def set_tone_bins(self,
bins,
nsamp,
amps=None,
load=True,
normfact=None,
phases=None,
preset_norm=True):
"""
Set the stimulus tones by specific integer bins
bins : array of bins at which tones should be placed
For Heterodyne system, negative frequencies should be placed in canonical FFT order
If 2d, interpret as (nwaves,ntones)
nsamp : int, must be power of 2
number of samples in the playback buffer. Frequency resolution will be fs/nsamp
amps : optional array of floats, same length as bins array
specify the relative amplitude of each tone. Can set to zero to read out a portion
of the spectrum with no stimulus tone.
load : bool (debug only). If false, don't actually load the waveform, just calculate it.
"""
if self.BYTES_PER_SAMPLE * nsamp > self.MEMORY_SIZE_BYTES:
message = "Requested tone size ({:d} bytes) exceeds available memory ({:d} bytes)"
raise ValueError(
message.format(self.BYTES_PER_SAMPLE * nsamp,
self.MEMORY_SIZE_BYTES))
if bins.ndim == 1:
bins.shape = (1, bins.shape[0])
nwaves = bins.shape[0]
spec = np.zeros((nwaves, nsamp // 2 + 1), dtype='complex')
self.tone_bins = bins.copy()
self.tone_nsamp = nsamp
if phases is None:
phases = np.random.random(bins.shape[1]) * 2 * np.pi
self.phases = phases.copy()
if amps is None:
amps = 1.0
self.amps = amps
for k in range(nwaves):
spec[k, bins[k, :]] = amps * np.exp(1j * phases)
wave = np.fft.irfft(spec, axis=1)
if preset_norm and not normfact:
self.wavenorm = tools.calc_wavenorm(bins.shape[1],
nsamp,
baseband=True)
else:
self.wavenorm = np.abs(wave).max()
if normfact is not None:
wn = (2.0 / normfact) * len(bins) / float(nsamp)
logger.debug(
"Using user provide waveform normalization resulting in wavenorm %f versus optimal %f. "
"Ratio is %f" % (wn, self.wavenorm, self.wavenorm / wn))
self.wavenorm = wn
qwave = np.round((wave / self.wavenorm) * (2**15 - 1024)).astype('>i2')
qwave.shape = (qwave.shape[0] * qwave.shape[1], )
self.qwave = qwave
if load:
self.load_waveform(qwave)
self.save_state()
def set_tone_bins(self, bins, nsamp, amps=None, load=True, normfact=None, phases=None, preset_norm=True):
"""
Set the stimulus tones by specific integer bins
bins : array of bins at which tones should be placed
For Heterodyne system, negative frequencies should be placed in canonical FFT order
If 2d, interpret as (nwaves,ntones)
nsamp : int, must be power of 2
number of samples in the playback buffer. Frequency resolution will be fs/nsamp
amps : optional array of floats, same length as bins array
specify the relative amplitude of each tone. Can set to zero to read out a portion
of the spectrum with no stimulus tone.
load : bool (debug only). If false, don't actually load the waveform, just calculate it.
"""
if self.BYTES_PER_SAMPLE * nsamp > self.MEMORY_SIZE_BYTES:
message = "Requested tone size ({:d} bytes) exceeds available memory ({:d} bytes)"
raise ValueError(message.format(self.BYTES_PER_SAMPLE * nsamp, self.MEMORY_SIZE_BYTES))
if bins.ndim == 1:
bins.shape = (1, bins.shape[0])
nwaves = bins.shape[0]
spec = np.zeros((nwaves, nsamp // 2 + 1), dtype='complex')
self.tone_bins = bins.copy()
self.tone_nsamp = nsamp
if phases is None:
phases = np.random.random(bins.shape[1]) * 2 * np.pi
self.phases = phases.copy()
if amps is None:
amps = 1.0
self.amps = amps
for k in range(nwaves):
spec[k, bins[k, :]] = amps * np.exp(1j * phases)
wave = np.fft.irfft(spec, axis=1)
if preset_norm and not normfact:
self.wavenorm = tools.calc_wavenorm(bins.shape[1], nsamp, baseband=True)
else:
self.wavenorm = np.abs(wave).max()
if normfact is not None:
wn = (2.0 / normfact) * len(bins) / float(nsamp)
logger.debug("Using user provide waveform normalization resulting in wavenorm %f versus optimal %f. "
"Ratio is %f" % (wn,self.wavenorm,self.wavenorm/wn))
self.wavenorm = wn
qwave = np.round((wave / self.wavenorm) * (2 ** 15 - 1024)).astype('>i2')
qwave.shape = (qwave.shape[0] * qwave.shape[1],)
self.qwave = qwave
if load:
self.load_waveform(qwave)
self.save_state()
def add_tone_bins(self, bins, amps=None, preset_norm=True):
nsamp = self.tone_nsamp
spec = np.zeros((nsamp // 2 + 1,), dtype='complex')
self.tone_bins = np.vstack((self.tone_bins, bins))
phases = self.phases
if amps is None:
amps = 1.0
# self.amps = amps # TODO: Need to figure out how to deal with this
spec[bins] = amps * np.exp(1j * phases)
wave = np.fft.irfft(spec)
if preset_norm:
self.wavenorm = tools.calc_wavenorm(self.tone_bins.shape[1], nsamp, baseband=True)
else:
self.wavenorm = np.abs(wave).max()
qwave = np.round((wave / self.wavenorm) * (2 ** 15 - 1024)).astype('>i2')
# self.qwave = qwave # TODO: Deal with this, if we ever use it
start_offset = self.tone_bins.shape[0] - 1
self.load_waveform(qwave, start_offset=start_offset)
self.save_state()
def add_tone_bins(self, bins, amps=None, preset_norm=True):
nsamp = self.tone_nsamp
spec = np.zeros((nsamp // 2 + 1, ), dtype='complex')
self.tone_bins = np.vstack((self.tone_bins, bins))
phases = self.phases
if amps is None:
amps = 1.0
# self.amps = amps # TODO: Need to figure out how to deal with this
spec[bins] = amps * np.exp(1j * phases)
wave = np.fft.irfft(spec)
if preset_norm:
self.wavenorm = tools.calc_wavenorm(self.tone_bins.shape[1],
nsamp,
baseband=True)
else:
self.wavenorm = np.abs(wave).max()
qwave = np.round((wave / self.wavenorm) * (2**15 - 1024)).astype('>i2')
# self.qwave = qwave # TODO: Deal with this, if we ever use it
start_offset = self.tone_bins.shape[0] - 1
self.load_waveform(qwave, start_offset=start_offset)
self.save_state()
