Lots of things improved. Forgot to count, became big commit, excuse myself

CMakeLists.txt

@@ -30,7 +30,7 @@ endif(LASP_FLOAT STREQUAL "double")
 
 
 if(NOT DEFINED LASP_DEBUG)
-  message(SEND_ERROR "LASP_DEBUG flag not defined. Please set -DLASP_DEBUG=TRUE or -DLASP_DEBUG=FALSE")
+  message(FATAL_ERROR "LASP_DEBUG flag not defined. Please set -DLASP_DEBUG=TRUE or -DLASP_DEBUG=FALSE")
 endif(NOT DEFINED LASP_DEBUG)
 
 # ##################### END Cmake variables converted to a macro
@@ -98,12 +98,6 @@ else()
   set(win32 false)
 endif(CMAKE_SYSTEM_NAME STREQUAL "Windows")
 
-# If numpy cannot be found in the standard include path of the Python 
-if(DEFINED NUMPY_INCLUDE)
-  include_directories(${NUMPY_INCLUDE})
-endif(DEFINED NUMPY_INCLUDE)
-
-
 add_subdirectory(fftpack)
 include_directories(
   fftpack
@@ -112,8 +106,6 @@ include_directories(
 add_subdirectory(lasp)
 add_subdirectory(test)
 
-find_program(PYTHON "python")
-
 if (PYTHON)
     # set(SETUP_PY_IN "${CMAKE_CURRENT_SOURCE_DIR}/setup.py.in")
     set(SETUP_PY    "${CMAKE_CURRENT_BINARY_DIR}/setup.py")
@@ -134,4 +126,3 @@ endif()
 
 
 ############################## End compiler settings
-

lasp/CMakeLists.txt

@@ -1,16 +1,15 @@
 add_subdirectory(c)
-
 configure_file(config.pxi.in config.pxi)
-
 set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_CURRENT_SOURCE_DIR}/cmake")
-find_package( PythonLibs REQUIRED )
+find_package(PythonLibs REQUIRED )
 include(UseCython)
-
+find_package(Numpy REQUIRED )
 
 include_directories(
-  .
+   ${PYTHON_NUMPY_INCLUDE_DIR}
-  c
+   .
-  )
+   c
+ )
 
 # add the command to generate the source code
 # add_custom_command (

lasp/cmake/FindNumpy.cmake

@@ -0,0 +1,41 @@
+# Find the Python NumPy package
+# PYTHON_NUMPY_INCLUDE_DIR
+# PYTHON_NUMPY_FOUND
+# will be set by this script
+
+cmake_minimum_required(VERSION 2.6)
+
+if(NOT PYTHON_EXECUTABLE)
+  if(NumPy_FIND_QUIETLY)
+    find_package(PythonInterp QUIET)
+  else()
+    find_package(PythonInterp)
+    set(__numpy_out 1)
+  endif()
+endif()
+
+if (PYTHON_EXECUTABLE)
+  # Find out the include path
+  execute_process(
+    COMMAND "${PYTHON_EXECUTABLE}" -c
+            "from __future__ import print_function\ntry: import numpy; print(numpy.get_include(), end='')\nexcept:pass\n"
+            OUTPUT_VARIABLE __numpy_path)
+  # And the version
+  execute_process(
+    COMMAND "${PYTHON_EXECUTABLE}" -c
+            "from __future__ import print_function\ntry: import numpy; print(numpy.__version__, end='')\nexcept:pass\n"
+    OUTPUT_VARIABLE __numpy_version)
+elseif(__numpy_out)
+  message(STATUS "Python executable not found.")
+endif(PYTHON_EXECUTABLE)
+
+find_path(PYTHON_NUMPY_INCLUDE_DIR numpy/arrayobject.h
+  HINTS "${__numpy_path}" "${PYTHON_INCLUDE_PATH}" NO_DEFAULT_PATH)
+
+if(PYTHON_NUMPY_INCLUDE_DIR)
+  set(PYTHON_NUMPY_FOUND 1 CACHE INTERNAL "Python numpy found")
+endif(PYTHON_NUMPY_INCLUDE_DIR)
+
+include(FindPackageHandleStandardArgs)
+find_package_handle_standard_args(NumPy REQUIRED_VARS PYTHON_NUMPY_INCLUDE_DIR
+VERSION_VAR __numpy_version)

lasp/filter/bandpass_fir.py

@@ -175,6 +175,8 @@ class ThirdOctaveBankDesigner(FilterBankDesigner):
                             '6.3k', '8k', '10k',
                             '12.5k', '16k', '20k']
 
+        assert len(self.xs) == len(self.nominal_txt)
+
     @property
     def b(self):
         # Band division factor, 3 for one-third octave bands

lasp/lasp_measurement.py

@@ -35,6 +35,8 @@ The video dataset can possibly be not present in the data.
 
 
 """
+__all__ = ['Measurement']
+from contextlib import contextmanager
 import h5py as h5
 import numpy as np
 from .lasp_config import LASP_NUMPY_FLOAT_TYPE
@@ -47,7 +49,7 @@ class BlockIter:
     Iterate over the blocks in the audio data of a h5 file
     """
 
-    def __init__(self, faudio):
+    def __init__(self, f):
         """
         Initialize a BlockIter object
 
@@ -55,8 +57,8 @@ class BlockIter:
             faudio: Audio dataset in the h5 file, accessed as f['audio']
         """
         self.i = 0
-        self.nblocks = faudio.shape[0]
+        self.nblocks = f['audio'].shape[0]
-        self.fa = faudio
+        self.fa = f['audio']
 
     def __iter__(self):
         return self
@@ -121,35 +123,55 @@ class Measurement:
 
         # Full filepath
         self.fn = fn
+
         # Base filename
         self.fn_base = os.path.split(fn)[1]
 
         # Open the h5 file in read-plus mode, to allow for changing the
         # measurement comment.
-        f = h5.File(fn, 'r+')
+        with h5.File(fn, 'r+') as f:
-        self.f = f
+            # Check for video data
+            try:
+                f['video']
+                self.has_video = True
+            except KeyError:
+                self.has_video = False
 
-        # Check for video data
+            self.nblocks, self.blocksize, self.nchannels = f['audio'].shape
-        try:
+            dtype = f['audio'].dtype
-            f['video']
+            self.sampwidth = getSampWidth(dtype)
-            self.has_video = True
-        except KeyError:
-            self.has_video = False
 
-        self.nblocks, self.blocksize, self.nchannels = f['audio'].shape
+            self.samplerate = f.attrs['samplerate']
-        dtype = f['audio'].dtype
+            self.N = (self.nblocks*self.blocksize)
-        self.sampwidth = getSampWidth(dtype)
+            self.T = self.N/self.samplerate
 
-        self.samplerate = f.attrs['samplerate']
+            # comment = read-write thing
-        self.N = (self.nblocks*self.blocksize)
+            try:
-        self.T = self.N/self.samplerate
+                self._comment = f.attrs['comment']
+            except KeyError:
+                f.attrs['comment'] = ''
+                self._comment = ''
 
-        # comment = read-write thing
+            # Sensitivity
-        try:
+            try:
-            self._comment = self.f.attrs['comment']
+                self._sens = f.attrs['sensitivity']
-        except KeyError:
+            except KeyError:
-            self.f.attrs['comment'] = ''
+                self._sens = np.ones(self.nchannels)
-            self._comment = ''
+
+            self._time = f.attrs['time']
+
+    @contextmanager
+    def file(self, mode='r'):
+        """
+        Contextmanager which opens the storage file and yields the file.
+
+        Args:
+            mode: Opening mode for the file. Should either be 'r', or 'r+'
+        """
+        if mode not in ('r','r+'):
+            raise ValueError('Invalid file opening mode.')
+        with h5.File(self.fn, mode) as f:
+            yield f
 
     @property
     def comment(self):
@@ -157,19 +179,23 @@ class Measurement:
 
     @comment.setter
     def comment(self, cmt):
-        self.f.attrs['comment'] = cmt
+        with self.file('r+') as f:
-        self._comment = cmt
+            f.attrs['comment'] = cmt
+            self._comment = cmt
 
     @property
     def recTime(self):
-        return (self.blocksize*self.nblocks)/self.samplerate
+        """
+        Returns the total recording time of the measurement, in float seconds.
+        """
+        return self.blocksize*self.nblocks/self.samplerate
 
     @property
     def time(self):
         """
         Returns the measurement time in seconds since the epoch.
         """
-        return self.f.attrs['time']
+        return self._time
 
     @property
     def prms(self):
@@ -186,7 +212,7 @@ class Measurement:
         except AttributeError:
             pass
 
-        sens = self.sensitivity
+        sens = self._sens
         pms = 0.
         for block in self.iterBlocks():
             pms += np.sum(block/sens[np.newaxis, :], axis=0)**2/self.N
@@ -198,13 +224,14 @@ class Measurement:
         Returns the raw uncalibrated data, converted to floating point format.
         """
         if block is not None:
-            blocks = self.f['audio'][block]
+            with self.file() as f:
+                blocks = f['audio'][block]
         else:
             blocks = []
-            for block in self.iterBlocks():
+            with self.file() as f:
-                blocks.append(block)
+                for block in self.iterBlocks(f):
+                    blocks.append(block)
             blocks = np.asarray(blocks)
-
             blocks = blocks.reshape(self.nblocks*self.blocksize,
                                     self.nchannels)
 
@@ -220,13 +247,19 @@ class Measurement:
         else:
             raise RuntimeError(
                 f'Unimplemented data type from recording: {blocks.dtype}.')
-        sens = self.sensitivity
+        sens = self._sens
         blocks = blocks.astype(LASP_NUMPY_FLOAT_TYPE)/fac/sens[np.newaxis, :]
 
         return blocks
 
-    def iterBlocks(self):
+    def iterBlocks(self, opened_file):
-        return BlockIter(self.f['audio'])
+        """
+        Iterate over all the audio blocks in the opened file
+
+        Args:
+            opened_file: The h5File with the data
+        """
+        return BlockIter(opened_file)
 
     @property
     def sensitivity(self):
@@ -235,10 +268,7 @@ class Measurement:
         between -1.0 and 1.0 to Pascal. If the sensitivity is not stored in
         the measurement file, this function returns 1.0
         """
-        try:
+        return self._sens
-            return self.f.attrs['sensitivity']
-        except KeyError:
-            return np.ones(self.nchannels)
 
     @sensitivity.setter
     def sensitivity(self, sens):
@@ -257,8 +287,8 @@ class Measurement:
         valid &= isinstance(sens.dtype, float)
         if not valid:
             raise ValueError('Invalid sensitivity value(s) given')
-
+        with self.file('r+') as f:
-        self.f.attrs['sensitivity'] = sens
+            f.attrs['sensitivity'] = sens
 
     def exportAsWave(self, fn=None, force=False, sampwidth=None):
         """
@@ -286,8 +316,8 @@ class Measurement:
 
         if os.path.exists(fn) and not force:
             raise RuntimeError(f'File already exists: {fn}')
-
+        with self.file() as f:
-        audio = self.f['audio']
+            audio = self.f['audio'][:]
 
         if isinstance(audio.dtype, float):
             if sampwidth is None:
@@ -373,8 +403,5 @@ class Measurement:
             ad[0] = dat
         return Measurement(mfn)
 
-    def __del__(self):
+    # def __del__(self):
-        try:
+    #     self.f.close()
-            self.f.close()
-        except AttributeError:
-            pass

lasp/lasp_octavefilter.py

@@ -17,21 +17,19 @@ class FilterBank:
     Single channel octave filter bank implementation
     """
 
-    def __init__(self, fs, designer):
+    def __init__(self, fs):
         """
         Initialize a OctaveFilterBank object.
 
         Args:
             fs: Sampling frequency of base signal
-            designer: FIR Filter designer for filterbank
 
         """
         assert np.isclose(fs, 48000), "Only sampling frequency" \
             " available is 48 kHz"
 
-        self.fs = fs
 
-        maxdecimation = designer.decimation(designer.xs[0])
+        maxdecimation = self.decimation(self.xs[0])
         self.decimators = []
         for dec in maxdecimation:
             self.decimators.append(Decimator(1, dec))
@@ -44,8 +42,8 @@ class FilterBank:
 
         self.filterbanks = []
         # Sort the x values in categories according to the required decimation
-        for x in designer.xs:
+        for x in self.xs:
-            dec = designer.decimation(x)
+            dec = self.decimation(x)
             if len(dec) == 1 and dec[0] == 1:
                 xs_d1.append(x)
             elif len(dec) == 1 and dec[0] == 4:
@@ -62,12 +60,12 @@ class FilterBank:
         xs_all = [xs_d1, xs_d4, xs_d16, xs_d64, xs_d256]
         for xs in xs_all:
             nominals = []
-            firs = np.empty((designer.L, len(xs)), order='F')
+            firs = np.empty((self.L, len(xs)), order='F')
             for i, x in enumerate(xs):
                 #  These are the filters that do not require lasp_decimation
                 #  prior to filtering
-                nominals.append(designer.nominal(x))
+                nominals.append(self.nominal(x))
-                firs[:, i] = designer.createFilter(fs, x)
+                firs[:, i] = self.createFilter(fs, x)
             filterbank = {'fb': pyxFilterBank(firs, 1024),
                           'xs': xs,
                           'nominals': nominals}
@@ -78,16 +76,10 @@ class FilterBank:
 
         # Filter output counters
         self.dec = [1, 4, 16, 64, 256]
-        Pdec = 128
-        Pfil = 256
 
-        # Initial filtered number
+        # These intial delays are found experimentally using a toneburst
-        self.Nf = [-Pfil, -(Pdec/4 + Pfil),
+        # response.
-                   -(Pfil + Pdec/4 + Pdec/16),
+        self.Nf = [915, 806, 780, 582, 338]
-                   -(Pfil + Pdec/64 + Pdec/4 + Pdec/16),
-                   -(Pfil + Pdec/256 + Pdec/64 + Pdec/4 + Pdec/16)]
-
-        self.delay_set = [False, False, False, False, False]
 
     def filterd(self, dec_stage, data):
         """
@@ -110,10 +102,12 @@ class FilterBank:
             oldNf = self.Nf[dec_stage]
             tstart = oldNf/fd
             tend = tstart + Nf/fd
+
             t = np.linspace(tstart, tend, Nf, endpoint=False)
             self.Nf[dec_stage] += Nf
             for i, nom in enumerate(self.filterbanks[dec_stage]['nominals']):
-                output[nom] = {'t': t, 'data': filtered[:, i]}
+                output[nom] = {'t': t, 'data': filtered[:, [i]]}
+
         return output
 
     def filter_(self, data):
@@ -142,13 +136,13 @@ class FilterBank:
         return output
 
 
-class OctaveFilterBank(FilterBank):
+class OctaveFilterBank(FilterBank, OctaveBankDesigner):
     def __init__(self, fs):
-        designer = OctaveBankDesigner()
+        OctaveBankDesigner.__init__(self)
-        super().__init__(fs, designer)
+        FilterBank.__init__(self, fs)
 
 
-class ThirdOctaveFilterBank(FilterBank):
+class ThirdOctaveFilterBank(FilterBank, ThirdOctaveBankDesigner):
     def __init__(self, fs):
-        designer = ThirdOctaveBankDesigner()
+        ThirdOctaveBankDesigner.__init__(self)
-        super().__init__(fs, designer)
+        FilterBank.__init__(self, fs)

lasp/lasp_reverb.py

@@ -24,7 +24,8 @@ class ReverbTime:
             dB.
 
         """
-        assert level.ndim == 1, 'Invalid number of dimensions in level'
+        assert level.ndim == 2, 'Invalid number of dimensions in level'
+        assert level.shape[1] == 1,'Invalid number of channels, should be 1'
         self._level = level
         # Number of time samples
         self._N = self._level.shape[0]

lasp/lasp_slm.py

@@ -14,7 +14,8 @@ from .lasp_weighcal import WeighCal
 from .lasp_gui_tools import wait_cursor
 from .lasp_figure import PlotOptions, Plotable
 from .ui_slmwidget import Ui_SlmWidget
-
+from .filter.bandpass_fir import OctaveBankDesigner, ThirdOctaveBankDesigner
+from .lasp_octavefilter import OctaveFilterBank, ThirdOctaveFilterBank
 __all__ = ['SLM', 'SlmWidget']
 
 
@@ -29,30 +30,39 @@ class Dummy:
 
 class SLM:
     """
-    Sound Level Meter, implements the single pole lowpass filter
+    Multi-channel sound Level Meter. Input data: time data with a certain
+    sampling frequency. Output: time-weighted (fast/slow) sound pressure
+    levels in dB(A/C/Z).
+
     """
 
-    def __init__(self, fs, weighcal,
+    def __init__(self, fs, tw=TimeWeighting.default):
-                 tw=TimeWeighting.default,
-                 ):
         """
-        Initialize a sound level meter object. Number of channels comes from
+        Initialize a sound level meter object.
-        the weighcal object
+        Number of channels comes from the weighcal object.
 
         Args:
             fs: Sampling frequency [Hz]
-            weighcal: WeighCal instance used for calibration and frequency
+            tw: Time Weighting to apply
-            weighting.
-            nchannels: Number of channels to allocate filters for
         """
-        nchannels = weighcal.nchannels
+
-        self.nchannels = nchannels
-        self._weighcal = weighcal
         if tw[0] is not TimeWeighting.none[0]:
-            self._lps = [SPLowpass(fs, tw[0]) for i in range(nchannels)]
+            self._lp = SPLowpass(fs, tw[0])
         else:
-            self._lps = [Dummy() for i in range(nchannels)]
+            self._lp = Dummy()
-        self._Lmax = zeros(nchannels)
+        self._Lmax = 0.
+
+        # Storage for computing the equivalent level
+        self._sq = 0.
+        self._N = 0
+        self._Leq = 0.
+
+    @property
+    def Leq(self):
+        """
+        Returns the equivalent level of the recorded signal so far
+        """
+        return self._Leq
 
     @property
     def Lmax(self):
@@ -68,26 +78,26 @@ class SLM:
         Args:
             data:
         """
-        if data.ndim == 1:
+        assert data.ndim == 2
-            data = data[:, np.newaxis]
+        assert data.shape[1] == 1
 
-        data_weighted = self._weighcal.filter_(data)
+        P_REFsq = P_REF**2
 
         # Squared
-        sq = data_weighted**2
+        sq = data**2
-        if sq.shape[0] == 0:
-            return np.array([])
 
-        tw = []
+        # Update equivalent level
+        N1 = sq.shape[0]
+        self._sq = (np.sum(sq) + self._sq*self._N)/(N1+self._N)
+        self._N += N1
+        self._Leq = 10*np.log10(self._sq/P_REFsq)
 
         # Time-weight the signal
-        for chan, lp in enumerate(self._lps):
+        tw = self._lp.filter_(sq)
-            tw.append(lp.filter_(sq[:, chan])[:, 0])
 
-        tw = np.asarray(tw).transpose()
+        Level = 10*np.log10(tw/P_REFsq)
-
-        Level = 10*np.log10(tw/P_REF**2)
 
+        # Update maximum level
         curmax = np.max(Level)
         if curmax > self._Lmax:
             self._Lmax = curmax
@@ -103,8 +113,8 @@ class SlmWidget(ComputeWidget, Ui_SlmWidget):
         super().__init__(parent)
         self.setupUi(self)
 
-        FreqWeighting.fillComboBox(self.tfreqweighting)
+        self.eqFreqBandChanged(0)
-        FreqWeighting.fillComboBox(self.eqfreqweighting)
+        self.tFreqBandChanged(0)
         self.setMeas(None)
 
     def init(self, fm):
@@ -115,6 +125,9 @@ class SlmWidget(ComputeWidget, Ui_SlmWidget):
         fm.registerCombo(self.tfigure)
         fm.registerCombo(self.eqfigure)
 
+        self.tbandstart.setEnabled(False)
+        self.tbandstop.setEnabled(False)
+
     def setMeas(self, meas):
         """
         Set the current measurement for this widget.
@@ -151,16 +164,33 @@ class SlmWidget(ComputeWidget, Ui_SlmWidget):
         channel = self.eqchannel.currentIndex()
         fw = FreqWeighting.getCurrent(self.eqfreqweighting)
 
-        startpos = self.eqstarttime.value
+        istart, istop = self.getStartStopIndices(meas, self.eqstarttime,
-        stoppos = self.eqstoptime.value
+                                                 self.eqstoptime)
-        N = meas.N
-        istart = int(startpos*fs)
-        if istart >= N:
-            raise ValueError("Invalid start position")
-        istop = int(stoppos*fs)
-        if istart > N:
-            raise ValueError("Invalid stop position")
 
+        bands = self.eqfreqband.currentIndex()
+        if bands == 0:
+            # 1/3 Octave bands
+            filt = ThirdOctaveFilterBank(fs)
+            xs = filt.xs
+            xmin = xs[0] + self.eqbandstart.currentIndex()
+            xmax = xs[0] + self.eqbandstop.currentIndex()
+        if bands == 1:
+            # Octave bands
+            filt = OctaveFilterBank(fs)
+            xs = filt.xs
+            xmin = xs[0] + self.eqbandstart.currentIndex()
+            xmax = xs[0] + self.eqbandstop.currentIndex()
+
+        leveltype = self.eqleveltype.currentIndex()
+        if leveltype == 0:
+            # equivalent levels
+            tw = TimeWeighting.fast
+        elif leveltype == 1:
+            # fast time weighting
+            tw = TimeWeighting.fast
+        elif leveltype == 2:
+            # slow time weighting
+            tw = TimeWeighting.slow
 
         with wait_cursor():
             # This one exctracts the calfile and sensitivity from global
@@ -170,8 +200,28 @@ class SlmWidget(ComputeWidget, Ui_SlmWidget):
                                 fs=fs, calfile=calfile,
                                 sens=sens)
             praw = meas.praw()[istart:istop, [channel]]
-            pto = PlotOptions()
+
+            weighted = weighcal.filter_(praw)
+            filtered_out = filt.filter_(weighted)
+
+            levels = np.empty((xmax - xmin + 1))
+            xlabels = []
+            for i, x in enumerate(range(xmin, xmax+1)):
+                nom = filt.nominal(x)
+                xlabels.append(nom)
+                filt_x = filtered_out[nom]['data']
+                slm = SLM(filt.fs, tw)
+                slm.addData(filt_x)
+                if leveltype > 0:
+                    level = slm.Lmax
+                else:
+                    level = slm.Leq
+                levels[i] = level
+
+            pto = PlotOptions.forLevelBars()
+            pta = Plotable(xlabels, levels)
             fig, new = self.getFigure(self.eqfigure, pto, 'bar')
+            fig.fig.add(pta)
             fig.show()
 
     def computeT(self):
@@ -184,46 +234,95 @@ class SlmWidget(ComputeWidget, Ui_SlmWidget):
         tw = TimeWeighting.getCurrent(self.ttimeweighting)
         fw = FreqWeighting.getCurrent(self.tfreqweighting)
 
+        istart, istop = self.getStartStopIndices(meas, self.tstarttime,
+                                                 self.tstoptime)
+
+        bands = self.tfreqband.currentIndex()
+        if bands == 0:
+            # Overall
+            filt = Dummy()
+        else:
+            # Octave bands
+            filt = OctaveFilterBank(
+                fs) if bands == 1 else ThirdOctaveFilterBank(fs)
+            xs = filt.xs
+            xmin = xs[0] + self.tbandstart.currentIndex()
+            xmax = xs[0] + self.tbandstop.currentIndex()
+
         # Downsampling factor of result
         dsf = self.tdownsampling.value()
-        # gb = self.slmFre
 
         with wait_cursor():
             # This one exctracts the calfile and sensitivity from global
             # variables defined at the top. # TODO: Change this to a more
             # robust variant.
+
+            praw = meas.praw()[istart:istop, [channel]]
+
             weighcal = WeighCal(fw, nchannels=1,
                                 fs=fs, calfile=calfile,
                                 sens=sens)
 
-            slm = SLM(fs, weighcal, tw)
+            weighted = weighcal.filter_(praw)
-            praw = meas.praw()[:, [channel]]
 
-            # Filter, downsample data
+            if bands == 0:
-            filtered = slm.addData(praw)[::dsf, :]
+                slm = SLM(fs, tw)
-            N = filtered.shape[0]
+                level = slm.addData(weighted)[::dsf]
-            time = getTime(float(fs)/dsf, N)
-            Lmax = slm.Lmax
 
-            pto = PlotOptions()
+                # Filter, downsample data
-            pto.ylabel = f'L{fw[0]} [dB({fw[0]})]'
+                N = level.shape[0]
-            pto.xlim = (time[0], time[-1])
+                time = getTime(float(fs)/dsf, N)
+                Lmax = slm.Lmax
 
-            pta = Plotable(time, filtered)
+                pta = Plotable(time, level,
+                               name=f'Overall level [dB([fw[0]])]')
+                pto = PlotOptions()
+                pto.ylabel = f'L{fw[0]} [dB({fw[0]})]'
+                pto.xlim = (time[0], time[-1])
+                fig, new = self.getFigure(self.tfigure, pto, 'line')
+                fig.fig.add(pta)
 
-            fig, new = self.getFigure(self.tfigure, pto, 'line')
+            else:
-            fig.fig.add(pta)
+                pto = PlotOptions()
+                fig, new = self.getFigure(self.tfigure, pto, 'line')
+                pto.ylabel = f'L{fw[0]} [dB({fw[0]})]'
+
+                out = filt.filter_(weighted)
+                tmin = 0
+                tmax = 0
+
+                for x in range(xmin, xmax+1):
+                    dec = np.prod(filt.decimation(x))
+                    fd = filt.fs/dec
+                    # Nominal frequency text
+                    nom = filt.nominal(x)
+
+                    leg = f'{nom} Hz - [dB({fw[0]})]'
+
+                    # Find global tmin and tmax, used for xlim
+                    time = out[nom]['t']
+                    tmin = min(tmin, time[0])
+                    tmax = max(tmax, time[-1])
+                    slm = SLM(fd, tw)
+                    level = slm.addData(out[nom]['data'])
+                    plotable = Plotable(time[::dsf//dec],
+                                        level[::dsf//dec],
+                                        name=leg)
+
+                    fig.fig.add(plotable)
+                pto.xlim = (tmin, tmax)
+                fig.fig.setPlotOptions(pto)
             fig.show()
 
-        stats = f"""Statistical results:
+#         stats = f"""Statistical results:
-=============================
+# =============================
-Applied frequency weighting: {fw[1]}
+# Applied frequency weighting: {fw[1]}
-Applied time weighting: {tw[1]}
+# Applied time weighting: {tw[1]}
-Applied Downsampling factor: {dsf}
+# Applied Downsampling factor: {dsf}
-Maximum level (L{fw[0]} max): {Lmax:4.4} [dB({fw[0]})]
+# Maximum level (L{fw[0]} max): {Lmax:4.4} [dB({fw[0]})]
-
+#
-        """
+#         """
-        self.results.setPlainText(stats)
+#         self.results.setPlainText(stats)
 
     def compute(self):
         """
@@ -234,3 +333,61 @@ Maximum level (L{fw[0]} max): {Lmax:4.4} [dB({fw[0]})]
             self.computeT()
         elif self.eqtab.isVisible():
             self.computeEq()
+
+    def eqFreqBandChanged(self, idx):
+        """
+        User changes frequency bands to plot time-dependent values for
+        """
+        self.eqbandstart.clear()
+        self.eqbandstop.clear()
+
+        if idx == 1:
+            # 1/3 Octave bands
+            o = OctaveBankDesigner()
+            for x in o.xs:
+                nom = o.nominal(x)
+                self.eqbandstart.addItem(nom)
+                self.eqbandstop.addItem(nom)
+                self.eqbandstart.setCurrentIndex(0)
+                self.eqbandstop.setCurrentIndex(len(o.xs)-1)
+        elif idx == 0:
+            # Octave bands
+            o = ThirdOctaveBankDesigner()
+            for x in o.xs:
+                nom = o.nominal(x)
+                self.eqbandstart.addItem(nom)
+                self.eqbandstop.addItem(nom)
+                self.eqbandstart.setCurrentIndex(2)
+                self.eqbandstop.setCurrentIndex(len(o.xs) - 3)
+
+    def tFreqBandChanged(self, idx):
+        """
+        User changes frequency bands to plot time-dependent values for
+        """
+        self.tbandstart.clear()
+        self.tbandstop.clear()
+        enabled = False
+
+        if idx == 1:
+            # Octave bands
+            enabled = True
+            o = OctaveBankDesigner()
+            for x in o.xs:
+                nom = o.nominal(x)
+                self.tbandstart.addItem(nom)
+                self.tbandstop.addItem(nom)
+                self.tbandstart.setCurrentIndex(2)
+                self.tbandstop.setCurrentIndex(len(o.xs)-1)
+        elif idx == 2:
+            # Octave bands
+            enabled = True
+            o = ThirdOctaveBankDesigner()
+            for x in o.xs:
+                nom = o.nominal(x)
+                self.tbandstart.addItem(nom)
+                self.tbandstop.addItem(nom)
+                self.tbandstart.setCurrentIndex(2)
+                self.tbandstop.setCurrentIndex(len(o.xs) - 3)
+
+        self.tbandstart.setEnabled(enabled)
+        self.tbandstop.setEnabled(enabled)

lasp/lasp_weighcal.py

@@ -4,10 +4,10 @@
 Weighting and calibration filter in one
 @author: J.A. de Jong - ASCEE
 """
-from .filter_design.freqweighting_fir import A,C
+from .filter.freqweighting_fir import A, C
 from .lasp_common import FreqWeighting
-from .filter_design.fir_design import (arbitrary_fir_design,
+from .filter.fir_design import (arbitrary_fir_design,
-                                       freqResponse as frp)
+                                freqResponse as frp)
 from lasp.lasp_config import ones, empty
 from .wrappers import FilterBank
 import numpy as np
@@ -17,7 +17,7 @@ __all__ = ['WeighCal']
 
 class WeighCal:
     """
-    Time weighting and calibration FIR filter
+    Frequency weighting and calibration FIR filter
     """
     def __init__(self, fw=FreqWeighting.default,
                  nchannels=1,
@@ -48,15 +48,17 @@ class WeighCal:
         # Objective function for the frequency response
         frp_obj = self.frpObj(freq_design)
 
-        self._firs = []
+        P = 2048 # Filter length (number of taps)
+
+        self._firs = np.empty((P, self.nchannels))
         self._fbs = []
         for chan in range(self.nchannels):
-            fir = arbitrary_fir_design(fs, 2048, freq_design,
+            fir = arbitrary_fir_design(fs, P, freq_design,
                                        frp_obj[:, chan],
                                        window='rectangular')
-            self._firs.append(fir)
+            self._firs[:, chan] = fir
 
-            self._fbs.append(FilterBank(fir[:, np.newaxis], 4096))
+            self._fbs.append(FilterBank(fir[:, np.newaxis], 2*P))
 
         self._freq_design = freq_design
 
@@ -66,22 +68,21 @@ class WeighCal:
 
         Args:
             data: (Weighted) raw time data that needs to be filtered, should
-            have the same number of columns as the number of channels, or should
+            have the same number of columns as the number of channels. First
-            have dimension 1 in case of a single channel.
+            axis is assumed to be the time axis
 
         Retuns:
             Filtered data for each channel
 
         """
         nchan = self.nchannels
-        if data.ndim == 1:
+        assert data.ndim == 2
-            data = data[:, np.newaxis]
         assert data.shape[1] == nchan
         assert data.shape[0] > 0
 
         filtered = []
         for chan in range(nchan):
-            filtered.append(self._fbs[chan].filter_(data[:, chan])[:, 0])
+            filtered.append(self._fbs[chan].filter_(data[:, [chan]])[:, 0])
         filtered = np.asarray(filtered).transpose()/self.sens
         if filtered.ndim == 1:
             filtered = filtered[:, np.newaxis]
@@ -133,7 +134,7 @@ class WeighCal:
         """
         # Objective function for the frequency response
         frp_objective = self.frpCalObj(freq_design) * \
-                            self.frpWeightingObj(freq_design)[:, np.newaxis]
+            self.frpWeightingObj(freq_design)[:, np.newaxis]
         frp_objective[-1] = 0.
 
         return frp_objective

lasp/plot/bar.py

@@ -55,10 +55,15 @@ class BarScene(QGraphicsScene):
             xvals: labels and x positions of the bars
             G: Number of bars per x value
             ylim: y limits of the figure
-
+            xlabel: label below x-axis
-
+            ylabel: label on left side of the y-axis
+            title: figure title
+            colors: color cycler
+            size: size of the plot in pixels
+            legend: list of legend strings to show.
         """
         super().__init__(parent=parent)
+        self.setSceneRect(QRect(0,0,*size))
 
         # self.setBackgroundBrush(ASCEEColors.bgBrush(0, size[0]))
         self.ylim = ylim
@@ -68,8 +73,7 @@ class BarScene(QGraphicsScene):
         self.bgs = []
 
         self.size = size
-        xsize = size[0]
+        xsize, ysize = size
-        ysize = size[1]
 
         self.xsize = xsize
         self.ysize = ysize

lasp/wrappers.pyx

@@ -377,12 +377,13 @@ cdef class SPLowpass:
         if self.lp:
             SPLowpass_free(self.lp)
 
-    def filter_(self,d[:] input_):
+    def filter_(self,d[::1,:] input_):
+        assert input_.shape[1] == 1
         if input_.shape[0] == 0:
             return np.array([],dtype=NUMPY_FLOAT_TYPE)
 
         cdef vd input_vd = dmat_foreign_data(input_.shape[0],1,
-                                             &input_[0],False)
+                                             &input_[0,0],False)
 
         cdef dmat output = SPLowpass_filter(self.lp,&input_vd)
 

setup.py

@@ -16,9 +16,8 @@ setup(
       author_email="j.a.dejong@ascee.nl",
       # Project uses reStructuredText, so ensure that the docutils get
       # installed or upgraded on the target machine
-      install_requires=['matplotlib>=1.0', 'scipy>=0.17', 'numpy>=1.0'],
+      install_requires=['matplotlib>=1.0', 'scipy>=1.0', 'numpy>=1.0'],
       license='MIT',
-
       description=descr,
       keywords="",
       url="http://www.ascee.nl/lasp/",   # project home page, if any