def apply_DAC_filter(sig, fs, cutoff=18e9, fn=None, ch=1):
"""
Apply the frequency response filter of the DAC. This function
uses either a 2nd order Bessel filter or a measured frequency response
loaded from a file.
Parameters
----------
sig : array_like
signal to be filtered. Can be real or complex
fs : float
sampling rate of the signal
cutoff : float, optional
Cutoff frequency used by only by Bessel filter
fn : string, optional
filename of a experimentally measured response, if None use a Bessel
filter approximation
ch : int, optional
channel number of the measured response to use
Returns
-------
filter_sig : array_like
filtered signal
"""
# filtering was split into real and imaginary before but that should not be necessary
if fn is None:
filter_sig = filter_signal(sig, fs, cutoff, ftype="bessel", order=2)
else:
H_dac = load_dac_response(fn, fs, sig.shape[-1], ch=ch).astype(sig) # should check if response is real
sigf = fft.fft(sig)
filter_sig = fft.ifft(sigf * H_dac)
return filter_sig
def test_filter_signal_1d(self):
x = np.random.randn(2**15) + 0.j
y = cfilter.filter_signal(x, 2, 0.01)
assert x.shape == y.shape
def test_filter_signal(self):
s2 = cfilter.filter_signal(self.s, self.s.fs, 0.001)
assert type(self.s) is type(s2)
def test_filter_signal_attr(self, attr):
s2 = cfilter.filter_signal(self.s, self.s.fs, 0.01)
assert getattr(self.s, attr) is getattr(s2, attr)
def test_filter_signal(self, ndim):
x = np.random.randn(ndim, 2**15) + 0.j
y = cfilter.filter_signal(x, 2, 0.01)
assert x.shape == y.shape
def test_filter_signal_analog(self, dtype):
s = self.s.astype(dtype)
s2 = cfilter.filter_signal(s, s.fs, 0.001, analog=True)
assert s2.dtype is np.dtype(dtype)
def test_filter_signal(self, dtype):
s = self.s.astype(dtype)
s2 = cfilter.filter_signal(s, s.fs, 0.001)
assert s2.dtype == np.dtype(dtype)
def test_filter_signal_1d(self, ftype, analog):
x = np.random.randn(2**15) + 0.j
y = cfilter.filter_signal(x, 2, 0.01, ftype=ftype, analog=analog)
assert x.shape == y.shape
def test_filter_signal_type(self, ndim, ftype, analog, dtype):
x = np.random.randn(ndim, 2**15) + 0.j
x = x.astype(dtype)
y = cfilter.filter_signal(x, 2, 0.01, ftype=ftype, analog=analog)
assert x.shape == y.shape
assert x.dtype == y.dtype
def test_filter_signal_analog_attr(self, attr):
s = self.s
s2 = cfilter.filter_signal(s, s.fs, 0.01, analog=True)
assert getattr(s, attr) is getattr(s2, attr)
