forked from moreo/QuaPy
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
import os
|
|
import pandas as pd
|
|
from quapy.protocol import AbstractProtocol
|
|
|
|
class IFCBTrainSamplesFromDir(AbstractProtocol):
|
|
|
|
def __init__(self, path_dir:str, classes: list):
|
|
self.path_dir = path_dir
|
|
self.classes = classes
|
|
self.samples = []
|
|
for filename in os.listdir(path_dir):
|
|
if filename.endswith('.csv'):
|
|
self.samples.append(filename)
|
|
|
|
def __call__(self):
|
|
for sample in self.samples:
|
|
s = pd.read_csv(os.path.join(self.path_dir,sample))
|
|
# all columns but the first where we get the class
|
|
X = s.iloc[:, 1:].to_numpy()
|
|
y = s.iloc[:, 0].to_numpy()
|
|
yield X, y
|
|
|
|
def total(self):
|
|
"""
|
|
Returns the total number of samples that the protocol generates.
|
|
|
|
:return: The number of training samples to generate.
|
|
"""
|
|
return len(self.samples)
|
|
|
|
|
|
class IFCBTestSamples(AbstractProtocol):
|
|
|
|
def __init__(self, path_dir:str, test_prevalences_path: str):
|
|
self.path_dir = path_dir
|
|
self.test_prevalences = pd.read_csv(os.path.join(path_dir, test_prevalences_path))
|
|
|
|
def __call__(self):
|
|
for _, test_sample in self.test_prevalences.iterrows():
|
|
#Load the sample from disk
|
|
X = pd.read_csv(os.path.join(self.path_dir,test_sample['sample']+'.csv')).to_numpy()
|
|
prevalences = test_sample.iloc[1:].to_numpy().astype(float)
|
|
yield X, prevalences
|
|
|
|
def total(self):
|
|
"""
|
|
Returns the total number of samples that the protocol generates.
|
|
|
|
:return: The number of test samples to generate.
|
|
"""
|
|
return len(self.test_prevalences.index) |