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()