Warpx_Sims/vrcf_plot.py at main · jdl99/Warpx_Sims · GitHub

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import h5py
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import use as mpluse
mpluse("Agg", force=True)
from matplotlib import gridspec
from matplotlib import colors
from matplotlib import cm
from scipy import constants
from openpmd_viewer.addons import LpaDiagnostics
import gc

nc = 6.968e27
qe = constants.e
mp = constants.m_p
me = constants.m_e
c = constants.c

l0 = 400e-9
w0 = 2*np.pi*c/l0 #rad/s
T0 = l0/c
t_peak = 90e-15
tzero = 29e-6 / c + t_peak


simroot = "/dfs6/pub/jdlewis2/warpx/CSU_Protons/RZ/hom/t200nm_nc40/"
saveroot = "/dfs6/pub/jdlewis2/warpx/CSU_Protons/RZ/hom/t200nm_nc40/pscan_plots/"


a0s = ["a01/", "a015/", "a040/"]
sls = ["sl5/", "sl20/", "sl100/"]
sds = sum([[sl + a0 for a0 in a0s] for sl in sls], []) # magic~!

sds = ["sl5/a01/", "sl5/a015/", "sl5/a040/", "sl20/a01/", "sl20/a015/", "sl100/a015/"]

plt.rcParams["figure.figsize"] = (18,15) #20
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12


## begin plotting loop
for i in range(len(sds)):

    if sds[i].split("/")[1] == "a01":
        j = -1
    else:
        j = 10

    simdir = simroot + sds[i]
    savedir = saveroot + sds[i]
    comment = "_4096x12096_az2_48ppc_" + sds[i].replace("/", "_")
    Data = simdir + 'diags/diag1/'
    try:
        ts = LpaDiagnostics(Data)
    except FileNotFoundError:
        print("skipped " + sds[i])
        continue

    it = ts.iterations
    time = ts.t

    ## Load particles and do some calculations
    spec = 'hydrogen'
    w = ts.get_particle(var_list=['w'], t=time[j], species=spec)
    z, uz = ts.get_particle(var_list=['z', 'uz'], t=time[j], species=spec, plot=False)
    x, ux, uy = ts.get_particle(var_list=['x', 'ux', 'uy'], t=time[j], species=spec, plot=False, norm=colors.LogNorm())

    mask = uz>0

    w = w[0][mask]
    x = x[mask]
    z = z[mask]
    ux = ux[mask]
    uz = uz[mask]
    uy = uy[mask]

    # get gamma and ke
    gamma = np.sqrt(1 + ux**2 + uz**2 +uy**2)
    ke = (gamma - 1)* mp * c**2 / qe /10**6 # kinetic energy in MeV

    #ke = ts.get_mean_gamma(t=time[j], species=spec)


    lq = np.quantile(ke,0.955)

    nbins=9
    ncols = 3
    nrows = int(np.ceil(nbins/ncols))
    mine = lq
    mine = 1
    if sds[i].split("/")[1] == "a01":
        mine = 0
        nbins = 6
    maxe = np.max(ke)
    emask = np.logical_and(ke>mine, ke<maxe)

    uze = uz[emask]
    uxe = ux[emask]
    uye = uy[emask]
    we = w[emask]
    kee = ke[emask]
    gammae = gamma[emask]

    bz = uze/gammae
    bx = uxe/gammae
    by = uye/gammae
    thetax = np.arctan(bx / bz) * 180/np.pi
    thetay = np.arctan(by / bz) * 180/np.pi


    ## make a plot


    G = gridspec.GridSpec(nrows, ncols,hspace=0.5,wspace=0.05)
    plt.suptitle('Virtual RCF - Even Bins',ha='center', fontsize=20)

    cutoff = np.quantile(kee, 0.99)
    bw = np.concatenate(([mine + (cutoff-mine)/(nbins-1)*i for i in range(nbins)], [maxe]))

    for n in range(nbins):

        kmin = bw[n]
        kmax = bw[n+1]
        #kmin = n*bwidth(0)
        #kmax = (n+1)*bwidth(0)
        km = np.logical_and(kee>kmin, kee<kmax)

        ax = plt.subplot(G[int(np.floor(n/ncols)),n%ncols])
        pdose = ax.hist2d(thetax[km], thetay[km], bins=150, weights=we[km], cmap='cubehelix_r') # this returns a tuple
        cb = plt.colorbar(pdose[3], ax=ax) # index 3 has the mappable, which is what colorbar needs
        cb.set_label('# protons', fontsize=14)

        ax.set_xlim(-30, 30)
        ax.set_ylim(-30,30)

        ax.set_ylabel(r'$\theta\degree$', fontsize=14)
        ax.set_xlabel(r'$\theta\degree$', fontsize=14)
        ax.set_title('{:.2f}'.format(kmin) + r' $<$ KE $\leq$ ' + '{:.2f}'.format(kmax), fontsize=14)

        ax.set_aspect('equal')


    plt.savefig(savedir + "vrcf" + comment + str(int(time[j]*1e15)) + "fs.png", dpi=300)
    plt.close('all')


    del w, x, z, ux, uy, uz, gamma, ke, uze, uxe, uye, we, kee, gammae, bz, bx, by, thetax, thetay, pdose

    if j % 1 == 0:
        print("garbage collected")
        gc.collect()