{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#Codes by Shucheng Yang\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import pycbc.psd\n",
    "\n",
    "from pycbc.types.timeseries import TimeSeries\n",
    "from pycbc.types.frequencyseries import FrequencySeries\n",
    "from pycbc import filter\n",
    "\n",
    "from scipy.interpolate import interp1d #导入scipy库\n",
    "import os\n",
    "import time\n",
    "\n",
    "def file2series(path):\n",
    "    with open(path, 'r') as f:\n",
    "        datafile = f.readlines()\n",
    "\n",
    "    datafile = [np.fromstring(item.replace(\"D\",\"e\").replace('\\n','').strip(), dtype= float, sep =' ') for item in datafile]\n",
    "    datafile = np.array(datafile)\n",
    "    ans = {}\n",
    "    \n",
    "    ans['timeVec'] = datafile[:,0]\n",
    "    ans['n'] = len(ans['timeVec'])\n",
    "    ans['sampIntrvl'] = ans['timeVec'][1]-ans['timeVec'][0]\n",
    "    \n",
    "    ans['hp'] = TimeSeries( datafile[:,5], delta_t=ans['sampIntrvl'], dtype = float,copy=True)\n",
    "    ans['hc'] = TimeSeries( datafile[:,6], delta_t=ans['sampIntrvl'], dtype = float,copy=True)    \n",
    "    return ans\n",
    "\n",
    "\n",
    "#绘制波形图\n",
    "def plotwave(hp,hc):\n",
    "    plt.figure(figsize=(8,8/1.5))\n",
    "    plt.plot(hp.sample_times, hp, label = '$h_{+}$')\n",
    "    plt.plot(hc.sample_times, hc, label = '$h_{\\\\times}$')\n",
    "    # plt.xlim(40,40.5)\n",
    "    # plt.ylim(- 2e-22,2e-22)\n",
    "    plt.xlabel(\"Time / s\")\n",
    "    plt.ylabel(\"$Strain$\")\n",
    "    plt.legend()\n",
    "    plt.tight_layout()\n",
    "    plt.grid(linestyle = \"dotted\", color = \"#d3d3d3\" , which=\"both\")\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def stdf(h, f_max, freqIntrvl):\n",
    "    #interp1d\n",
    "    hf = h.to_frequencyseries()    \n",
    "    freqVec = hf.sample_frequencies\n",
    "    hf_value = np.array(hf)\n",
    "    fit=interp1d(freqVec, hf_value,fill_value = \"extrapolate\")  \n",
    "    #\n",
    "    stdFreqVec = np.arange(0, f_max, freqIntrvl)\n",
    "    hf_value_std = fit(stdFreqVec)\n",
    "    stdf_series = pycbc.types.frequencyseries.FrequencySeries(hf_value_std, delta_f=freqIntrvl, epoch='', copy=True)\n",
    "    return stdf_series\n",
    "\n",
    "def overlap_match_func(hf1, hf2, psd, f_min, f_max):\n",
    "    roverlap = filter.matchedfilter.overlap(hf1, hf2, psd=psd, low_frequency_cutoff=f_min , high_frequency_cutoff=f_max, normalized=True)  \n",
    "    amplitude1 = filter.matchedfilter.sigmasq(hf1, psd=psd, low_frequency_cutoff=f_min, high_frequency_cutoff=f_max )\n",
    "    amplitude2 = filter.matchedfilter.sigmasq(hf2, psd=psd, low_frequency_cutoff=f_min, high_frequency_cutoff=f_max )\n",
    "    rmatch,nn =filter.matchedfilter.match(hf1, hf2, psd=psd, low_frequency_cutoff=f_min , high_frequency_cutoff=f_max,v1_norm=True ,v2_norm=True)\n",
    "    rmatch = rmatch / np.sqrt(amplitude1 * amplitude2)\n",
    "    return roverlap, rmatch\n",
    "\n",
    "def compare_multi(filepath1, dirpath2, filename2, parse_file_name_func):\n",
    "    #filepath1, 被比较的波形文件的路径\n",
    "    #dirpath2, 不同参数波形文件的文件夹路径\n",
    "    #filename2, 不同参数波形文件的文件名\n",
    "    #parse_file_name_func， 从文件名提取参数的函数 \n",
    "    \n",
    "    #filepath1 波形导入\n",
    "    ans1 = file2series(path1)\n",
    "    hp1 = ans1[\"hp\"]\n",
    "    hc1 = ans1[\"hc\"]\n",
    "    timeVec1 = ans1[\"timeVec\"]\n",
    "    n1 = ans1[\"n\"]\n",
    "    sampIntrvl1 = ans1[\"sampIntrvl\"]\n",
    "\n",
    "    #filename2 提取参数\n",
    "    a, nu = parse_file_name_func(filename2)\n",
    "    \n",
    "    #filepath1 波形导入\n",
    "    ans2 = file2series( dirpath2 + filename2)\n",
    "    hp2 = ans2[\"hp\"]\n",
    "    hc2 = ans2[\"hc\"]\n",
    "    timeVec2 = ans2[\"timeVec\"]\n",
    "    n2 = ans2[\"n\"]\n",
    "    sampIntrvl2 = ans2[\"sampIntrvl\"]\n",
    "    assert sampIntrvl1 == sampIntrvl2 \n",
    "    sampIntrvl = sampIntrvl1\n",
    "    n_min = min(n1,n2)          #采样点数(Sampling Number), 有时也称为信号长度(Length of Signal) 2^16为2的幂时，快速傅里叶变化效率最高\n",
    "                                #n =  duration * sampFreqint = (duration / sampIntrvl)\n",
    "    sampFreq = 1/sampIntrvl  #采样频率(Sampling frequency)，单位时间样本点个数，应大于 2f（即Nyquist频率)\n",
    "    #duration = n/sampFreq     #信号持续时间(duration of signal) 2^16, 0.75d, 2^25 ,1.06yr\n",
    "    #sampIntrvl = 1.0/sampFreq #采样周期(Sampling period)，隔多少时间取样一次，或步长\n",
    "    \n",
    "\n",
    "    freqIntrvl = 1.0 / (n_min * sampIntrvl) #傅里叶变换 频率分辨率(Frequency Interval) #freqIntrvl=1/duration=1/(n*sampIntrvl)=sampFreq/n  \n",
    "\n",
    "    f_min = 20                              #低于此频率的psd将被设置为0\n",
    "    f_max = sampFreq/2                      #信号模式的最大频率\n",
    "\n",
    "    #示例，psd参见， https://dcc.ligo.org/LIGO-T1800044/public\n",
    "    psd = pycbc.psd.from_string('aLIGOaLIGODesignSensitivityT1800044', n_min , freqIntrvl, f_min)\n",
    "\n",
    "\n",
    "    hpf1 = stdf(hp1, f_max, freqIntrvl)\n",
    "    hpf2 = stdf(hp2, f_max, freqIntrvl)\n",
    "\n",
    "    hcf1 = stdf(hc1, f_max, freqIntrvl)\n",
    "    hcf2 = stdf(hc2, f_max, freqIntrvl)\n",
    "\n",
    "    overlap_hp, match_hp = overlap_match_func(hpf1, hpf2, psd, f_min, f_max)\n",
    "    overlap_hc, match_hc = overlap_match_func(hcf1, hcf2, psd, f_min, f_max)\n",
    "\n",
    "    return a, nu, match_hp, match_hc, overlap_hp, overlap_hc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#下面用于[文件名解析参数]的函数要根据实际情况进行修改################################################################################\n",
    "def parse_file_name_func(filename):\n",
    "    ##下面要根据实际情况修改\n",
    "    anu = filename.replace(\"hbh60_NS14_a\",\"\").replace(\"_f20Hz_fisco.dat\",\"\").split(\"_nu\")    \n",
    "    a = float(\"0.\" + anu[0]) \n",
    "    nu = float(\"0.0\" +anu[1])\n",
    "    return a, nu\n",
    "\n",
    "path1 = \"/home/ysc/Desktop/nw5/heco60_NS14_a60s50_R9_nu250_f20Hz_fisco.dat\"  #被比较的波形文件的路径\n",
    "dirpath2 = \"/home/ysc/Desktop/data/\"                                          #不同参数波形文件的文件夹路径\n",
    "##################################################################################################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "._hbh60_NS14_a60_nu250_f20Hz_fisco.dat\n",
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      "(0.5, 0.016, 0.2349163726997819, 0.23883710683556694, 0.19420408280480383, 0.19310382786256697)\n",
      "(0.55, 0.022, 0.47357598260989214, 0.47509291147936605, -0.09946669238773606, -0.09688052998534619)\n",
      "(0.67, 0.0205, 0.1771706543826184, 0.1750427469082334, 0.022896913227935762, 0.025623074630116007)\n",
      "(0.53, 0.0295, 0.2209704062855991, 0.22635295258844712, 0.05701612390744263, 0.049058225302856695)\n",
      "(0.52, 0.0265, 0.2878761037390031, 0.28602796764148103, 0.03096979789729513, 0.026449818727008478)\n",
      "(0.69, 0.0385, 0.2849090302018168, 0.2850781709940544, -0.2182440536144788, -0.22778505170127672)\n",
      "(0.5, 0.0235, 0.6148642353117684, 0.6176599064301268, 0.04779295949455584, 0.05027178457164998)\n",
      "(0.61, 0.0295, 0.3063779564589075, 0.3071164586696332, -0.03230127616002827, -0.03437010882226752)\n",
      "(0.68, 0.0355, 0.3088272653411819, 0.30603599448608637, 0.021452190422639558, 0.02137468955622034)\n",
      "(0.66, 0.01, 0.08643311647333993, 0.0878613877849982, 0.02175987144662398, 0.020454899989203273)\n",
      "(0.68, 0.0325, 0.38054720695246075, 0.37813383524151645, -0.15556375908856146, -0.15354622351295258)\n",
      "(0.66, 0.0235, 0.2600153489521674, 0.2604362438367294, -0.015186616569871931, -0.015250375540367346)\n",
      "(0.58, 0.01, 0.1011647418867555, 0.09999096548921162, -0.027664533990880893, -0.03137552569753513)\n",
      "(0.69, 0.0295, 0.5179087886846034, 0.5160032076423193, -0.21479155694673252, -0.22244437994336222)\n",
      "(0.68, 0.0235, 0.246090078041962, 0.2433586454086649, 0.03155873155629053, 0.033796941091511726)\n",
      "(0.63, 0.016, 0.13637060908126286, 0.13565465260716722, -0.039023105063025275, -0.04094327092346264)\n",
      "(0.52, 0.019, 0.3185801113904002, 0.32131769851740133, 0.2537126169728925, 0.2546975970622651)\n",
      "(0.51, 0.0115, 0.13896655154688142, 0.13854381242127356, -0.11121657196436781, -0.1095644126471624)\n",
      "(0.61, 0.025, 0.8244470599050758, 0.8232283038162195, -0.15798784752671824, -0.1597021934403987)\n",
      "(0.5, 0.022, 0.6343624387425283, 0.6335439232088823, 0.18186835933928155, 0.18128050407166724)\n",
      "(0.68, 0.0175, 0.1361232103757484, 0.13534142535051122, 0.017993339797524908, 0.01481351571493697)\n",
      "(0.65, 0.019, 0.1637756723647436, 0.1621171542873833, 0.02788612299683737, 0.02502979093841888)\n",
      "(0.64, 0.025, 0.4254992825045007, 0.4265590546590569, 0.029761407288787543, 0.025962221864911636)\n",
      "(0.5, 0.04, 0.16158903545335637, 0.1690064336320242, 0.04066329002681659, 0.031215901111636246)\n",
      "(0.7, 0.01, 0.08455326972028866, 0.08291881733692155, -0.00047202313506454545, 0.0007477843577781206)\n",
      "(0.65, 0.031, 0.3678934630334435, 0.36531219549391164, -0.22260195977280792, -0.2241411319788294)\n",
      "(0.7, 0.028, 0.5817215482421702, 0.5779530164422579, -0.023200067602797178, -0.020884663503319884)\n",
      "(0.56, 0.0325, 0.2130182414471225, 0.21430353864213592, -0.05605552429581561, -0.05282942737893477)\n",
      "(0.69, 0.034, 0.3521418794918111, 0.3503959232285469, -0.17136418991730737, -0.16884215535878325)\n",
      "(0.64, 0.034, 0.2758531424251363, 0.27215070630941385, 0.24962052745250118, 0.24740184488075112)\n",
      "(0.54, 0.0145, 0.170341288622789, 0.16892765774899252, -0.06740910608738462, -0.06601016295634778)\n",
      "(0.56, 0.04, 0.17107032777804979, 0.1785752216801685, 0.06430702972819491, 0.05569562582785173)\n",
      "(0.69, 0.0205, 0.16637009711064768, 0.16445386487929906, -0.015786082012667936, -0.01812508022110958)\n",
      "(0.54, 0.0385, 0.17501023664578544, 0.17728326825133744, 0.05302707983442899, 0.047211371670687216)\n",
      "(0.63, 0.025, 0.500226895497532, 0.4986743379656583, 0.08276517588561079, 0.08449157720328719)\n",
      "(0.5, 0.0325, 0.18135796120462563, 0.18043150605940406, 0.01290091158306104, 0.0057236303006584525)\n",
      "(0.66, 0.0265, 0.7371596595734102, 0.7406228062838217, 0.18887776838788647, 0.18298119092841275)\n",
      "(0.51, 0.0325, 0.1920707064138163, 0.19178243734274777, -0.02092255125723646, -0.019490253221585)\n",
      "(0.59, 0.0355, 0.20186518041574036, 0.20728770832783644, 0.10130293865468176, 0.09349345509235964)\n",
      "(0.66, 0.0175, 0.1386223831853854, 0.14019520115915438, 0.032159633534897904, 0.032904041444818795)\n",
      "(0.65, 0.025, 0.39545469815587275, 0.39510666700787933, -0.011041988119829935, -0.0177542697287867)\n",
      "(0.53, 0.0145, 0.17111257675404618, 0.1719332568485969, -0.1608686254878661, -0.15884826576384511)\n",
      "(0.64, 0.022, 0.2302134819258402, 0.229914636063181, 0.055577652520321943, 0.05585978738242847)\n",
      "(0.51, 0.0145, 0.19126959535154414, 0.19309614851461346, -0.08174431457884977, -0.08495953383255016)\n",
      "(0.57, 0.0235, 0.6072084259579408, 0.607900631017592, 0.570122222592446, 0.565658677894036)\n",
      "(0.61, 0.0325, 0.25254219260294347, 0.2492842669691462, -0.059785508486854294, -0.060187988994761556)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.64, 0.0295, 0.4126320622085741, 0.4120332622837592, 0.312463219937546, 0.316038401952483)\n",
      "(0.55, 0.01, 0.10882285644217302, 0.10889921942874473, 0.08296288305452072, 0.0794336222919122)\n",
      "(0.67, 0.016, 0.12457977289339811, 0.12398268960281394, 0.025137140755005775, 0.025054966913802035)\n",
      "(0.59, 0.028, 0.3226134139030034, 0.3299596735652543, 0.15725666255785706, 0.15054272859544804)\n",
      "(0.59, 0.037, 0.19508134466857482, 0.2022181300328618, 0.09728470068602768, 0.08912255651228232)\n",
      "(0.54, 0.019, 0.28732649861932275, 0.28380244812917527, 0.19958920583883866, 0.19408859860823577)\n",
      "(0.51, 0.016, 0.2324432154364541, 0.2362062559038737, -0.21090517428656108, -0.21196800356126125)\n",
      "(0.57, 0.013, 0.12949048148715023, 0.12874106751211006, -0.08183754523646987, -0.08303108903810358)\n",
      "(0.58, 0.016, 0.162576277800838, 0.16334053860317232, -0.09917049001106375, -0.10061581523300929)\n",
      "(0.7, 0.019, 0.15535788242503376, 0.15304996779974483, -0.01632220082166932, -0.020028374538103196)\n",
      "(0.69, 0.0355, 0.3233285425065716, 0.32162684308052986, -0.20160790684244276, -0.20362274804606878)\n",
      "(0.7, 0.0175, 0.136974734994595, 0.1386801187200681, 0.009775804374669657, 0.01241217495127839)\n",
      "(0.57, 0.0205, 0.2853307209483595, 0.28594859350244, -0.1844039719597942, -0.18558375242589048)\n",
      "(0.63, 0.0175, 0.15023420731413636, 0.1522190614676782, -0.00830787276487441, -0.00657040480698327)\n",
      "(0.53, 0.0385, 0.176539389799992, 0.17322202451937158, 0.01850207067976121, 0.018196839192076483)\n",
      "(0.66, 0.037, 0.26883595543713507, 0.26526368069708506, 0.2618717860914679, 0.25970719484039795)\n",
      "(0.64, 0.028, 0.5081296748520001, 0.5073772971843802, 0.46737758662922096, 0.4720255767428943)\n",
      "(0.52, 0.013, 0.15857991974523852, 0.1572590840152047, 0.1082827909208201, 0.10430629624390306)\n",
      "(0.55, 0.0355, 0.18834793602731278, 0.19004646069523987, -0.047603213984395265, -0.04450400327815841)\n",
      "(0.65, 0.013, 0.10323028055899175, 0.10345279420643885, 0.025521110458182387, 0.0271372503815048)\n",
      "(0.68, 0.019, 0.15260685722279851, 0.15145480361966518, 0.00231541930220964, -0.0031904513124004033)\n",
      "(0.53, 0.022, 0.5489773908207924, 0.5504470567085625, -0.2817181256017599, -0.28125338625473834)\n",
      "cost 271.45 s\n"
     ]
    }
   ],
   "source": [
    "#将dirpath2下的文件的文件名转换成一个列表 file_name_list\n",
    "file_name_list = os.listdir(dirpath2)\n",
    "anslist = []\n",
    "\n",
    "\n",
    "#计时\n",
    "time0 = time.time()\n",
    "for item in file_name_list:\n",
    "    try:\n",
    "        ans = compare_multi(path1, dirpath2, item, parse_file_name_func)\n",
    "        print(ans)\n",
    "        anslist.append(ans)\n",
    "    except Exception:\n",
    "        print(item) #如果打印文件名，则说明出错了，请查看上面一个代码框排错    \n",
    "timet = time.time()\n",
    "print(\"cost %4.2f s\"%(timet-time0))\n",
    "\n",
    "\n",
    "#排序, 转换为numpy序列\n",
    "anslist = sorted(anslist)\n",
    "ansarray = np.array(anslist)\n",
    "\n",
    "#输出到文件 读取用np.loadtxt\n",
    "np.savetxt(\"a_nu_match_hp_hc_overlap_hp_hc.data\",ansarray, fmt='%s')\n",
    "\n",
    "#结果分别存储给a,nu等，用于作图\n",
    "a = ansarray[:,0]\n",
    "nu = ansarray[:,1]\n",
    "hp_match = ansarray[:,2]\n",
    "hc_match = ansarray[:,3]\n",
    "hp_overlap = ansarray[:,4]\n",
    "hc_overlap = ansarray[:,5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘图字体参数设置\n",
    "matplotlib.rcParams.update({'font.size': 15, 'font.family': 'STIXGeneral', 'mathtext.fontset': 'stix'})\n",
    "\n",
    "x = a\n",
    "y = nu\n",
    "z = hp_match\n",
    "\n",
    "cmap = matplotlib.cm.get_cmap('jet')#viridis\n",
    "normalize = matplotlib.colors.Normalize(vmin=0, vmax=1)\n",
    "colors = [cmap(normalize(value)) for value in z]\n",
    "\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "ax = fig.add_subplot()\n",
    "ax.scatter(x, y, color=colors)\n",
    "ax.set_xlabel(\"$a$\")\n",
    "ax.set_ylabel(\"$\\\\nu$\")\n",
    "ax.set_xlim([0.49,0.71])\n",
    "ax.set_ylim([0.01-0.001,0.04 + 0.001])\n",
    "#ax.set_title(\"hp_match\")\n",
    "plt.xticks([0.5,0.55,0.6,0.65,0.7])\n",
    "plt.yticks([0.01, 0.015, 0.02, 0.025, 0.03, 0.035, 0.04])\n",
    "\n",
    "# Optionally add a colorbar\n",
    "cax, item = matplotlib.colorbar.make_axes(ax)\n",
    "cbar = matplotlib.colorbar.ColorbarBase(cax, cmap=cmap, norm=normalize)\n",
    "\n",
    "ax.grid(linestyle = \"dotted\", color = \"#d3d3d3\" , which=\"both\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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A3wO/k5lP9hMrSZIGe+W/CrgxM6+NiL2A9RGxITNX95RbATyYmVdFRAB3RsTGzFwZEa8BngBOAA4H7gB+G7husthBHKAkaZrY7N+ogVRtRCwBFgNvBsjMbRFxC7AMOKer3NHAm4DX1OUyIlYBFwErgQ2Z+YW6+A8iYvUuxI5vd8qmNS2dknXYP/D9CuNL93/YU/qWzahaPqXt8wrjf2bI8YueKAp/2RFri+JLp8R9Id8pin8x64ri96Ss/vYonFJ4AWVTGgN8sHgNYzD5N2pQz/kvAbZlZvfE0/cAZ/SUW0z1V76up9wpEXFwd3xEHErVCvDxfmKn5SgkSYPRSf5TfWlCg0r+R/Dc66stwLyIOLCnHD1lt9TvCwEiYreIuAD4GnAqcGK/sd0i4vyIWBMRa3j64V05FknSAOTcqb80sUEl/yeBp8bZ9pyecvSU3alcZm6nuse/FNgM3NBvbLfMXJGZizJzEXMO7fMwJEma+QbVOPIAcEDPsoOArZn5SE856rJbusoBz96YyswngDUR8RaqjoPz+42VJLVfBuyw+b4xg7ryvxXYPyIO61p2fL282+3ADuDYnnJrM3OstvmHgK1UyX5XYyVJbVUn/6m+NLGBJP/MXAuspmqqJyL2oOrstzwiToyIayJibp2kV3bK1c4Cltdxr4iIl3V99xvAn2fmjsliJUkzRwZsnztnyi9NbJA1tBR4dUS8A7gKuCQzb6O6Uj8T2Kcudx4wPyKWRcRfUo0P8LH6u9cB/xIRH4+It1M9QXBp1zYmipUkSQzwgYjM3AScO8byVVRJuvP5caokPtY6LgEumWAb48ZKkmaOjGDHbiUpqmz8g9nOOyOSpFbaMddn9ppi8pcktU4S7HBmn8aY/CVJrZME203+jbFLpCRJI8Yrf0lSK+0wRTXGmpUktY73/Jtl8pcktY7Jv1kmf4DdgecXxJfORz+vML7030fp9vcqjC9VOh/99sL4l01eZCJzXrW1KP6IwzeVxfP9ovi57CiKfwP/rSj+lXy1KH7PwufBT9r4raJ4HioL54dl4evPeEHhDsAHi9cwNpN/c+zwJ0nSiPHKX5LUOj7q1yyTvySpdap7/qaoplizkqRW8p5/c0z+kqTWsbd/s+zwJ0nSiPHKX5LUOgl2+GuQyV+S1EJ2+GuSNStJah3v+TfLe/6SJI0Yr/wlSa3klX9zTP6SpNax2b9ZJn9JUus4vG+zTP6SpFayt39zrFmopqQ9oSD+8MLtl06pu2dh/EGF8aXmF8aXTMcM7H3ClqL44/a/pyh+Mf9cFP8GbiiKP4r7iuKff2/hnLK/Vxb+4M1l8Ye/pSy++N//YYXxS8rCj/nd7xXugGYik78kqXW8598sk78kqXVM/s0y+UuSWskOf80x+UuSWicd3rdRjvAnSdKI8bRKktQ63vNvlslfktRKJv9dExHPz8wH+ilr8pcktY4j/I0vIvYBfhVYCM9UUgCn0efIDyZ/SVLr2OFvQjcBxwPfAp6ul81lF4ars2YlSZpZjgKOzsxt3QsjYnG/KzD5S5JayXv+4/onxs7ffd3vZ5xgSZKGyt7+z4qIY4GzuhZtAFZGxFe7ls0BTgde3c86Tf6SpNZpe/KPiAWZuXFAm/sx8D7g6z3Lf6nrz3OAY/tdoclfkjSSImI+cClwN3AS8KXM/NQ4Zd8LXNa16DeBT9XfnQacA/wH8ArgfZl533TtZ2ZuioizM/OfJioXEb/Q7zpN/pKkVhrAo36rgBsz89qI2AtYHxEbMnN1d6GI2BM4GTi1XvQU1QkDEfFS4NPAsZm5OSLuBz4bESdnZk7XjnYn/ojYDfilzPzH+vMLgZ9m5h39rs/kD7Affd4lGcdRZZs/5PS++2iM6YQ564riD+LRovi57CiKL53P/nRuK4o/6aJvFcV/6P8rCueRsnCeXxh/+I/K4i87+p1F8Tfd9Pqi+Ps4uij+e99fUBTPD/Ysi/9fZeEU/v3tceljhTsAfOSA8nX0aPpRv4hYAiwG3gyQmdsi4hZgGdVVfLffpnqUbj/gnzOz+z+9dwN3Z+bm+vPNwH8DzgT+vqHd/xDwpoh4QWY+lpnfiYj3R8Q/9nsC4Nj+kqTW6dzzn+qrD0uAbZl5b9eye4Azxih7AtVtgS9StQ68smc9z1yBZeZTVB3yxlrPdNkdWJiZ3Wdun6A6KejLrE/+EVF4Wi9JGobC5D8/ItZ0vc7vWf0R8Jxmzy3AvIg4sHthZl6YmScALwE2AjdHxOGTrGfhNFTBeL6Rmb3b/FngRf2uYGDJPyLmR8RHI+KC+v2N45TbOyKujoh3RsSVEfGuru8iIi6JiI0R8WhE3FB32OiOf29EZOdFWYO+JGlm2pyZi7peK3q+f5Lq3n23OT3vO8nMdVTN+VuApZOsp8n8unvdyRCAiFgELAf+pd8VDPKef18dK4AVwIOZeVVEBHBnRGzMzJXA71KdYb0WeDnVwX4Y+DWYuFOGJGnmGMDY/g8AvZ0VDgK2Zua4XXEy8/GI+HxX7Hjr+dp07egYrgA+HBErqcb0PwC4A3hbvyvoK/nXSfV1wM8AX8vMf9uVvey3Y0VEHA28CXhNXS4jYhVwEbAS2D0zr66Lr4uI46lOCDom6pQhSZohBjC2/63AZRFxWGY+VC87vl4+md149j7/rXQ9X19f3B7V53qmJDO3A+dFxMXAMcAPqMYC2NrvOvpqlsjMJzLzf1JdlS+IiOsj4uW7sK/9dqxYTHUWs66n3CkRcXBX4u/YBNzX9XmiThmSpBmkyQ5/mbkWWE3dfB8Re1DlpOURcWJEXBMRcyNiQUQs69xijoiFwAKqXv0A1wGvjIiD68+nU+Wmz09nXXSLiPfVx7A5M++oxxR4BPiLftexS6dV9TOLqyLiH4DrI2JVZt7QR+iEHSu6Oi4cUb8/2lMOqs4TvU0xpwLPnBBk5oXAhRHxYuAjVJ0yjsvMB3t3qO78UXUAObjJfhmSpF01oBH+lgKX11frxwGXZOZtEXE21b39i4F5wFuBd0TEXwOPA2/otCxn5tcj4tx6PXcBrwJeX/f6n1YR8ZtUV/q/WD/r3+1Q4I3A7/Wzrn6b/fcF9srMHwJk5taIeDOwOiK+kZmTPanab8eKJ+v3pyYpR0QcA8zNzL/r3VhmrouIM6nu9y+lOhHoLbOCqiWDOHLRtA3EIEmaGTJzE3DuGMtXUfVTg6ol+rhJ1vM54HP1x2umcx973AT8HVXP/t4zox8DF/S7on6v/A8ANkbEvwNfAG6nmlXow8AfUp1tTKTfjhWd0W4O4Nkr/oPq92fGUI6IeVRnN+N2bhijU4YkaQZp89j+w5CZP4qIXwVOzczuSX2IiLk8my8n1Vfyz8zvR8T1wJepOuN9hKrz3330l1z77VhxO7CDqvPEv3aVW5uZD0P1KCDwHuCPMvOn9bI9MvNJnqu7U4YkaYYYQG//Gam+nfDViNifKv9G/dWBwFXAaePFdtuVe/5/kJk/Aj4OzzS7nw6c0sfOro2ITseKj3Z1rHhzRJxIdQX/jsx8uH50YSnPJv+zqB7p63TIuBK4HnhB9SQgzweOjIh/BH4D+C/1+Mq9nTIkSTPEAHr7z1gR8Xaqx/3m8GzyT+Db/a6j75qtE3/35/XA+n7j6a9jxePAecAVEbEMOJzqvsvH6nXcAPwKOzf3J9X9jwk7ZUiSZhab/cd1CtWTba8A1lDN8PAKdmGqkIGdVvXZsYLM7JwAjLWOpWMt7zJhpwxJkmaBr2Tmf0TEBuA/Z+Zy4LsR8c/0Ob6AbSqSpNYZ0KN+M9XJEfEZ4EJg34j4CNUtgJP7XYHJHzjloDv5t3Ni8oLjiNsLd+DCwvh7Jy8yocIpQQtnVK1u+hTYelbZENp3X9b3XBhj+u5lz2nQ2iX/wGuL4j+wYVFRPGum/tsH4K6ycLYVxpf+/ktvDD5eGP9EYfymsvAnj92/cAeaYYe/Cb2f6om3H1Pd+7+SqjP+H/a7ApO/JKmV7PA3rp8C3wT+E7AnsBm4kaqDfF/T+lqzkiTNLJ+nmr53PfB0vSzYhX5vJn9JUut4z39CPwMc1TuEcET8fL8rMPlLklrH5D+hW3j2ir9b+x71kyRpV5j8x/UXwN9GxLe6lgVVp79f7GcFJn9JUuvY239CN1I9Z7WAnVsA+n72yuQvSdLMsh9wZGZu714YEaf2uwKTvySpdRzbf0JfBXYHtvcsf2iMsmOyZiVJreQ9/3HdD3wqIr7Ws/wXgNf3swKTvySpdeztP6FfAg6hmtK3I4Dj+12ByV+S1Dp2+JvQBzPzORP4RMSr+l1B2aDokiRpoMZK/PXyr/S7Dq/8JUmtZIe/5lizkqTW8Z5/s0z+kqTWMfk3y+QPsB2i76cjn+uxpXsUbf6+c44qin+Qw4ri7+LlRfEbWVAU/3VOHOr2v/PVlxTFs7ksnPWF8YXzufOdwvjS+ey3FsY/XBj/RGF875PWu+qpyYtMqLT+HiyMb5Ad/ppjhz9JkkaMV/6SpNZxhL9mWbOSpNbxnn+zTP6SpFYy+TfHe/6SJI0Yr/wlSa1js3+zTP6SpNZJfNSvSSZ/SVIL2du/SdasJKl1bPZvlh3+JEkaMV75S5JaySv/5pj8JUmtk4Qd/hpk8pcktY7D+zbLmpUktZLN/s0x+QPf3WsBbzv+3VOOf5QDi7Z/H0cXxZduf/2DLyyKf/o7+xbF84OycP5XYXzplLSlU+KWHv+PhxxfOqXxsKfELd1+sSEfwMa9C7evmcjkL0lqHR/1a5bJX5LUOkmw42mTf1NM/pKk9knYvt3k3xSTvySpdTKDHdtNUU1xhD9JkkaMp1WSpNaprvxt9m+KyV+S1D6Jyb9BA0v+ETEfuBS4GzgJ+FJmfmqMcnsDlwH3AkcC92fmlfV3Afwx8FZgHvAPwAWZuXmyWEnSzJEZbH/K5N+UQV75rwJuzMxrI2IvYH1EbMjM1T3lVgAPZuZVdbK/MyI2ZuZK4HeBR4HXAi8HlgMfBn6tj1hJksSAOvxFxBJgMXATQGZuA24BlvWUOxp4U1e5pDppuKgusntmXp2Z6zLzE8BfAb/UZ6wkacYInt6x25RfmtigamgJsC0z7+1adg/w/p5yi4EA1vWUOyUiDs7Mq3vKbwLu6zP2kbJDkCQNTALe82/MoJL/EVTN9d22APMi4sDMfLSrHD1lt9TvC4HeBH4q0Dkh2KXYiDgfOB9gv4UH9XcUkqTByDD5N2hQyf9Jnjt7xZye9045esqOVY6IOAaYm5l/t6uxAJm5gqqPAIcuWpiT7L8kaZAS2B7D3otZa1CD/DwAHNCz7CBga09z/AP1+wE95QA2dhZExDzg94C37WqsJEmjblBX/rcCl0XEYZn5UL3s+Hp5t9uBHcCxwL92lVubmQ/DM4/zvQf4o8z8ab1sj35ix7P5icNYseH3p350jxaenX67LJwHC+N7b8jsqtIpaSf82+lD6fGXTkm7rTC+dErhrYXxPy2ML1Y6pW3pAZTGl+5/qdIf0Lxp2YtGDH265dlrIFf+mbkWWA0shWeS9RnA8og4MSKuiYi5dZJe2SlXO4vqkb5O3JXA54AXRMTxEfEa4Lcmi5UkzSBJlfyn+tKEBvk8xFLg8voZ/+OASzLztog4GzgTuJjqFPY84IqIWAYcTvW43sfqddwA/Ao7N/cn8LP1nyeKlSTNFJ3kr0YMLPln5ibg3DGWr6JK0p3PnROAsdaxdKzl/cRKkmaQZPh3VGYxZ/WTJGnEOAySJKl9kqoLtxph8pcktZP3/Btj8pcktY8d/hpl8pcktY/Jv1F2+JMkacR45S9Jah+v/Btl8pcktY/Jv1Emf0lSO5n8G+M9f0mSRoxX/pKk9nF430aZ/CVJ7eMIf40y+QM8Anw8ph5fOh98afyPC+MfneHbL53OvLT+i5Ve3pTeGH2sMP6nQ44fdv2VGvb+l9Z/Q+zw1yjv+UuS2qeT/Kf66kNEzI+Ij0bEBfX7G8cp94KI+PuIeCgivhURZ/R8f1pELI+It0fEJyPiqF0+3gHzyl+SNKpWATdm5rURsRewPiI2ZObqnnLvAN6WmQ9ExHuB64EXAETES4FPA8dm5uaIuB/4bEScnJk5wGPZJV75S5Lap+Er/4hYAiwGbgLIzG3ALXnHo+cAABAsSURBVMCynnL7An+RmQ/Uiz7bs6p3A3dnZucG4s3AscCZ/R7qMJj8JUnt1Gyz/xJgW2be27XsHmCnJv3M3JqZD3Utej3w//SsZ11X+aeADb3raRuTvySpfcqv/OdHxJqu1/k9WziC53Y33gLMi4gDe3cnIk6MiE8AfwacHhGd/Dneehbu6iEPkvf8JUntU97bf3NmLprg+yd57qMWc3reu32D6t7/HcAHga8B/3WC9bT64rrVOydJUkMeAA7oWXYQsDUzH+ktnJlPZ+bmzPwQcAPwv02ynvuneX+nlclfktQ+nRH+pvqa3K3A/hFxWNey4+vlk3kI2Ni1nmM7X9RPDRzV53qGxuQvSWqfzgh/U31NtvrMtcBqYClAROxB1UlveX1//5qImBsRe0fEG+qkTkTsDZwKXFev6jrglRFxcP35dGAT8PmSw2+a9/wlSe3U/Ah/S4HL68R+HHBJZt4WEWdTPap3MVWT/p8BfxoRfwNsA87NzB8CZObXI+Lcej13Aa8CXl/3+m8tk78kqX0GMLxvZm4Czh1j+SqqAYCgGkD8hZOs53PA5+qP10znPjbFZn9JkkaMV/6SpPZxYp9GmfwlSe3T6e2vRpj8obqj86WC+NKz002F8VsL40un5C2dEbT47L70f4jSAyidEnfYU7IOu/5Kj3/YU+KWGvb+710Y35BOb381wnv+kiSNGK/8JUntNOxGmVnM5C9Jah87/DXK5C9Jah87/DXK5C9Jah87/DXKDn+SJI0Yr/wlSe3jPf9GmfwlSe1k8m+MyV+S1D52+GuUyV+S1D52+GuUHf4kSRoxXvlLktrHDn+NmrHJPyL2BeZk5uOTlFuYmfcPaLckSdPB5N+ogTX7R8T8iPhoRFxQv79xnHJ7R8TVEfHOiLgyIt7V8/0+EbEMuA94yRjxb4iI7LyANzVxPJKkBnU6/E31pQkN8sp/FXBjZl4bEXsB6yNiQ2au7im3AngwM6+KiADujIiNmbmy/v4w4CvA/HG28yvAqfWfE/j36T0MSdJA2OGvMQNJ/hGxBFgMvBkgM7dFxC3AMuCcrnJHU12pv6YulxGxCrgIWFkvu686JxhzO78MHFq/vpCZT/a1gz8B7prKkdW2FcRC+XToQz/NfWTI23+sMH7CO0cDUPoDGPZ88DN9+8Pe/1Kl+7/7tOyFZpZBNfsvAbZl5r1dy+4BzugptxgIYF1PuVMi4uA+tvNyqsT/98D3IuL/mvouS5KGpnPPf6ovTWhQyf8I4NGeZVuAeRFxYE85espuqd8XTraRzLw8M08Gjgb+BVgZESeOVTYizo+INRGxhny4n2OQJA2Kyb9Rg0r+T/Lctqk5Pe+dcvSUHavchOre/b8OfI1xOvxl5orMXJSZi4hD+121JGkQ7PDXqEEl/weAA3qWHQRszcxHesrRU/ag+n3jrmwwM7dTdTLs3a4kSSNtUMn/VmD/iDisa9nx9fJut1P17zy2p9zazCm1ze/Gzv0HJEkzQWd436m+NKGBJP/MXAusBpYCRMQeVJ39lkfEiRFxTUTMrRP8yk652lnA8p5Vzu3dRkQcEBEXRcSR9ecDgdOAv5nu45EkDYD3/BszyOf8lwKX18/4Hwdckpm3RcTZwJnAxVTPXJ0HXFEP5HM4VdP9xzoriYgXAW+vP/5ORGzNzK8DewG/BiyLiI9QPf917mQjAEqSWsgR/hoVmTnsfRi62G1Rsv+aqa/A5/yHvH2f8y8z7Ofsh739Ye9/qTY85/9bd2bmomlY0TNir0XJgoL/l9fHtO/TbOKsfpIkjZgZO7GPJGkW63T4UyNM/pKk9vGef6NM/pKkdjL5N8bkL0lqn84If2qEHf4kSRoxXvkD7EjYUnKKWdo2VfqoWumjYqXbLz3+UX/UbdSPv9So73+plqYBO/w1qqV/65KkkWaHv0aZ/CVJ7WPyb5TJX5LUPnb4a5Qd/iRJGjFe+UuS2skOf40x+UuS2sl55xpjs78kSSPG5C9J0ogx+UuSNGJM/pIkjRg7/EmSWsgH/Ztk8pcktZBD/DXJZn9JkkaMV/6SpBay2b9JJn9JUgvZ7N8kkz8A24D/KIgf9g/0scL40vnkhz2f+kyfz37Yv59R3/9SM/34d5+WvZh+Xvk3yeQvSWohk3+T7PAnSdKI8cpfktRSw76lMnuZ/CVJLWSzf5NM/pKkFrK3f5NM/pKkFvLKv0l2+JMkacR45S9JaiGb/Ztk8pcktZDN/k0y+UuSWsgr/yZ5z1+SpBHjlb8kqYVs9m+SyV+S1EI2+zfJ5C9JaiGv/Jtk8geqH9hDBfGlU+L+pDC+VOn+l04JWrr9Yf8HUXp1UvrPsLT+Sg376mzYf/+lhl1/w97+RNq8bzObHf4kSRoxM/bKPyL2BeZk5uPD3hdJ0nSz2b9JA0v+ETEfuBS4GzgJ+FJmfmqMcnsDlwH3AkcC92fmlV3f7wNcALwHOAu4o+u7OcCfAFuB/YC5wB9m5tMNHZYkqREm/yYN8sp/FXBjZl4bEXsB6yNiQ2au7im3AngwM6+KiADujIiNmbmy/v4w4CvA/DG28SfACZl5DkBEfAa4EPjLJg5IktQUe/s3aSD3/CNiCbAYuAkgM7cBtwDLesodDbypq1xSnTRc1CmTmfcB3x9jG/sC7+rE1j4NXBgRpT3SJEkD1bnyn+pLExlUh78lwLbMvLdr2T3AGT3lFgMBrOspd0pEHDzJNk4B9h0j9nnAiVPZaUmSZqNBJf8jgEd7lm0B5kXEgT3l6Cm7pX5f2Mc2+o6NiPMjYk1ErIEfTbJqSdJgdZr9p/rSRAZ1z/9JntsOM6fnvVOOnrJjlRtvG33HZuYKqv4FRLwoJ1m3JGmg7PDXpEEl/weAA3qWHQRszcxHespRl93SVQ5gYx/b6MR2bwPg/v53VZI0fHb4a9Kgmv1vBfaPiMO6lh1fL+92O7ADOLan3NrMfHiSbdwJ/HCM2IeBu6ay05KkYbHDX5MGkvwzcy2wGlgKEBF7UHX2Wx4RJ0bENRExt07wKzvlamcBy3tWOXeMbWwHrhsjdkX9nSRJz4iI+RHx0Yi4oH5/4zjl9o6IqyPinRFxZUS8q+f7N0bEByLi7RFxfUScMpgjmLpBPue/FLi8fsb/OOCSzLwtIs4GzgQuBh4HzgOuiIhlwOFUj/p9rLOSiHgR8Pb64+9ExNbM/Hr9+f3AZRHxx1QnNvdTPfsvSZpRBtLsXzz+TEScCLwvM08EiIifpXqU/UVN73yJgSX/zNwEnDvG8lVUfwGdz50TgPHW8y2q5P/2Mb57Cnj3dOyvJGmYmu3w1zX+zJuhGn8mIjrjz5zTVa4z/sxr6nIZEZ3xZ1ZSXcweFBG71a3MW4BDGtvxaeLEPpKkFmr8Ub/pGn/mi8AewPURMQ+4hJ4B7Npoxk7sM72+vRl++bsTFJgPbB7U3sxC1l8567CM9Vdmsvo7cvo3uekf4ANjDePer72qcVyesaJ+xLtjwvFnMvPRrnIwzhgymXlXRJxONbrsg8AfZOb1Bfs9ECZ/IDMPnej7iFiTmYsGtT+zjfVXzjosY/2VGUb9ZebrGt7EdI4/cwTwCeAY4EMREZl57TTu67Qz+UuSRtG0jD8TES+nmon25zLz6Yh4J3B1RNySmd9paN+Lec9fkjSKpmv8mdOBb3amjs/Mq4BvAy9vaseng8m/PysmL6IJWH/lrMMy1l+ZWVd/0zj+zJ3Az0XEbvV65lLl1lYPLhfVrLmSJI2WiHgecDmwhuqRva9l5nX1+DMfBE7KzMfrXvxXAN+iGn/mEeDP62nniYjzgFcAXweeD/xzZv7PgR/QLjD5S5I0YuzwNwURsSAzJ5toSOOYqP7q52afyMytA96tVouI/YC3UD1PfGdmfnm4ezSz9Ft//v40Kkb2nn+/YzrXZd8bEdl5Aa/u+u60iFhej+n8yYg4agC7P3TTWH/7RMTmru++CvxkAIcwVLtYf79A1Sz5g8y8ojtx+fsrrj9/f+PUX1S+3f1vt37d0VVmJH9/s8EoX/n3NaZzROwJnAycWi96Cri7/u6lwKeBYzNzc0TcD3w2Ik7O2X8/pbj+am+lGqr52/XnjSNQd9B//b0Y+EfgzfVQ2N3f+fsrqL+av7/x6+904K+oBq95ul52PvAjGPnf38yXmSP3ohrWMYGju5ZdB6wco+x5wA3A/w7M7fnuvwBf7vq8O/BT4P8c9jHOkPrbjepE4C3A84d9XC2tvy8At4+zHn9/ZfXn72+C+hurToCvAMfUfx7J399seY1qs3+/YzoDnACcRDV+8/qIeGXPep4Z7zmriYU2jLOe2WS66u+lVFcRVwP3R8RHOo/LzHJ91V9ELAROA7ZHxIcj4t8j4n9ExOFd6/H3V5lK/fn7e9Zz6i8zH+j+HBELgH0yc33Xekbx9zcrjGryn3BM5+6FmXlhZp4AvATYCNzc9Z/HeOtZOP273CrTUn+ZeVdmLgYOA36f6grsTxve9zbot/46g4T8WWb+LtWtk/k8+8y1v79n7XL9+fvbyZj/fnucQ9cMrBOsZ7b//maFUU3+/Y7p/IzMXAecSfXj7gz2MN56Znu9Tlf9db57IqtxsP+A6j/g2a7f+tuH6l7rlwEy80ngr4EzoxqQxN/fs6ZSf9TL/f1N8u+39utU9/gnW89s//3NCqP6l9TvmM47yczHgc93xY63nvunaT/barrqr9eNE3w3m/Rbf9+n+je6T9ey7wJz63h/f8+aSv318vc3zr/f+hbKAfVJ/GTrme2/v1lhVJN/v2M6j2U3nr3PdStd4z3XvWaP6nM9M9l01d+ufDeb9Ft/a4AfU/Wb6NgHeCyrIUf9/T1rKvXXy9/f+M5h56v+znpG8fc3K4xk8s8+x3SOiAURsSwi5tflFgILgJvrVV0HvDKqgUGgejRmE9XV7aw1XfUXEedGxOu7Vn0h8IEBHspQ9Ft/WQ00cz3wW13hr+HZMcX9/TH1+vP3N3H99YT1NvnDiP7+ZouRHd43+hjTmSpRfQbYl+pe4ePAdZn5WNd6zgL+b6pJHF4F/ElmfnOQxzIM01F/EfFBqueGPw+sBf4tM28b9LEMQz/1l9WY4ntTjSn+GNVV7CHAe+r71/7+CurP39/k9VeXXUj1uOQxY6xnJH9/s8HIJn9JkkbVSDb7S5I0ykz+kiSNGJO/JEkjxuQvSdKIMflLkjRiTP6SJI0Yk78kSSPG5C9J0ogx+UuSNGJ2G/YOSBpfRLyYamz6tcDRwBsy85Th7pWkmc7kL7VURJwCXAOcnplbI+IqqglZJKmIzf5SC9XTo34K+PN6djqAFwJfGN5eSZotTP5SO/0GsD0zPwtQT5t6GvClYe6UpNnB5C+102uBL3Z9/gPg3sz84ZD2R9IsYvKX2mk/YA+Aeo71/YB/jYjXRcTuQ90zSTOeyV9qpw8DZ0fEZ4DvA/cCL6O6+n9qqHsmacaLzBz2PkiSpAHyyl+SpBFj8pckacSY/CVJGjEmf0mSRozJX5KkEWPylyRpxJj8JUkaMSZ/SZJGjMlfkqQR8/8DLCBxuLSm6QkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 527.04x399.6 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = a\n",
    "y = nu\n",
    "z = hp_match\n",
    "\n",
    "\n",
    "xstep = (max(x)-min(x))/21/2 #调整刻度，符合科学性\n",
    "ystep = (max(y)-min(y))/21/2\n",
    "\n",
    "\n",
    "plt.figure(figsize=(7.32,5.55))\n",
    "plt.hist2d(x,y, bins=[21,21], weights = z, cmap=plt.cm.jet)\n",
    "plt.xlabel(\"$a$\")\n",
    "plt.ylabel(\"$\\\\nu$\")\n",
    "plt.xlim([0.50,0.70])\n",
    "plt.ylim([0.01, 0.04])\n",
    "plt.xticks(np.linspace(0.5+xstep, 0.7-xstep,5),[\"0.50\",\"0.55\", \"0.60\", \"0.65\", \"0.70\"])\n",
    "plt.yticks(np.linspace(0.01+ystep, 0.04-ystep,7),[\"0.010\", \"0.015\", \"0.020\", \"0.025\", \"0.030\", \"0.035\", \"0.040\"])\n",
    "\n",
    "#add a colorbar\n",
    "cbar =plt.colorbar()\n",
    "cbar.ax.text(3.5, 0.45, 'match', rotation=90)\n",
    "cbar.set_ticks([min(z), 0.3, 0.5, 0.7,max(z)])\n",
    "cbar.set_ticklabels([round(min(z),2), \"0.30\", \"0.50\", \"0.70\",round(max(z),2)])\n",
    "\n",
    "#plt.grid(linestyle = \"dotted\", color = \"#d3d3d3\" , which=\"both\")\n",
    "plt.tight_layout()\n",
    "plt.savefig('hp_match.pdf', format = 'pdf', dpi = 300)     #保存图像\n",
    "plt.show()"
   ]
  }
 ],
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   "hotkeys": {
    "equation": "Ctrl-E",
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  "toc": {
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   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
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   "toc_position": {},
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  "varInspector": {
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   "kernels_config": {
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     "delete_cmd_postfix": "",
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   "types_to_exclude": [
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