def __init__(self):
self.c = config.Configuration()
keyFile = open('api_credentials.txt', 'r')
self.key = keyFile.readline().rstrip()
self.secret = keyFile.readline().rstrip()
self.base_url = 'https://api.binance.com'
self.trade_engine = Engine()
self.performance = per.Performance()
# Put imports here
import nearestneighbor
import performance
import random
# Put code for performance analysis here
def setup(size):
global rand_lst
rand_lst = []
for i in range(size):
rand_lst.append((random.random(), random.random()), )
def code():
global rand_lst
nearestneighbor.closest_2d(rand_lst)
for i in range(0, 9):
size = 100 * (2**i)
p = performance.Performance(lambda: code(), lambda: setup(size), 5,
'\n\nNearest Neighbor, size = ' + str(size))
p.evaluate()
p.analyze()
import performance
import ml_predict
import argparse
# code for testing the performance
performance_test = performance.Performance()
performance_test.run()
parser = argparse.ArgumentParser(description="Predict a robot movements in next 2 seconds")
parser.add_argument("--training", help = "file pattern to training data", default = "./inputs/training_data.txt")
parser.add_argument("--input", help = "file pattern to input data", default = "./inputs/test01.txt")
parser.add_argument("--output", help = "file pattern to output data", default = "./output.txt")
# KNN ML predictor performs much better. Therefore, we use it for our final
# output.
args = parser.parse_args()
predictor = ml_predict.MLPredictor(12, args.training)
predictions = predictor.make_prediction(args.input)[0]
print predictions
# output the predictions
with open(args.output, 'w') as f:
for point in predictions:
f.write(str(point[0])+','+str(point[1])+'\n')
] #编译关联文件
TestFile = ["timer/timer.c"]
#待测试测试文件
#/************************************************************/
import sys
sys.path.append(UnitPath + "python")
import common
import performance
import coverage
import index
#处理命令行
common.HandleCmdArg()
#执行代码
try:
try:
File = common.GenerateCmd(FilePath, UnitPath, GccFile) #组装编译命令
GccCmd = common.Gcc + " " + common.Args + " " + File + " -o test " + common.Libs
common.Compile(GccCmd) # 编译文件
common.CreateDir() #生存文件夹
common.ExecuteTest() #执行程序
HtmlCover = coverage.Coverage(FilePath, UnitPath, common.ResultDir,
common.Gcov, TestFile) #生成覆盖率文件
performance.Performance(UnitPath, common.ResultDir,
common.Gprof) #生成性能文件
index.Index(UnitPath, common.ResultDir, HtmlCover) #生成index文件
except UserWarning:
print "编译出错(complie was fault!)"
finally:
common.CleanUp(UnitPath) #清理现场
