def analyze_data2(save_var, sample_size, weight_values, file_path, data_filename):
if not weight_values:
return
_datalist, _fencelist, f, ss = [0.0], [], Fence(), sample_size+10
_fencelist.append(f)
total_weight = 0.0
for i in range(len(weight_values)):
try:
data = float(weight_values[i])
except:
continue
_datalist.append(data)
########## Algorithms Part ##########
if (data - total_weight) >= save_var: # record weight
_fencelist[-1].piglet_list[-1].weight_list.append(data)
elif (total_weight - data) >= save_var: # pick up pig
if data < save_var:
total_weight = 0.0
f = Fence()
_fencelist.append(f)
# claculate the average
if(len(_fencelist[-1].piglet_list[-1].weight_list)) >= ss:
temp_list = _fencelist[-1].piglet_list[-1].weight_list[(ss-sample_size):]
for i in range(len(temp_list)):
temp_list[i] -= total_weight
temp_list[i] = round(temp_list[i],2)
_fencelist[-1].piglet_list[-1].real_weight_list = [""] * (ss-sample_size)
_fencelist[-1].piglet_list[-1].real_weight_list.extend(temp_list)
_fencelist[-1].piglet_list[-1].weight = round(np.mean(temp_list),2)
total_weight += round(np.mean(temp_list), 2)
_fencelist[-1].weight = total_weight
p = Pig() # create a new pig
_fencelist[-1].piglet_list.append(p)
_fencelist[-1].piglet_num = len(_fencelist[-1].piglet_list) -1
x = PrettyTable()
x.field_names = ["pig"]
for k in range(1, ss + 1):
x.field_names.append(str(k))
x.field_names.append("weight")
for i in range(len(_fencelist[0].piglet_list)):
temp = [str(i+1)+"_measure"]
temp.extend(list(_fencelist[0].piglet_list[i].weight_list))
temp.append(_fencelist[0].piglet_list[i].weight)
while(len(temp) < ss + 2):
temp.append("none")
x.add_row(temp)
temp = [str(i+1)+"_calculate"]
temp.extend(list(_fencelist[0].piglet_list[i].real_weight_list))
temp.append(_fencelist[0].piglet_list[i].weight)
while(len(temp) < ss + 2):
temp.append("none")
x.add_row(temp)
datafile = open(today()+'.html','a', newline='')
datafile.write(data_filename + ' method2, sample: '+str(sample_size)+ x.get_html_string()+'\n===========\n')
datafile.write('\n')
datafile.close()
analyzed_data_output("Method2", file_path, data_filename, _fencelist)
def __init__(self, parent, controller, system):
tk.Frame.__init__(self, parent)
self.controller = controller
self.system = system
# initial frame
self.data_frame()
self.weight_frame()
self.table_frame()
# start weighting
self.system.datafile = open(today()+'_'+time()+'.log',"w")
f = Fence()
self.system.fence_list.append(f)
self.totalWeight = 0.0
self.zeroing()
self.system.serialthread.start()
self.read_data()
def output_csv(self):
file_path = getcwd() #取路徑的資料
with open(file_path + "/" + today() + "weaned weight" +'.csv','a+',encoding="utf-8",newline='') as csv_file:
write = csv.writer(csv_file)
header = ["sow id", "piglet id", "weight","fence weight","number born alive"]
write.writerow(header)
print("===OUTPUT CSV DEBUG PART===")
for j in range(len(self.system.fence_list)-1):
print("fence_weight: "+str(self.system.fence_list[j].weight)) # 印在終端機的
if self.system.fence_list[j].weight is not None:
for i in range(len(self.system.fence_list[j].piglet_list)-1):
print("pig_weight: "+str(self.system.fence_list[j].piglet_list[i].weight))
temp = self.system.fence_list[j].pig_id[i] # [母豬，小豬]
temp.append(str(self.system.fence_list[j].piglet_list[i].weight)) # [母豬，小豬，小豬重量]
print(list_to_str(temp)) # 印在終端機的
write.writerow(temp)
temp1 = ["", "", "", self.system.fence_list[j].weight, len(self.system.fence_list[j].piglet_list)-1]
write.writerow(temp1)
print("===OUTPUT CSV DEBUG PART===")
def analyzed_data_output(statistic_method, file_path, data_filename, _fencelist):
#儲存不同統計方法所得之秤重值，並輸出至csv檔
with open(file_path + "/" + today() + "analyzed data" +'.csv','a',encoding="utf-8",newline='') as csv_file:
write = csv.writer(csv_file)
inner_list = [data_filename, str(statistic_method)]
for j in range(1):
# for j in range(len(_fencelist)):
for i in range(len(_fencelist[j].piglet_list)):
if _fencelist[j].piglet_list[i].weight is not None:
inner_list.append(_fencelist[j].piglet_list[i].weight)
analyzed_datalist = [inner_list]
print(analyzed_datalist)
output_list = zip(*analyzed_datalist)
write.writerows(output_list)
return analyzed_datalist
def analyze_data4(save_var, sample_size, weight_values, file_path, data_filename):
if not weight_values:
return
_datalist, _fencelist, f, ss = [0.0], [], Fence(), sample_size+10
_fencelist.append(f)
total_weight = 0.0
for i in range(len(weight_values)):
try:
data = float(weight_values[i])
except:
continue
_datalist.append(data)
########## Algorithms Part ##########
if (data - total_weight) >= save_var: # record weight
_fencelist[-1].piglet_list[-1].weight_list.append(data)
elif (total_weight - data) >= save_var: # pick up pig
if data < save_var:
total_weight = 0.0
f = Fence()
_fencelist.append(f)
# claculate the average
if(len(_fencelist[-1].piglet_list[-1].weight_list)) >= ss:
temp_list = _fencelist[-1].piglet_list[-1].weight_list[(ss-sample_size):]
for i in range(len(temp_list)):
temp_list[i] -= total_weight
temp_list[i] = round(temp_list[i], 2)
_fencelist[-1].piglet_list[-1].real_weight_list = [""] * (ss-sample_size)
_fencelist[-1].piglet_list[-1].real_weight_list.extend(temp_list)
# ave = round(mean(temp_list), 2) # 平均
# std_err = round(std(temp_list), 2) # 標準差
# _fencelist[-1].piglet_list[-1].std_err = std_err
ave = np.mean(temp_list) # 平均
std_err = np.std(temp_list) # 標準差
_fencelist[-1].piglet_list[-1].std_err = round(std_err,2)
temp_list_std, _fencelist[-1].piglet_list[-1].mark_std = [], [0] * ss
for i in range(len(temp_list)):
if abs(temp_list[i] - ave) <= 0.8*std_err:
temp_list_std.append(temp_list[i])
_fencelist[-1].piglet_list[-1].mark_std[i+(ss-sample_size)] = 1
_fencelist[-1].piglet_list[-1].std_weight_list = temp_list_std
last_ave = round(np.mean(temp_list_std), 2)
_fencelist[-1].piglet_list[-1].weight = last_ave
total_weight += last_ave
_fencelist[-1].weight = total_weight
p = Pig() # create a new pig
_fencelist[-1].piglet_list.append(p)
_fencelist[-1].piglet_num = len(_fencelist[-1].piglet_list) -1
x = PrettyTable()
x.field_names = ["pig"]
for k in range(1, ss+1):
x.field_names.append(str(k))
x.field_names.extend(["std", "weight"])
for i in range(len(_fencelist[0].piglet_list)):
if _fencelist[0].piglet_list[0] == 0.0:
continue
temp = [str(i+1)+"_measure"]
temp.extend(list(_fencelist[0].piglet_list[i].weight_list))
while(len(temp) < ss + 3):
temp.append("none")
x.add_row(temp)
temp = [str(i+1)+"_calculate"]
temp.extend(list(_fencelist[0].piglet_list[i].real_weight_list))
temp.append(_fencelist[0].piglet_list[i].std_err)
while(len(temp) < ss + 3):
temp.append("none")
x.add_row(temp)
temp = [str(i+1)+"_std"]
for j in range(len(_fencelist[0].piglet_list[i].real_weight_list)):
if j < ss-sample_size:
continue
if _fencelist[0].piglet_list[i].mark_std[j] == 0:
_fencelist[0].piglet_list[i].real_weight_list[j] = '-'
temp.extend(_fencelist[0].piglet_list[i].real_weight_list)
while(len(temp) < ss + 1):
temp.append("none")
temp.append(_fencelist[0].piglet_list[i].std_err)
temp.append(_fencelist[0].piglet_list[i].weight)
x.add_row(temp)
datafile = open(today()+'.html', 'a', newline='\n')
datafile.write(data_filename+' method4, sample: '+str(sample_size)+x.get_html_string()+'\n===========\n')
datafile.write('\n')
datafile.close()
analyzed_data_output("Method4", file_path, data_filename, _fencelist)
def read_data(self): #讀取資料
value = True
while self.system.dataQueue.qsize():
try: # get data from queue
data = self.system.dataQueue.get()
currentTime = self.system.timeQueue.get()
# print("original data: "+ str(data))
data = data.decode().strip("ST,GS,").strip("US,GS,").strip("ST,NT,").strip("ST,TR,").strip("OL,GS")
data = data.strip().strip("kg").strip().strip("+").replace(" ", "")
if value:
try: # transfer to float
data = float(data)
value = False
error = 0
except:
error = 1
print("read_data except_error")
if not error:
self.weight_var.set(data)
# local_dt = datetime.utcnow().replace(tzinfo=pytz.utc).astimezone(pytz.timezone('Asia/Taipei'))
# currentTime = pytz.timezone('Asia/Taipei').normalize(local_dt).strftime('%H:%M:%S\'%f')[:-3]
print("serial: " + currentTime + " " + str(data))
self.system.datafile.write(currentTime + " " + str(data) + "\n")
########## Algorithms Part ##########
if (data - self.totalWeight) >= self.system.threshold: # record weight
self.system.fence_list[-1].piglet_list[-1].weight_list.append(data)
self.system.fence_list[-1].piglet_list[-1].time_list.append(currentTime)
self.pig_weight_show.configure(bg="gray77",fg="gray77")
self.litter_weighing_show.configure(bg="gray77",fg="gray77")
elif (self.totalWeight - data) >= self.system.threshold: # pick up pig
if data < self.system.threshold and data >=0:
self.litter_weight.set(str(round(self.system.fence_list[-1].weight,2))+"kg")
self.litter_weighing_show.configure(bg="white",fg="black")
self.en_sow.configure(font=("Calibri",26),width=10, fg="red")
self.input_sow_id.set("請輸入耳號")
self.totalWeight = 0.0
self.clear_table()
self.system.datafile.close()
self.system.datafile = open(today()+'_'+time()+'.log',"w")
f = Fence()
self.system.fence_list.append(f)
self.zeroing()
# claculate the average
statement = False #自動/手動決定重量有不同的判斷式
if (len(self.system.fence_list[-1].piglet_list[-1].weight_list)) >= self.system.sampleSize:
if self.system.autoMode:
statement = True
if str(self.focus_get()) == ".!frame.!frame.!button2":
if not self.system.autoMode:
statement = True
local_dt = datetime.utcnow().replace(tzinfo=pytz.utc).astimezone(pytz.timezone('Asia/Taipei'))
tmp = pytz.timezone('Asia/Taipei').normalize(local_dt).strftime('%H:%M:%S\'%f')[:-3] + " press_decide_weight_button\n"
self.system.datafile.write(tmp) #記錄按按鈕的時間
if statement:
# check if stationary or not
index = self.system.fence_list[-1].piglet_list[-1].index
temp_list = self.system.fence_list[-1].piglet_list[-1].weight_list[index:index+self.system.sampleSize]
time_list = self.system.fence_list[-1].piglet_list[-1].time_list[index:index+self.system.sampleSize]
self.system.fence_list[-1].piglet_list[-1].index += 1
# pass the temp_list and time_list into kpss_test function to check if it is stationary or not
ser_data = pd.Series(temp_list, index=time_list)
self.system.fence_list[-1].piglet_list[-1].kptest.append(1 if kpss_test(ser_data) else 0) # record the kpss return value
if len(self.system.fence_list[-1].piglet_list[-1].kptest) < 5:
continue # less than five times
if self.system.fence_list[-1].piglet_list[-1].kptest[-5:] != [1]*5:
continue # the latest five value is not stationary
# is stationary! -> calculate the average
temp_list = self.system.fence_list[-1].piglet_list[-1].weight_list[index-4:index+self.system.sampleSize]
temp_list = [round(i-self.totalWeight, 2) for i in temp_list] # minus the former totalWeight to get actual weight
last_ave = round(np.mean(temp_list), 2) # get the average
self.system.fence_list[-1].piglet_list[-1].weight = last_ave # record the pig weight actual value
self.totalWeight += last_ave # renew totalWeight
self.system.fence_list[-1].weight = self.totalWeight # record the fence weight
# 儲存豬耳號
temp_ID=[self.input_sow_id.get() ,self.input_piglet_id.get()]
self.system.fence_list[-1].pig_id.append(temp_ID) # record ID
self.tree.insert("","end",values=[self.input_piglet_id.get(), str(last_ave)]) # add pigID and weight in the table
self.update_minmax(last_ave) # update the min and max value
# claculate pig number
if self.system.fence_list[-1].piglet_list is not []:
self.piglet_save_num.set("已存豬數："+str(len(self.system.fence_list[-1].piglet_list)))
self.system.fence_list[-1].piglet_num = len(self.system.fence_list[-1].piglet_list)
# show information on GUI
self.piglet_weight.set(str(round(self.system.fence_list[-1].piglet_list[-1].weight,2))+"kg")
self.pig_weight_show.configure(bg="white",fg="black")
self.en_piglet.configure(font=("Calibri",26),width=10, fg="red")
self.input_piglet_id.set("請輸入耳號")
# create a new pig, be ready to weight the next pig
p = Pig()
self.system.fence_list[-1].piglet_list.append(p)
except queue.Empty:
pass
self.weight_value_show = self.label_weighing_nowshow.after(100, self.read_data)