print("Read config from " + os.path.abspath(r_cfg_file))

config = configparser.ConfigParser()

config.read(r_cfg_file, encoding='utf-8')

config_dict = dict(config.items(section))

# print(config.sections())

print('{0} = {1}'.format(section, config_dict))

print("Save config to " + os.path.abspath(w_cfg_file))

config = configparser.ConfigParser()

config.read(w_cfg_file, encoding='utf-8')

config.set(section, key, value)

with open(w_cfg_file, 'w', encoding='utf-8') as cfgfile:

global uploadTime

global collectRange

global collectTime

try:

def wirtedata(datatype,datavalue):

headers = ['type', 'value', 'createTime', 'sensorId']

rows = [

datatype,

datavalue,

time_now,

fj_id['id']

]

print('rows',rows)

with open('/home/pi/laser/python_demo/data.csv', 'a')as f:

f_csv = csv.writer(f)

#f_csv.writerow(headers)

f_csv.writerow(rows)

json_url = url['laserres_url']

#url = 'http://192.168.199.124:12521/laser-data/laserDataupload.do'

#url1 = url.encode('url-8')

OriginData = {

"createTime": time_now,

"sensorId": fj_id['id'],

"value": datavalue,

"type" : datatype

}

print(OriginData)

resp = requests.post(json_url, json = OriginData,timeout=5)

if(resp.status_code == 200):

json = resp.json()

print(json)

collectTime = json['data']['collectTime']

collectRange = json['data']['collectRange']

uploadTime = json['data']['uploadTime'] * 10

print('\033[1;33m post k = {0}\033[0m'.format(uploadTime))

print('RECORD_SECONDS', collectTime)

print('sleep_time', collectRange)

set_config(cfg_file,'record_time','collect_time')

set_config(cfg_file, 'record_time','collect_range')

set_config(cfg_file, 'record_time', 'update_time')

else:

#upload failed ,save data to csv

print('\033[1;35mupload failed ,save to csv \033[0m')

wirtedata(datatype,datavalue)

except :

print('weizhiyichang')

print('\033[1;35mupload failed ,save to csv \033[0m')

global laser_filename

global time_now

print('laser record...')

time_now = str(int(time.time()))

print(serial.port)

#file_dir = "./"

laser_filename = save_dir['datadir']+'laser_'+time_now+'_'+ fj_id['id']+'.txt'

print(laser_filename)

time1 = int(time.time())

#laser_record_time = 5

if not serial.is_open:

print('open')

serial.open()

try:

while True:

Byte_H = serial.read(1)

Byte_L = serial.read(1)

res = (ord(Byte_H) & 0x7f) * 128 + (ord(Byte_L) & 0x7f)

print(res)

ss = str(res) + '\n'

with open(laser_filename, 'a') as f:

f.write(ss)

time2 = int(time.time())

#print(time2)

#print(time1)

print(time2 - time1)

if (time2 - time1 == collectTime):

print('close')

serial.close()

print(serial.isOpen())

except Exception as e:

global am_ratio

global am_diff

# 原始数据

data = []

# 这里是读取文件中的数据

#file = open("/home/pi/laser/python_demo/laser_1603765204_sdrc54350.txt")

file = open(laser_filename)

for line in file.readlines():

data.append(float(line.split()[0]))

f = 312.66 # 频率hz

Lt = 15590 # 距离阈值

Lt_ = 4000 # 距离下阈值

filt_per = 0.2 # 头尾数据过滤百分比

quan_di = 0.8

quan_zh = 0.6

quan_ga = 0.6 # 低中高风速下的权重

di_w = 10

zh_w = 8

ga_w = 6 # 低中高转速临界值

# 叶片原始距离数据

data123 = []

data12 = []

data1 = []

data2 = []

data3 = []

# 清洗后的叶片距离数据

data11 = []

data22 = []

data33 = []

# 叶片转速

w1 = []

w2 = []

w3 = []

# 叶片均值

la1 = []

la2 = []

la3 = []

# 叶片标准差

ld1 = []

ld2 = []

ld3 = []

# 叶片振幅

am1 = []

am2 = []

am3 = []

index1 = [] # 一号叶片

index2 = [] # 二号叶片

index3 = [] # 三号叶片

# print(np.where(np.array(data12)<Lt))

for index, value in enumerate(data[:-2]):

if value > Lt:

data12.append(value)

if value < Lt and value > Lt_:

if np.min([data[index - 2], data[index - 1], data[index + 1], data[index + 2]]) < Lt:

data12.append(value)

# 筛选阈值以内的数据

b = np.where(np.array(data12) < Lt)

# 一些初始参数

k = 1

t3 = b[0][0]

m3 = 0

m2 = 0

q1 = []

q2 = []

q3 = []

am_ratio = [] # 最大幅值与最小之比

am_diff = [] # 幅值之差

for index, value in enumerate(b[0]):

# print(value,b[0][index])

data123.append(data12[value])

print(data123)

for index, value in enumerate(b[0]):

if b[0][index] - b[0][index - 1] > 3:

if k == 1:

t1 = value

m1 = index

w_1 = 1 / 3 * 60 * f / (t1 - t3)

w1.append(w_1)

recount1 = int((m1 - m3 + 1) * filt_per) # 设置去掉头尾的数据，剩余的用来求均值和方差

x1max = np.mean(data123[m3 + recount1:m1 - recount1]) + 2 * np.std(

data123[m3 + recount1:m1 - recount1]) # 2倍σ以下

x1min = np.mean(data123[m3 + recount1:m1 - recount1]) - 2 * np.std(

data123[m3 + recount1:m1 - recount1]) # 2倍σ以上

d1new = list(filter(lambda x: (x < x1max or x == x1max) and (x > x1min or x == x1min), data123[m3:m1]))

aam1 = np.max(d1new) - np.min(d1new)

am1.append(aam1)

data11.extend(d1new)

q1.append(len(data11))

# print(data11)

# qqq.append(len(data11))

# print(np.median(data1))

# print(np.std(data1))

# la1.append(np.average(list(filter(lambda x : x < np.median(data123[m3:m1])+3*np.std(data123[m3:m1]) ,data123[m3:m1]))))

la1.append(np.average(d1new))

ld1.append(np.std(d1new))

# print(t1,m1)

if k == 2:

t2 = value

m2 = index

w_2 = 1 / 3 * 60 * f / (t2 - t1)

w2.append(w_2)

recount2 = int((m2 - m1 + 1) * filt_per) # 设置去掉头尾部分的数据，剩余的用来求均值和方差

x2max = np.mean(data123[m1 + recount2:m2 - recount2]) + 2 * np.std(

data123[m1 + recount2:m2 - recount2]) # 2倍σ以下

x2min = np.mean(data123[m1 + recount2:m2 - recount2]) - 2 * np.std(

data123[m1 + recount2:m2 - recount2]) # 2倍σ以上

print(recount2, x2max, x2min)

d2new = list(filter(lambda x: (x < x2max or x == x2max) and (x > x2min or x == x2min), data123[m1:m2]))

# print(d2new)

aam2 = np.max(d2new) - np.min(d2new)

am2.append(aam2)

data22.extend(d2new)

q2.append(len(data22))

la2.append(np.average(d2new))

ld2.append(np.std(d2new))

# print(t2,m2)

if k == 3:

t3 = value

m3 = index

w_3 = 1 / 3 * 60 * f / (t3 - t2)

w3.append(w_3)

recount3 = int((m3 - m2 + 1) * filt_per) # 设置去掉头尾部分的数据，剩余的用来求均值和方差

x3max = np.mean(data123[m2 + recount3:m3 - recount3]) + 2 * np.std(

data123[m2 + recount3:m3 - recount3]) # 2倍σ以下

x3min = np.mean(data123[m2 + recount3:m3 - recount3]) - 2 * np.std(

data123[m2 + recount3:m3 - recount3]) # 2倍σ以上

d3new = list(filter(lambda x: (x < x3max or x == x3max) and (x > x3min or x == x3min), data123[m2:m3]))

aam3 = np.max(d3new) - np.min(d3new)

am3.append(aam3)

data33.extend(d3new)

q3.append(len(data33))

la3.append(np.average(d3new))

ld3.append(np.std(d3new))

amm_ratio = np.max([aam1, aam2, aam3]) / np.min([aam1, aam2, aam3])

am_ratio.append(amm_ratio)

amm_diff = np.max([aam1, aam2, aam3]) - np.min([aam1, aam2, aam3])

am_diff.append(amm_diff)

w_mean = (w_1 + w_2 + w_3) / 3

quan = np.select([w_mean >= ga_w, w_mean >= zh_w, w_mean >= di_w],

[quan_ga, quan_zh, quan_di]) # 低中高风速下的权重

# print(t3,m3)

k = 1 if k == 3 else k + 1

if k == 1:

index1.append(value)

data1.append(data[value])

if k == 2:

index2.append(value)

data2.append(data[value])

if k == 3:

index3.append(value)

data3.append(data[value])

# print(data11)

# print(la1)

# print(la2)

# print(w1,w2,w3)

ytickmin = int((np.min([np.min(data11), np.min(data22), np.min(data33)])))

while not is_exit:

try:

if event_laser_record.is_set():

event_laser_record.clear()

laser_record()

event_laser_jisuan.set()

else:

event_laser_record.wait()

except ValueError as e:

print("record error")

while not is_exit:

try:

if event_laser_jisuan.is_set():

event_laser_jisuan.clear()

print('laser jisuan start！')

laser_jisuan()

print('laser jisuan ok!')

event_laser_post.set()

else:

event_laser_jisuan.wait()

except BaseException as e:

print(e)

global collectRange

global collectTime

global count

global uploadTime

''' 文件上传'''

#30一次post laser 原始文件

laser_count = 0

while not is_exit:

try:

if event_laser_post.is_set():

event_laser_post.clear()

print('upload')

postmydata("ratio",am_ratio)

postmydata("diff",am_diff)

print("post res ok!")

# upload

#laser_url = 'http://192.168.199.124:10001/file/fileUpload/laser'

laser_url = url['laser_url']

print(laser_url)

#上传原始文件

laser_count = laser_count + 1

print('\033[1;33m laser post count = {0}/{1}\033[0m'.format(laser_count,uploadTime))

if laser_count == uploadTime:

#喂狗

laser_count = 0

file3 = {'fileName': open(laser_filename, 'rb')}

response = requests.post(laser_url, files=file3)

if response.status_code == 200:

json = response.json()

print(json)

collectTime = json['data']['collectTime']

collectRange = json['data']['collectRange']

uploadTime = json['data']['uploadTime'] * 10

print('\033[1;33m post k = {0}\033[0m'.format(uploadTime))

print('RECORD_SECONDS', collectTime)

print('sleep_time', collectRange)

os.remove(laser_filename)

# event_video_record.set()

else:

event_laser_post.wait()

except BaseException as e:

print(e)

global thread_laser_record

if thread_laser_record is None:

print("laser_record_thread_start")

thread_audio_record = threading.Thread(target=laser_record_thread)

thread_audio_record.setDaemon(True)

global thread_laser_jisuan

if thread_laser_jisuan is None:

print("laser_jisuan_thread_start")

thread_laser_jisuan = threading.Thread(target=laser_jisuan_thread)

thread_laser_jisuan.setDaemon(True)

global thread_laser_post

if thread_laser_post is None:

print("laser_post_thread_start")

thread_laser_post = threading.Thread(target=laser_post_thread)

thread_laser_post.setDaemon(True)

laser_record_thread_start()

laser_jisuan_thread_start()

laser_post_thread_start()

while not is_exit:

# start record

event_laser_record.set()

#event_laser_jisuan.set()

print('sleep for ', collectRange)