Python Plugins.showMsgBox方法代码示例

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def removeoutlier():
    if len(ep.EpmDatasetPens.SelectedPens) != 1:
        ep.showMsgBox("EPM - Histograma",
                      "Execute a consulta do Dataset Analysis \n e selecione uma pena antes de aplicar a funcao.",
                      "Warning")
        return 0

    epm_tag = ep.EpmDatasetPens.SelectedPens[0].Values
    
    FATOR = 1.5
    values = epm_tag["Value"]

    q3, q1 = np.percentile(values, [75, 25])
    iqr = q3 - q1

    lowpass = q1 - (iqr * FATOR)

    highpass = q3 + (iqr * FATOR)   


    epmarray = np.dtype([('Value','>f8'),('Timestamp','object'),('Quality','object')])


    print data 

    ep.plotValues('No_Outliers',values)

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def histograma():
    # Verifica se existe apenas uma pena selecionada no Dataset Analysis.
    if len(ep.EpmDatasetPens.SelectedPens) != 1:
        ep.showMsgBox("EPM - Histograma",
                      "Execute a consulta do Dataset Analysis \n e selecione uma pena antes de aplicar a funcao.",
                      "Warning")
        return 0

    # Passa para a variavel 'epm_tag' a variavel selecionada.
    epm_tag = ep.EpmDatasetPens.SelectedPens[0].Values
    x = epm_tag["Value"]
    mu = epm_tag["Value"].mean()  # Mediana da amostra
    sigma = epm_tag["Value"].std()  # Desvio padrao da amostra

    # Quantidade de valores que desejamos agrupar. (barras verdes)
    num_bins = 20
    # Gera o histograma
    n, bins, ignore = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)
    # Adiciona uma linha indicando a curva de normalidade (vermelha tracejada)
    y = mlab.normpdf(bins, mu, sigma)
    plt.plot(bins, y, 'r--')
    plt.title("Histograma  \n $\mu=" + "{:.3f}".format(mu) + "$, $\sigma=" + "{:.3f}".format(sigma) + "$")

    # Mostra na tela o gráfico
    plt.subplots_adjust(left=0.15)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def windSpeedPowerChart():
    """Grafico de potencia com a velocidade do vento
    Apresenta um grafico de dispersao da potencia com a velocidade do vento e calcula a curva que melhor o representa
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 2:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select two interpolated pens before applying this function!', 'Warning')
        return 0
    global minSpeed
    global nominalPower    
    runDialogMinSpeedNomPower()
    minSpeed = float(minSpeed)
    nominalPower = float(nominalPower)
    rawSpeed, rawPower = getSpeedPowerValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1])
    speed, power = cleanSpeedPowerData(rawSpeed, rawPower, minSpeed, nominalPower )
    xm, ym = windPowerAverage(speed, power)
    par0 = [1.0, 1.0, 1500.0, 1.0]
    binSpeed = 0.5
    parest,cov,infodict,mesg,ier = optimize.leastsq(residualsSPPn4, par0, args=(xm, ym), full_output=True)
    xEst = np.arange(xm.min(), xm.max(), binSpeed)
    yEst = powerFitPn4(parest, xEst)
    posAbove = np.argwhere(yEst > nominalPower)
    yEst[posAbove] = nominalPower
    fig1 = plt.figure()
    ax1 = fig1.add_subplot(1, 1, 1)
    ax1.set_ylim(0, 1.05*nominalPower)
    ax1.set_xlim(minSpeed-1, 1.1*speed.max())
    ax1.set_xlabel(r'$Speed (m/s)$')
    ax1.set_ylabel(r'$Power (KW)$')    
    ax1.scatter(speed, power)
    ax1.plot(xEst, yEst, color='r', linewidth=3)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def windDirectionPieChart():
    """Grafico de pizza da direcao do vento
    Apresenta um grafico de pizza baseado no percentual de tempo da direcao do vento
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 1:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select one pen before applying this function!', 'Warning')
        return 0
    rawDirection = ep.EpmDatasetPens.SelectedPens[0]
    nodesPercents, nodesLabels = percentTimeIn(rawDirection.Values)
    colors = ['blue','yellowgreen', 'cyan', 'gold', 'lightskyblue', 'magenta', 'green', 'lightcoral']
    plt.pie(nodesPercents[:,1], labels=nodesLabels, colors=colors,autopct='%1.1f%%', shadow=False, startangle=90)
    plt.axis('equal')
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def PolarScatterWindDirection():
    """Grafico polar de dispersao da direcaodo vento
    Apresenta um grafico polar de dispersao com a direcao do vento
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 2:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select 2 interpolated pens before applying this function!', 'Warning')
        return 0
    speed, direction = getSpeedDirectionValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1])
    ax1 = plt.subplot(111, polar=True)
    ax1.set_theta_zero_location('N')
    ax1.set_theta_direction(-1)
    ax1.grid(True)
    ax1.xaxis.set_ticklabels(['N',r"$45^{o}$",'E',r"$135^{o}$",'S',r"$225^{o}$",'W', r"$315^{o}$"])
    ax1.set_title("Wind direction", va='bottom')
    ax1.plot(direction, speed, 'bo')
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def PolarScatterAreaWind():
    """Grafico polar de dispersao-area da direcao, velocidade e potencia do vento
    Apresenta um grafico polar de dispersao com a direcao, a velocidade e potencia do vento
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 3:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select 3 interpolated pens before applying this function!', 'Warning')
        return 0
    speed, direction, power = getSpeedPowerDirectionValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1],
                                                           ep.EpmDatasetPens.SelectedPens[2])
    colors = power/1000.
    area = np.pi * speed**2
    ax1 = plt.subplot(111, polar=True)
    ax1.set_theta_zero_location('N')
    ax1.set_theta_direction(-1)
    ax1.xaxis.set_ticklabels(['N',r"$45^{o}$",'E',r"$135^{o}$",'S',r"$225^{o}$",'W', r"$315^{o}$"])
    c = plt.scatter(direction, speed, c=colors, s=area, cmap=plt.cm.hsv)
    c.set_alpha(0.75)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def thirtyDaysProfilePlugin():
    """
    Gera uma superfície para avaliar a variação diária e ao longo do mês (30 dias).
    Dados devem corresponder a uma consulta com 30 dias e serem interpolados (ProcessingInterval < 1h).
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 1:
        ep.showMsgBox('EPM Python Plugin - Demo Power', 'Please select a single pen before applying this function!', 'Warning')
        return 0
    epmData = ep.EpmDatasetPens.SelectedPens[0].Values
    sampling = 30
    pHours = 24
    iniPeriod = epmData['Timestamp'][0]
    endPeriod = epmData['Timestamp'][-1]
    dTotal = endPeriod - iniPeriod
    totDays = dTotal.days
    evalPeriod = dt.timedelta(hours = pHours)
    nextPeriod = iniPeriod + evalPeriod
    profileList = []
    for i in range(totDays+1):
        iniP = epmData['Timestamp'] >= iniPeriod
        endP = epmData['Timestamp'] < nextPeriod
        epmDataValue = epmData['Value']
        dataPeriod = epmDataValue[iniP * endP]
        profileList.append( dataPeriod )
        iniPeriod = iniPeriod + dt.timedelta( 1 )
        nextPeriod = iniPeriod + evalPeriod
    profileMatrix = np.array(profileList)
    days  = np.arange(totDays)+1
    hours = np.arange(0,pHours*60,sampling)
    meshTime, indices = np.meshgrid(hours, days)
    meshProfile = np.zeros(meshTime.shape)
    for i in range( indices.shape[0] ):
        for j in range( indices.shape[1] ):
            meshProfile[i,j] = profileMatrix[i,j]
    fig = plt.figure(figsize=(15, 8))
    ax = fig.gca(projection='3d')
    X = meshTime
    Y = indices
    Z = meshProfile
    ax.plot_surface(X/60., Y, Z, rstride=1, cstride=1, cmap='coolwarm', alpha=0.8)
    ax.set_xlabel('hour')
    ax.set_ylabel('day')
    ax.set_zlabel('Power')
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def PowerCurve3d():
    """Grafico de dispersão em 3D"""    
    if len(ep.EpmDatasetPens.SelectedPens) != 3:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select 3 interpolated pens before applying this function!', 'Warning')
        return 0
    speed, direction, power = getSpeedPowerDirectionValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1],
                                                           ep.EpmDatasetPens.SelectedPens[2])
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')

    c = np.abs(speed)
    cmwinter = plt.get_cmap("winter")

    ax.scatter(speed, direction, power, c=c, cmap=cmwinter)
    ax.set_xlabel('Power (KW)')
    ax.set_ylabel('Direction')
    ax.set_zlabel('Speed (m/s)')

    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def PolarBarWind():
    """Grafico de polar de barras da direcao, velocidade e potencia do vento
    Apresenta um grafico polar de dispersao com a direcao, a velocidade e potencia do vento
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 3:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select 3 interpolated pens before applying this function!', 'Warning')
        return 0
    speed, direction, power = getSpeedPowerDirectionValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1],
                                                           ep.EpmDatasetPens.SelectedPens[2])
    spd4, dir4, pow4 = groupByDirection(speed, direction, power)
    width = pow4/1000.
    ax1 = plt.subplot(111, polar=True)
    ax1.set_theta_zero_location('N')
    ax1.set_theta_direction(-1)
    ax1.xaxis.set_ticklabels(['N',r"$45^{o}$",'E',r"$135^{o}$",'S',r"$225^{o}$",'W', r"$315^{o}$"])
    bars = ax1.bar(dir4, spd4, width=width, bottom=0.0)
    for r, bar in zip(spd4, bars):
        bar.set_facecolor(plt.cm.jet(r / 10.))
        bar.set_alpha(0.5)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def suplierSpeedPowerChart():
    """Grafico de potencia com a velocidade do vento comparada com a cruva do fornecedor em um arquivo CSV
    Apresenta um grafico de dispersao da potencia com a velocidade do vento, calculan a curva que melhor o representa e compara com a curva
    de referencia fornecida pelo fornecedor
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 2:
        ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select two interpolated pens before applying this function!', 'Warning')
        return 0
    global minSpeed
    global nominalPower
    global supplierCurveFile
    runDialogMinSpeedNomPowerSupplier()
    minSpeed = float(minSpeed)
    nominalPower = float(nominalPower)
    rawSpeed, rawPower = getSpeedPowerValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1])
    speed, power = cleanSpeedPowerData(rawSpeed, rawPower, minSpeed, nominalPower )
    xm, ym = windPowerAverage(speed, power)
    par0 = [1.0, 1.0, 1500.0, 1.0]
    binSpeed = 0.5
    parest,cov,infodict,mesg,ier = optimize.leastsq(residualsSPPn4, par0, args=(xm, ym), full_output=True)
    xEst = np.arange(xm.min(), xm.max(), binSpeed)
    yEst = powerFitPn4(parest, xEst)
    posAbove = np.argwhere(yEst > nominalPower)
    yEst[posAbove] = nominalPower
    speedRef, powerRef = readFromCsv(fileName=supplierCurveFile, delimiter=';')
    tckRef = interpolate.splrep(speedRef, powerRef, s=0)
    binSpeed = 0.5
    xRef = np.arange(speedRef.min(), speedRef.max(), binSpeed)
    yRef = interpolate.splev(xRef, tckRef, der=0)
    energyLost = integrate.simps(yRef, dx=binSpeed) - integrate.simps(yEst, dx=binSpeed)
    fig1 = plt.figure()
    ax1 = fig1.add_subplot(1, 1, 1)
    ax1.set_ylim(0, 1.05*nominalPower)
    ax1.set_xlim(minSpeed-1, 1.1*speed.max())
    ax1.set_xlabel(r'$Speed (m/s)$')
    ax1.set_ylabel(r'$Power (KW)$')    
    ax1.scatter(speed, power)
    ax1.plot(xEst, yEst, color='r', linewidth=3)
    ax1.plot(xRef, yRef, color='g', linewidth=3)
    ax1.text(15, 1100, 'Lost: ' + str(round(energyLost/1000,2)) + '(MW)', fontsize=14)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def ExpectedProduction():
    if len(ep.EpmDatasetPens.SelectedPens) != 2:
       ep.showMsgBox('EPM Python Plugin - Demo Tools', 'Please select Power and Speed pens before applying this function!', 'Warning')
       return 0

    global minSpeed
    global nominalPower
    global supplierCurveFile
    runDialogMinSpeedNomPowerSupplier()
    minSpeed = float(minSpeed)
    nominalPower = float(nominalPower)
    
    rawSpeed, rawPower = getSpeedPowerValues(ep.EpmDatasetPens.SelectedPens[0], ep.EpmDatasetPens.SelectedPens[1])
    speed, power = cleanSpeedPowerData(rawSpeed, rawPower, minSpeed, nominalPower )

    speedRef, powerRef = readFromCsv(fileName=supplierCurveFile, delimiter=';')

    #idx = []
    #for item in speed:
    #	idx.append(find_nearest(speedRef, item)

    idx = [find_nearest(speedRef, item) for item in speed]

    expected = [powerRef[index] for index in idx]

    #TODO: Calculo de perdas
    #lost = sum(expected - power)
    #print lost
    
    fig, ax = plt.subplots()

    line1 = ax.plot(power, label='Realized')
    line2 = ax.plot(expected, label='Expected')

    plt.ylabel('Power (Kw)')
    plt.xlabel('Time Unit')
    
    ax.legend(loc='lower right')
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def xyzScatter3DPlugin():
    """
    Apresenta gráficos de dispersão comparando 3 variáves entre si duas a duas e as 3 simultaneamente.
    Os dados das 3 variáveis devem estar igualmente espaçados.
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 3:
        ep.showMsgBox('EPM Python Plugin - Demo Power', 'Please select 3 pens before applying this function!', 'Warning')
        return 0

    epmDataX = ep.EpmDatasetPens.SelectedPens[0].Values['Value']
    Xlabel = ep.EpmDatasetPens.SelectedPens[0].Name
    epmDataY = ep.EpmDatasetPens.SelectedPens[1].Values['Value']
    Ylabel = ep.EpmDatasetPens.SelectedPens[1].Name
    epmDataZ  = ep.EpmDatasetPens.SelectedPens[2].Values['Value']
    Zlabel = ep.EpmDatasetPens.SelectedPens[2].Name
    fig = plt.figure(figsize=(15, 8))
    ax1 = plt.subplot2grid((3, 3), (0, 0))
    ax2 = plt.subplot2grid((3, 3), (0, 1))
    ax3 = plt.subplot2grid((3, 3), (0, 2))
    ax4 = plt.subplot2grid((3, 3), (1, 0), colspan=3, rowspan=3,  projection='3d')
    x = (epmDataX-epmDataX.mean())/epmDataX.std()
    y = (epmDataY-epmDataY.mean())/epmDataY.std()
    z = (epmDataZ-epmDataZ.mean())/epmDataZ.std()
    ax1.scatter(x, y)
    ax1.set_xlabel(Xlabel, fontsize=10)
    ax1.set_ylabel(Ylabel, fontsize=10)
    ax2.scatter(x, z)
    ax2.set_xlabel(Xlabel, fontsize=10)
    ax2.set_ylabel(Zlabel, fontsize=10)
    ax3.scatter(y, z)
    ax3.set_xlabel(Ylabel, fontsize=10)
    ax3.set_ylabel(Zlabel, fontsize=10)
    #ax4.scatter(x, y, z, cmap='hot')
    ax4.scatter(x, y, z)
    ax4.set_xlabel(Xlabel, fontsize=10)
    ax4.set_ylabel(Ylabel, fontsize=10)
    ax4.set_zlabel(Zlabel, fontsize=10)
    plt.tight_layout(pad=0.5, w_pad=0.5, h_pad=1.0)
    plt.show()

# 需要导入模块: import Plugins [as 别名]
# 或者: from Plugins import showMsgBox [as 别名]
def fiveDaysProfilePlugin():
    """
    Gráfico de área do perfil diário médio da variável a partir de dados de 5 dias.
    Dados devem corresponder a uma consulta de 5 dias (úteis) com valores médios a cada hora.
    """
    if len(ep.EpmDatasetPens.SelectedPens) != 1:
        ep.showMsgBox('EPM Python Plugin - Demo Power', 'Please select a single pen before applying this function!', 'Warning')
        return 0
    def cc(arg): return colorConverter.to_rgba(arg, alpha=0.6)
    epmDataValue = ep.EpmDatasetPens.SelectedPens[0].Values['Value']
    epmAvg = np.vstack((epmDataValue[0:24], epmDataValue[24:2*24], epmDataValue[2*24:3*24], epmDataValue[3*24:4*24], epmDataValue[4*24:5*24]))
    epmAvg = epmAvg.mean(axis=0)
    epmAvg[0], epmAvg[-1] = 0,0
    ys = np.arange(1, 25)
    zs = [0., 1., 2., 3., 4., 5.]
    profileList = []
    profileList.append( list(zip(ys, epmAvg)))
    ini = 0
    end = 24
    for i in range(5):
        dataPeriod = epmDataValue[ini:end]
        dataPeriod[0], dataPeriod[-1] = 0,0
        profileList.append( list(zip(ys, dataPeriod)))
        ini += 24
        end += 24
    poly = PolyCollection(profileList, facecolors=[cc('k'), cc('r'), cc('g'), cc('b'), cc('y'), cc('c')])
    fig = plt.figure(figsize=(15, 8))
    ax = fig.gca(projection='3d')
    poly.set_alpha(0.7)
    ax.add_collection3d(poly, zs=zs, zdir='y')
    ax.set_xlabel('hour')
    ax.set_xlim3d(1, 24)
    ax.set_ylabel('day')
    ax.set_ylim3d(-1, 6)
    ax.set_zlabel('power')
    ax.set_zlim3d(epmDataValue.min(), epmDataValue.max())
    plt.show()