def convert_to_pivot():
"""
統一ピボット形式へデータを変換
"""
# データ置き場
target_directory = "analysis/result/Comparison_20160222"
# 対象
target_method = "LDA"
target_data = "all"
plot_type = "box"
# pivot作成対象となるデータのパラメータ、結果ファイル名を格納したtable.csvを読込む
parameter_list, filename_list = read_table(os.path.join(target_directory, target_method, "table.csv"))
# パラメータの読み込み
parametername_list = ["_".join(str(p)) for p in parameter_list]
# 対応するデータの読み込み
data_list = []
for i in range(len(filename_list)):
target_filename = os.path.join(target_directory, target_method, filename_list[i])
# データの読み込み
_subject_list, _data_list = read_data(target_filename, target_data)
data_list.append(_data_list)
#
header_list = ["signal", "re_method", "re_size", "feature", "nfold",
"subject_id","accuracy","loss","average_precition",
"average_recall","average_Fmeasure","average_distance","corr","p_value"]
output_filename = os.path.join(target_directory, target_method + ".csv")
generate_pivot(header_list, parameter_list, data_list, output_filename)
def convert_to_pivot():
"""
統一ピボット形式へデータを変換
"""
# データ置き場
target_directory = "analysis/result/Comparison_20160222"
# 対象
target_method = "LDA"
target_data = "all"
plot_type = "box"
# pivot作成対象となるデータのパラメータ、結果ファイル名を格納したtable.csvを読込む
parameter_list, filename_list = read_table(
os.path.join(target_directory, target_method, "table.csv"))
# パラメータの読み込み
parametername_list = ["_".join(str(p)) for p in parameter_list]
# 対応するデータの読み込み
data_list = []
for i in range(len(filename_list)):
target_filename = os.path.join(target_directory, target_method,
filename_list[i])
# データの読み込み
_subject_list, _data_list = read_data(target_filename, target_data)
data_list.append(_data_list)
#
header_list = [
"signal", "re_method", "re_size", "feature", "nfold", "subject_id",
"accuracy", "loss", "average_precition", "average_recall",
"average_Fmeasure", "average_distance", "corr", "p_value"
]
output_filename = os.path.join(target_directory, target_method + ".csv")
generate_pivot(header_list, parameter_list, data_list, output_filename)
def visualize():
# データ置き場
target_directory = "analysis/result/Comparison_20160222"
# 視覚化対象
target_method = "LDA"
target_data = "accuracy"
plot_type = "box"
# 描画
parameter_list, filename_list = read_table(os.path.join(target_directory, target_method, "table.csv"))
parametername_list = ["_".join(p) for p in parameter_list]
data_list = []
for i in range(len(parameter_list)):
target_filename = os.path.join(target_directory, target_method, filename_list[i])
subject, data = read_data(target_filename, target_data)
data_list.append(data)
data_size = len(data_list)
box_plot(data_list[:data_size/3], parametername_list[:data_size/3], target_data, 0.0, _title = "HBX")
box_plot(data_list[data_size/3:data_size/3*2], parametername_list[data_size/3:data_size/3*2], target_data, 0.0, _title = "HBX3")
box_plot(data_list[data_size/3*2:], parametername_list[data_size/3*2:], target_data, 0.0, _title = "HBX1")
def visualize():
# データ置き場
target_directory = "analysis/result/Comparison_20160222"
# 視覚化対象
target_method = "LDA"
target_data = "accuracy"
plot_type = "box"
# 描画
parameter_list, filename_list = read_table(
os.path.join(target_directory, target_method, "table.csv"))
parametername_list = ["_".join(p) for p in parameter_list]
data_list = []
for i in range(len(parameter_list)):
target_filename = os.path.join(target_directory, target_method,
filename_list[i])
subject, data = read_data(target_filename, target_data)
data_list.append(data)
data_size = len(data_list)
box_plot(data_list[:data_size / 3],
parametername_list[:data_size / 3],
target_data,
0.0,
_title="HBX")
box_plot(data_list[data_size / 3:data_size / 3 * 2],
parametername_list[data_size / 3:data_size / 3 * 2],
target_data,
0.0,
_title="HBX3")
box_plot(data_list[data_size / 3 * 2:],
parametername_list[data_size / 3 * 2:],
target_data,
0.0,
_title="HBX1")