def build_waveforms(seqs, shapeLib):
# apply amplitude, phase, and modulation and add the resulting waveforms to the library
wfLib = {wf_sig(padding_entry(0)) : TAZShape}
for wf in flatten(seqs):
if isinstance(wf, Compiler.Waveform) and wf_sig(wf) not in wfLib:
shape = np.exp(1j*wf.phase) * wf.amp * shapeLib[wf.key]
if wf.frequency != 0 and wf.amp != 0:
shape *= np.exp(-1j*2*np.pi*wf.frequency*np.arange(wf.length)/SAMPLING_RATE) #minus from negative frequency qubits
wfLib[wf_sig(wf)] = shape
return wfLib
def build_waveforms(seqs, shapeLib):
# apply amplitude, phase, and modulation and add the resulting waveforms to the library
wfLib = {wf_sig(padding_entry(0)): TAZShape}
for wf in flatten(seqs):
if isinstance(wf, APSWaveform) and wf_sig(wf) not in wfLib:
shape = np.exp(1j * wf.phase) * wf.amp * shapeLib[wf.key]
if wf.frequency != 0 and wf.amp != 0:
shape *= np.exp(
-1j * 2 * np.pi * wf.frequency * np.arange(len(shape)) /
SAMPLING_RATE) #minus from negative frequency qubits
wfLib[wf_sig(wf)] = shape
return wfLib
def flattenSeqs(seq):
hasList = False
for el in seq:
if isinstance(el, collections.Iterable) and not isinstance(
el, (str, Pulse, CompositePulse)):
hasList = True
break
if hasList:
newS = []
for el in flatten(seq):
newS.append(el)
return newS
else:
return seq