def clear_ogp(self):
'''
Clears the OGP registers on the ADC.
'''
for core in range(1, 5):
adc.set_spi_gain(self._roach, 0, core, 0)
adc.set_spi_offset(self._roach, 0, core, 0)
adc.set_spi_phase(self._roach, 0, core, 0)
def clear_ogp():
"""
Clear all of the Offset, Gain and Phase corrections registers on the adc.
"""
for core in range(1,5):
adc5g.set_spi_gain(roach2,zdok, core, 0)
adc5g.set_spi_offset(roach2,zdok, core, 0)
adc5g.set_spi_phase(roach2,zdok, core, 0)
def clear_ogp():
"""
Clear all of the Offset, Gain and Phase corrections registers on the adc.
"""
for core in range(1, 5):
adc5g.set_spi_gain(roach2, zdok, core, 0)
adc5g.set_spi_offset(roach2, zdok, core, 0)
adc5g.set_spi_phase(roach2, zdok, core, 0)
def set_ogp(self, ogp):
'''
Sets the OGP registers on the ADC. Input shape must be (4, 3).
'''
offs = ogp[:, 0]
gains = ogp[:, 1]
phase = ogp[:, 2]
for i in range(len(offs)):
adc.set_spi_offset(self._roach, 0, i+1, offs[i])
adc.set_spi_gain(self._roach, 0, i+1, gains[i])
adc.set_spi_phase(self._roach, 0, i+1, phase[i])
def clear_ogp(self, chans=[0, 1, 2, 3]):
"""
Sets OGP to 0 for channels in 'chans'
"""
for chan in chans:
zdok, cores = self.get_channel_core_spi(chan)
for core in cores:
adc5g.set_spi_offset(self.roach, zdok, core, 0)
adc5g.set_spi_gain(self.roach, zdok, core, 0)
adc5g.set_spi_phase(self.roach, zdok, core, 0)
def clear_ogp(self, chans = [0,1,2,3]):
"""
Sets OGP to 0 for channels in 'chans'
"""
for chan in chans:
zdok, cores = self.get_channel_core_spi(chan)
for core in cores:
adc5g.set_spi_offset(self.roach, zdok, core, 0)
adc5g.set_spi_gain(self.roach, zdok, core, 0)
adc5g.set_spi_phase(self.roach, zdok, core, 0)
def set_gains(g1, g2, g3, g4): """ Set the gains for each core in the order a, b, c, d. """ t = float(g1) print math.floor(.5+t*255/36.)+0x80, adc5g.set_spi_gain(roach2,zdok, 1, t) t = float(g2) print math.floor(.5+t*255/36.)+0x80, adc5g.set_spi_gain(roach2,zdok, 2, t) t = float(g3) print math.floor(.5+t*255/36.)+0x80, adc5g.set_spi_gain(roach2,zdok, 3, t) t = float(g4) print math.floor(.5+t*255/36.)+0x80 adc5g.set_spi_gain(roach2,zdok, 4, t)
def set_gains(g1, g2, g3, g4):
"""
Set the gains for each core in the order a, b, c, d.
"""
t = float(g1)
print math.floor(.5 + t * 255 / 36.) + 0x80,
adc5g.set_spi_gain(roach2, zdok, 1, t)
t = float(g2)
print math.floor(.5 + t * 255 / 36.) + 0x80,
adc5g.set_spi_gain(roach2, zdok, 2, t)
t = float(g3)
print math.floor(.5 + t * 255 / 36.) + 0x80,
adc5g.set_spi_gain(roach2, zdok, 3, t)
t = float(g4)
print math.floor(.5 + t * 255 / 36.) + 0x80
adc5g.set_spi_gain(roach2, zdok, 4, t)
def set_ogp(self, ogp_chan, chan):
"""
Sets ogp for two cores of channel 'chan'
multi_ogp is format (ogp1, ogp2)
"""
zdok, cores = self.get_channel_core_spi(chan)
i = 0
for core in cores:
off, gain, phase = ogp_chan[i]
off_spi = math.floor(.5 + off * 255 / 100.) + 0x80
adc5g.set_spi_offset(self.roach, zdok, core, float(off))
gain_spi = math.floor(.5 + gain * 255 / 36.) + 0x80
adc5g.set_spi_gain(self.roach, zdok, core, float(gain))
phase_spi = math.floor(.5 + phase * 255 / 28.) + 0x80
adc5g.set_spi_phase(self.roach, zdok, core, float(phase) * 0.65)
i += 1
def set_ogp(self, ogp_chan, chan):
"""
Sets ogp for two cores of channel 'chan'
multi_ogp is format (ogp1, ogp2)
"""
zdok, cores = self.get_channel_core_spi(chan)
i = 0
for core in cores:
off, gain, phase = ogp_chan[i]
off_spi = math.floor(.5 + off*255/100.) + 0x80
adc5g.set_spi_offset(self.roach, zdok, core, float(off))
gain_spi = math.floor(.5 + gain*255/36.) + 0x80
adc5g.set_spi_gain(self.roach, zdok, core, float(gain))
phase_spi = math.floor(.5 + phase*255/28.) + 0x80
adc5g.set_spi_phase(self.roach, zdok, core, float(phase)*0.65)
i += 1
def calibrate_adc_gain(self, zdok=0, giter=10, gtol=0.005, verbose=10):
"""
Attempt to match the core gains within the ADC.
See ArtooDaq.calibrate_adc_ogp for more details.
"""
# gain controlled by float varying over [-18%,18%] with 0.14% resolution
res_gain = 0.14
lim_gain = [-18.0, 18.0]
groups = 8
test_step = 10 * res_gain
if verbose > 3:
print " Gain calibration ZDOK{0}:".format(zdok)
for ic in xrange(1, 5):
adc5g.set_spi_gain(self.roach2, zdok, ic, 0)
x1 = self._snap_per_core(zdok=zdok, groups=groups)
sx1 = x1.std(axis=0)
s0 = sx1[0]
sx1 = sx1 / s0
if verbose > 5:
print " ...gain: with zero-offsets, stds are [{0}]".format(
", ".join(["{0:+7.4f}".format(isx) for isx in sx1]))
# only adjust gains for last three cores, core1 is the reference
for ic in xrange(2, 5):
adc5g.set_spi_gain(self.roach2, zdok, ic, test_step)
x2 = self._snap_per_core(zdok=zdok, groups=groups)
sx2 = x2.std(axis=0)
s0 = sx2[0]
sx2 = sx2 / s0
if verbose > 5:
print " ...gain: with {0:+6.2f}% gain, stds are [{1}]".format(
test_step, ", ".join(["{0:+7.4f}".format(isx) for isx in sx2]))
d_sx = 100 * (sx2 - sx1) / test_step
# give differential for core1 a non-zero value, it won't be used anyway
d_sx[0] = 1.0
# gains are in units percentage
core_gains = 100 * (1.0 - sx1) / d_sx
# set core1 gain to zero
core_gains[0] = 0
for ic in xrange(2, 5):
adc5g.set_spi_gain(self.roach2, zdok, ic, core_gains[ic - 1])
core_gains[ic - 1] = adc5g.get_spi_gain(self.roach2, zdok, ic)
x = self._snap_per_core(zdok=zdok, groups=groups)
sx = x.std(axis=0)
s0 = sx[0]
sx = sx / s0
if verbose > 5:
print " ...gain: solution gains are [{0}]%, stds are [{1}]".format(
", ".join(["{0:+6.2f}".format(ico) for ico in core_gains]),
", ".join(["{0:+7.4f}".format(isx) for isx in sx]))
if any(abs(1.0 - sx) >= gtol):
if verbose > 5:
print " ...gain: solution not good enough, iterating (tol={0:4.4f},iter={1:d})".format(
gtol, giter)
for ii in xrange(0, giter):
for ic in xrange(2, 5):
if (1.0 - sx[ic - 1]) > gtol:
adc5g.set_spi_gain(self.roach2, zdok, ic,
core_gains[ic - 1] + res_gain)
elif (1.0 - sx[ic - 1]) < -gtol:
adc5g.set_spi_gain(self.roach2, zdok, ic,
core_gains[ic - 1] - res_gain)
core_gains[ic - 1] = adc5g.get_spi_gain(
self.roach2, zdok, ic)
x = self._snap_per_core(zdok=zdok, groups=groups)
sx = x.std(axis=0)
s0 = sx[0]
sx = sx / s0
if verbose > 7:
print " ...gain: solution gains are [{0}]%, stds are [{1}]".format(
", ".join(
["{0:+6.2f}".format(ico) for ico in core_gains]),
", ".join(["{0:+7.4f}".format(isx) for isx in sx]))
if all(abs(1.0 - sx) < gtol):
if verbose > 5:
print " ...gain: solution good enough"
break
if ii == giter - 1:
if verbose > 5:
print " ...gain: maximum number of iterations reached, aborting"
else:
if verbose > 5:
print " ...gain: solution good enough"
return core_gains
def calibrate_adc_gain(self,zdok=0,giter=10,gtol=0.005,verbose=10):
"""
Attempt to match the core gains within the ADC.
See ArtooDaq.calibrate_adc_ogp for more details.
"""
# gain controlled by float varying over [-18%,18%] with 0.14% resolution
res_gain = 0.14
lim_gain = [-18.0,18.0]
groups = 8
test_step = 10*res_gain
if verbose > 3:
print " Gain calibration ZDOK{0}:".format(zdok)
for ic in xrange(1,5):
adc5g.set_spi_gain(self.roach2,zdok,ic,0)
x1 = self._snap_per_core(zdok=zdok,groups=groups)
sx1 = x1.std(axis=0)
s0 = sx1[0]
sx1 = sx1/s0
if verbose > 5:
print " ...gain: with zero-offsets, stds are [{0}]".format(
", ".join(["{0:+7.4f}".format(isx) for isx in sx1])
)
# only adjust gains for last three cores, core1 is the reference
for ic in xrange(2,5):
adc5g.set_spi_gain(self.roach2,zdok,ic,test_step)
x2 = self._snap_per_core(zdok=zdok,groups=groups)
sx2 = x2.std(axis=0)
s0 = sx2[0]
sx2 = sx2/s0
if verbose > 5:
print " ...gain: with {0:+6.2f}% gain, stds are [{1}]".format(
test_step,
", ".join(["{0:+7.4f}".format(isx) for isx in sx2])
)
d_sx = 100*(sx2 - sx1)/test_step
# give differential for core1 a non-zero value, it won't be used anyway
d_sx[0] = 1.0
# gains are in units percentage
core_gains = 100*(1.0-sx1)/d_sx
# set core1 gain to zero
core_gains[0] = 0
for ic in xrange(2,5):
adc5g.set_spi_gain(self.roach2,zdok,ic,core_gains[ic-1])
core_gains[ic-1] = adc5g.get_spi_gain(self.roach2,zdok,ic)
x = self._snap_per_core(zdok=zdok,groups=groups)
sx = x.std(axis=0)
s0 = sx[0]
sx = sx/s0
if verbose > 5:
print " ...gain: solution gains are [{0}]%, stds are [{1}]".format(
", ".join(["{0:+6.2f}".format(ico) for ico in core_gains]),
", ".join(["{0:+7.4f}".format(isx) for isx in sx])
)
if any(abs(1.0-sx) >= gtol):
if verbose > 5:
print " ...gain: solution not good enough, iterating (tol={0:4.4f},iter={1:d})".format(gtol,giter)
for ii in xrange(0,giter):
for ic in xrange(2,5):
if (1.0-sx[ic-1]) > gtol:
adc5g.set_spi_gain(self.roach2,zdok,ic,core_gains[ic-1]+res_gain)
elif (1.0-sx[ic-1]) < -gtol:
adc5g.set_spi_gain(self.roach2,zdok,ic,core_gains[ic-1]-res_gain)
core_gains[ic-1] = adc5g.get_spi_gain(self.roach2,zdok,ic)
x = self._snap_per_core(zdok=zdok,groups=groups)
sx = x.std(axis=0)
s0 = sx[0]
sx = sx/s0
if verbose > 7:
print " ...gain: solution gains are [{0}]%, stds are [{1}]".format(
", ".join(["{0:+6.2f}".format(ico) for ico in core_gains]),
", ".join(["{0:+7.4f}".format(isx) for isx in sx])
)
if all(abs(1.0-sx) < gtol):
if verbose > 5:
print " ...gain: solution good enough"
break
if ii==giter-1:
if verbose > 5:
print " ...gain: maximum number of iterations reached, aborting"
else:
if verbose > 5:
print " ...gain: solution good enough"
return core_gains
def ogapply(sol):
for i in [0, 1]:
for j in [0, 1, 2, 3]:
adc5g.set_spi_offset(r2, i, corder[j], sol[i,j,0])
adc5g.set_spi_gain(r2, i, corder[j], sol[i,j,1])
plt.xlim(-128, 128)
plt.ylim(0, 1.05 * np.max(counts))
plt.yticks([])
plt.xticks([])
means[j] = ret[1]
stds[j] = ret[2]
print "IF%d Core %d: mean %5.2f std %5.2f" % (i, j, ret[1], ret[2])
avg_std = np.mean(stds) # target std
for j in [0,1,2,3]:
orig_off = adc5g.get_spi_offset(r2, i, corder[j])
orig_gain = adc5g.get_spi_gain(r2, i, corder[j])
new_off = orig_off - means[j] * 500./256.
new_gain = (100. + orig_gain) * (avg_std / stds[j]) - 100.
if setog:
adc5g.set_spi_offset(r2, i, corder[j], new_off)
adc5g.set_spi_gain(r2, i, corder[j], new_gain)
sol[i,j,0] = new_off
sol[i,j,1] = new_gain
if doplot:
plt.suptitle('%s ADC 8bit population\n%s' % (open('/etc/hostname').read().strip(), tag))
plt.subplots_adjust(hspace=0, wspace=0)
plt.setp(plt.gcf(), figwidth=8, figheight=12)
figfile = 'ogplot-%s.png' % tag
print "saving figure to: %s" % figfile
plt.savefig(figfile)
solfile = 'ogsol-%s.npy' % tag
print "saving solution to: %s" % solfile
np.save(solfile, sol)
