Commit b022b990 authored by Zolnierczuk, Piotr's avatar Zolnierczuk, Piotr
Browse files

updates to xyz plot

parent 11f552eb

pysen/plot/xyzplotlib.py

+79 −59
Original line number Diff line number Diff line
@@ -20,6 +20,52 @@ def _norm_pix(x1, x2, nx, whole_detector=False): 
    return np.mod(x1,nx), np.mod(x2,nx)





def xyz_decomposition(xyzdata):

    """Decompose {x,y,z}_{up,down} measurements

    into nuclear coherent, incoherent and magnetic components



    Data is expected to be a dictionary of numbers or numpy arrays

    with six keys: {x,y,z}_{up,dn}"""



    res = {}

    # sum of x, y and z  measurements

    sX  = xyzdata['x_up'] + xyzdata['x_dn']

    sY  = xyzdata['y_up'] + xyzdata['y_dn']

    sZ  = xyzdata['z_up'] + xyzdata['z_dn']



    # diff up-down for x, y and z measurements

    dX  = xyzdata['x_up'] - xyzdata['x_dn']

    dY  = xyzdata['y_up'] - xyzdata['y_dn']

    dZ  = xyzdata['z_up'] - xyzdata['z_dn']



    # sum of all up

    sUP    =    xyzdata['z_up'] + xyzdata['x_up'] + xyzdata['y_up']

    sDN    =    xyzdata['z_dn'] + xyzdata['x_dn'] + xyzdata['y_dn']

    # "magnetic" sum of up/down

    sM_UP  = +2*xyzdata['z_up'] - xyzdata['x_up'] - xyzdata['y_up']

    sM_DN  = -2*xyzdata['z_dn'] + xyzdata['x_dn'] + xyzdata['y_dn']



    # the results

    sTOT= (sUP + sDN)/3     # total "cross section"

    sM  =  2*dZ - (dX + dY) # magnetic "cross section"

    sN  = (2*sUP - sDN)/6   # nuclear coherent

    sI  = sTOT - sN - sM    # incoherent



    #

    res['n_coh'] = sN

    res['i_inc'] = sI

    res['m_mag'] = sM

    #

    res['sum_ave'] = sTOT

    res['sum_x'  ] = sX

    res['sum_y'  ] = sY

    res['sum_z'  ] = sZ

    res['m_ave'  ] = sM_UP + sM_DN

    res['m_up/2']  = sM_UP

    res['m_dn/2']  = sM_DN

    return res





def plot_xyz_single(hdfile, fig, axis, axis1=None, **kwargs):

    "xyz plot"

    #
@@ -139,7 +185,7 @@ def plot_xyz_single(hdfile, fig, axis, axis1=None, **kwargs): 






def xyz_analysis(results, axis, norm=False, output=None, details=False):

def xyz_analysis(results, fig, axes, norm=False, output=None, details=False):

    "XYZ decomposition"



    pcha = []
@@ -150,53 +196,38 @@ def xyz_analysis(results, axis, norm=False, output=None, details=False): 
        pcha = 1

    cnorm    = {}

    cdetails = {}

    ax_xyz, axn, axi, axm = axes  # xyz, nucl, inc, mag



    if fig is None:

        fig = plt.gcf()



    for key, val in results.items():

        cnorm[key] = val['counts']/val['proton_charge']*pcha



    sX  = cnorm['x_up'] + cnorm['x_dn']

    sY  = cnorm['y_up'] + cnorm['y_dn']

    sZ  = cnorm['z_up'] + cnorm['z_dn']

    sUP = cnorm['x_up'] + cnorm['y_up'] + cnorm['z_up']

    sDN = cnorm['x_dn'] + cnorm['y_dn'] + cnorm['z_dn']

    #

    dX  = cnorm['x_up'] - cnorm['x_dn']

    dY  = cnorm['y_up'] - cnorm['y_dn']

    dZ  = cnorm['z_up'] - cnorm['z_dn']

    #

    sM_UP  = +2*cnorm['z_up'] - (cnorm['x_up'] + cnorm['y_up'])

    sM_DN  = -2*cnorm['z_dn'] + (cnorm['x_dn'] + cnorm['y_dn'])

    sTOT= (sUP + sDN)/3

    sM  =  2*dZ - (dX + dY)

    sN  = (2*sUP - sDN)/6

    sI  = sTOT - sN - sM



    cnorm['m_mag'] = sM

    cnorm['n_coh'] = sN

    cnorm['i_inc'] = sI



    cdetails['sum_ave'] = sTOT

    cdetails['sum_x'  ] = sX

    cdetails['sum_y'  ] = sY

    cdetails['sum_z'  ] = sZ

    #cdetails['m_ave'  ] = sM_UP + sM_DN

    cdetails['m_up/2']  = sM_UP

    cdetails['m_dn/2']  = sM_DN

    xyz = xyz_decomposition(cnorm)



    for lbl in ('n_coh', 'i_inc', 'm_mag') :

        cnorm[lbl] = xyz[lbl]



    for lbl in ('sum_ave', 'sum_x', 'sum_y', 'sum_z', 'm_up/2', 'm_dn/2'):

        cdetails[lbl] = xyz[lbl]



    sTOT = xyz['sum_ave']



    keys = list(cnorm.keys())

    vals = np.asarray(list(cnorm.values()))

    axis.step(keys, vals, where='mid')

    axis.grid(True)



    ax_xyz.step(keys, vals, where='mid')

    ax_xyz.grid(True)

    # fixing yticks with matplotlib.ticker "FixedLocator"

    axis.xaxis.set_ticks(range(len(keys)))

    axis.set_xticklabels(keys, rotation=40 , ha='right')

    ax_xyz.xaxis.set_ticks(range(len(keys)))

    ax_xyz.set_xticklabels(keys, rotation=40 , ha='right')

    ax_xyz.set_ylim(bottom=min(min(vals),0))



    out = StringIO()

    out.write("#label   counts \taverage q \taverage wavelength\n")

    for key, cval in cnorm.items():

        if key.startswith('m_mag'):

        if key.startswith('n_coh'):

            out.write("#summary\n")

        if norm:

            out.write("%-8.8s %10.6f" % (key, cval))
@@ -227,7 +258,14 @@ def xyz_analysis(results, axis, norm=False, output=None, details=False): 
    else:

        print(out.getvalue())



    # summary plots

    image = { key : results[key]['image'] for key in results }

    imres = xyz_decomposition(image)



    for ax,key in zip((axn,axi,axm),('n_coh','i_inc','m_mag')):

        im = ax.imshow(imres[key], aspect='equal')

        fig.colorbar(im, ax=ax, use_gridspec=True)

        ax.set_title(key)



def plot_xyz(*hdfiles, **kwargs):

    "plot xyz"
@@ -255,6 +293,11 @@ def plot_xyz(*hdfiles, **kwargs): 
    ax_lam = fig.add_subplot(gs1[1] )

    ax_q   = fig.add_subplot(gs1[2] )

    #

    gs2  = gs[2,:].subgridspec(1,3)

    ax_n = fig.add_subplot(gs2[0])

    ax_i = fig.add_subplot(gs2[1])

    ax_m = fig.add_subplot(gs2[2])

    #

    for hfilename in hdfiles:

        log.info('processing %s', hfilename)

        basename , _ = os.path.splitext(os.path.basename(hfilename))
@@ -273,32 +316,9 @@ def plot_xyz(*hdfiles, **kwargs): 
                axis1=(ax_lam, ax_q)

            res = plot_xyz_single(hdf5file, fig, ax, axis1=axis1, label=label, **kwargs)

            results.update({label:res})

    #

    gsm = gs[2,0]

    axm = fig.add_subplot(gsm)



    dX  = results['x_up']['image'] + results['x_dn']['image']

    dY  = results['y_up']['image'] + results['y_dn']['image']

    dZ  = results['z_up']['image'] + results['z_dn']['image']

#    dX  = cnorm['x_up'] - cnorm['x_dn']

#    dY  = cnorm['y_up'] - cnorm['y_dn']

#    dZ  = cnorm['z_up'] - cnorm['z_dn']

#    #

#    sM_UP  = +2*cnorm['z_up'] - (cnorm['x_up'] + cnorm['y_up'])

#    sM_DN  = -2*cnorm['z_dn'] + (cnorm['x_dn'] + cnorm['y_dn'])

#    sTOT= (sUP + sDN)/3

    sM  =  2*dZ - (dX + dY)

    im = axm.imshow(sM , aspect='equal')

    fig.colorbar(im, ax=axm, use_gridspec=True)

#    sN  = (2*sUP - sDN)/6

#    sI  = sTOT - sN - sM



#    cnorm['m_mag'] = sM

#    cnorm['n_coh'] = sN

#    cnorm['i_inc'] = sI



    #

    xyz_analysis(results, ax_xyz, norm=normalize, output=savefile, details=details)

    xyz_analysis(results, fig, (ax_xyz,ax_n, ax_i, ax_m), norm=normalize, output=savefile, details=details)



    #

    title = title.replace('_', ' ')

pysen/revision.py

+2 −2
Original line number Diff line number Diff line
@@ -3,8 +3,8 @@ PySEN revision module 
"""

import sys

__version__  = "1.3"

__release__  = "a3"

__date__     = "June 1, 2023"

__release__  = "a4"

__date__     = "June 2, 2023"



def version(full=False):

    "get pysen version number"