def __call__(self):
        'Return the locations of the ticks'
        self.verify_intervals()
        b=self._base

        vmin, vmax = self.viewInterval.get_bounds()
        vmin = math.log(vmin)/math.log(b)
        vmax = math.log(vmax)/math.log(b)

        if vmax<vmin:
            vmin, vmax = vmax, vmin
        ticklocs = []

        numdec = math.floor(vmax)-math.ceil(vmin)
        if self._subs is None: # autosub
            if numdec>10: subs = array([1.0])
            elif numdec>6: subs = arange(2.0, b, 2.0)
            else: subs = arange(2.0, b)
        else:
            subs = self._subs
        for decadeStart in b**arange(math.floor(vmin),math.ceil(vmax)):
            ticklocs.extend( subs*decadeStart )

        if(len(subs) and subs[0]==1.0):
            ticklocs.append(b**math.ceil(vmax))


        ticklocs = array(ticklocs)
        ind = nonzero(logical_and(ticklocs>=b**vmin ,
                                  ticklocs<=b**vmax))


        ticklocs = take(ticklocs,ind)
        return ticklocs

 def _set_format(self):
     # set the format string to format all the ticklabels
     locs = (array(self.locs)-self.offset) / 10**self.orderOfMagnitude+1e-15
     sigfigs = [len(str('%1.3f'% loc).split('.')[1].rstrip('0')) \
                for loc in locs]
     sigfigs.sort()
     self.format = '%1.' + str(sigfigs[-1]) + 'f'

def idwt2(coeffs, wavelet, mode='sym'):
    """
    2D Inverse Discrete Wavelet Transform. Reconstruct data from coefficients
    arrays.
    
    coeffs  - four 2D coefficients arrays arranged as follows:
    
        (approximation,
                (horizontal details,
                vertical details,
                diagonal details)
        )

    wavelet - wavelet to use (Wavelet object or name string)
    mode    - signal extension mode, see MODES
    """
    
    if len(coeffs) != 2 or len(coeffs[1]) != 3:
        raise ValueError("Invalid coeffs param")
    
    # L -low-pass data, H - high-pass data
    LL, (LH, HL, HH) = coeffs

    (LL, LH, HL, HH) = (transpose(LL), transpose(LH), transpose(HL), transpose(HH))
    for arr in (LL, LH, HL, HH):
        if len(arr.shape) != 2:
            raise TypeError("All input coefficients arrays must be 2D")
    del arr
    
    if not isinstance(wavelet, Wavelet):
        wavelet = Wavelet(wavelet)

    mode = MODES.from_object(mode)
    
    # idwt columns
    L = []
    append_L = L.append
    for rowL, rowH in izip(LL, LH):
        append_L(idwt(rowL, rowH, wavelet, mode, 1))
    del LL, LH

    H = []
    append_H = H.append
    for rowL, rowH in izip(HL, HH):
        append_H(idwt(rowL, rowH, wavelet, mode, 1))
    del HL, HH

    L = transpose(L)
    H = transpose(H)

    # idwt rows
    data = []
    append_data = data.append
    for rowL, rowH in izip(L, H):
        append_data(idwt(rowL, rowH, wavelet, mode, 1))

    return array(data, default_dtype)