiocode.data_generation.make_s_curve as s_curve
import qbiocode.data_generation.make_spheres as spheres
import qbiocode.data_generation.make_spirals as spirals
import qbiocode.data_generation.make_swiss_roll as swiss_roll
### Main Function ###
# parameters to vary across the configurations
N_SAMPLES = list(range(100, 300, 20))
NOISE = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
HOLE = [True, False]
N_CLASSES = [2]
DIM = [3, 6, 9, 12]
RAD = [3, 6, 9, 12]
N_FEATURES = list(range(10, 60, 20))
N_INFORMATIVE = list(range(2, 8, 4))
N_REDUNDANT = list(range(2, 8, 4))
N_CLUSTERS_PER_CLASS = list(range(1, 2, 3))
WEIGHTS = [[0.3, 0.7], [0.4, 0.6], [0.5, 0.5]]
[docs]
def generate_data(
type_of_data=None,
save_path=None,
n_samples=N_SAMPLES,
noise=NOISE,
hole=HOLE,
n_classes=N_CLASSES,
dim=DIM,
rad=RAD,
n_features=N_FEATURES,
n_informative=N_INFORMATIVE,
n_redundant=N_REDUNDANT,
n_clusters_per_class=N_CLUSTERS_PER_CLASS,
weights=WEIGHTS
):
"""
Main function to generate datasets using various methods.
"""
if type_of_data is 'circles':
# Generate circles dataset
circles.my_make_classification(n_samples=n_samples,
noise=noise,
save_path=save_path)
elif type_of_data is 'moons':
# Generate moons dataset
moons.my_make_classification(n_samples=n_samples,
noise=noise,
save_path=save_path)
elif type_of_data is 'classes':
# Generate higher-dimensional classification dataset
make_class.my_make_classification(n_samples=n_samples,
n_features=n_features,
n_informative=n_informative,
n_redundant=n_redundant,
n_classes=n_classes,
n_clusters_per_class=n_clusters_per_class,
weights=weights,
save_path=save_path
)
elif type_of_data is 's_curve':
# Generate S-curve dataset
s_curve.my_make_s_curve(n_samples=n_samples,
noise=noise,
save_path=save_path
)
elif type_of_data is 'spheres':
# Generate spheres dataset
spheres.my_make_spheres(n_s=n_samples,
dim=dim,
radius=rad,
save_path=save_path
)
elif type_of_data is 'spirals':
# Generate spirals dataset
spirals.my_make_spirals(n_s=n_samples,
n_c=n_classes,
n_n=noise,
n_d=dim,
save_path=save_path
)
elif type_of_data is 'swiss_roll':
# Generate Swiss roll dataset
swiss_roll.my_make_swiss_roll(n_samples=n_samples,
noise=noise,
hole=hole,
save_path=save_path
)
else:
raise ValueError("Invalid type_of_data. Choose from 'circles', 'moons', 'classes', 's_curve', 'spheres', 'spirals', or 'swiss_roll'.")
print("Dataset generation complete.")
return
