numpyデータで返すメソッドを追加

diff --git a/src/main/Python/DataGenerator.py b/src/main/Python/DataGenerator.py
deleted file mode 100644 (file)
index 0784883..0000000
--- a/src/main/Python/DataGenerator.py
+++ /dev/null
@@ -1,13 +0,0 @@
-from Data import Data
-from typing import List
-"""
-学習データファイルの読み込みデータから、学習データ形式に変換するモジュール
-
-学習データx：array[総データファイル][日][価格データ]を想定
-学習データy: array[総データファイル][正解ラベル]
-
-となるように生成する。
-
-"""
-
-__whole_data: List[Data]

diff --git a/src/main/Python/DataReader.py b/src/main/Python/DataReader.py
index f273dc7..08775e4 100644 (file)
--- a/src/main/Python/DataReader.py
+++ b/src/main/Python/DataReader.py
@@ -18,15 +18,24 @@ class DataReader:
             self.DATA_SOURCE = confdata['dataPath']
 
     def get_learning_data(self):
+        '''
+
+        :return: トレーニングデータ、トレーニングラベル、テストデータ、テストラベル
+        '''
+
         target_data = self.parse_data_files()
         datasets: List(numpy.ndarray) = []
-        labels: List(str) =[]
+        labels: List(str) = []
 
         for cdata in target_data:
             datasets.append(cdata.get_array_data())
             labels.append(cdata.getLable())
 
-        return numpy.array(datasets), numpy.array(labels)
+        center = len(datasets)//2
+        offset = len(datasets) % 2
+        center = center + offset
+
+        return numpy.array(datasets[:center]), numpy.array(labels[:center]), numpy.array(datasets[center:]), numpy.array(labels[center:])
 
     def __check_data(self, data: Data):
 

diff --git a/src/main/Python/Lern.py b/src/main/Python/Lern.py
deleted file mode 100644 (file)
index f1123d7..0000000
--- a/src/main/Python/Lern.py
+++ /dev/null
@@ -1,78 +0,0 @@
-from chainer import Function, gradient_check, report, training, utils, Variable
-from chainer import datasets, iterators, optimizers, serializers
-from chainer import Link, Chain, ChainList
-import chainer.functions as F
-import chainer.links as L
-from chainer.training import extensions
-import math
-from DataReader import DataReader
-from DatasetGenerator import DatasetGenerator
-
-from Data import Data
-
-class MyChain(Chain):
-    def __init__(self):
-        super(MyChain,self).__init__(
-            l1=L.Linear(500,100),
-            l2=L.Linear(100,100),
-            l3=L.Linear(100,10),
-        )
-
-    def __call__(self,x,t):
-        return F.softmax_cross_entropy(self.fwd(x),t)
-
-    def fwd(self,x):
-        h1=F.relu(self.l1(x))
-        h2=F.relu(self.l2(h1))
-        return self.l3(h2)
-
-
-class MyClassifer(Chain):
-    def __init__(self,predictor):
-        super(MyClassifer,self).__init__()
-        with self.init_scope():
-            self.predictor = predictor
-    def __call__(self,x,t):
-        y = self.predictor(x)
-        loss = F.softmax_cross_entropy(y,t)
-        accuracy = F.accuracy(y,t)
-        report({'loss': loss, 'accuracy': accuracy}, self)
-        return loss;
-
-def main():
-#    try:
-        #モデルを準備
-        model   = MyChain()
-
-        #オプティマイザを準備
-        optimizer = optimizers.Adam()
-        optimizer.setup(model)
-
-        #データを準備
-        train,test = dataPreparation()
-
-        updater = training.StandardUpdater(train,optimizer)
-        trainer = training.Trainer(updater,(10,'epoch'))
-        trainer.extend(extensions.progress_bar)
-        trainer.run()
-
-def dataPreparation():
-    return "hoge"
-
-def dataPreparation_back():
-    # データ用意
-    train_data = []
-    train_label = []
-    # 元データ生成
-    reader = DataReader()  # type DataReader
-    dgene = DatasetGenerator()  # type DataSetGenerator
-    dataist = []
-    dataList = reader.createLearningData()
-    train_data, train_label = dgene.generateDataset(dataList)
-    dust, batchsize = math.modf(len(dataList) / 2)
-    batchsize = int(batchsize)
-    train = datasets.tuple_dataset.TupleDataset(train_data[0:batchsize], train_label[0:batchsize])
-    test = datasets.tuple_dataset.TupleDataset(train_data[batchsize:], train_label[batchsize:])
-    return train,test
-
-main()
\ No newline at end of file

diff --git a/src/main/Python/TestFileUtil.py b/src/main/Python/TestFileUtil.py
deleted file mode 100644 (file)
index 72a9166..0000000
--- a/src/main/Python/TestFileUtil.py
+++ /dev/null
@@ -1,14 +0,0 @@
-import unittest
-
-class TestFileUtil (unittest.TestCase):
-    """test class of hoge"""
-
-    def test_1(self):
-        print(1)
-    def test_2(self):
-        print(2)
-
-if __name__ == "__main__":
-    unittest.main()
-
-

diff --git a/src/main/Python/sample1.py b/src/main/Python/sample1.py
deleted file mode 100644 (file)
index a3e493b..0000000
--- a/src/main/Python/sample1.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import os
-import yaml
-
-DATA_SOURCE = ''
-
-with open('config\\toolconf.yml' , 'r') as yml:
-    data = yaml.load(yml)
-    # 設定値の読み込み
-    DATA_SOURCE = data['dataPath']
-
-def find_all_files(directory):
-    for root, dirs, files in os.walk(directory):
-        yield root
-        for file in files:
-            yield  os.path.join(root,file)
-
-for file in find_all_files(DATA_SOURCE):
-    print(file)
\ No newline at end of file

diff --git a/src/test/Python/HelloChainar.py b/src/test/Python/HelloChainar.py
deleted file mode 100644 (file)
index 6e3c8ff..0000000
--- a/src/test/Python/HelloChainar.py
+++ /dev/null
@@ -1 +0,0 @@
-from chainer.datasets import mnist