Exemplo n.º 1
0
def calculate_beta(m, vcc):
    col = ColsProxy(m)

    col.Ab = uarray((col.Ab, 1))
    col.Ac = uarray((col.Ac, 1))

    col.Ub = an2v(col.Ab, vcc)
    col.Uc = an2v(col.Ac, vcc)

    Rout = 20

    pnp = col.polarity == 'PNP'
    npn = col.polarity == 'NPN'

    col.Urb[pnp] = col.Ub[pnp]
    col.Urb[npn] = vcc - col.Ub[npn]

    col.Urc[pnp] = col.Uc[pnp]
    col.Urc[npn] = vcc - col.Uc[npn]

    col.Ib = col.Urb / (col.Rb + Rout)
    col.Ic = col.Urc / (col.Rc + Rout)
    col.Ie = col.Ib + col.Ic
    col.beta = col.Ic / col.Ib[nominal_values(col.Ib) != 0]

    col.Ue[pnp] = vcc - (Rout * col.Ie[pnp])
    col.Ue[npn] = Rout * col.Ie[npn]

    col.Ube[pnp] = -(col.Ub[pnp] - col.Ue[pnp])
    col.Ube[npn] = (col.Ub[npn] - col.Ue[npn])
Exemplo n.º 2
0
def calculate_beta(m, vcc):
        col = ColsProxy(m)
        
        col.Ab=uarray((col.Ab,1))
        col.Ac=uarray((col.Ac,1))
        
        
        col.Ub = an2v(col.Ab, vcc)
        col.Uc = an2v(col.Ac, vcc)

        Rout = 20

        pnp = col.polarity == 'PNP'
        npn = col.polarity == 'NPN'

        col.Urb[pnp] = col.Ub[pnp]
        col.Urb[npn] = vcc - col.Ub[npn]

        col.Urc[pnp] = col.Uc[pnp]
        col.Urc[npn] = vcc - col.Uc[npn]

        col.Ib = col.Urb / (col.Rb + Rout)
        col.Ic = col.Urc / (col.Rc + Rout)
        col.Ie = col.Ib + col.Ic
        col.beta = col.Ic / col.Ib[nominal_values(col.Ib) != 0]

        col.Ue[pnp] = vcc - (Rout * col.Ie[pnp])
        col.Ue[npn] = Rout * col.Ie[npn]

        col.Ube[pnp] = -(col.Ub[pnp] - col.Ue[pnp])
        col.Ube[npn] = (col.Ub[npn] - col.Ue[npn])
Exemplo n.º 3
0
def extend(data):
    #    dw = DataWrapper(data)
    data.measurements = filter_measurements(data.measurements,
                                            ['pwm_value', 'rail'],
                                            ['Aout', 'Ain', 'Aamp'])
    #    print 111,unbunchify(dw.data)
    #    print 222,(dw.data)
    R = data.config.R
    vcc = data.vcc
    #    def calc(x):
    #            x.Vin = an2v(x.Ain, vcc)
    #            x.Vout = an2v(x.Aout, vcc)
    #            x.Vamp = an2v(x.Aamp, vcc)
    #            x.Vx = x.Vout - x.Vin
    #            x.I = (x.Vin - x.Vamp) / R
    data.Vmax = data.vcc
    data.Imax = data.vcc / R
    #    ls=[]
    #    pwm_current=0
    #    for x in dw.data.measurements:
    #        # group by pwm_value
    #        x.pwm_value==pwm_current:
    #            ls.append(x)
    #        else:
    #            calc(x)
    #            ls=[]
    #            pwm_current=x.pwm_value
    d = groupped_measurements(data.measurements, ['pwm_value', 'rail'])
    for p in range(256):
        for r in [0, 1]:
            ls = d[p, r]
            # ls = [x for x in dw.data.measurements if x.pwm_value == p and x.rail ==
            # r]
            if not len(ls):
                continue

            Ain = ls[0].Ain
            Aout = ls[0].Aout
            Aamp = ls[0].Aamp

            Vin = an2v(Ain, vcc)
            Vout = an2v(Aout, vcc)
            Vamp = an2v(Aamp, vcc)
            Vx = Vout - Vin
            I = (Vin - Vamp) / R

            for x in ls:
                x.I = I
                x.Vx = Vx
                x.Vin = Vin
                x.Vout = Vout
                x.Vamp = Vamp
Exemplo n.º 4
0
def extend(data):
    m = filter_measurements(data.measurements, ['Dout', 'pwm_value'],
                            ['Aout', 'Aamp'])

    R = data.config.R
    vcc = data.vcc

    m['Vout'] = an2v(m.Aout, vcc)
    m['Vamp'] = an2v(m.Aamp, vcc)
    m['I'] = (m.Vout - m.Vamp) / R
    m['Iabs'] = abs(m.I)

    data.measurements = m
Exemplo n.º 5
0
def extend(data):
#    dw = DataWrapper(data)
    data.measurements = filter_measurements(
        data.measurements, ['pwm_value', 'rail'], ['Aout', 'Ain', 'Aamp'])
#    print 111,unbunchify(dw.data)
#    print 222,(dw.data)
    R = data.config.R
    vcc = data.vcc
#    def calc(x):
#            x.Vin = an2v(x.Ain, vcc)
#            x.Vout = an2v(x.Aout, vcc)
#            x.Vamp = an2v(x.Aamp, vcc)
#            x.Vx = x.Vout - x.Vin
#            x.I = (x.Vin - x.Vamp) / R
    data.Vmax = data.vcc
    data.Imax = data.vcc / R
#    ls=[]
#    pwm_current=0
#    for x in dw.data.measurements:
#        # group by pwm_value
#        x.pwm_value==pwm_current:
#            ls.append(x)
#        else:
#            calc(x)
#            ls=[]
#            pwm_current=x.pwm_value
    d = groupped_measurements(data.measurements, ['pwm_value', 'rail'])
    for p in range(256):
        for r in [0, 1]:
            ls = d[p, r]
# ls = [x for x in dw.data.measurements if x.pwm_value == p and x.rail ==
# r]
            if not len(ls):
                continue

            Ain = ls[0].Ain
            Aout = ls[0].Aout
            Aamp = ls[0].Aamp

            Vin = an2v(Ain, vcc)
            Vout = an2v(Aout, vcc)
            Vamp = an2v(Aamp, vcc)
            Vx = Vout - Vin
            I = (Vin - Vamp) / R

            for x in ls:
                x.I = I
                x.Vx = Vx
                x.Vin = Vin
                x.Vout = Vout
                x.Vamp = Vamp
Exemplo n.º 6
0
def transfer_plot(data, fig, error_plot=False):
    data.measurements = filter_measurements(data.measurements, ['pwm_value'],
                                            ['Ain'])
    title = 'Transfer error plot (%s)' if error_plot else 'Transfer plot (%s)'
    title = title % (data.model)
    fw = FigureWrapper(
        data,
        fig,
        x='voltage',
        y='error (V)' if error_plot else 'voltage',
        title=title,
    )

    vcc = data.vcc
    fw.addcol(
        legend=data.config.pin_in,
        x=lambda e: pwm2v(e.pwm_value, vcc),
        y=lambda e: an2v(e.Ain, vcc) - (pwm2v(e.pwm_value, vcc)
                                        if error_plot else 0),
    )
    ax = fw.subplot
    if error_plot:
        ax.axis([0, 5.1, -0.050, 0.050])

    return fig
Exemplo n.º 7
0
def transfer_plot(data, fig, error_plot=False):
    data.measurements = filter_measurements(data.measurements, ['value'],
                                            ['Ain'])
    title = 'Transfer error plot' if error_plot else 'Transfer plot'
    title = title
    fw = FigureWrapper(
        data,
        fig,
        x='voltage',
        y='error (V)' if error_plot else 'voltage',
        title=title,
    )

    vcc = data.vcc

    if error_plot:
        fw.subplot.plot([0, vcc], [vcc / 99, vcc / 99], 'r-')
        fw.subplot.plot([0, vcc], [-vcc / 99, -vcc / 99], 'r-')
    else:
        fw.subplot.plot([0, 0], [vcc, vcc], 'r-')

    fw.addcol(
        legend=data.config.pin_in,
        x=lambda e: pot2v(e.value, vcc),
        y=lambda e: an2v(e.Ain, vcc) - (pot2v(e.value, vcc)
                                        if error_plot else 0),
    )
    ax = fw.subplot
    if error_plot:
        ax.axis([0, 5.1, -0.1, 0.1])

    return fig
Exemplo n.º 8
0
def extend(data):
    m = filter_measurements(
        data.measurements,
        ['Dout', 'pwm_value'],
        ['Aout', 'Aamp']
    )

    R = data.config.R
    vcc = data.vcc

    m['Vout'] = an2v(m.Aout, vcc)
    m['Vamp'] = an2v(m.Aamp, vcc)
    m['I'] = (m.Vout - m.Vamp) / R
    m['Iabs'] = abs(m.I)

    data.measurements = m
Exemplo n.º 9
0
def calculate_ohm(data, Vnull, Ain):
    vcc = data.vcc
    #    print 'calibration', calibration
    Vin = an2v(Ain, vcc)
    #    Ain, Vin = maxi(ls, vcc)

    R1 = data.config.R1
    R2 = data.config.R2

    Ramp1 = data.config.Ramp1
    Ramp2 = data.config.Ramp2

    #    def perc1(x):
    #        return ufloat((x, x * 0.01))
    Rout = 24

    #    R1 = perc1(R1) + ufloat((Rout, Rout * 0.1))
    #    R2 = perc1(R2)
    R1 = R1 + Rout

    #    Ramp1 = perc1(Ramp1)
    #    Ramp2 = perc1(Ramp2)

    A = Ramp2 / Ramp1

    Vgen = R2 / (R2 + R1) * vcc
    Rgen = R1 * R2 / (R1 + R2)

    #    print R2, Vgen, Rgen, vcc, R1
    Vampout = Vin
    Vampout_pp = 2 * (Vampout - Vnull)
    Vampin_pp = Vampout_pp / A
    divider = (Vampin_pp / Vgen)

    def calc_Rx(cal):
        return Rgen / (1 - divider / cal) - Rgen

    Rx_raw = calc_Rx(1)

    calibration_open = Vampin_pp / Vgen

    #    calibration = 0.93
    #    Rx_cal = calc_Rx(calibration)

    #    def calibration_x(x):
    #        return divider / (1 - (Rgen / (x + Rgen)))
    #    print 555, calibration_x(1.8)

    Rx = Rx_raw
    #    print 'Rx_raw,Rx_cal', Rx_raw, Rx_cal
    #    if Rx > 30:
    #        Rx = None
    return Rx, calibration_open
Exemplo n.º 10
0
def analyse(data):
    m = data.measurements

    vcc = data.vcc

    stats = m.Ain.describe()

    count = stats['count']
    Amean = stats['mean']
    Amin = stats['min']
    Amax = stats['max']
    Arange = Amax - Amin
    Amiddle = (Amin + Amax) / 2
    duty_cycle = len(m.Ain[m.Ain > Amiddle]) / len(m.Ain)

    Astd = stats['std']
    Arms = (Astd ** 2 + Amean ** 2) ** 0.5

    return dict(
                count=count,
        Amin=Amin,
        Amax=Amax,
        Arange=Arange,
        Amean=Amean,
        duty_cycle=duty_cycle,
        Astd=Astd,
        Arms=Arms,
        Vmean=an2v(Amean, vcc),
        Vstd=an2v(Astd, vcc),
        Vrms=an2v(Arms, vcc),
        Vmin=an2v(Amin, vcc),
        Vmax=an2v(Amax, vcc),
        Vrange=an2v(Arange, vcc),
    )
Exemplo n.º 11
0
def calculate_ohm(data, Vnull, Ain):
    vcc = data.vcc
#    print 'calibration', calibration
    Vin = an2v(Ain, vcc)
#    Ain, Vin = maxi(ls, vcc)

    R1 = data.config.R1
    R2 = data.config.R2

    Ramp1 = data.config.Ramp1
    Ramp2 = data.config.Ramp2

#    def perc1(x):
#        return ufloat((x, x * 0.01))
    Rout = 24

#    R1 = perc1(R1) + ufloat((Rout, Rout * 0.1))
#    R2 = perc1(R2)
    R1 = R1 + Rout

#    Ramp1 = perc1(Ramp1)
#    Ramp2 = perc1(Ramp2)

    A = Ramp2 / Ramp1

    Vgen = R2 / (R2 + R1) * vcc
    Rgen = R1 * R2 / (R1 + R2)

#    print R2, Vgen, Rgen, vcc, R1
    Vampout = Vin
    Vampout_pp = 2 * (Vampout - Vnull)
    Vampin_pp = Vampout_pp / A
    divider = (Vampin_pp / Vgen)

    def calc_Rx(cal):
        return  Rgen / (1 - divider / cal) - Rgen
    Rx_raw = calc_Rx(1)

    calibration_open = Vampin_pp / Vgen

#    calibration = 0.93
#    Rx_cal = calc_Rx(calibration)

#    def calibration_x(x):
#        return divider / (1 - (Rgen / (x + Rgen)))
#    print 555, calibration_x(1.8)

    Rx = Rx_raw
#    print 'Rx_raw,Rx_cal', Rx_raw, Rx_cal
#    if Rx > 30:
#        Rx = None
    return Rx, calibration_open
Exemplo n.º 12
0
def extend(data):
    m = filter_measurements(
        data.measurements,
        ['pwm_value', 'rail'],
        ['Aout', 'Ain', 'Aamp'])

    R = data.config.R
    vcc = data.vcc

    data.Vmax = data.vcc
    data.Imax = data.vcc / R

    col = ColsProxy(m)
    col.Vin = an2v(col.Ain, vcc)
    col.Vout = an2v(col.Aout, vcc)
    col.Vamp = an2v(col.Aamp, vcc)
    col.Vx = col.Vout - col.Vin
    col.I = (col.Vin - col.Vamp) / R
    m = m.sort_index(by='Vx')

    col.I = pandas.rolling_median(col.I, window=5)

    data.measurements = m
Exemplo n.º 13
0
    def addcol(self,
               x=None,
               y=None,
               legend=None,
               lineformat=None,
               filter_func=None,
               sortbyx=None):
        ax = self.subplot
        if x and not callable(x):
            ax.set_xlabel(x)
        else:
            if self.x == 'time':
                x = 't'
        if not x:
            x = self.x

        if not lineformat:
            lineformat = '-o'

        if not callable(y):
            if not legend:
                legend = y

        if self.convert2voltage and self.y == 'analog_value':
            f2 = lambda e: an2v(e[y], self.data['vcc'])
        else:
            f2 = y

        xcol = self._col(x, filter_func=filter_func)
        ycol = self._col(f2, filter_func=filter_func)
        if sortbyx:
            ls = sorted(zip(xcol, ycol), key=lambda e: e[0])
            xcol = [e[0] for e in ls]
            ycol = [e[1] for e in ls]
        assert len(xcol) == len(ycol)
        assert len(xcol)
        assert len(ycol)
        ax.plot(nominal_values(xcol),
                nominal_values(ycol),
                lineformat,
                label=legend)
        self.update_legend()
Exemplo n.º 14
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    def addcol(self, x=None, y=None, legend=None, lineformat=None, filter_func=None, sortbyx=None):
        ax = self.subplot
        if x and not callable(x):
            ax.set_xlabel(x)
        else:
            if self.x == 'time':
                x = 't'
        if not x:
            x = self.x

        if not lineformat:
            lineformat = '-o'

        if not callable(y):
            if not legend:
                legend = y

        if self.convert2voltage and self.y == 'analog_value':
            f2 = lambda e: an2v(e[y], self.data['vcc'])
        else:
            f2 = y

        xcol = self._col(x, filter_func=filter_func)
        ycol = self._col(f2, filter_func=filter_func)
        if sortbyx:
            ls = sorted(zip(xcol, ycol), key=lambda e: e[0])
            xcol = [e[0] for e in ls]
            ycol = [e[1] for e in ls]
        assert len(xcol) == len(ycol)
        assert len(xcol)
        assert len(ycol)
        ax.plot(
            nominal_values(xcol),
            nominal_values(ycol),
            lineformat,
            label=legend)
        self.update_legend()
Exemplo n.º 15
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def transfer_plot(data, fig, error_plot=False):
    data.measurements = filter_measurements(
        data.measurements, ['pwm_value'], ['Ain'])
    title = 'Transfer error plot (%s)' if error_plot else 'Transfer plot (%s)'
    title = title % (data.model)
    fw = FigureWrapper(
        data,
        fig,
        x='voltage',
        y='error (V)' if error_plot else 'voltage',
        title=title,
    )

    vcc = data.vcc
    fw.addcol(legend=data.config.pin_in,
              x=lambda e: pwm2v(e.pwm_value, vcc),
              y=lambda e: an2v(
                  e.Ain, vcc) - (pwm2v(e.pwm_value, vcc) if error_plot else 0),
              )
    ax = fw.subplot
    if error_plot:
        ax.axis([0, 5.1, -0.050, 0.050])

    return fig
Exemplo n.º 16
0
def transfer_plot(data, fig, error_plot=False):
    data.measurements = filter_measurements(data.measurements, ["value"], ["Ain"])
    title = "Transfer error plot" if error_plot else "Transfer plot"
    title = title
    fw = FigureWrapper(data, fig, x="voltage", y="error (V)" if error_plot else "voltage", title=title)

    vcc = data.vcc

    if error_plot:
        fw.subplot.plot([0, vcc], [vcc / 99, vcc / 99], "r-")
        fw.subplot.plot([0, vcc], [-vcc / 99, -vcc / 99], "r-")
    else:
        fw.subplot.plot([0, 0], [vcc, vcc], "r-")

    fw.addcol(
        legend=data.config.pin_in,
        x=lambda e: pot2v(e.value, vcc),
        y=lambda e: an2v(e.Ain, vcc) - (pot2v(e.value, vcc) if error_plot else 0),
    )
    ax = fw.subplot
    if error_plot:
        ax.axis([0, 5.1, -0.1, 0.1])

    return fig
Exemplo n.º 17
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def avgAV(df, vcc):
    a = averaged_median_arr(df.Ain)
    Ain = ufloat((a, 1))
    Vin = an2v(Ain, vcc)
    return Ain, Vin
Exemplo n.º 18
0
def avgAV(df, vcc):
    a = averaged_median_arr(df.Ain)
    Ain = ufloat((a, 1))
    Vin = an2v(Ain, vcc)
    return Ain, Vin