import numpy as np 
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec

## define colours for plot
CB_color_cycle = ['#377eb8', '#ff7f00', '#4daf4a',
                  '#f781bf', '#a65628', '#984ea3',
                  '#999999', '#e41a1c', '#dede00']

## dataset
subplots_all = {
    'x11':[0.001, 0.0010353218432956625, 0.0010718913192051276, 0.0011097524964120721, 0.0011489510001873086, 0.0011895340673703195, 0.0012315506032928262, 0.0012750512407130128, 0.001320088400831418, 0.001366716356462006, 0.0014149912974345759, 0.0014649713983072863, 0.0015167168884709225, 0.0015702901247293774, 0.0016257556664437934, 0.0016831803533309566, 0.0017426333860096508, 0.0018041864093920718, 0.0018679135990207828, 0.0019338917504552302, 0.0020022003718155844, 0.002072921779595372, 0.0021461411978584036, 0.002221946860939524, 0.002300430119772917, 0.002381685551976158, 0.002465811075822604, 0.0025529080682395165, 0.0026430814869741054, 0.0027364399970746718, 0.002833096101839324, 0.0029331662783900455, 0.0030367711180354575, 0.0031440354715915, 0.0032550885998350564, 0.003370064329271928, 0.0034891012134067737, 0.0036123426997094303, 0.0037399373024787977, 0.003872038781812557, 0.004008806328898464, 0.004150404757850477, 0.00429700470432084, 0.004448782831127585, 0.004605922041145104, 0.004768611697714469, 0.004937047852839003, 0.005111433483440166, 0.005291978735958442, 0.005478901179593945, 0.005672426068491977, 0.005872786613189483, 0.006080224261649421, 0.006294988990221888, 0.00651733960488242, 0.006747544053110693, 0.0069858797467852495, 0.007232633896483534, 0.007488103857590023, 0.007752597488629464, 0.008026433522257174, 0.008309941949353396, 0.008603464416684501, 0.00890735463861044, 0.009221978823334321, 0.009547716114208056, 0.009884959046625586, 0.010234114021054532, 0.010595601792776159, 0.010969857978923836, 0.01135733358343105, 0.011758495540521564, 0.012173827277396614, 0.012603829296797275, 0.013049019780144023, 0.013509935211980266, 0.01398713102647238, 0.014481182276745337, 0.014992684327860457, 0.015522253574270471, 0.016070528182616384, 0.016638168860761283, 0.017225859653987867, 0.017834308769319095, 0.018464249428955436, 0.019116440753857017, 0.019791668678535563, 0.020490746898158472, 0.021214517849106298, 0.02196385372416546, 0.022739657523579274, 0.023542864143224165, 0.024374441501222206, 0.02523539170434766, 0.026126752255633278, 0.027049597304631343, 0.02800503894183631, 0.028994228538828767, 0.03001835813575589, 0.031078661877820123, 0.032176417502507354, 0.03331294787934674, 0.03448962260405758, 0.03570785964900463, 0.03696912707195026, 0.03827494478516311, 0.03962688638701478, 0.04102658105827192, 0.04247571552536898, 0.04397603609302719, 0.04552935074866948, 0.047137531341167244, 0.04880251583654431, 0.0505263106533568, 0.052310993080562605, 0.054158713780794704, 0.05607169938205458, 0.05805225516094899, 0.06010276782070382, 0.06222570836730228, 0.0644236350872137, 0.06669919663030122, 0.06905513520162328, 0.07149428986597577, 0.07401959996915641, 0.07663410868007454, 0.07934096665797492, 0.08214343584919426, 0.08504489341802678, 0.0880488358164346, 0.09115888299750818, 0.09437878277775381, 0.09771241535346496, 0.1011637979766207, 0.10473708979594497, 0.10843659686896098, 0.11226677735108136, 0.11623224686798518, 0.12033778407775893, 0.12458833642950082, 0.1289890261253308, 0.13354515629298988, 0.1382622173764655, 0.14314589375234785, 0.14820207057988585, 0.15343684089300116, 0.15885651294280528, 0.16446761779946628, 0.17027691722258995, 0.1762914118095948, 0.18251834943190426, 0.18896523396912096, 0.1956398343517063, 0.20255019392306664, 0.2097046401323233, 0.21711179456945032, 0.22478058335487253, 0.23272024789604073, 0.24094035602395245, 0.24945081352303167, 0.2582618760682675, 0.26738416158399464, 0.2768286630392064, 0.286606761694825, 0.29673024081888694, 0.3072112998861756, 0.3180625692794119, 0.3292971255097148, 0.3409285069746811, 0.352970730273065, 0.36543830709572545, 0.3783462617131929, 0.39171014908092566, 0.4055460735840828, 0.419870708444391, 0.4347013158125022, 0.4500557675700497, 0.46595256686646774, 0.48241087041653685, 0.499450511585514, 0.5170920242896755, 0.5353566677410724, 0.5542664520663102, 0.5738441648302393, 0.5941133984965034, 0.6150985788580497, 0.6368249944718586, 0.6593188271333542, 0.6826071834272386, 0.7067181273927491, 0.7316807143427192, 0.7575250258771913, 0.7842822061337682, 0.8119844993184009, 0.8406652885618325, 0.8703591361485157, 0.9011018251665018, 0.9329304026284686, 0.9658832241158698, 1.0],
    'y11':[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9999999999999999, 0.9999999999999978, 0.9999999999999709, 0.999999999999657, 0.9999999999964727, 0.999999999969199, 0.9999999997788965, 0.9999999987417768, 0.9999999945499478, 0.9999999798457404, 0.9999999280246556, 0.9999997530641285, 0.9999991905611038, 0.9999974795080797, 0.9999925889407693, 0.9999795516476949, 0.9999473965276227, 0.9998746683918128, 0.9997253115215402, 0.9994500200133533, 0.9989967354012885, 0.9982547158614034, 0.997066294082157, 0.9952387679213456, 0.9925418379069715, 0.9887212393704632, 0.9835177108322071, 0.9766830593010466, 0.9679772119398091, 0.9564531511852907, 0.9418218635618063, 0.926316936898384, 0.9900191252357348, 0.9852776985019668, 0.9928164907559957, 0.9983848734482714, 0.9985105411832054, 0.9990847100341061, 0.9981740169680021, 0.9979469696278016, 0.9964864200761303, 0.9946104196556688, 0.9918126805532357, 0.9877279637744335, 0.9819260761353986, 0.9739708891090775, 0.9635454057762622, 0.9506582197445924, 0.9359034839127208, 0.9188111568786028, 0.8984640344028156, 0.8749861692830565, 0.8489568245684982, 0.8215742257461601, 0.7947736153284957, 0.769622739338226, 0.7425631824876671, 0.7132920357909309, 0.6819267084076833, 0.6486823399728522, 0.613889499326449, 0.578010059047813, 0.5416492149458147, 0.5055612135113531, 0.47064608680980846, 0.4379346839192374, 0.4085596510249184, 0.3813502428803627, 0.35441795604616466, 0.3280906564630075, 0.30273768955580205, 0.27876672081298415, 0.25661885717062527, 0.236761293941248, 0.21967726009924826, 0.20504999511592004, 0.19082293097713499, 0.176924657898624, 0.16342927843395927, 0.15041150183742769, 0.13794512315525842, 0.1261012046862986, 0.11494594252865231, 0.10453820495078114, 0.0949267335091144, 0.08614700148166354, 0.07821744676954845, 0.07044887126573596, 0.06326425242917466, 0.1723960107763629, 0.16615360998529183, 0.15601943270788876, 0.23582864469396958, 0.21343080119768343, 0.19149544372423666, 0.17705793446458273, 0.16358804728111676, 0.1506602294023316, 0.13839442555712334, 0.1269184859242407, 0.11636735996255088, 0.10684379019521817, 0.09788997914242548, 0.0894351381469366, 0.08163071966476676, 0.07465013358539407, 0.06868913176384206, 0.06334289752999978, 0.058186651006304935, 0.053254453007782865, 0.0485828202308759, 0.044210735426081005, 0.04017962702834044, 0.03653331255298442, 0.0333178996089718, 0.030471444509086454, 0.027775432679648104, 0.02525382820237776, 0.02294577712567125, 0.02089549317243533, 0.019152768909563966, 0.01775240204182016, 0.01646437272102841, 0.015214066510638613, 0.01400736961939808, 0.012850511753352056, 0.011750063559969881, 0.010712930065620685, 0.00974633939702918, 0.008857825991976598, 0.008055207412207555, 0.007346553772117237, 0.006740148690236203, 0.006225209377058394, 0.005742047876350798, 0.005288233092054062, 0.004866766477097051, 0.004480735826092541, 0.004133298564998111, 0.0038276610496615904, 0.0035670532935909716, 0.0033517337249258095, 0.003151570957601657, 0.002958510621828281, 0.0027733207220306255, 0.002596777373735648, 0.0024296574814920424, 0.0022727299288375358, 0.0021267450665413135, 0.001992422258598192, 0.0018704352155748394, 0.0017613948115130507, 0.0016658290432649547, 0.0015820656384665233, 0.0015039432710685086, 0.0014311102242987594, 0.0013635800131984732, 0.0013012712076986288, 0.0012439881206942616, 0.0011913986737688287, 0.0011430090776128887, 0.0010981305800866759, 0.0010561513462142846, 0.001016973332855331, 0.000980505187948677, 0.0009465838269901994, 0.0009149609609861997, 0.0008852877033959095, 0.0008571539977476617, 0.0008305135914078443, 0.0008054865637437958, 0.0007821898762181423, 0.0007607353256217086, 0.0007408459881734775, 0.0007215477095010581, 0.0007028237498786227, 0.0006847127886191462, 0.0006672482912646327, 0.0006504569845630082, 0.0006343570859924652, 0.0006189562549553385, 0.0006042581491353394, 0.0005902986206907102, 0.0005770047568127712, 0.0005642508395423684, 0.0005518704440317102, 0.0005396495907424859, 0.0005273189588778093],
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}

## plotting

fig,ax = plt.subplots(2,2,figsize=(5, 4))
ax = ax.ravel()
for i, m in enumerate(['CsI','YAG','Si','CZT']):
    for j,ell in enumerate([20,70,150,500]):
        if ell == 500:
            ax[i].plot(subplots_all[f'x{i+1}{j+1}'], subplots_all[f'y{i+1}{j+1}'], 
                       alpha=np.sqrt(ell/500),color=CB_color_cycle[i])
            # ax[i].set_title(label=m.materialstr)
        
        else:
            ax[i].plot(subplots_all[f'x{i+1}{j+1}'], subplots_all[f'y{i+1}{j+1}'], 
                       alpha=np.sqrt(ell/500), color=CB_color_cycle[i])
        

for i,a in enumerate(ax):
    # a.set_yscale('log')
    a.set_xscale('log')
    a.set_xlim([5e-3, 1])
    a.set_yticks([0.0,0.50,1])

for a in ax[[0,1]]:
    a.set_xticks([])

for a in ax[[1, 3]]:
    a.set_yticks([])

for a,t,c in zip(ax,['CsI','YAG','Si','CZT'],CB_color_cycle[:4]):
    a.text(0.20,0.75,t,color=c,fontsize=14)

ax[2].set_xlabel('Photon Energy (MeV)')
ax[2].xaxis.set_label_coords(1.12, -0.25)

ax[0].set_ylabel('Absorption (pt.)')
ax[0].yaxis.set_label_coords(-0.25, -0.2)

for a,l in zip(ax,'abcd'):
    a.text(0.003,1.1,f'{l})')

plt.show()