peri/viz/plots.py
def crb_compare(state0, samples0, state1, samples1, crb0=None, crb1=None,
        zlayer=None, xlayer=None):
    """
    To run, do:

    s,h = pickle...
    s1,h1 = pickle...
        i.e. /media/scratch/bamf/vacancy/vacancy_zoom-1.tif_t002.tif-featured-v2.pkl
        i.e. /media/scratch/bamf/frozen-particles/0.tif-featured-full.pkl
    crb0 = diag_crb_particles(s); crb1 = diag_crb_particles(s1)
    crb_compare(s,h[-25:],s1,h1[-25:], crb0, crb1)
    """
    s0 = state0
    s1 = state1
    h0 = np.array(samples0)
    h1 = np.array(samples1)

    slicez = zlayer or s0.image.shape[0]//2
    slicex = xlayer or s0.image.shape[2]//2
    slicer1 = np.s_[slicez,s0.pad:-s0.pad,s0.pad:-s0.pad]
    slicer2 = np.s_[s0.pad:-s0.pad,s0.pad:-s0.pad,slicex]
    center = (slicez, s0.image.shape[1]//2, slicex)

    mu0 = h0.mean(axis=0)
    mu1 = h1.mean(axis=0)

    std0 = h0.std(axis=0)
    std1 = h1.std(axis=0)

    mask0 = (s0.state[s0.b_typ]==1.) & (
        analyze.trim_box(s0, mu0[s0.b_pos].reshape(-1,3)))
    mask1 = (s1.state[s1.b_typ]==1.) & (
        analyze.trim_box(s1, mu1[s1.b_pos].reshape(-1,3)))
    active0 = np.arange(s0.N)[mask0]#s0.state[s0.b_typ]==1.]
    active1 = np.arange(s1.N)[mask1]#s1.state[s1.b_typ]==1.]

    pos0 = mu0[s0.b_pos].reshape(-1,3)[active0]
    pos1 = mu1[s1.b_pos].reshape(-1,3)[active1]
    rad0 = mu0[s0.b_rad][active0]
    rad1 = mu1[s1.b_rad][active1]

    link = analyze.nearest(pos0, pos1)
    dpos = pos0 - pos1[link]
    drad = rad0 - rad1[link]

    drift = dpos.mean(axis=0)
    log.info('drift {}'.format(drift))

    dpos -= drift

    fig = pl.figure(figsize=(24,10))

    #=========================================================================
    #=========================================================================
    gs0 = ImageGrid(fig, rect=[0.02, 0.4, 0.4, 0.60], nrows_ncols=(2,3), axes_pad=0.1)

    lbl(gs0[0], 'A')
    for i,slicer in enumerate([slicer1, slicer2]):
        ax_real = gs0[3*i+0]
        ax_fake = gs0[3*i+1]
        ax_diff = gs0[3*i+2]

        diff0 = s0.get_model_image() - s0.image
        diff1 = s1.get_model_image() - s1.image
        a = (s0.image - s1.image)
        b = (s0.get_model_image() - s1.get_model_image())
        c = (diff0 - diff1)

        ptp = 0.7*max([np.abs(a).max(), np.abs(b).max(), np.abs(c).max()])
        cmap = pl.cm.RdBu_r
        ax_real.imshow(a[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)
        ax_real.set_xticks([])
        ax_real.set_yticks([])
        ax_fake.imshow(b[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)
        ax_fake.set_xticks([])
        ax_fake.set_yticks([])
        ax_diff.imshow(c[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)#cmap=pl.cm.RdBu, vmin=-1.0, vmax=1.0)
        ax_diff.set_xticks([])
        ax_diff.set_yticks([])

        if i == 0:
            ax_real.set_title(r"$\Delta$ Confocal image", fontsize=24)
            ax_fake.set_title(r"$\Delta$ Model image", fontsize=24)
            ax_diff.set_title(r"$\Delta$ Difference", fontsize=24)
            ax_real.set_ylabel('x-y')
        else:
            ax_real.set_ylabel('x-z')

    #=========================================================================
    #=========================================================================
    gs1 = GridSpec(1,3, left=0.05, bottom=0.125, right=0.42, top=0.37,
                wspace=0.15, hspace=0.05)

    spos0 = std0[s0.b_pos].reshape(-1,3)[active0]
    spos1 = std1[s1.b_pos].reshape(-1,3)[active1]
    srad0 = std0[s0.b_rad][active0]
    srad1 = std1[s1.b_rad][active1]

    def hist(ax, vals, bins, *args, **kwargs):
        y,x = np.histogram(vals, bins=bins)
        x = (x[1:] + x[:-1])/2
        y /= len(vals)
        ax.plot(x,y, *args, **kwargs)

    def pp(ind, tarr, tsim, tcrb, var='x'):
        bins = 10**np.linspace(-3, 0.0, 30)
        bin2 = 10**np.linspace(-3, 0.0, 100)
        bins = np.linspace(0.0, 0.2, 30)
        bin2 = np.linspace(0.0, 0.2, 100)
        xlim = (0.0, 0.12)
        #xlim = (1e-3, 1e0)
        ylim = (1e-2, 30)

        ticks = ticker.FuncFormatter(lambda x, pos: '{:0.0f}'.format(np.log10(x)))
        scaler = lambda x: x #np.log10(x)

        ax_crb = pl.subplot(gs1[0,ind])
        ax_crb.hist(scaler(np.abs(tarr)), bins=bins,
                normed=True, alpha=0.7, histtype='stepfilled', lw=1)
        ax_crb.hist(scaler(np.abs(tcrb)).ravel(), bins=bin2,
                normed=True, alpha=1.0, histtype='step', ls='solid', lw=1.5, color='k')
        ax_crb.hist(scaler(np.abs(tsim).ravel()), bins=bin2,
                normed=True, alpha=1.0, histtype='step', lw=3)
        ax_crb.set_xlabel(r"$\Delta = |%s(t_1) - %s(t_0)|$" % (var,var), fontsize=24)
        #ax_crb.semilogx()
        ax_crb.set_xlim(xlim)
        #ax_crb.semilogy()
        #ax_crb.set_ylim(ylim)
        #ax_crb.xaxis.set_major_formatter(ticks)
        ax_crb.grid(b=False, which='both', axis='both')

        if ind == 0:
            lbl(ax_crb, 'B')
            ax_crb.set_ylabel(r"$P(\Delta)$")
        else:
            ax_crb.set_yticks([])

        ax_crb.locator_params(axis='x', nbins=3)

    f,g = 1.5, 1.95
    sim = f*sim_crb_diff(spos0[:,1], spos1[:,1][link])
    crb = g*sim_crb_diff(crb0[0][:,1][active0], crb1[0][:,1][active1][link])
    pp(0, dpos[:,1], sim, crb, 'x')

    sim = f*sim_crb_diff(spos0[:,0], spos1[:,0][link])
    crb = g*sim_crb_diff(crb0[0][:,0][active0], crb1[0][:,0][active1][link])
    pp(1, dpos[:,0], sim, crb, 'z')

    sim = f*sim_crb_diff(srad0, srad1[link])
    crb = g*sim_crb_diff(crb0[1][active0], crb1[1][active1][link])
    pp(2, drad, sim, crb, 'a')

    #ax_crb_r.locator_params(axis='both', nbins=3)
    #gs1.tight_layout(fig)

    #=========================================================================
    #=========================================================================
    gs2 = GridSpec(2,2, left=0.48, bottom=0.12, right=0.99, top=0.95,
                wspace=0.35, hspace=0.35)

    ax_hist = pl.subplot(gs2[0,0])
    ax_hist.hist(std0[s0.b_pos], bins=np.logspace(-3.0, 0, 50), alpha=0.7, label='POS', histtype='stepfilled')
    ax_hist.hist(std0[s0.b_rad], bins=np.logspace(-3.0, 0, 50), alpha=0.7, label='RAD', histtype='stepfilled')
    ax_hist.set_xlim((10**-3.0, 1))
    ax_hist.semilogx()
    ax_hist.set_xlabel(r"$\bar{\sigma}$")
    ax_hist.set_ylabel(r"$P(\bar{\sigma})$")
    ax_hist.legend(loc='upper right')
    lbl(ax_hist, 'C')

    imdiff = ((s0.get_model_image() - s0.image)/s0._sigma_field)[s0.image_mask==1.].ravel()
    mu = imdiff.mean()
    #sig = imdiff.std()
    #print mu, sig
    x = np.linspace(-5,5,10000)

    ax_diff = pl.subplot(gs2[0,1])
    ax_diff.plot(x, 1.0/np.sqrt(2*np.pi) * np.exp(-(x-mu)**2 / 2), '-', alpha=0.7, color='k', lw=2)
    ax_diff.hist(imdiff, bins=1000, histtype='step', alpha=0.7, normed=True)
    ax_diff.semilogy()
    ax_diff.set_ylabel(r"$P(\delta)$")
    ax_diff.set_xlabel(r"$\delta = (M_i - d_i)/\sigma_i$")
    ax_diff.locator_params(axis='x', nbins=5)
    ax_diff.grid(b=False, which='minor', axis='y')
    ax_diff.set_xlim(-5, 5)
    ax_diff.set_ylim(1e-4, 1e0)
    lbl(ax_diff, 'D')

    pos = mu0[s0.b_pos].reshape(-1,3)
    rad = mu0[s0.b_rad]
    mask = analyze.trim_box(s0, pos)
    pos = pos[mask]
    rad = rad[mask]

    gx, gy = analyze.gofr(pos, rad, mu0[s0.b_zscale][0], resolution=5e-2,mask_start=0.5)
    mask = gx < 5
    gx = gx[mask]
    gy = gy[mask]
    ax_gofr = pl.subplot(gs2[1,0])
    ax_gofr.plot(gx, gy, '-', lw=1)
    ax_gofr.set_xlabel(r"$r/a$")
    ax_gofr.set_ylabel(r"$g(r/a)$")
    ax_gofr.locator_params(axis='both', nbins=5)
    #ax_gofr.semilogy()
    lbl(ax_gofr, 'E')

    gx, gy = analyze.gofr(pos, rad, mu0[s0.b_zscale][0], method='surface')
    mask = gx < 5
    gx = gx[mask]
    gy = gy[mask]
    gy[gy <= 0.] = gy[gy>0].min()
    ax_gofrs = pl.subplot(gs2[1,1])
    ax_gofrs.plot(gx, gy, '-', lw=1)
    ax_gofrs.set_xlabel(r"$r/a$")
    ax_gofrs.set_ylabel(r"$g_{\rm{surface}}(r/a)$")
    ax_gofrs.locator_params(axis='both', nbins=5)
    ax_gofrs.grid(b=False, which='minor', axis='y')
    #ax_gofrs.semilogy()
    lbl(ax_gofrs, 'F')

    ylim = ax_gofrs.get_ylim()
    ax_gofrs.set_ylim(gy.min(), ylim[1])
def crb_compare(state0, samples0, state1, samples1, crb0=None, crb1=None,
        zlayer=None, xlayer=None):
    """
    To run, do:

    s,h = pickle...
    s1,h1 = pickle...
        i.e. /media/scratch/bamf/vacancy/vacancy_zoom-1.tif_t002.tif-featured-v2.pkl
        i.e. /media/scratch/bamf/frozen-particles/0.tif-featured-full.pkl
    crb0 = diag_crb_particles(s); crb1 = diag_crb_particles(s1)
    crb_compare(s,h[-25:],s1,h1[-25:], crb0, crb1)
    """
    s0 = state0
    s1 = state1
    h0 = np.array(samples0)
    h1 = np.array(samples1)

    slicez = zlayer or s0.image.shape[0]//2
    slicex = xlayer or s0.image.shape[2]//2
    slicer1 = np.s_[slicez,s0.pad:-s0.pad,s0.pad:-s0.pad]
    slicer2 = np.s_[s0.pad:-s0.pad,s0.pad:-s0.pad,slicex]
    center = (slicez, s0.image.shape[1]//2, slicex)

    mu0 = h0.mean(axis=0)
    mu1 = h1.mean(axis=0)

    std0 = h0.std(axis=0)
    std1 = h1.std(axis=0)

    mask0 = (s0.state[s0.b_typ]==1.) & (
        analyze.trim_box(s0, mu0[s0.b_pos].reshape(-1,3)))
    mask1 = (s1.state[s1.b_typ]==1.) & (
        analyze.trim_box(s1, mu1[s1.b_pos].reshape(-1,3)))
    active0 = np.arange(s0.N)[mask0]#s0.state[s0.b_typ]==1.]
    active1 = np.arange(s1.N)[mask1]#s1.state[s1.b_typ]==1.]

    pos0 = mu0[s0.b_pos].reshape(-1,3)[active0]
    pos1 = mu1[s1.b_pos].reshape(-1,3)[active1]
    rad0 = mu0[s0.b_rad][active0]
    rad1 = mu1[s1.b_rad][active1]

    link = analyze.nearest(pos0, pos1)
    dpos = pos0 - pos1[link]
    drad = rad0 - rad1[link]

    drift = dpos.mean(axis=0)
    log.info('drift {}'.format(drift))

    dpos -= drift

    fig = pl.figure(figsize=(24,10))

    #=========================================================================
    #=========================================================================
    gs0 = ImageGrid(fig, rect=[0.02, 0.4, 0.4, 0.60], nrows_ncols=(2,3), axes_pad=0.1)

    lbl(gs0[0], 'A')
    for i,slicer in enumerate([slicer1, slicer2]):
        ax_real = gs0[3*i+0]
        ax_fake = gs0[3*i+1]
        ax_diff = gs0[3*i+2]

        diff0 = s0.get_model_image() - s0.image
        diff1 = s1.get_model_image() - s1.image
        a = (s0.image - s1.image)
        b = (s0.get_model_image() - s1.get_model_image())
        c = (diff0 - diff1)

        ptp = 0.7*max([np.abs(a).max(), np.abs(b).max(), np.abs(c).max()])
        cmap = pl.cm.RdBu_r
        ax_real.imshow(a[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)
        ax_real.set_xticks([])
        ax_real.set_yticks([])
        ax_fake.imshow(b[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)
        ax_fake.set_xticks([])
        ax_fake.set_yticks([])
        ax_diff.imshow(c[slicer], cmap=cmap, vmin=-ptp, vmax=ptp)#cmap=pl.cm.RdBu, vmin=-1.0, vmax=1.0)
        ax_diff.set_xticks([])
        ax_diff.set_yticks([])

        if i == 0:
            ax_real.set_title(r"$\Delta$ Confocal image", fontsize=24)
            ax_fake.set_title(r"$\Delta$ Model image", fontsize=24)
            ax_diff.set_title(r"$\Delta$ Difference", fontsize=24)
            ax_real.set_ylabel('x-y')
        else:
            ax_real.set_ylabel('x-z')

    #=========================================================================
    #=========================================================================
    gs1 = GridSpec(1,3, left=0.05, bottom=0.125, right=0.42, top=0.37,
                wspace=0.15, hspace=0.05)

    spos0 = std0[s0.b_pos].reshape(-1,3)[active0]
    spos1 = std1[s1.b_pos].reshape(-1,3)[active1]
    srad0 = std0[s0.b_rad][active0]
    srad1 = std1[s1.b_rad][active1]

    def hist(ax, vals, bins, *args, **kwargs):
        y,x = np.histogram(vals, bins=bins)
        x = (x[1:] + x[:-1])/2
        y /= len(vals)
        ax.plot(x,y, *args, **kwargs)

    def pp(ind, tarr, tsim, tcrb, var='x'):
        bins = 10**np.linspace(-3, 0.0, 30)
        bin2 = 10**np.linspace(-3, 0.0, 100)
        bins = np.linspace(0.0, 0.2, 30)
        bin2 = np.linspace(0.0, 0.2, 100)
        xlim = (0.0, 0.12)
        #xlim = (1e-3, 1e0)
        ylim = (1e-2, 30)

        ticks = ticker.FuncFormatter(lambda x, pos: '{:0.0f}'.format(np.log10(x)))
        scaler = lambda x: x #np.log10(x)

        ax_crb = pl.subplot(gs1[0,ind])
        ax_crb.hist(scaler(np.abs(tarr)), bins=bins,
                normed=True, alpha=0.7, histtype='stepfilled', lw=1)
        ax_crb.hist(scaler(np.abs(tcrb)).ravel(), bins=bin2,
                normed=True, alpha=1.0, histtype='step', ls='solid', lw=1.5, color='k')
        ax_crb.hist(scaler(np.abs(tsim).ravel()), bins=bin2,
                normed=True, alpha=1.0, histtype='step', lw=3)
        ax_crb.set_xlabel(r"$\Delta = |%s(t_1) - %s(t_0)|$" % (var,var), fontsize=24)
        #ax_crb.semilogx()
        ax_crb.set_xlim(xlim)
        #ax_crb.semilogy()
        #ax_crb.set_ylim(ylim)
        #ax_crb.xaxis.set_major_formatter(ticks)
        ax_crb.grid(b=False, which='both', axis='both')

        if ind == 0:
            lbl(ax_crb, 'B')
            ax_crb.set_ylabel(r"$P(\Delta)$")
        else:
            ax_crb.set_yticks([])

        ax_crb.locator_params(axis='x', nbins=3)

    f,g = 1.5, 1.95
    sim = f*sim_crb_diff(spos0[:,1], spos1[:,1][link])
    crb = g*sim_crb_diff(crb0[0][:,1][active0], crb1[0][:,1][active1][link])
    pp(0, dpos[:,1], sim, crb, 'x')

    sim = f*sim_crb_diff(spos0[:,0], spos1[:,0][link])
    crb = g*sim_crb_diff(crb0[0][:,0][active0], crb1[0][:,0][active1][link])
    pp(1, dpos[:,0], sim, crb, 'z')

    sim = f*sim_crb_diff(srad0, srad1[link])
    crb = g*sim_crb_diff(crb0[1][active0], crb1[1][active1][link])
    pp(2, drad, sim, crb, 'a')

    #ax_crb_r.locator_params(axis='both', nbins=3)
    #gs1.tight_layout(fig)

    #=========================================================================
    #=========================================================================
    gs2 = GridSpec(2,2, left=0.48, bottom=0.12, right=0.99, top=0.95,
                wspace=0.35, hspace=0.35)

    ax_hist = pl.subplot(gs2[0,0])
    ax_hist.hist(std0[s0.b_pos], bins=np.logspace(-3.0, 0, 50), alpha=0.7, label='POS', histtype='stepfilled')
    ax_hist.hist(std0[s0.b_rad], bins=np.logspace(-3.0, 0, 50), alpha=0.7, label='RAD', histtype='stepfilled')
    ax_hist.set_xlim((10**-3.0, 1))
    ax_hist.semilogx()
    ax_hist.set_xlabel(r"$\bar{\sigma}$")
    ax_hist.set_ylabel(r"$P(\bar{\sigma})$")
    ax_hist.legend(loc='upper right')
    lbl(ax_hist, 'C')

    imdiff = ((s0.get_model_image() - s0.image)/s0._sigma_field)[s0.image_mask==1.].ravel()
    mu = imdiff.mean()
    #sig = imdiff.std()
    #print mu, sig
    x = np.linspace(-5,5,10000)

    ax_diff = pl.subplot(gs2[0,1])
    ax_diff.plot(x, 1.0/np.sqrt(2*np.pi) * np.exp(-(x-mu)**2 / 2), '-', alpha=0.7, color='k', lw=2)
    ax_diff.hist(imdiff, bins=1000, histtype='step', alpha=0.7, normed=True)
    ax_diff.semilogy()
    ax_diff.set_ylabel(r"$P(\delta)$")
    ax_diff.set_xlabel(r"$\delta = (M_i - d_i)/\sigma_i$")
    ax_diff.locator_params(axis='x', nbins=5)
    ax_diff.grid(b=False, which='minor', axis='y')
    ax_diff.set_xlim(-5, 5)
    ax_diff.set_ylim(1e-4, 1e0)
    lbl(ax_diff, 'D')

    pos = mu0[s0.b_pos].reshape(-1,3)
    rad = mu0[s0.b_rad]
    mask = analyze.trim_box(s0, pos)
    pos = pos[mask]
    rad = rad[mask]

    gx, gy = analyze.gofr(pos, rad, mu0[s0.b_zscale][0], resolution=5e-2,mask_start=0.5)
    mask = gx < 5
    gx = gx[mask]
    gy = gy[mask]
    ax_gofr = pl.subplot(gs2[1,0])
    ax_gofr.plot(gx, gy, '-', lw=1)
    ax_gofr.set_xlabel(r"$r/a$")
    ax_gofr.set_ylabel(r"$g(r/a)$")
    ax_gofr.locator_params(axis='both', nbins=5)
    #ax_gofr.semilogy()
    lbl(ax_gofr, 'E')

    gx, gy = analyze.gofr(pos, rad, mu0[s0.b_zscale][0], method='surface')
    mask = gx < 5
    gx = gx[mask]
    gy = gy[mask]
    gy[gy <= 0.] = gy[gy>0].min()
    ax_gofrs = pl.subplot(gs2[1,1])
    ax_gofrs.plot(gx, gy, '-', lw=1)
    ax_gofrs.set_xlabel(r"$r/a$")
    ax_gofrs.set_ylabel(r"$g_{\rm{surface}}(r/a)$")
    ax_gofrs.locator_params(axis='both', nbins=5)
    ax_gofrs.grid(b=False, which='minor', axis='y')
    #ax_gofrs.semilogy()
    lbl(ax_gofrs, 'F')

    ylim = ax_gofrs.get_ylim()
    ax_gofrs.set_ylim(gy.min(), ylim[1])
def crb_compare ( state0 , samples0 , state1 , samples1 , crb0 = None , crb1 = None , zlayer = None , xlayer = None ) : s0 = state0 s1 = state1 h0 = np . array ( samples0 ) h1 = np . array ( samples1 ) slicez = zlayer or s0 . image . shape [ 0 ] // 2 slicex = xlayer or s0 . image . shape [ 2 ] // 2 slicer1 = np . s_ [ slicez , s0 . pad : - s0 . pad , s0 . pad : - s0 . pad ] slicer2 = np . s_ [ s0 . pad : - s0 . pad , s0 . pad : - s0 . pad , slicex ] center = ( slicez , s0 . image . shape [ 1 ] // 2 , slicex ) mu0 = h0 . mean ( axis = 0 ) mu1 = h1 . mean ( axis = 0 ) std0 = h0 . std ( axis = 0 ) std1 = h1 . std ( axis = 0 ) mask0 = ( s0 . state [ s0 . b_typ ] == 1. ) & ( analyze . trim_box ( s0 , mu0 [ s0 . b_pos ] . reshape ( - 1 , 3 ) ) ) mask1 = ( s1 . state [ s1 . b_typ ] == 1. ) & ( analyze . trim_box ( s1 , mu1 [ s1 . b_pos ] . reshape ( - 1 , 3 ) ) ) active0 = np . arange ( s0 . N ) [ mask0 ] #s0.state[s0.b_typ]==1.] active1 = np . arange ( s1 . N ) [ mask1 ] #s1.state[s1.b_typ]==1.] pos0 = mu0 [ s0 . b_pos ] . reshape ( - 1 , 3 ) [ active0 ] pos1 = mu1 [ s1 . b_pos ] . reshape ( - 1 , 3 ) [ active1 ] rad0 = mu0 [ s0 . b_rad ] [ active0 ] rad1 = mu1 [ s1 . b_rad ] [ active1 ] link = analyze . nearest ( pos0 , pos1 ) dpos = pos0 - pos1 [ link ] drad = rad0 - rad1 [ link ] drift = dpos . mean ( axis = 0 ) log . info ( 'drift {}' . format ( drift ) ) dpos -= drift fig = pl . figure ( figsize = ( 24 , 10 ) ) #========================================================================= #========================================================================= gs0 = ImageGrid ( fig , rect = [ 0.02 , 0.4 , 0.4 , 0.60 ] , nrows_ncols = ( 2 , 3 ) , axes_pad = 0.1 ) lbl ( gs0 [ 0 ] , 'A' ) for i , slicer in enumerate ( [ slicer1 , slicer2 ] ) : ax_real = gs0 [ 3 * i + 0 ] ax_fake = gs0 [ 3 * i + 1 ] ax_diff = gs0 [ 3 * i + 2 ] diff0 = s0 . get_model_image ( ) - s0 . image diff1 = s1 . get_model_image ( ) - s1 . image a = ( s0 . image - s1 . image ) b = ( s0 . get_model_image ( ) - s1 . get_model_image ( ) ) c = ( diff0 - diff1 ) ptp = 0.7 * max ( [ np . abs ( a ) . max ( ) , np . abs ( b ) . max ( ) , np . abs ( c ) . max ( ) ] ) cmap = pl . cm . RdBu_r ax_real . imshow ( a [ slicer ] , cmap = cmap , vmin = - ptp , vmax = ptp ) ax_real . set_xticks ( [ ] ) ax_real . set_yticks ( [ ] ) ax_fake . imshow ( b [ slicer ] , cmap = cmap , vmin = - ptp , vmax = ptp ) ax_fake . set_xticks ( [ ] ) ax_fake . set_yticks ( [ ] ) ax_diff . imshow ( c [ slicer ] , cmap = cmap , vmin = - ptp , vmax = ptp ) #cmap=pl.cm.RdBu, vmin=-1.0, vmax=1.0) ax_diff . set_xticks ( [ ] ) ax_diff . set_yticks ( [ ] ) if i == 0 : ax_real . set_title ( r"$\Delta$ Confocal image" , fontsize = 24 ) ax_fake . set_title ( r"$\Delta$ Model image" , fontsize = 24 ) ax_diff . set_title ( r"$\Delta$ Difference" , fontsize = 24 ) ax_real . set_ylabel ( 'x-y' ) else : ax_real . set_ylabel ( 'x-z' ) #========================================================================= #========================================================================= gs1 = GridSpec ( 1 , 3 , left = 0.05 , bottom = 0.125 , right = 0.42 , top = 0.37 , wspace = 0.15 , hspace = 0.05 ) spos0 = std0 [ s0 . b_pos ] . reshape ( - 1 , 3 ) [ active0 ] spos1 = std1 [ s1 . b_pos ] . reshape ( - 1 , 3 ) [ active1 ] srad0 = std0 [ s0 . b_rad ] [ active0 ] srad1 = std1 [ s1 . b_rad ] [ active1 ] def hist ( ax , vals , bins , * args , * * kwargs ) : y , x = np . histogram ( vals , bins = bins ) x = ( x [ 1 : ] + x [ : - 1 ] ) / 2 y /= len ( vals ) ax . plot ( x , y , * args , * * kwargs ) def pp ( ind , tarr , tsim , tcrb , var = 'x' ) : bins = 10 ** np . linspace ( - 3 , 0.0 , 30 ) bin2 = 10 ** np . linspace ( - 3 , 0.0 , 100 ) bins = np . linspace ( 0.0 , 0.2 , 30 ) bin2 = np . linspace ( 0.0 , 0.2 , 100 ) xlim = ( 0.0 , 0.12 ) #xlim = (1e-3, 1e0) ylim = ( 1e-2 , 30 ) ticks = ticker . FuncFormatter ( lambda x , pos : '{:0.0f}' . format ( np . log10 ( x ) ) ) scaler = lambda x : x #np.log10(x) ax_crb = pl . subplot ( gs1 [ 0 , ind ] ) ax_crb . hist ( scaler ( np . abs ( tarr ) ) , bins = bins , normed = True , alpha = 0.7 , histtype = 'stepfilled' , lw = 1 ) ax_crb . hist ( scaler ( np . abs ( tcrb ) ) . ravel ( ) , bins = bin2 , normed = True , alpha = 1.0 , histtype = 'step' , ls = 'solid' , lw = 1.5 , color = 'k' ) ax_crb . hist ( scaler ( np . abs ( tsim ) . ravel ( ) ) , bins = bin2 , normed = True , alpha = 1.0 , histtype = 'step' , lw = 3 ) ax_crb . set_xlabel ( r"$\Delta = |%s(t_1) - %s(t_0)|$" % ( var , var ) , fontsize = 24 ) #ax_crb.semilogx() ax_crb . set_xlim ( xlim ) #ax_crb.semilogy() #ax_crb.set_ylim(ylim) #ax_crb.xaxis.set_major_formatter(ticks) ax_crb . grid ( b = False , which = 'both' , axis = 'both' ) if ind == 0 : lbl ( ax_crb , 'B' ) ax_crb . set_ylabel ( r"$P(\Delta)$" ) else : ax_crb . set_yticks ( [ ] ) ax_crb . locator_params ( axis = 'x' , nbins = 3 ) f , g = 1.5 , 1.95 sim = f * sim_crb_diff ( spos0 [ : , 1 ] , spos1 [ : , 1 ] [ link ] ) crb = g * sim_crb_diff ( crb0 [ 0 ] [ : , 1 ] [ active0 ] , crb1 [ 0 ] [ : , 1 ] [ active1 ] [ link ] ) pp ( 0 , dpos [ : , 1 ] , sim , crb , 'x' ) sim = f * sim_crb_diff ( spos0 [ : , 0 ] , spos1 [ : , 0 ] [ link ] ) crb = g * sim_crb_diff ( crb0 [ 0 ] [ : , 0 ] [ active0 ] , crb1 [ 0 ] [ : , 0 ] [ active1 ] [ link ] ) pp ( 1 , dpos [ : , 0 ] , sim , crb , 'z' ) sim = f * sim_crb_diff ( srad0 , srad1 [ link ] ) crb = g * sim_crb_diff ( crb0 [ 1 ] [ active0 ] , crb1 [ 1 ] [ active1 ] [ link ] ) pp ( 2 , drad , sim , crb , 'a' ) #ax_crb_r.locator_params(axis='both', nbins=3) #gs1.tight_layout(fig) #========================================================================= #========================================================================= gs2 = GridSpec ( 2 , 2 , left = 0.48 , bottom = 0.12 , right = 0.99 , top = 0.95 , wspace = 0.35 , hspace = 0.35 ) ax_hist = pl . subplot ( gs2 [ 0 , 0 ] ) ax_hist . hist ( std0 [ s0 . b_pos ] , bins = np . logspace ( - 3.0 , 0 , 50 ) , alpha = 0.7 , label = 'POS' , histtype = 'stepfilled' ) ax_hist . hist ( std0 [ s0 . b_rad ] , bins = np . logspace ( - 3.0 , 0 , 50 ) , alpha = 0.7 , label = 'RAD' , histtype = 'stepfilled' ) ax_hist . set_xlim ( ( 10 ** - 3.0 , 1 ) ) ax_hist . semilogx ( ) ax_hist . set_xlabel ( r"$\bar{\sigma}$" ) ax_hist . set_ylabel ( r"$P(\bar{\sigma})$" ) ax_hist . legend ( loc = 'upper right' ) lbl ( ax_hist , 'C' ) imdiff = ( ( s0 . get_model_image ( ) - s0 . image ) / s0 . _sigma_field ) [ s0 . image_mask == 1. ] . ravel ( ) mu = imdiff . mean ( ) #sig = imdiff.std() #print mu, sig x = np . linspace ( - 5 , 5 , 10000 ) ax_diff = pl . subplot ( gs2 [ 0 , 1 ] ) ax_diff . plot ( x , 1.0 / np . sqrt ( 2 * np . pi ) * np . exp ( - ( x - mu ) ** 2 / 2 ) , '-' , alpha = 0.7 , color = 'k' , lw = 2 ) ax_diff . hist ( imdiff , bins = 1000 , histtype = 'step' , alpha = 0.7 , normed = True ) ax_diff . semilogy ( ) ax_diff . set_ylabel ( r"$P(\delta)$" ) ax_diff . set_xlabel ( r"$\delta = (M_i - d_i)/\sigma_i$" ) ax_diff . locator_params ( axis = 'x' , nbins = 5 ) ax_diff . grid ( b = False , which = 'minor' , axis = 'y' ) ax_diff . set_xlim ( - 5 , 5 ) ax_diff . set_ylim ( 1e-4 , 1e0 ) lbl ( ax_diff , 'D' ) pos = mu0 [ s0 . b_pos ] . reshape ( - 1 , 3 ) rad = mu0 [ s0 . b_rad ] mask = analyze . trim_box ( s0 , pos ) pos = pos [ mask ] rad = rad [ mask ] gx , gy = analyze . gofr ( pos , rad , mu0 [ s0 . b_zscale ] [ 0 ] , resolution = 5e-2 , mask_start = 0.5 ) mask = gx < 5 gx = gx [ mask ] gy = gy [ mask ] ax_gofr = pl . subplot ( gs2 [ 1 , 0 ] ) ax_gofr . plot ( gx , gy , '-' , lw = 1 ) ax_gofr . set_xlabel ( r"$r/a$" ) ax_gofr . set_ylabel ( r"$g(r/a)$" ) ax_gofr . locator_params ( axis = 'both' , nbins = 5 ) #ax_gofr.semilogy() lbl ( ax_gofr , 'E' ) gx , gy = analyze . gofr ( pos , rad , mu0 [ s0 . b_zscale ] [ 0 ] , method = 'surface' ) mask = gx < 5 gx = gx [ mask ] gy = gy [ mask ] gy [ gy <= 0. ] = gy [ gy > 0 ] . min ( ) ax_gofrs = pl . subplot ( gs2 [ 1 , 1 ] ) ax_gofrs . plot ( gx , gy , '-' , lw = 1 ) ax_gofrs . set_xlabel ( r"$r/a$" ) ax_gofrs . set_ylabel ( r"$g_{\rm{surface}}(r/a)$" ) ax_gofrs . locator_params ( axis = 'both' , nbins = 5 ) ax_gofrs . grid ( b = False , which = 'minor' , axis = 'y' ) #ax_gofrs.semilogy() lbl ( ax_gofrs , 'F' ) ylim = ax_gofrs . get_ylim ( ) ax_gofrs . set_ylim ( gy . min ( ) , ylim [ 1 ] )
To run, do:

    s,h = pickle...
    s1,h1 = pickle...
        i.e. /media/scratch/bamf/vacancy/vacancy_zoom-1.tif_t002.tif-featured-v2.pkl
        i.e. /media/scratch/bamf/frozen-particles/0.tif-featured-full.pkl
    crb0 = diag_crb_particles(s); crb1 = diag_crb_particles(s1)
    crb_compare(s,h[-25:],s1,h1[-25:], crb0, crb1)
To run do :