class Firwin(QWidget):
FRMT = 'ba' # output format(s) of filter design routines 'zpk' / 'ba' / 'sos'
# currently, only 'ba' is supported for firwin routines
sig_tx = pyqtSignal(object)
def __init__(self):
QWidget.__init__(self)
self.ft = 'FIR'
self.fft_window = None
# dictionary for firwin window settings
self.win_dict = fb.fil[0]['win_fir']
c = Common()
self.rt_dict = c.rt_base_iir
self.rt_dict_add = {
'COM': {
'min': {
'msg':
('a',
r"<br /><b>Note:</b> Filter order is only a rough approximation "
"and most likely far too low!")
},
'man': {
'msg':
('a', r"Enter desired filter order <b><i>N</i></b> and "
"<b>-6 dB</b> pass band corner "
"frequency(ies) <b><i>F<sub>C</sub></i></b> .")
},
},
'LP': {
'man': {},
'min': {}
},
'HP': {
'man': {
'msg': ('a', r"<br /><b>Note:</b> Order needs to be odd!")
},
'min': {}
},
'BS': {
'man': {
'msg': ('a', r"<br /><b>Note:</b> Order needs to be odd!")
},
'min': {}
},
'BP': {
'man': {},
'min': {}
},
}
self.info = """**Windowed FIR filters**
are designed by truncating the
infinite impulse response of an ideal filter with a window function.
The kind of used window has strong influence on ripple etc. of the
resulting filter.
**Design routines:**
``scipy.signal.firwin()``
"""
#self.info_doc = [] is set in self._update_UI()
#------------------- end of static info for filter tree ---------------
#----------------------------------------------------------------------
def construct_UI(self):
"""
Create additional subwidget(s) needed for filter design:
These subwidgets are instantiated dynamically when needed in
select_filter.py using the handle to the filter object, fb.filObj .
"""
# Combobox for selecting the algorithm to estimate minimum filter order
self.cmb_firwin_alg = QComboBox(self)
self.cmb_firwin_alg.setObjectName('wdg_cmb_firwin_alg')
self.cmb_firwin_alg.addItems(['ichige', 'kaiser', 'herrmann'])
# Minimum size, can be changed in the upper hierarchy levels using layouts:
self.cmb_firwin_alg.setSizeAdjustPolicy(QComboBox.AdjustToContents)
self.cmb_firwin_alg.hide()
# Combobox for selecting the window used for filter design
self.cmb_firwin_win = QComboBox(self)
self.cmb_firwin_win.addItems(get_window_names())
self.cmb_firwin_win.setObjectName('wdg_cmb_firwin_win')
# Minimum size, can be changed in the upper hierarchy levels using layouts:
self.cmb_firwin_win.setSizeAdjustPolicy(QComboBox.AdjustToContents)
self.but_fft_win = QPushButton(self)
self.but_fft_win.setText("WIN FFT")
self.but_fft_win.setToolTip(
"Show time and frequency response of FFT Window")
self.but_fft_win.setCheckable(True)
self.but_fft_win.setChecked(False)
self.lblWinPar1 = QLabel("a", self)
self.lblWinPar1.setObjectName('wdg_lbl_firwin_1')
self.ledWinPar1 = QLineEdit(self)
self.ledWinPar1.setText("0.5")
self.ledWinPar1.setObjectName('wdg_led_firwin_1')
self.lblWinPar1.setVisible(False)
self.ledWinPar1.setVisible(False)
self.lblWinPar2 = QLabel("b", self)
self.lblWinPar2.setObjectName('wdg_lbl_firwin_2')
self.ledWinPar2 = QLineEdit(self)
self.ledWinPar2.setText("0.5")
self.ledWinPar2.setObjectName('wdg_led_firwin_2')
self.ledWinPar2.setVisible(False)
self.lblWinPar2.setVisible(False)
self.layHWin1 = QHBoxLayout()
self.layHWin1.addWidget(self.cmb_firwin_win)
self.layHWin1.addWidget(self.but_fft_win)
self.layHWin1.addWidget(self.cmb_firwin_alg)
self.layHWin2 = QHBoxLayout()
self.layHWin2.addWidget(self.lblWinPar1)
self.layHWin2.addWidget(self.ledWinPar1)
self.layHWin2.addWidget(self.lblWinPar2)
self.layHWin2.addWidget(self.ledWinPar2)
self.layVWin = QVBoxLayout()
self.layVWin.addLayout(self.layHWin1)
self.layVWin.addLayout(self.layHWin2)
self.layVWin.setContentsMargins(0, 0, 0, 0)
# Widget containing all subwidgets (cmbBoxes, Labels, lineEdits)
self.wdg_fil = QWidget(self)
self.wdg_fil.setObjectName('wdg_fil')
self.wdg_fil.setLayout(self.layVWin)
#----------------------------------------------------------------------
# SIGNALS & SLOTs
#----------------------------------------------------------------------
self.cmb_firwin_alg.activated.connect(self._update_win_fft)
self.cmb_firwin_win.activated.connect(self._update_win_fft)
self.ledWinPar1.editingFinished.connect(self._read_param1)
self.ledWinPar2.editingFinished.connect(self._read_param2)
self.but_fft_win.clicked.connect(self.show_fft_win)
#----------------------------------------------------------------------
self._load_dict() # get initial / last setting from dictionary
self._update_win_fft()
#=============================================================================
# Copied from impz()
#==============================================================================
def _read_param1(self):
"""Read out textbox when editing is finished and update dict and fft window"""
param = safe_eval(self.ledWinPar1.text(),
self.win_dict['par'][0]['val'],
sign='pos',
return_type='float')
if param < self.win_dict['par'][0]['min']:
param = self.win_dict['par'][0]['min']
elif param > self.win_dict['par'][0]['max']:
param = self.win_dict['par'][0]['max']
self.ledWinPar1.setText(str(param))
self.win_dict['par'][0]['val'] = param
self._update_win_fft()
def _read_param2(self):
"""Read out textbox when editing is finished and update dict and fft window"""
param = safe_eval(self.ledWinPar2.text(),
self.win_dict['par'][1]['val'],
return_type='float')
if param < self.win_dict['par'][1]['min']:
param = self.win_dict['par'][1]['min']
elif param > self.win_dict['par'][1]['max']:
param = self.win_dict['par'][1]['max']
self.ledWinPar2.setText(str(param))
self.win_dict['par'][1]['val'] = param
self._update_win_fft()
def _update_win_fft(self):
""" Update window type for FirWin """
self.alg = str(self.cmb_firwin_alg.currentText())
self.fir_window_name = qget_cmb_box(self.cmb_firwin_win, data=False)
self.win = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
n_par = self.win_dict['n_par']
self.lblWinPar1.setVisible(n_par > 0)
self.ledWinPar1.setVisible(n_par > 0)
self.lblWinPar2.setVisible(n_par > 1)
self.ledWinPar2.setVisible(n_par > 1)
if n_par > 0:
self.lblWinPar1.setText(
to_html(self.win_dict['par'][0]['name'] + " =", frmt='bi'))
self.ledWinPar1.setText(str(self.win_dict['par'][0]['val']))
self.ledWinPar1.setToolTip(self.win_dict['par'][0]['tooltip'])
if n_par > 1:
self.lblWinPar2.setText(
to_html(self.win_dict['par'][1]['name'] + " =", frmt='bi'))
self.ledWinPar2.setText(str(self.win_dict['par'][1]['val']))
self.ledWinPar2.setToolTip(self.win_dict['par'][1]['tooltip'])
# sig_tx -> select_filter -> filter_specs
self.sig_tx.emit({'sender': __name__, 'filt_changed': 'firwin'})
#=============================================================================
def _load_dict(self):
"""
Reload window selection and parameters from filter dictionary
and set UI elements accordingly. load_dict() is called upon
initialization and when the filter is loaded from disk.
"""
self.N = fb.fil[0]['N']
win_idx = 0
alg_idx = 0
if 'wdg_fil' in fb.fil[0] and 'firwin' in fb.fil[0]['wdg_fil']:
wdg_fil_par = fb.fil[0]['wdg_fil']['firwin']
if 'win' in wdg_fil_par:
if np.isscalar(
wdg_fil_par['win']): # true for strings (non-vectors)
window = wdg_fil_par['win']
else:
window = wdg_fil_par['win'][0]
self.ledWinPar1.setText(str(wdg_fil_par['win'][1]))
if len(wdg_fil_par['win']) > 2:
self.ledWinPar2.setText(str(wdg_fil_par['win'][2]))
# find index for window string
win_idx = self.cmb_firwin_win.findText(
window, Qt.MatchFixedString) # case insensitive flag
if win_idx == -1: # Key does not exist, use first entry instead
win_idx = 0
if 'alg' in wdg_fil_par:
alg_idx = self.cmb_firwin_alg.findText(wdg_fil_par['alg'],
Qt.MatchFixedString)
if alg_idx == -1: # Key does not exist, use first entry instead
alg_idx = 0
self.cmb_firwin_win.setCurrentIndex(
win_idx) # set index for window and
self.cmb_firwin_alg.setCurrentIndex(alg_idx) # and algorithm cmbBox
def _store_entries(self):
"""
Store window and alg. selection and parameter settings (part of
self.firWindow, if any) in filter dictionary.
"""
if not 'wdg_fil' in fb.fil[0]:
fb.fil[0].update({'wdg_fil': {}})
fb.fil[0]['wdg_fil'].update(
{'firwin': {
'win': self.firWindow,
'alg': self.alg
}})
def _get_params(self, fil_dict):
"""
Translate parameters from the passed dictionary to instance
parameters, scaling / transforming them if needed.
"""
self.N = fil_dict['N']
self.F_PB = fil_dict['F_PB']
self.F_SB = fil_dict['F_SB']
self.F_PB2 = fil_dict['F_PB2']
self.F_SB2 = fil_dict['F_SB2']
self.F_C = fil_dict['F_C']
self.F_C2 = fil_dict['F_C2']
# firwin amplitude specs are linear (not in dBs)
self.A_PB = fil_dict['A_PB']
self.A_PB2 = fil_dict['A_PB2']
self.A_SB = fil_dict['A_SB']
self.A_SB2 = fil_dict['A_SB2']
# self.alg = 'ichige' # algorithm for determining the minimum order
# self.alg = self.cmb_firwin_alg.currentText()
def _test_N(self):
"""
Warn the user if the calculated order is too high for a reasonable filter
design.
"""
if self.N > 1000:
return qfilter_warning(self, self.N, "FirWin")
else:
return True
def _save(self, fil_dict, arg):
"""
Convert between poles / zeros / gain, filter coefficients (polynomes)
and second-order sections and store all available formats in the passed
dictionary 'fil_dict'.
"""
fil_save(fil_dict, arg, self.FRMT, __name__)
try: # has the order been calculated by a "min" filter design?
fil_dict['N'] = self.N # yes, update filterbroker
except AttributeError:
pass
# self._store_entries()
#------------------------------------------------------------------------------
def firwin(self,
numtaps,
cutoff,
window=None,
pass_zero=True,
scale=True,
nyq=1.0,
fs=None):
"""
FIR filter design using the window method. This is more or less the
same as `scipy.signal.firwin` with the exception that an ndarray with
the window values can be passed as an alternative to the window name.
The parameters "width" (specifying a Kaiser window) and "fs" have been
omitted, they are not needed here.
This function computes the coefficients of a finite impulse response
filter. The filter will have linear phase; it will be Type I if
`numtaps` is odd and Type II if `numtaps` is even.
Type II filters always have zero response at the Nyquist rate, so a
ValueError exception is raised if firwin is called with `numtaps` even and
having a passband whose right end is at the Nyquist rate.
Parameters
----------
numtaps : int
Length of the filter (number of coefficients, i.e. the filter
order + 1). `numtaps` must be even if a passband includes the
Nyquist frequency.
cutoff : float or 1D array_like
Cutoff frequency of filter (expressed in the same units as `nyq`)
OR an array of cutoff frequencies (that is, band edges). In the
latter case, the frequencies in `cutoff` should be positive and
monotonically increasing between 0 and `nyq`. The values 0 and
`nyq` must not be included in `cutoff`.
window : ndarray or string
string: use the window with the passed name from scipy.signal.windows
ndarray: The window values - this is an addition to the original
firwin routine.
pass_zero : bool, optional
If True, the gain at the frequency 0 (i.e. the "DC gain") is 1.
Otherwise the DC gain is 0.
scale : bool, optional
Set to True to scale the coefficients so that the frequency
response is exactly unity at a certain frequency.
That frequency is either:
- 0 (DC) if the first passband starts at 0 (i.e. pass_zero
is True)
- `nyq` (the Nyquist rate) if the first passband ends at
`nyq` (i.e the filter is a single band highpass filter);
center of first passband otherwise
nyq : float, optional
Nyquist frequency. Each frequency in `cutoff` must be between 0
and `nyq`.
Returns
-------
h : (numtaps,) ndarray
Coefficients of length `numtaps` FIR filter.
Raises
------
ValueError
If any value in `cutoff` is less than or equal to 0 or greater
than or equal to `nyq`, if the values in `cutoff` are not strictly
monotonically increasing, or if `numtaps` is even but a passband
includes the Nyquist frequency.
See also
--------
scipy.firwin
"""
cutoff = np.atleast_1d(cutoff) / float(nyq)
# Check for invalid input.
if cutoff.ndim > 1:
raise ValueError("The cutoff argument must be at most "
"one-dimensional.")
if cutoff.size == 0:
raise ValueError("At least one cutoff frequency must be given.")
if cutoff.min() <= 0 or cutoff.max() >= 1:
raise ValueError(
"Invalid cutoff frequency {0}: frequencies must be "
"greater than 0 and less than nyq.".format(cutoff))
if np.any(np.diff(cutoff) <= 0):
raise ValueError("Invalid cutoff frequencies: the frequencies "
"must be strictly increasing.")
pass_nyquist = bool(cutoff.size & 1) ^ pass_zero
if pass_nyquist and numtaps % 2 == 0:
raise ValueError(
"A filter with an even number of coefficients must "
"have zero response at the Nyquist rate.")
# Insert 0 and/or 1 at the ends of cutoff so that the length of cutoff
# is even, and each pair in cutoff corresponds to passband.
cutoff = np.hstack(([0.0] * pass_zero, cutoff, [1.0] * pass_nyquist))
# `bands` is a 2D array; each row gives the left and right edges of
# a passband.
bands = cutoff.reshape(-1, 2)
# Build up the coefficients.
alpha = 0.5 * (numtaps - 1)
m = np.arange(0, numtaps) - alpha
h = 0
for left, right in bands:
h += right * sinc(right * m)
h -= left * sinc(left * m)
if type(window) == str:
# Get and apply the window function.
from scipy.signal.signaltools import get_window
win = get_window(window, numtaps, fftbins=False)
elif type(window) == np.ndarray:
win = window
else:
logger.error(
"The 'window' was neither a string nor a numpy array, it could not be evaluated."
)
return None
# apply the window function.
h *= win
# Now handle scaling if desired.
if scale:
# Get the first passband.
left, right = bands[0]
if left == 0:
scale_frequency = 0.0
elif right == 1:
scale_frequency = 1.0
else:
scale_frequency = 0.5 * (left + right)
c = np.cos(np.pi * m * scale_frequency)
s = np.sum(h * c)
h /= s
return h
def _firwin_ord(self, F, W, A, alg):
#http://www.mikroe.com/chapters/view/72/chapter-2-fir-filters/
delta_f = abs(F[1] - F[0]) * 2 # referred to f_Ny
delta_A = np.sqrt(A[0] * A[1])
if self.fir_window_name == 'kaiser':
N, beta = sig.kaiserord(20 * np.log10(np.abs(fb.fil[0]['A_SB'])),
delta_f)
self.ledWinPar1.setText(str(beta))
fb.fil[0]['wdg_fil'][1] = beta
self._update_UI()
else:
N = remezord(F, W, A, fs=1, alg=alg)[0]
return N
def LPmin(self, fil_dict):
self._get_params(fil_dict)
self.N = self._firwin_ord([self.F_PB, self.F_SB], [1, 0],
[self.A_PB, self.A_SB],
alg=self.alg)
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
fil_dict['F_C'] = (self.F_SB + self.F_PB
) / 2 # use average of calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
window=self.fir_window,
nyq=0.5))
def LPman(self, fil_dict):
self._get_params(fil_dict)
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
window=self.fir_window,
nyq=0.5))
def HPmin(self, fil_dict):
self._get_params(fil_dict)
N = self._firwin_ord([self.F_SB, self.F_PB], [0, 1],
[self.A_SB, self.A_PB],
alg=self.alg)
self.N = round_odd(N) # enforce odd order
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
fil_dict['F_C'] = (self.F_SB + self.F_PB
) / 2 # use average of calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
window=self.fir_window,
pass_zero=False,
nyq=0.5))
def HPman(self, fil_dict):
self._get_params(fil_dict)
self.N = round_odd(self.N) # enforce odd order
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
window=self.fir_window,
pass_zero=False,
nyq=0.5))
# For BP and BS, F_PB and F_SB have two elements each
def BPmin(self, fil_dict):
self._get_params(fil_dict)
self.N = remezord([self.F_SB, self.F_PB, self.F_PB2, self.F_SB2],
[0, 1, 0], [self.A_SB, self.A_PB, self.A_SB2],
fs=1,
alg=self.alg)[0]
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
fil_dict['F_C'] = (self.F_SB + self.F_PB
) / 2 # use average of calculated F_PB and F_SB
fil_dict['F_C2'] = (self.F_SB2 + self.F_PB2
) / 2 # use average of calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.fir_window,
pass_zero=False,
nyq=0.5))
def BPman(self, fil_dict):
self._get_params(fil_dict)
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.fir_window,
pass_zero=False,
nyq=0.5))
def BSmin(self, fil_dict):
self._get_params(fil_dict)
N = remezord([self.F_PB, self.F_SB, self.F_SB2, self.F_PB2], [1, 0, 1],
[self.A_PB, self.A_SB, self.A_PB2],
fs=1,
alg=self.alg)[0]
self.N = round_odd(N) # enforce odd order
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
fil_dict['F_C'] = (self.F_SB + self.F_PB
) / 2 # use average of calculated F_PB and F_SB
fil_dict['F_C2'] = (self.F_SB2 + self.F_PB2
) / 2 # use average of calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.fir_window,
pass_zero=True,
nyq=0.5))
def BSman(self, fil_dict):
self._get_params(fil_dict)
self.N = round_odd(self.N) # enforce odd order
if not self._test_N():
return -1
self.fir_window = calc_window_function(self.win_dict,
self.fir_window_name,
N=self.N,
sym=True)
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.fir_window,
pass_zero=True,
nyq=0.5))
#------------------------------------------------------------------------------
def show_fft_win(self):
"""
Pop-up FFT window
"""
if self.but_fft_win.isChecked():
qstyle_widget(self.but_fft_win, "changed")
else:
qstyle_widget(self.but_fft_win, "normal")
if self.fft_window is None: # no handle to the window? Create a new instance
if self.but_fft_win.isChecked():
# important: Handle to window must be class attribute
# pass the name of the dictionary where parameters are stored and
# whether a symmetric window or one that can be continued periodically
# will be constructed
self.fft_window = Plot_FFT_win(self,
win_dict=self.win_dict,
sym=True,
title="pyFDA FIR Window Viewer")
self.sig_tx.connect(self.fft_window.sig_rx)
self.fft_window.sig_tx.connect(self.close_fft_win)
self.fft_window.show(
) # modeless i.e. non-blocking popup window
else:
if not self.but_fft_win.isChecked():
if self.fft_window is None:
logger.warning("FFT window is already closed!")
else:
self.fft_window.close()
def close_fft_win(self):
self.fft_window = None
self.but_fft_win.setChecked(False)
qstyle_widget(self.but_fft_win, "normal")
class Firwin(QWidget):
FRMT = 'ba' # output format(s) of filter design routines 'zpk' / 'ba' / 'sos'
# currently, only 'ba' is supported for firwin routines
sig_tx = pyqtSignal(
object) # local signal between FFT widget and FFTWin_Selector
sig_tx_local = pyqtSignal(object)
from pyfda.libs.pyfda_qt_lib import emit
def __init__(self):
QWidget.__init__(self)
self.ft = 'FIR'
win_names_list = [
"Boxcar", "Rectangular", "Barthann", "Bartlett", "Blackman",
"Blackmanharris", "Bohman", "Cosine", "Dolph-Chebyshev", "Flattop",
"General Gaussian", "Gauss", "Hamming", "Hann", "Kaiser",
"Nuttall", "Parzen", "Slepian", "Triangular", "Tukey"
]
self.cur_win_name = "Kaiser" # set initial window type
self.alg = "ichige"
# initialize windows dict with the list above for firwin window settings
self.win_dict = get_windows_dict(win_names_list=win_names_list,
cur_win_name=self.cur_win_name)
# get initial / last setting from dictionary, updating self.win_dict
self._load_dict()
# instantiate FFT window with windows dict
self.fft_widget = Plot_FFT_win(self,
win_dict=self.win_dict,
sym=True,
title="pyFDA FIR Window Viewer")
# hide window initially, this is modeless i.e. a non-blocking popup window
self.fft_widget.hide()
c = Common()
self.rt_dict = c.rt_base_iir
self.rt_dict_add = {
'COM': {
'min': {
'msg':
('a', "<br /><b>Note:</b> Filter order is only a rough "
"approximation and most likely far too low!")
},
'man': {
'msg':
('a', "Enter desired filter order <b><i>N</i></b> and "
"<b>-6 dB</b> pass band corner "
"frequency(ies) <b><i>F<sub>C</sub></i></b> .")
},
},
'LP': {
'man': {},
'min': {}
},
'HP': {
'man': {
'msg': ('a', r"<br /><b>Note:</b> Order needs to be odd!")
},
'min': {}
},
'BS': {
'man': {
'msg': ('a', r"<br /><b>Note:</b> Order needs to be odd!")
},
'min': {}
},
'BP': {
'man': {},
'min': {}
},
}
self.info = """**Windowed FIR filters**
are designed by truncating the
infinite impulse response of an ideal filter with a window function.
The kind of used window has strong influence on ripple etc. of the
resulting filter.
**Design routines:**
``scipy.signal.firwin()``
"""
# self.info_doc = [] is set in self._update_UI()
# ------------------- end of static info for filter tree ---------------
# ------------------------------------------------------------------------------
def process_sig_rx(self, dict_sig=None):
"""
Process local signals from / for
- FFT window widget
- qfft_win_select
"""
logger.debug("SIG_RX - vis: {0}\n{1}".format(self.isVisible(),
pprint_log(dict_sig)))
if dict_sig['id'] == id(self):
logger.warning(f"Stopped infinite loop:\n{pprint_log(dict_sig)}")
# --- signals coming from the FFT window widget or the qfft_win_select
if dict_sig['class'] in {'Plot_FFT_win', 'QFFTWinSelector'}:
if 'closeEvent' in dict_sig: # hide FFT window windget and return
self.hide_fft_wdg()
return
else:
if 'view_changed' in dict_sig and 'fft_win' in dict_sig[
'view_changed']:
# self._update_fft_window() # TODO: needed?
# local connection to FFT window widget and qfft_win_select
self.emit(dict_sig, sig_name='sig_tx_local')
# global connection to upper hierachies
# send notification that filter design has changed
self.emit({'filt_changed': 'firwin'})
# --------------------------------------------------------------------------
def construct_UI(self):
"""
Create additional subwidget(s) needed for filter design:
These subwidgets are instantiated dynamically when needed in
select_filter.py using the handle to the filter object, fb.filObj .
"""
# Combobox for selecting the algorithm to estimate minimum filter order
self.cmb_firwin_alg = QComboBox(self)
self.cmb_firwin_alg.setObjectName('wdg_cmb_firwin_alg')
self.cmb_firwin_alg.addItems(['ichige', 'kaiser', 'herrmann'])
# Minimum size, can be changed in the upper hierarchy levels using layouts:
self.cmb_firwin_alg.setSizeAdjustPolicy(QComboBox.AdjustToContents)
self.cmb_firwin_alg.hide()
self.qfft_win_select = QFFTWinSelector(self, self.win_dict)
# Minimum size, can be changed in the upper hierarchy levels using layouts:
# self.qfft_win_select.setSizeAdjustPolicy(QComboBox.AdjustToContents)
self.but_fft_wdg = QPushButton(self)
self.but_fft_wdg.setIcon(QIcon(":/fft.svg"))
but_height = self.qfft_win_select.sizeHint().height()
self.but_fft_wdg.setIconSize(QSize(but_height, but_height))
self.but_fft_wdg.setFixedSize(QSize(but_height, but_height))
self.but_fft_wdg.setToolTip(
'<span>Show / hide FFT widget (select window type '
' and display its properties).</span>')
self.but_fft_wdg.setCheckable(True)
self.but_fft_wdg.setChecked(False)
self.layHWin1 = QHBoxLayout()
# self.layHWin1.addWidget(self.cmb_firwin_win)
# self.layHWin1.addWidget(self.but_fft_wdg)
self.layHWin1.addWidget(self.cmb_firwin_alg)
self.layHWin2 = QHBoxLayout()
self.layHWin2.addWidget(self.but_fft_wdg)
self.layHWin2.addWidget(self.qfft_win_select)
self.layVWin = QVBoxLayout()
self.layVWin.addLayout(self.layHWin1)
self.layVWin.addLayout(self.layHWin2)
self.layVWin.setContentsMargins(0, 0, 0, 0)
# Widget containing all subwidgets (cmbBoxes, Labels, lineEdits)
self.wdg_fil = QWidget(self)
self.wdg_fil.setObjectName('wdg_fil')
self.wdg_fil.setLayout(self.layVWin)
# ----------------------------------------------------------------------
# GLOBAL SIGNALS & SLOTs
# ----------------------------------------------------------------------
# connect FFT widget to qfft_selector and vice versa and to signals upstream:
self.fft_widget.sig_tx.connect(self.process_sig_rx)
self.qfft_win_select.sig_tx.connect(self.process_sig_rx)
# connect process_sig_rx output to both FFT widgets
self.sig_tx_local.connect(self.fft_widget.sig_rx)
self.sig_tx_local.connect(self.qfft_win_select.sig_rx)
# ----------------------------------------------------------------------
# SIGNALS & SLOTs
# ----------------------------------------------------------------------
self.cmb_firwin_alg.currentIndexChanged.connect(
self._update_fft_window)
self.but_fft_wdg.clicked.connect(self.toggle_fft_wdg)
# ----------------------------------------------------------------------
# ==============================================================================
def _update_fft_window(self):
""" Update window type for FirWin - unneeded at the moment """
self.alg = str(self.cmb_firwin_alg.currentText())
self.emit({'filt_changed': 'firwin'})
# --------------------------------------------------------------------------
def _load_dict(self):
"""
Reload window selection and parameters from filter dictionary
and set UI elements accordingly. load_dict() is called upon
initialization and when the filter is loaded from disk.
"""
self.N = fb.fil[0]['N']
# alg_idx = 0
if 'wdg_fil' in fb.fil[0] and 'firwin' in fb.fil[0]['wdg_fil']\
and type(fb.fil[0]['wdg_fil']['firwin']) is dict:
self.win_dict = fb.fil[0]['wdg_fil']['firwin']
self.emit({'view_changed': 'fft_win_type'}, sig_name='sig_tx_local')
# --------------------------------------------------------------------------
def _store_dict(self):
"""
Store window and parameter settings using `self.win_dict` in filter dictionary.
"""
if 'wdg_fil' not in fb.fil[0]:
fb.fil[0].update({'wdg_fil': {}})
fb.fil[0]['wdg_fil'].update({'firwin': self.win_dict})
# --------------------------------------------------------------------------
def _get_params(self, fil_dict):
"""
Translate parameters from the passed dictionary to instance
parameters, scaling / transforming them if needed.
"""
self.N = fil_dict['N']
self.F_PB = fil_dict['F_PB']
self.F_SB = fil_dict['F_SB']
self.F_PB2 = fil_dict['F_PB2']
self.F_SB2 = fil_dict['F_SB2']
self.F_C = fil_dict['F_C']
self.F_C2 = fil_dict['F_C2']
# firwin amplitude specs are linear (not in dBs)
self.A_PB = fil_dict['A_PB']
self.A_PB2 = fil_dict['A_PB2']
self.A_SB = fil_dict['A_SB']
self.A_SB2 = fil_dict['A_SB2']
# self.alg = 'ichige' # algorithm for determining the minimum order
# self.alg = self.cmb_firwin_alg.currentText()
def _test_N(self):
"""
Warn the user if the calculated order is too high for a reasonable filter
design.
"""
if self.N > 1000:
return qfilter_warning(self, self.N, "FirWin")
else:
return True
def _save(self, fil_dict, arg):
"""
Convert between poles / zeros / gain, filter coefficients (polynomes)
and second-order sections and store all available formats in the passed
dictionary 'fil_dict'.
"""
fil_save(fil_dict, arg, self.FRMT, __name__)
try: # has the order been calculated by a "min" filter design?
fil_dict['N'] = self.N # yes, update filterbroker
except AttributeError:
pass
self._store_dict()
# ------------------------------------------------------------------------------
def firwin(self,
numtaps,
cutoff,
window=None,
pass_zero=True,
scale=True,
nyq=1.0,
fs=None):
"""
FIR filter design using the window method. This is more or less the
same as `scipy.signal.firwin` with the exception that an ndarray with
the window values can be passed as an alternative to the window name.
The parameters "width" (specifying a Kaiser window) and "fs" have been
omitted, they are not needed here.
This function computes the coefficients of a finite impulse response
filter. The filter will have linear phase; it will be Type I if
`numtaps` is odd and Type II if `numtaps` is even.
Type II filters always have zero response at the Nyquist rate, so a
ValueError exception is raised if firwin is called with `numtaps` even and
having a passband whose right end is at the Nyquist rate.
Parameters
----------
numtaps : int
Length of the filter (number of coefficients, i.e. the filter
order + 1). `numtaps` must be even if a passband includes the
Nyquist frequency.
cutoff : float or 1D array_like
Cutoff frequency of filter (expressed in the same units as `nyq`)
OR an array of cutoff frequencies (that is, band edges). In the
latter case, the frequencies in `cutoff` should be positive and
monotonically increasing between 0 and `nyq`. The values 0 and
`nyq` must not be included in `cutoff`.
window : ndarray or string
string: use the window with the passed name from scipy.signal.windows
ndarray: The window values - this is an addition to the original
firwin routine.
pass_zero : bool, optional
If True, the gain at the frequency 0 (i.e. the "DC gain") is 1.
Otherwise the DC gain is 0.
scale : bool, optional
Set to True to scale the coefficients so that the frequency
response is exactly unity at a certain frequency.
That frequency is either:
- 0 (DC) if the first passband starts at 0 (i.e. pass_zero
is True)
- `nyq` (the Nyquist rate) if the first passband ends at
`nyq` (i.e the filter is a single band highpass filter);
center of first passband otherwise
nyq : float, optional
Nyquist frequency. Each frequency in `cutoff` must be between 0
and `nyq`.
Returns
-------
h : (numtaps,) ndarray
Coefficients of length `numtaps` FIR filter.
Raises
------
ValueError
If any value in `cutoff` is less than or equal to 0 or greater
than or equal to `nyq`, if the values in `cutoff` are not strictly
monotonically increasing, or if `numtaps` is even but a passband
includes the Nyquist frequency.
See also
--------
scipy.firwin
"""
cutoff = np.atleast_1d(cutoff) / float(nyq)
# Check for invalid input.
if cutoff.ndim > 1:
raise ValueError("The cutoff argument must be at most "
"one-dimensional.")
if cutoff.size == 0:
raise ValueError("At least one cutoff frequency must be given.")
if cutoff.min() <= 0 or cutoff.max() >= 1:
raise ValueError(
"Invalid cutoff frequency {0}: frequencies must be "
"greater than 0 and less than nyq.".format(cutoff))
if np.any(np.diff(cutoff) <= 0):
raise ValueError("Invalid cutoff frequencies: the frequencies "
"must be strictly increasing.")
pass_nyquist = bool(cutoff.size & 1) ^ pass_zero
if pass_nyquist and numtaps % 2 == 0:
raise ValueError(
"A filter with an even number of coefficients must "
"have zero response at the Nyquist rate.")
# Insert 0 and/or 1 at the ends of cutoff so that the length of cutoff
# is even, and each pair in cutoff corresponds to passband.
cutoff = np.hstack(([0.0] * pass_zero, cutoff, [1.0] * pass_nyquist))
# `bands` is a 2D array; each row gives the left and right edges of
# a passband.
bands = cutoff.reshape(-1, 2)
# Build up the coefficients.
alpha = 0.5 * (numtaps - 1)
m = np.arange(0, numtaps) - alpha
h = 0
for left, right in bands:
h += right * sinc(right * m)
h -= left * sinc(left * m)
if type(window) == str:
# Get and apply the window function.
# from scipy.signal.signaltools import get_window
win = signaltools.get_window(window, numtaps, fftbins=False)
elif type(window) == np.ndarray:
win = window
else:
logger.error(
"The 'window' was neither a string nor a numpy array, "
"it could not be evaluated.")
return None
# apply the window function.
h *= win
# Now handle scaling if desired.
if scale:
# Get the first passband.
left, right = bands[0]
if left == 0:
scale_frequency = 0.0
elif right == 1:
scale_frequency = 1.0
else:
scale_frequency = 0.5 * (left + right)
c = np.cos(np.pi * m * scale_frequency)
s = np.sum(h * c)
h /= s
return h
def _firwin_ord(self, F, W, A, alg):
# http://www.mikroe.com/chapters/view/72/chapter-2-fir-filters/
delta_f = abs(F[1] - F[0]) * 2 # referred to f_Ny
# delta_A = np.sqrt(A[0] * A[1])
if "Kaiser" in self.win_dict and self.win_dict[
'cur_win_name'] == "Kaiser":
N, beta = sig.kaiserord(20 * np.log10(np.abs(fb.fil[0]['A_SB'])),
delta_f)
# logger.warning(f"N={N}, beta={beta}, A_SB={fb.fil[0]['A_SB']}")
self.win_dict["Kaiser"]["par"][0]["val"] = beta
self.qfft_win_select.led_win_par_0.setText(str(beta))
self.qfft_win_select.ui2dict_params(
) # pass changed parameter to other widgets
else:
N = remezord(F, W, A, fs=1, alg=alg)[0]
self.emit({'view_changed': 'fft_win_type'}, sig_name='sig_tx_local')
return N
def LPmin(self, fil_dict):
self._get_params(fil_dict)
self.N = self._firwin_ord([self.F_PB, self.F_SB], [1, 0],
[self.A_PB, self.A_SB],
alg=self.alg)
if not self._test_N():
return -1
fil_dict['F_C'] = (self.F_SB +
self.F_PB) / 2 # average calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
nyq=0.5,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
def LPman(self, fil_dict):
self._get_params(fil_dict)
if not self._test_N():
return -1
logger.warning(self.win_dict["cur_win_name"])
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
nyq=0.5,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
def HPmin(self, fil_dict):
self._get_params(fil_dict)
N = self._firwin_ord([self.F_SB, self.F_PB], [0, 1],
[self.A_SB, self.A_PB],
alg=self.alg)
self.N = round_odd(N) # enforce odd order
if not self._test_N():
return -1
fil_dict['F_C'] = (self.F_SB +
self.F_PB) / 2 # average calculated F_PB and F_SB
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
pass_zero=False,
nyq=0.5,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
def HPman(self, fil_dict):
self._get_params(fil_dict)
self.N = round_odd(self.N) # enforce odd order
if not self._test_N():
return -1
self._save(
fil_dict,
self.firwin(self.N,
fil_dict['F_C'],
pass_zero=False,
nyq=0.5,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
# For BP and BS, F_PB and F_SB have two elements each
def BPmin(self, fil_dict):
self._get_params(fil_dict)
self.N = remezord([self.F_SB, self.F_PB, self.F_PB2, self.F_SB2],
[0, 1, 0], [self.A_SB, self.A_PB, self.A_SB2],
fs=1,
alg=self.alg)[0]
if not self._test_N():
return -1
fil_dict['F_C'] = (self.F_SB +
self.F_PB) / 2 # average calculated F_PB and F_SB
fil_dict['F_C2'] = (self.F_SB2 + self.F_PB2) / 2
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
nyq=0.5,
pass_zero=False,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
def BPman(self, fil_dict):
self._get_params(fil_dict)
if not self._test_N():
return -1
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
nyq=0.5,
pass_zero=False,
window=self.qfft_win_select.get_window(self.N,
sym=True)))
def BSmin(self, fil_dict):
self._get_params(fil_dict)
N = remezord([self.F_PB, self.F_SB, self.F_SB2, self.F_PB2], [1, 0, 1],
[self.A_PB, self.A_SB, self.A_PB2],
fs=1,
alg=self.alg)[0]
self.N = round_odd(N) # enforce odd order
if not self._test_N():
return -1
fil_dict['F_C'] = (self.F_SB +
self.F_PB) / 2 # average calculated F_PB and F_SB
fil_dict['F_C2'] = (self.F_SB2 + self.F_PB2) / 2
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.qfft_win_select.get_window(self.N,
sym=True),
pass_zero=True,
nyq=0.5))
def BSman(self, fil_dict):
self._get_params(fil_dict)
self.N = round_odd(self.N) # enforce odd order
if not self._test_N():
return -1
self._save(
fil_dict,
self.firwin(self.N, [fil_dict['F_C'], fil_dict['F_C2']],
window=self.qfft_win_select.get_window(self.N,
sym=True),
pass_zero=True,
nyq=0.5))
# ------------------------------------------------------------------------------
def toggle_fft_wdg(self):
"""
Show / hide FFT widget depending on the state of the corresponding button
When widget is shown, trigger an update of the window function.
"""
if self.but_fft_wdg.isChecked():
self.fft_widget.show()
self.emit({'view_changed': 'fft_win_type'},
sig_name='sig_tx_local')
else:
self.fft_widget.hide()
# --------------------------------------------------------------------------
def hide_fft_wdg(self):
"""
The closeEvent caused by clicking the "x" in the FFT widget is caught
there and routed here to only hide the window
"""
self.but_fft_wdg.setChecked(False)
self.fft_widget.hide()
