Analyses des données

- numpy - pandas - openpyxl - matplotlib - panel==0.13.1a2

import matplotlib import matplotlib.pyplot as plt import asyncio import panel as pn import datetime import pandas as pd import asyncio from panel.io.pyodide import show from pyodide import create_proxy import io ########## def Setup_Button_Listeners(): btnList = document.querySelectorAll(".button") for i in range(len(btnList)): e = document.getElementById(btnList[i].id) btn_event = create_proxy(Process_Button) e.addEventListener("click", btn_event) async def Process_Button(event): if document.getElementById("evtMsg").innerHTML == '100': # button plot_it fig = await process_file() pyscript.write('plot', fig) async def process_file(*args, **kwargs): if file_input.value is not None : file = pd.ExcelFile(file_input.value) data=pd.read_excel(file_input.value,sheet_name=file.sheet_names[1]) # sheet_name = 'C.N.' n, m = data.shape nb_j = 12 * n // (24 * 60) D = [data['Date'][0]] P=[data['Poids'][0]] T = [data['Température'][0]] err=[0] Tc=[data['Température couvain'][0]] for i in range(0, n - 1): D.append(data['Date'][i]) P.append(data['Poids'][i]) T.append(data['Température'][i]) err.append(0) D[i] = D[i].split(' ') D[i] = D[i][0].split('-') + D[i][1].split(':') D[i] = datetime.datetime(int(D[i][0]), int(D[i][1]), int(D[i][2]), int(D[i][3]), int(D[i][4]), int(D[i][5])) Tc.append(data['Température couvain'][i]) # if data['Température couvain'][i]!='NA': # Tc.append(data['Température couvain'][i]) print(D,P) def annomalie_poid(P): for i in range(len(P) - 1): if abs(P[i] - P[i + 1]) > 1: # P[i][1] = P[i + 1][0] - P[i][0] err[i] = 1 P[i] = P[i - 1] def nb_buttineuses(data, n): nb_j = 12 * n // (24 * 60) heure = list( map(int, data['Date'][0].split(' ')[0].split('-') + data['Date'][0].split(' ')[1].split(':'))) t0 = datetime.datetime(heure[0], heure[1], heure[2], 0, 0, 0) heure1 = list(map(int, data['Date'][n - 1].split(' ')[0].split('-') + data['Date'][n - 1].split(' ')[ 1].split(':'))) t1 = datetime.datetime(heure1[0], heure1[1], heure1[2], 0, 0, 0) nb_j = datetime.timedelta(days=(t1 - t0).days) nb_j = nb_j.days print("nb jour=", nb_j) Lj = [[] for i in range(nb_j + 1)] nj_act = 0 Lj[0].append([0, t0]) for i in range(1, n): # heure=data['Date'][i].split(' ') heure = list(map(int, data['Date'][i].split(' ')[0].split('-') + data['Date'][i].split(' ')[1].split( ':'))) time = datetime.datetime(heure[0], heure[1], heure[2], heure[3], heure[4], heure[5]) # tdelta=datetime.timedelta(days=time.day-t0.day) if Lj[nj_act] != [] and Lj[nj_act][0][1].day != time.day: nj_act += 1 Lj[nj_act].append([i, time]) # print(nj_act) else: Lj[nj_act].append([i, time]) D = [] dP = [0] moy = [] miel_j = [0] miel_tot = [0] # ventil = [] # tracey=[] # tracex = [] Lj.pop() while Lj[-1] == []: Lj.pop() for day in Lj: anomalie = False for id in day: if err[id[0]] != 0: anomalie = True if anomalie: dP.append(dP[-1]) D.append(day[0][1]) miel_j.append(miel_j[-1]) miel_tot.append(miel_tot[-1]) # ventil.append(ventil[-1]) else: min = 1000 h7 = 0 ibis = 0 for id in day: i, date = id if date.hour > 6 and date.hour < 9 and min > data['Poids'][day[ibis][0]]: min = data['Poids'][day[ibis][0]] else: min = max(0, min) if date.hour == 7: h7 = data['Poids'][day[ibis][0]] else: h7 = max(h7, 0) ibis += 1 # print(day[1],min) dP.append(max((h7 - min) / (80 * 10 ** -6) / 500,0)) miel_j.append((data['Poids'][day[-1][0]] - data['Poids'][day[0][0]])) # ventil.append((max_n[0] - data['Poids'][day[6 * 60 // 12][0]])*10) if miel_tot == []: miel_tot.append(miel_j[-1]) else: miel_tot.append(miel_tot[-1] + miel_j[-1]) D.append(day[0][1]) if len(dP) <= 2: moy.append(sum(x for x in dP) / (len(dP))) else: moy.append(sum((dP[-1], dP[-2], dP[-3])) / 3) dP.pop() miel_j.pop() miel_tot.pop() moy.pop(0) moy.append((dP[-1] + dP[-2]) / 2) return D, err, moy, miel_j, miel_tot annomalie_poid(P) d, err,moy, miel_j, miel_tot = nb_buttineuses(data, n) fig, axs = plt.subplots(4,1) axs[0].plot(D, P, linestyle='-', color='b', label='Poids') first=False for i in range(len(err)): if err[i]!=0 and not first: first=True axs[0].axvline(D[i], linestyle='--',color='k',label='annomalie de poids') elif err[i]!=0 and first: axs[0].axvline(D[i], linestyle='--', color='k') axs[0].set_title('Poids et erreur') axs[0].legend() axs[0].tick_params('x', labelrotation=20) axs[0].grid() axs[1].plot(d, moy, linestyle='-', color='g', label='nombre de buttineuses') axs[1].set_title('Activité de la ruche') axs[1].legend() axs[1].tick_params('x', labelrotation=20) axs[1].grid() axs[2].plot(d, miel_j, linestyle='-', color='r', label=' miel journalier (depuis j1)') axs[2].plot(d, miel_tot, linestyle='-', color='y', label='miel total') axs[2].set_title('Evolution du miel (en kg)') axs[2].legend() axs[2].tick_params('x', labelrotation=20) axs[2].grid() axs[3].plot(D, T, linestyle='-', color='b',label='Température') axs[3].plot(D, Tc, linestyle='-', color='y', label='Température du couvain') axs[3].legend() axs[3].set_title('Températures') axs[3].tick_params('x', labelrotation=20) axs[3].grid() # fig.tight_layout() fig.set_figwidth(15) fig.set_figheight(40) fig return fig else: print("mauvaise feuille") file_input = pn.widgets.FileInput(accept='.xlsx', width=180) row = pn.Row(file_input, height=75) await show(row, 'fileinput') Setup_Button_Listeners()

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