def repeat_main():
repeat_num = 1
# パラメータモジュール
# for lm in ["LDA"]:
for lm in ["SVM", "LDA", "ANN"]:
for ts in ["HBX", "HBX3", "HBX1"]:
for re in ["none"]:
# for re in ["none", "bootstrap", "smote"]:
for fe in ["SSSM", "SMSK", "SLICE"]:
if re in ["bootstrap", "smote"]:
for rs in [20, 30, 40]:
for nf in [10, None]:
param = myParameter.myParameter()
# 乱数モジュール
param.RAND = random.Random()
param.LEARNING_METHOD = lm
param.TARGET_SIGNAL = ts
param.RESAMPLING_METHOD = re
param.RESAMPLING_SIZE = rs
param.FEATURE_TYPE = fe
param.N_FOLD = nf
fp = open("memo.txt", 'a')
fp.write(",".join([str(mm) for mm in [lm, ts, re, rs, fe, nf]]))
fp.write("\n")
fp.close()
# 実行
_addfilename = lm+ts+re+str(rs)+fe+str(nf)
main(param, addfilename = _addfilename)
elif re == "none":
rs = 0
for nf in [10, None]:
param = myParameter.myParameter()
# 乱数モジュール
param.RAND = random.Random()
param.LEARNING_METHOD = lm
param.TARGET_SIGNAL = ts
param.RESAMPLING_METHOD = re
param.RESAMPLING_SIZE = rs
param.FEATURE_TYPE = fe
param.N_FOLD = nf
_addfilename = lm+ts+re+str(rs)+fe+str(nf)
fp = open("memo.txt", 'a')
fp.write(",".join([str(mm) for mm in [lm, ts, re, rs, fe, nf]]))
fp.write("\n")
fp.close()
# 実行
main(param, addfilename = _addfilename)
def repeat_main():
repeat_num = 1
# パラメータモジュール
# for lm in ["LDA"]:
for lm in ["SVM", "LDA", "ANN"]:
for ts in ["HBX", "HBX3", "HBX1"]:
for re in ["none"]:
# for re in ["none", "bootstrap", "smote"]:
for fe in ["SSSM", "SMSK", "SLICE"]:
if re in ["bootstrap", "smote"]:
for rs in [20, 30, 40]:
for nf in [10, None]:
param = myParameter.myParameter()
# 乱数モジュール
param.RAND = random.Random()
param.LEARNING_METHOD = lm
param.TARGET_SIGNAL = ts
param.RESAMPLING_METHOD = re
param.RESAMPLING_SIZE = rs
param.FEATURE_TYPE = fe
param.N_FOLD = nf
fp = open("memo.txt", 'a')
fp.write(",".join([
str(mm) for mm in [lm, ts, re, rs, fe, nf]
]))
fp.write("\n")
fp.close()
# 実行
_addfilename = lm + ts + re + str(
rs) + fe + str(nf)
main(param, addfilename=_addfilename)
elif re == "none":
rs = 0
for nf in [10, None]:
param = myParameter.myParameter()
# 乱数モジュール
param.RAND = random.Random()
param.LEARNING_METHOD = lm
param.TARGET_SIGNAL = ts
param.RESAMPLING_METHOD = re
param.RESAMPLING_SIZE = rs
param.FEATURE_TYPE = fe
param.N_FOLD = nf
_addfilename = lm + ts + re + str(rs) + fe + str(
nf)
fp = open("memo.txt", 'a')
fp.write(",".join(
[str(mm) for mm in [lm, ts, re, rs, fe, nf]]))
fp.write("\n")
fp.close()
# 実行
main(param, addfilename=_addfilename)
"""
トライアルの開始時間を0.1[s]単位で抽出
@param target_file: 対象となるPresentationログファイル
@param param: パラメータモジュール
@return: シナリオ開始から各タスクの開始時間のリスト 0.1[s]単位
動作確認済
"""
if param.FS != 10.0:
raise NameError("This script can processing 10.0 Hz data.")
# データの読み出しとヘッダ行を飛ばす
cr = csv.reader(open(target_file, 'Ur'), delimiter="\t")
for i in range(5):
cr.next()
# データ取り出し
trial_start = []
for r in cr:
if len(r) > 0:
_time = int(r[3])
trial_start.append(int(round(_time / 1000.0, 0)))
else:
break
return trial_start
if __name__ == "__main__":
import myParameter
param = myParameter.myParameter()
target_file = "/Users/misato/Documents/eclipse/workspace/TwoChannelNIRS/dataset/presentation_log/ysakaguchi/session1.log"
print import_log(target_file, param)
@param param: パラメータモジュール
@return: シナリオ開始から各タスクの開始時間のリスト 0.1[s]単位
動作確認済
"""
if param.FS != 10.0:
raise NameError("This script can processing 10.0 Hz data.")
# データの読み出しとヘッダ行を飛ばす
cr = csv.reader(open(target_file, "Ur"), delimiter="\t")
for i in range(5):
cr.next()
# データ取り出し
trial_start = []
for r in cr:
if len(r) > 0:
_time = int(r[3])
trial_start.append(int(round(_time / 1000.0, 0)))
else:
break
return trial_start
if __name__ == "__main__":
import myParameter
param = myParameter.myParameter()
target_file = (
"/Users/misato/Documents/eclipse/workspace/TwoChannelNIRS/dataset/presentation_log/ysakaguchi/session1.log"
)
print import_log(target_file, param)
