예제 #1
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def speed_test3(imshape=(128,128,128), gshape=(4,4,4)):
    im = np.zeros(imshape)
    hs = np.ones(gshape+imshape)

    out, plan = convolve_spatial3(im, hs, return_plan=True)
    t  = time()
    out = convolve_spatial3(im, hs, plan=plan)
    t = time()-t
    print "imshape: %s \tgshape: %s   \ttime = %.2gs"%(imshape, gshape, t)
    return t
예제 #2
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def speed_test3(imshape=(128, 128, 128), gshape=(4, 4, 4)):
    im = np.zeros(imshape)
    hs = np.ones(gshape + imshape)

    out, plan = convolve_spatial3(im, hs, return_plan=True)
    t = time()
    out = convolve_spatial3(im, hs, plan=plan)
    t = time() - t
    print("imshape: %s \tgshape: %s   \ttime = %.2gs" % (imshape, gshape, t))
    return t
예제 #3
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def test_conv3():
    im = np.zeros((128, 64, 32))
    Gx = 8
    Gy = 4
    Gz = 2
    hs = psf_grid_linear3(Gx, Gy, Gz, 10)
    out = convolve_spatial3(im, hs)
    return im, out, hs
예제 #4
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def test_conv3():
    im = np.zeros((128,64,32))
    Gx = 8
    Gy = 4
    Gz = 2
    hs = psf_grid_linear3(Gx,Gy,Gz,10)
    out = convolve_spatial3(im, hs)
    return im,out, hs
def test_conv3_psfs():
    im = np.zeros((128, 128, 128))
    im[::16, ::16, ::16] = 1.
    Gx = 16
    Gy = 16
    Gz = 16
    hs = psf_grid_motion3(Gx, Gy, Gz, 20)

    out = convolve_spatial3(im, hs)
    return im, out, hs
예제 #6
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def test_conv3_psfs():

    im = np.zeros((128,64,32))
    im[::16,::16,::16] = 1.
    Gx = 16
    Gy = 16
    Gz = 16
    hs = psf_grid_motion3(Gx,Gy,Gz,20)

    out = convolve_spatial3(im, hs)
    return im,out, hs
예제 #7
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def test_single_z():
    Ng = 32
    Nx = 512
    Nh = 3

    im = np.zeros((16, Nx, Nx))
    im[4:-4, 4::16, 4::16] = 1.
    hs = np.zeros((16, Nx, Nx))

    for i in range(Ng):
        for j in range(Ng):
            si = slice(i * (Nx // Ng) - Nh + (Nx // Ng) // 2,
                       i * (Nx // Ng) + Nh + 1 + (Nx // Ng) // 2)
            sj = slice(j * (Nx // Ng) - Nh + (Nx // Ng) // 2,
                       j * (Nx // Ng) + Nh + 1 + (Nx // Ng) // 2)
            hs[:, sj, si] = np.ones((16, 2 * Nh + 1, 2 * Nh + 1))

    hs[:, Nx // Ng // 2::Nx // Ng, Nx // Ng // 2::Nx // Ng] = 1.

    out = convolve_spatial3(im, hs, grid_dim=(1, Ng, Ng), pad_factor=2)
    return im, out, hs
예제 #8
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파일: simlsm.py 프로젝트: maweigert/biobeam
    def simulate_image_z(self,
                         cz=0,
                         signal=None,
                         psf_grid_dim=(8, 8),
                         zslice=16,
                         conv_sub_blocks=(1, 1),
                         conv_pad_factor=2,
                         conv_mode="wrap",
                         mode="product",
                         with_sheet=True,
                         **bpm_kwargs):
        """
        mode = ["product","illum"]

        """
        if not mode in ["product", "illum"]:
            raise KeyError("unknown mode: %s" % mode)

        if signal is None:
            signal = self.signal
        if signal is None:
            raise ValueError("no signal defined (signal)!")

        # illumination

        psfs = self.psf_grid_z(cz=cz,
                               grid_dim=psf_grid_dim,
                               zslice=zslice,
                               **bpm_kwargs)

        offset_z = int(np.round(cz / self._bpm_detect.units[-1]))

        assert offset_z + zslice < self.Nz and self.Nz // 2 + offset_z - zslice >= 0

        s = slice(self.Nz // 2 + offset_z - zslice,
                  self.Nz // 2 + offset_z + zslice)

        signal = 1. * signal[s].copy()

        if with_sheet:
            print("illuminating at z= %s mu with psf mode %s" % (cz, mode))
            u = self.propagate_illum(cz=cz, **bpm_kwargs)

            if mode == "psf_product":
                psfs = psfs * u[s]
            else:
                signal = signal * u[s]

        print("spatially varying convolution: %s %s" %
              (signal.shape, psfs.shape))
        #convolve

        conv = convolve_spatial3(signal.copy(),
                                 psfs.copy(),
                                 grid_dim=(1, ) + psf_grid_dim,
                                 sub_blocks=(1, ) + conv_sub_blocks,
                                 pad_factor=conv_pad_factor,
                                 mode=conv_mode,
                                 verbose=True)

        #return u, self.signal[s].copy(), signal, psfs, conv

        return conv
def test_conv3_reflect():
    im = np.zeros((128, 64, 32))
    Gx, Gy, Gz = 8, 4, 2
    hs = psf_grid_linear3(Gx, Gy, Gz, 10)
    out = convolve_spatial3(im, hs, mode='reflect')
    return im, out, hs
예제 #10
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파일: simlsm.py 프로젝트: maweigert/biobeam
    def simulate_image_z(self, cz = 0,
                         signal = None,
                         psf_grid_dim = (8,8),
                         zslice = 16,
                         conv_sub_blocks = (1,1),
                         conv_pad_factor = 2,
                         conv_mode = "wrap",
                         mode = "product",
                         with_sheet = True,
                         **bpm_kwargs):
        """
        mode = ["product","illum"]

        """
        if not mode in ["product","illum"]:
            raise KeyError("unknown mode: %s"%mode)

        if signal is None:
            signal = self.signal
        if signal is None:
            raise ValueError("no signal defined (signal)!")


        # illumination



        psfs = self.psf_grid_z(cz = cz,
                               grid_dim=psf_grid_dim,
                               zslice=zslice,
                               **bpm_kwargs)

        offset_z = int(np.round(cz/self._bpm_detect.units[-1]))

        assert offset_z+zslice<self.Nz and self.Nz//2+offset_z-zslice>=0

        s = slice(self.Nz//2+offset_z-zslice,self.Nz//2+offset_z+zslice)

        signal = 1.*signal[s].copy()

        if with_sheet:
            print("illuminating at z= %s mu with psf mode %s" % (cz, mode))
            u = self.propagate_illum(cz = cz,**bpm_kwargs)

            if mode =="psf_product":
                psfs = psfs*u[s]
            else:
                signal = signal*u[s]

        print("spatially varying convolution: %s %s"%(signal.shape,psfs.shape))
        #convolve

        conv = convolve_spatial3(signal.copy(), psfs.copy(),
                                 grid_dim = (1,)+psf_grid_dim,
                                 sub_blocks=(1,)+conv_sub_blocks,
                                 pad_factor=conv_pad_factor,
                                 mode = conv_mode, verbose = True)

        #return u, self.signal[s].copy(), signal, psfs, conv

        return conv