{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Modeling of the thickness of the sensor\n", "\n", "In this notebook we will re-use the experiment done at ID28 and previously calibrated and model in 3D the detector.\n", "\n", "This detector is a Pilatus 1M with a 450µm thick silicon sensor. Let's first have a look at the absorption coefficients of this sensor material: https://physics.nist.gov/PhysRefData/XrayMassCoef/ElemTab/z14.html\n", "\n", "First we retieve the results of the previous step, then calculate the absorption efficiency:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "# use `widget` instead of `inline` for better user-exeperience. `inline` allows to store plots into notebooks." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "wavelength: 6.968e-11m,\t dist: 2.845e-01m,\t poni1: 8.865e-02m,\t poni2: 8.931e-02m,\t energy: 17.793keV\n" ] } ], "source": [ "import time\n", "start_time = time.perf_counter()\n", "from matplotlib.pyplot import subplots\n", "import numpy\n", "import fabio, pyFAI, pyFAI.units, pyFAI.detectors, pyFAI.azimuthalIntegrator\n", "import json\n", "with open(\"id28.json\") as f:\n", " calib = json.load(f)\n", "\n", "thickness = 450e-6\n", "wavelength = calib[\"wavelength\"]\n", "dist = calib[\"param\"][calib['param_names'].index(\"dist\")]\n", "poni1 = calib[\"param\"][calib['param_names'].index(\"poni1\")]\n", "poni2 = calib[\"param\"][calib['param_names'].index(\"poni2\")]\n", "energy = pyFAI.units.hc/(wavelength*1e10)\n", "print(\"wavelength: %.3em,\\t dist: %.3em,\\t poni1: %.3em,\\t poni2: %.3em,\\t energy: %.3fkeV\" % \n", " (wavelength, dist, poni1, poni2, energy))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Absorption coeficient at 17.8 keV" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "µ = 1537.024174 m^-1 hence absorption efficiency for 450µm: 49.9 %\n" ] } ], "source": [ "# density from https://en.wikipedia.org/wiki/Silicon\n", "rho = 2.3290 # g/cm^3\n", "\n", "#Absorption from https://physics.nist.gov/PhysRefData/XrayMassCoef/ElemTab/z14.html\n", "# Nota: enegies are in MeV !\n", "Si_abs = \"\"\"\n", " 2.00000E-03 2.777E+03 2.669E+03 \n", " 3.00000E-03 9.784E+02 9.516E+02 \n", " 4.00000E-03 4.529E+02 4.427E+02 \n", " 5.00000E-03 2.450E+02 2.400E+02 \n", " 6.00000E-03 1.470E+02 1.439E+02 \n", " 8.00000E-03 6.468E+01 6.313E+01 \n", " 1.00000E-02 3.389E+01 3.289E+01 \n", " 1.50000E-02 1.034E+01 9.794E+00 \n", " 2.00000E-02 4.464E+00 4.076E+00 \n", " 3.00000E-02 1.436E+00 1.164E+00 \n", " 4.00000E-02 7.012E-01 4.782E-01 \n", " 5.00000E-02 4.385E-01 2.430E-01 \n", " 6.00000E-02 3.207E-01 1.434E-01 \n", " 8.00000E-02 2.228E-01 6.896E-02 \n", " 1.00000E-01 1.835E-01 4.513E-02 \n", " 1.50000E-01 1.448E-01 3.086E-02 \n", " 2.00000E-01 1.275E-01 2.905E-02 \n", " 3.00000E-01 1.082E-01 2.932E-02 \n", " 4.00000E-01 9.614E-02 2.968E-02 \n", " 5.00000E-01 8.748E-02 2.971E-02 \n", " 6.00000E-01 8.077E-02 2.951E-02 \n", " 8.00000E-01 7.082E-02 2.875E-02 \n", " 1.00000E+00 6.361E-02 2.778E-02 \n", " 1.25000E+00 5.688E-02 2.652E-02 \n", " 1.50000E+00 5.183E-02 2.535E-02 \n", " 2.00000E+00 4.480E-02 2.345E-02 \n", " 3.00000E+00 3.678E-02 2.101E-02 \n", " 4.00000E+00 3.240E-02 1.963E-02 \n", " 5.00000E+00 2.967E-02 1.878E-02 \n", " 6.00000E+00 2.788E-02 1.827E-02 \n", " 8.00000E+00 2.574E-02 1.773E-02 \n", " 1.00000E+01 2.462E-02 1.753E-02 \n", " 1.50000E+01 2.352E-02 1.746E-02 \n", " 2.00000E+01 2.338E-02 1.757E-02 \"\"\"\n", "data = numpy.array([[float(i) for i in line.split()] for line in Si_abs.split(\"\\n\") if line])\n", "energy_tab, mu_over_rho, mu_en_over_rho = data.T\n", "abs_18 = numpy.interp(energy, energy_tab*1e3, mu_en_over_rho) \n", "mu = abs_18*rho*1e+2\n", "eff = 1.0-numpy.exp(-mu*thickness)\n", "\n", "print(\"µ = %f m^-1 hence absorption efficiency for 450µm: %.1f %%\"%(mu, eff*100))\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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jx9C/f3/Y2dlBIpFgz549z93n6NGjaNu2LeRyOVxcXPDjjz9We51ERESkPUQNN/n5+XB3d8fy5cvL1f7WrVvo27cvunfvjri4OEybNg1jxozBwYMHq7lSIiIi0haiTpz58ssv4+WXXy53+1WrVsHZ2RnffvstAKBFixY4ceIEFi1ahICAgOoqs9xupD+EjlQKJwtDsUshIiKqt7Sqz01kZCT8/f011gUEBCAyMvKZ+xQWFiI3N1djqQ4HL6Wi75ITmLo1DiVKVbWcg4iIiJ5Pq8JNamoqrK2tNdZZW1sjNzcXjx8/LnWf0NBQmJqaqhcHB4dqqa21vSn0dKQ4l5yNFUdvVss5iIiI6Pm0KtxUxuzZs5GTk6NekpOTq+U8dmb6+HRAKwDAkojruHAnp1rOQ0RERGXTqnBjY2ODtLQ0jXVpaWkwMTGBvr5+qfvI5XKYmJhoLNVlgIcd+ra2RYlKwLStsSgoVlbbuYiIiKh0WhVu/Pz8EBERobHu8OHD8PPzE6kiTRKJBJ8NbAVLYzluZuTjy/CrYpdERERU74gabvLy8hAXF4e4uDgAT171jouLQ1JSEoAnj5QCAwPV7cePH4+EhATMnDkTV69exYoVK7Bt2zZMnz5djPJL1cBQD1+91gYAsO6vRPx1I1PkioiIiOoXUcPN2bNn4enpCU9PTwBASEgIPD09MW/ePADAvXv31EEHAJydnbFv3z4cPnwY7u7u+Pbbb/H999/XitfA/6t7cyu84dsYADBj+znkPC4WuSIiIqL6QyIIgiB2ETUpNzcXpqamyMnJqdb+N/mFJeiz5Dhu33+EgR52WDzMs9rORUREVNdV5Ptbq/rcaBNDuQ4Wvu4BqQTYE3cXv5y7K3ZJRERE9QLDTTXycmyASd1dAAAf7L6Au9mlj8VDREREVYfhpppN7uEK90amyC0owYzt56BS1aungERERDWO4aaa6cqkWDTUA/q6Mpy8eR9r/7oldklERER1GsNNDWhiaYQP+rUAAHwVHo+rqdUzvxUREREx3NSYN3wao4ebFYqUKkzbEsfRi4mIiKoJw00NkUgk+PK1NrAw0sPV1If4Kjxe7JKIiIjqJIabGmRhJMfXr7kDANb+dQtH49NFroiIiKjuYbipYd3drBDk5wgAmLH9PO7nFYpcERERUd3CcCOC2X1aoJm1ETLzCvH+zvOoZ4NEExERVSuGGxEodGX4bpgn9GRS/H4lHRtPJz1/JyIiIioXhhuRtLA1wfsvuwEAPvvtMq6nPRS5IiIiorqB4UZEwR2c0KWZJQpLVJj8cyxfDyciIqoCDDcikkol+GZIGzQ0fPJ6+BcHropdEhERkdZjuBGZlbEC3wx58nr4jycTEXElTeSKiIiItBvDTS3Q3c0Kozs6AwDe23Ee6bkFIldERESkvRhuaon3X26OlrYmyMovQsg2zh5ORERUWQw3tYRcR4Ylwz2hryvDiRuZWHM8QeySiIiItBLDTS3iYmWE+f1bAgC+ORiP2KQHIldERESkfRhuapmh7RzQt40tSlQCpmyJRW5BsdglERERaRWGm1pGIpEgdHBrNGqgj+Ssx5i96wKnZyAiIqoAhptayEShi6XDPaEjlWDf+XvYciZZ7JKIiIi0BsNNLeXZuAHeC2gOAPjol0u4xukZiIiIyoXhphYb27mJenqGSZtj8LiI0zMQERE9D8NNLSaVSrDwdXdYGstxLS0PH/96SeySiIiIaj2Gm1rOwkiOxUM9IJEAW84kY29citglERER1WoMN1qgo4sFJnd3AQDM2XUBCRl5IldERERUezHcaImp/s3g62yO/CIlJm6ORUEx+98QERGVhuFGS8ikEiwZ7omGhnq4ci8Xn/52WeySiIiIaiWGGy1ibaLAor/732w6nYTfzt8VuyQiIqJah+FGy3RpZol3ujUFAMzaeQG3MvNFroiIiKh2ET3cLF++HE5OTlAoFPD19UVUVNQz2xYXF+OTTz5B06ZNoVAo4O7ujvDw8BqstnaY7t8MPk7myCsswcRNMex/Q0RE9B+ihputW7ciJCQE8+fPR0xMDNzd3REQEID09PRS23/wwQdYvXo1li5disuXL2P8+PEYNGgQYmNja7hycenIpOr+N5fv5eLjX9n/hoiI6B8SQcRZGX19fdGuXTssW7YMAKBSqeDg4IDJkydj1qxZT7W3s7PD3LlzMXHiRPW6V199Ffr6+ti4cWO5zpmbmwtTU1Pk5OTAxMSkaj6ISI5fz0Dg2igIArBoqDsGeTYSuyQiIqJqUZHvb9Hu3BQVFSE6Ohr+/v7/FiOVwt/fH5GRkaXuU1hYCIVCobFOX18fJ06cqNZaa6vOrpaY8j9XAMCcXRdxnfNPERERiRduMjMzoVQqYW1trbHe2toaqamppe4TEBCAhQsX4vr161CpVDh8+DB27dqFe/fuPfM8hYWFyM3N1Vjqkik9XNHJxQKPi5V4Z1MMHhWViF0SERGRqETvUFwR3333HVxdXeHm5gY9PT1MmjQJwcHBkEqf/TFCQ0NhamqqXhwcHGqw4uonk0qweJgHrIzluJ6eh7m7L0LEJ41ERESiEy3cWFhYQCaTIS0tTWN9WloabGxsSt3H0tISe/bsQX5+Pm7fvo2rV6/CyMgITZo0eeZ5Zs+ejZycHPWSnJxcpZ+jNrAwkmPZG20hk0qwOzYFm6OSxC6JiIhINKKFGz09PXh5eSEiIkK9TqVSISIiAn5+fmXuq1AoYG9vj5KSEuzcuRMDBgx4Zlu5XA4TExONpS7ycTbHzIDmAICPf7mM83eyxS2IiIhIJKI+lgoJCUFYWBjWr1+PK1euYMKECcjPz0dwcDAAIDAwELNnz1a3P336NHbt2oWEhAQcP34cvXv3hkqlwsyZM8X6CLXKuC5N0KulNYqUKkzYGIMH+UVil0RERFTjdMQ8+dChQ5GRkYF58+YhNTUVHh4eCA8PV3cyTkpK0uhPU1BQgA8++AAJCQkwMjJCnz598NNPP8HMzEykT1C7SCQSfD3EHfHLTuD2/UeYvi0Oa4PaQSqViF0aERFRjRF1nBsx1KVxbp7l8t1cDFrxFwpLVHi3ZzNM7uEqdklEREQvRCvGuaHq09LOBJ8ObAUAWPj7NRy/niFyRURERDWH4aaOet3bAcPaOUAQgCk/xyIl+7HYJREREdUIhps67KNXXkJre1M8eFSMCRujOcEmERHVCww3dZhCV4aVb7aFmYEuzt/Jwce/XhK7JCIiomrHcFPHNWpggCXDPCGRAD9HJWPrGQ7wR0REdRvDTT3QpZkl3u3ZDADw4d5LuHAnR+SKiIiIqg/DTT3xTjcX+LewQlGJCuM3RiOLA/wREVEdxXBTT0ilEnz7ugecGhogJfsxJv8cgxKlSuyyiIiIqhzDTT1iqq+L1SO9YaAnw1837uOrg/Fil0RERFTlGG7qmeY2xvj6NXcAwJpjCfj13F2RKyIiIqpaDDf1UN82tni7axMAwMwd53E1NVfkioiIiKoOw009NTPADZ1dLfC4WIlxG6KR86hY7JKIiIiqBMNNPSWTSrBkmCcaNdBHUtYjTN4SC6WqXs2hSkREdRTDTT3WwFAPq0d6QaErxbFrGfjq4FWxSyIiInphDDf13Et2puoOxqv/TMAv7GBMRERajuGG0N/dDuO7NgUAzNxxDhdTOIIxERFpL4YbAgC8F9AcXZtZoqBYhbd/isb9vEKxSyIiIqoUhhsC8G8H439GMJ64OQbFHMGYiIi0EMMNqZka6CIs0BtGch2cSsjCJ79eFrskIiKiCmO4IQ2u1sZYPNQDEgnw06nb2HT6ttglERERVQjDDT3Fv6U1ZvRqDgCYv/cSTifcF7kiIiKi8mO4oVK9060p+rWxRYlKwIRNMUjOeiR2SUREROXCcEOlkkgk+Po1d7SyN0FWfhHGbjiL/MISscsiIiJ6LoYbeiZ9PRnWjPSGhZEcV1MfImRbHFScooGIiGo5hhsqk52ZPlaPbAs9mRQHL6Vh4eFrYpdERERUJoYbei4vR3OEDm4NAFh25Ab2xqWIXBEREdGzMdxQubzq1Qhvd20CAHhvx3nEJj0QuSIiIqLSMdxQuc0McIN/CysUlagw7qdo3M1+LHZJRERET2G4oXKTSSVYPMwTbjbGyHhYiLEbzuJREd+gIiKi2oXhhirESK6DsEBvNDTUw6W7uZi2hW9QERFR7cJwQxXmYG6ANYFe0JNJcehyGr48eFXskoiIiNQYbqhSvBzN8dVrbQAAq/9MwLYzySJXRERE9ITo4Wb58uVwcnKCQqGAr68voqKiymy/ePFiNG/eHPr6+nBwcMD06dNRUFBQQ9XSfw30tMeUHq4AgDm7LyDyJuegIiIi8YkabrZu3YqQkBDMnz8fMTExcHd3R0BAANLT00ttv3nzZsyaNQvz58/HlStX8MMPP2Dr1q2YM2dODVdO/5ju76qeg2r8xmgkZOSJXRIREdVzooabhQsXYuzYsQgODkbLli2xatUqGBgYYO3ataW2P3nyJDp27Ig33ngDTk5O6NWrF4YPH/7cuz1UfSQSCb4Z4g4PBzPkPC7G6B/P4EF+kdhlERFRPSZauCkqKkJ0dDT8/f3/LUYqhb+/PyIjI0vdp0OHDoiOjlaHmYSEBOzfvx99+vSpkZqpdApdGcICvWFvpo/E+4/w9k/RKCxRil0WERHVU6KFm8zMTCiVSlhbW2ust7a2Rmpqaqn7vPHGG/jkk0/QqVMn6OrqomnTpujWrVuZj6UKCwuRm5ursVDVszSWY11wOxjLdRCVmIVZOy9AEPiKOBER1TzROxRXxNGjR7FgwQKsWLECMTEx2LVrF/bt24dPP/30mfuEhobC1NRUvTg4ONRgxfVLM2tjrHizLWRSCXbHpuC7iOtil0RERPWQaOHGwsICMpkMaWlpGuvT0tJgY2NT6j4ffvghRo4ciTFjxqB169YYNGgQFixYgNDQUKhUqlL3mT17NnJyctRLcjJfWa5OnV0t8dnAVgCAxb9fx+7YOyJXRERE9Y1o4UZPTw9eXl6IiIhQr1OpVIiIiICfn1+p+zx69AhSqWbJMpkMAJ75CEQul8PExERjoeo13KcxxndtCgCYueM8TiXwFXEiIqo5oj6WCgkJQVhYGNavX48rV65gwoQJyM/PR3BwMAAgMDAQs2fPVrfv378/Vq5ciS1btuDWrVs4fPgwPvzwQ/Tv318dcqh2mBnQHH1a26BYKWDchrO4kf5Q7JKIiKie0BHz5EOHDkVGRgbmzZuH1NRUeHh4IDw8XN3JOCkpSeNOzQcffACJRIIPPvgAKSkpsLS0RP/+/fH555+L9RHoGaRSCRa+7oHUnFOIScrGqHVnsOudDrAyVohdGhER1XESoZ690pKbmwtTU1Pk5OTwEVUNyMovwuAVfyHx/iO0tjfF1rfbw0BP1ExNRERaqCLf31r1thRpH3NDPfwY7IMGBrq4kJKDKT/HQslZxImIqBox3FC1c7IwxPdB7SDXkeL3K+n46JdLHAOHiIiqDcMN1QgvxwZYPNQDEgnw06nbWPVngtglERFRHcVwQzXm5da2+LBvSwDAl+FXsSc2ReSKiIioLmK4oRo1upMzxnRyBgC8t+Mc/rqRKXJFRERU1zDcUI2b06cF+rWxRbFSwPifonHlHuf7IiKiqsNwQzVOKpXg29fd4etsjoeFJRi1Lgop2Y/FLouIiOoIhhsShVxHhjWB3mhmbYS03EIErY1C9qMiscsiIqI6gOGGRGOqr4sfg31ga6rAjfQ8jP7xDB4XKcUui4iItBzDDYnKzkwf60f7wEShg5ikbEz+ORYlytJneCciIioPhhsSXTNrY6wd9c8gf2n4cO9FDvJHRESVxnBDtYK3kzmWDPeEVAL8HJWMRb9fF7skIiLSUgw3VGsEvGSDTwe2AgAsibiODZGJ4hZERERaieGGapURvo6Y7t8MADD/l0v49dxdkSsiIiJtw3BDtc6UHi4I9HOEIAAh2+Jw/HqG2CUREZEWYbihWkcikWB+/5fQ9+9RjN/+KRrnkrPFLouIiLQEww3VSjKpBAtfd0cnFws8KlJi1Loo3EjPE7ssIiLSAgw3VGvJdWRYNdILbRqZ4sGjYgT+cJrTNBAR0XMx3FCtZiTXwbpR7dDU0hB3cwow8ofTuJ9XKHZZRERUizHcUK3X0EiOn97yhZ2pAgkZ+QhaF4WHBcVil0VERLUUww1pBTszffw0xhcNDfVwMSUXY9afRUEx56EiIqKnMdyQ1mhqaYT1o31gLNfB6VtZmLQ5BsWch4qIiP4fhhvSKq3sTfF9kPff81ClY8b2c1CpOA8VERH9i+GGtI5vk4ZY9aYXdKQS7I27y4k2iYhIA8MNaaXublZYNNQDEgmw6XQSvjhwlQGHiIgAMNyQFuvvbofQQa0BAKuPJWD5kRsiV0RERLWBTnkaeXp6QiKRlOuAMTExL1QQUUUM82mMvMISfLbvCr45dA2Gch0Ed3QWuywiIhJRucLNwIEDq7kMosob07kJHhaU4LuI6/j418sw0JNhaLvGYpdFREQikQj1rKNCbm4uTE1NkZOTAxMTE7HLoSoiCAIW7L+CsOO3IJEAi4d6YICHvdhlERFRFanI9zf73FCdIJFIMKdPC7zZvjEEAQjZdg4HL6WKXRYREYmgwuFGqVTim2++gY+PD2xsbGBubq6xEIlFIpHgk1da4dW2jaBUCZi8ORZ/XssQuywiIqphFQ43H3/8MRYuXIihQ4ciJycHISEhGDx4MKRSKT766KNqKJGo/KRSCb58tTX6trZFkVKFcRvO4uTNTLHLIiKiGlThcLNp0yaEhYXh3XffhY6ODoYPH47vv/8e8+bNw6lTpypVxPLly+Hk5ASFQgFfX19ERUU9s223bt0gkUieWvr27Vupc1PdoyOTYtFQD/i3sEJhiQpv/XgWZxKzxC6LiIhqSIXDTWpqKlq3fjK2iJGREXJycgAA/fr1w759+ypcwNatWxESEoL58+cjJiYG7u7uCAgIQHp6eqntd+3ahXv37qmXixcvQiaTYciQIRU+N9VdejpSLB/RFl2aWeJxsRLB684gNumB2GUREVENqHC4adSoEe7duwcAaNq0KQ4dOgQAOHPmDORyeYULWLhwIcaOHYvg4GC0bNkSq1atgoGBAdauXVtqe3Nzc9jY2KiXw4cPw8DAgOGGniLXkWHNSC/4NWmIvMISBK6NwoU7OWKXRURE1azC4WbQoEGIiIgAAEyePBkffvghXF1dERgYiNGjR1foWEVFRYiOjoa/v/+/BUml8Pf3R2RkZLmO8cMPP2DYsGEwNDQsdXthYSFyc3M1Fqo/FLoy/DDKG+2cGuBhQQlGrj2Ny3f5/wARUV1WrkH8/uuLL75Q/3no0KFo3LgxIiMj4erqiv79+1foWJmZmVAqlbC2ttZYb21tjatXrz53/6ioKFy8eBE//PDDM9uEhobi448/rlBdVLcY6Olg7ah2GPlDFOKSs/HmD6fx89j2aG5jLHZpRERUDV54nBs/Pz+EhIRUONhUhR9++AGtW7eGj4/PM9vMnj0bOTk56iU5ObkGK6Tawlihi/WjfdCmkSmy8ovwRtgpXE97KHZZRERUDSp85wYArl+/jiNHjiA9PR0qlUpj27x588p9HAsLC8hkMqSlpWmsT0tLg42NTZn75ufnY8uWLfjkk0/KbCeXyyvVF4jqHlN9Xfw02hdvfH8Kl+7mYnjYaWwZ1x4uVkZil0ZERFWowuEmLCwMEyZMgIWFBWxsbDQm1JRIJBUKN3p6evDy8kJERIR6/iqVSoWIiAhMmjSpzH23b9+OwsJCvPnmmxX9CFSPmRroYuNbvnjj+9O4ci8Xb4SdwpZx7dHEkgGHiKiuqPDcUo6OjnjnnXfw/vvvV0kBW7duRVBQEFavXg0fHx8sXrwY27Ztw9WrV2FtbY3AwEDY29sjNDRUY7/OnTvD3t4eW7ZsqdD5OLcUAVA/mrqa+hDWJnJsGecHZ4vSO6UTEZH4KvL9XeE7Nw8ePKjS166HDh2KjIwMzJs3D6mpqfDw8EB4eLi6k3FSUhKkUs2uQfHx8Thx4oT6NXSiijI31MOmMb4YHnYK19LyMGxNJH4eyzs4RER1QYXv3Lz11lto164dxo8fX101VSveuaH/yswrxBt/BxwrYzkfURER1VLVeufGxcUFH374IU6dOoXWrVtDV1dXY/uUKVMqekgi0VgYybF5bHuMCDuN+LSHGLbmFH4e1x5NGXCIiLRWhe/cODs7P/tgEgkSEhJeuKjqxDs3VJr7eYV44++AY2UsZ8AhIqplKvL9XeFwo+0YbuhZ/htwLI3l2DzGF67WHOiPiKg2qMj39wsP4kdUVzQ0kmPzWF+42Rgj42Ehhq05hfhUDvRHRKRtKnznJiQkpPQDSSRQKBRwcXHBgAEDYG5uXiUFVjXeuaHneZBfhBHfn8ble7kwN9TDxrd80dKO/68QEYmpWh9Lde/eHTExMVAqlWjevDkA4Nq1a5DJZHBzc0N8fDwkEglOnDiBli1bVv5TVBOGGyqP7EdFGPlDFC6k5MDs74H/Wtmbil0WEVG9Va2PpQYMGAB/f3/cvXsX0dHRiI6Oxp07d9CzZ08MHz4cKSkp6NKlC6ZPn17pD0AkNjMDPWwc4wsPBzNkPyrGG2GnEJecLXZZRERUDhW+c2Nvb4/Dhw8/dVfm0qVL6NWrF1JSUhATE4NevXohMzOzSoutCrxzQxXxsKAYo9adQfTtBzCS6+DH4Hbwdqqdj1yJiOqyar1zk5OTg/T09KfWZ2RkIDc3FwBgZmaGoqKiih6aqNb5ZzZxX2dz5BWWIHBtFE7erH2hnYiI/lWpx1KjR4/G7t27cefOHdy5cwe7d+/GW2+9pZ78MioqCs2aNavqWolE8eSOjQ86u1rgUZESwevO4M9rGWKXRUREz1Dhx1J5eXmYPn06NmzYgJKSEgCAjo4OgoKCsGjRIhgaGiIuLg4A4OHhUdX1vjA+lqLKKihWYtLmGPx+JR16MimWj2iLni2txS6LiKheqJFB/PLy8tSjETdp0gRGRtoxmivDDb2IohIVpm6JxYGLqdCRSrBoqAf6u9uJXRYRUZ3HEYrLwHBDL6pEqcKM7eewJ+4uJBLgy8Ft8Ho7B7HLIiKq06p84szBgwfjxx9/hImJCQYPHlxm2127dpW/UiItpCOTYuHrHtDX08HPUUmYufM88otKENzx2fOuERFRzSlXuDE1NYVEIlH/mai+k0olWDCoFQz1ZPj+xC18/OtlPCpSYmJ3F7FLIyKq9/hYiugFCIKAxb9fx3cR1wEAE7o1xcyA5upfBoiIqGpU6zg3jx8/xqNHj9Q/3759G4sXL8ahQ4cqXimRlpNIJJjesxnm9HEDAKw8ehMf7LkIlape/c5ARFSrVGqcmw0bNgAAsrOz4ePjg2+//RYDBgzAypUrq7xAIm0wrktThA5uDYkE2HQ6CdO3xaFYqRK7LCKieqnC4SYmJgadO3cGAOzYsQM2Nja4ffs2NmzYgCVLllR5gUTaYrhPYywZ5gkdqQR74+5i/E/RKChWil0WEVG9U+Fw8+jRIxgbGwMADh06hMGDB0MqlaJ9+/a4fft2lRdIpE36u9shLNAbch0pIq6mI2htFB4WFItdFhFRvVLhcOPi4oI9e/YgOTkZBw8eRK9evQAA6enp7KBLBKC7mxU2jPaBkVwHp29lYXjYKWTmFYpdFhFRvVHhcDNv3jzMmDEDTk5O8PX1hZ+fH4And3E8PT2rvEAibeTbpCG2jGuPhoZ6uJiSi9dXReLOg0fP35GIiF5YpV4FT01Nxb179+Du7g6p9Ek+ioqKgomJCdzc3Kq8yKrEV8GpJiVk5GHkD1FIyX4MW1MFfnrLBy5WxmKXRUSkdTj9QhkYbqim3ct5jJE/ROFGeh4aGOhiXbAPPBzMxC6LiEirVOs4N0RUMbam+tj+th/cHczw4FExhq85haPx6WKXRURUZzHcENWABoZ62DzGF51dLfC4WIkx689iT2yK2GUREdVJDDdENcRQroMfgtrhFXc7lKgETNsahx9O3BK7LCKiOofhhqgG6elIsXioB4I7OgEAPv3tMkIPXEE96/pGRFStyjUr+C+//FLuA77yyiuVLoaoPpBKJZjXryUsjeX4Kjweq/9MQEZuIb58rQ10Zfx9g4joRZXrbal/Xvd+7sEkEiiVtXu4eb4tRbXJtrPJmL3rApQqAZ1dLbDyTS8Yycv1OwcRUb1S5W9LqVSqci21PdgQ1Tavezvg+0Bv6OvKcPx6JoavOYWMhxzNmIjoRfAeOJHIurtZ4edx7WFuqIcLKTl4bdVJJGbmi10WEZHWqlS4yc/Px/79+7Fq1SosWbJEY6mo5cuXw8nJCQqFAr6+voiKiiqzfXZ2NiZOnAhbW1vI5XI0a9YM+/fvr8zHIKo1PBzMsHNCBziY6+P2/UcYvPIkYpMeiF0WEZFWqvAIxbGxsejTpw8ePXqE/Px8mJubIzMzEwYGBrCyskJCQkK5j7V161YEBgZi1apV8PX1xeLFi7F9+3bEx8fDysrqqfZFRUXo2LEjrKysMGfOHNjb2+P27dswMzODu7t7uc7JPjdUm6U/LMBbP57FhZQcKHSlWDLME71eshG7LCIi0VXr9AvdunVDs2bNsGrVKpiamuLcuXPQ1dXFm2++ialTp2Lw4MHlPpavry/atWuHZcuWAXjSt8fBwQGTJ0/GrFmznmq/atUqfP3117h69Sp0dXUrUrYaww3VdvmFJZi0OQZH4jMglQAfvfISAv2cxC6LiEhU1Tr9QlxcHN59911IpVLIZDIUFhbCwcEBX331FebMmVPu4xQVFSE6Ohr+/v7/FiOVwt/fH5GRkaXu88svv8DPzw8TJ06EtbU1WrVqhQULFpTZkbmwsBC5ubkaC1FtZijXQVigN4b7OEAlAPP2XkLogStQqTgWDhFReVQ43Ojq6qpfDbeyskJSUhIAwNTUFMnJyeU+TmZmJpRKJaytrTXWW1tbIzU1tdR9EhISsGPHDiiVSuzfvx8ffvghvv32W3z22WfPPE9oaChMTU3Vi4ODQ7lrJBKLjkyKBYNaY0avZgCA1X8mYPKWWBQU841EIqLnqXC48fT0xJkzZwAAXbt2xbx587Bp0yZMmzYNrVq1qvIC/0ulUsHKygpr1qyBl5cXhg4dirlz52LVqlXP3Gf27NnIyclRLxUJYERikkgkmPQ/Vyx83R26Mgn2nb+HN78/jaz8IrFLIyKq1SocbhYsWABbW1sAwOeff44GDRpgwoQJyMjIwJo1a8p9HAsLC8hkMqSlpWmsT0tLg41N6R0obW1t0axZM8hkMvW6Fi1aIDU1FUVFpf+DL5fLYWJiorEQaZPBbRthfbAPjBU6OHv7AV5dyVfFiYjKUuFw4+3tje7duwN48lgqPDwcubm5iI6OLvcbSwCgp6cHLy8vREREqNepVCpERETAz8+v1H06duyIGzduQKVSqdddu3YNtra20NPTq+hHIdIaHVwssGtCB9ib6eNWZj4GrfgL0bezxC6LiKhWEnUQv5CQEISFhWH9+vW4cuUKJkyYgPz8fAQHBwMAAgMDMXv2bHX7CRMmICsrC1OnTsW1a9ewb98+LFiwABMnThTrIxDVGFdrY+ye2AFtGpniwaNiDA87jV/O3RW7LCKiWqfCk9g4OztDIpE8c3tFxrkZOnQoMjIyMG/ePKSmpsLDwwPh4eHqTsZJSUka81o5ODjg4MGDmD59Otq0aQN7e3tMnToV77//fkU/BpFWsjJWYMu49pi6JQ6HL6dhys+xuJ2Zj0n/cynz7yURUX1S4XFuvvvuO42fi4uLERsbi/DwcLz33nuljk9Tm3CcG6oLlCoBXxy4grDjtwAAgz3tEfpqa8h1ZM/Zk4hIO1Xk+7vCd26mTp1a6vrly5fj7NmzFT0cEVWCTCrB3L4t4WRhiHl7L2FXbAruZD/Gqje9YG7I/mdEVL9VWZ+bl19+GTt37qyqwxFROYzwdcS6Ue1gLNdB1K0sDFrxF26k54ldFhGRqKos3OzYsQPm5uZVdTgiKqcuzSyx850OaNTgyaSbg1b8hePXM8Qui4hINBV+LOXp6anRcVEQBKSmpiIjIwMrVqyo0uKIqHyaWRtj78SOePunaJy9/QCj1p3BR6+8hJHtHcUujYioxlU43AwcOFDjZ6lUCktLS3Tr1g1ubm5VVRcRVVBDIzk2jfXF7J0XsCs2BR/uuYgbaQ/xYb+W0JGJOuoDEVGNqvDbUtqOb0tRXScIAlYcvYmvD8YDADq5WGD5G21haqArcmVERJVXke/vcoWbisykXdsDA8MN1RfhF1MxfWscHhcr4WxhiO+DvNHU0kjssoiIKqXKw41UKi33AGFKZe2etZjhhuqTS3dzMG5DNFKyH8NYoYNlb7RF12aWYpdFRFRhVT7OzZEjR9R/TkxMxKxZszBq1Cj1HFCRkZFYv349QkNDX6BsIqpqL9mZYu+kjhj/d0fj4HVRmNOnBd7qVPZI40RE2qzCfW569OiBMWPGYPjw4RrrN2/ejDVr1uDo0aNVWV+V450bqo8KS5T4YPdFbI++AwB4tW0jfD6oFRS6HNGYiLRDRb6/K/wKRWRkJLy9vZ9a7+3tjaioqIoejohqgFxHhq9ea4MP+7WEVALsjLmDYWtOIT23QOzSiIiqXIXDjYODA8LCwp5a//3338PBwaFKiiKiqieRSPBWJ2dsGO0LU31dxCVno/+yE4hLzha7NCKiKlXhx1L79+/Hq6++ChcXF/j6+gIAoqKicP36dezcuRN9+vSplkKrCh9LEQGJmfkYu+EsrqfnQU9His8GtsLr3vzlhIhqr2p9LNWnTx9cu3YN/fv3R1ZWFrKystC/f39cu3at1gcbInrCycIQuyd2RM+W1igqUWHmjvP46JdLKFaqxC6NiOiFcRA/onpMpRKw5I/rWPz7dQCAr7M5lo9oCwsjuciVERFpqvJxbs6fP49WrVpBKpXi/PnzZbZt06ZNxaqtYQw3RE87dCkVIdvOIa+wBHamCqwe6Y3WjUzFLouISK1aBvFLTU2FlZWVekC/0naTSCQcxI9IS91If4hxG6KRkJkPPR0pPh/YCkPYD4eIaokqH8Tv1q1bsLS0VP+ZiOoeFytj7JnUESFb4/D7lXS8t+M8zt3Jxrx+L0FPhxNvEpH2YJ8bItKgUglYduQGFv1+DYIAeDY2w8oRXrAxVYhdGhHVY9X6ttT69euxb98+9c8zZ86EmZkZOnTogNu3b1e8WiKqVaRSCab0cMXaoHYwUeggNikb/ZaewKmE+2KXRkRULhUONwsWLIC+vj6AJ6MVL1u2DF999RUsLCwwffr0Ki+QiMTR3c0Kv07uBDcbY2TmFWLE96cRdiyh1P52RES1SYXDTXJyMlxcXAAAe/bswWuvvYZx48YhNDQUx48fr/ICiUg8jg0NseudDhjkaQ+lSsDn+69g4uYY5BWWiF0aEdEzVTjcGBkZ4f79J7enDx06hJ49ewIAFAoFHj9+XLXVEZHoDPR0sPB1d3w64CXoyiTYfyEVryw7getpD8UujYioVBUONz179sSYMWMwZswYjVGJL126BCcnp6quj4hqAYlEgpF+Ttj6th9sTRVIyMjHK8v+wt64FLFLIyJ6SoXDzfLly+Hn54eMjAzs3LkTDRs2BABER0dj+PDhVV4gEdUebRs3wK+TO6GjS0M8LlZi6pY4fLDnAgpLavf4VkRUv/BVcCKqMKVKwHe/X8OSP24AANo0MsXyN9rCwdxA5MqIqK6q1lfBAeD48eN488030aFDB6SkPLkt/dNPP+HEiROVORwRaRmZVIKQXs2xLrgdzAx0cf5ODvouOY7Dl9PELo2IqOLhZufOnQgICIC+vj5iYmJQWFgIAMjJycGCBQuqvEAiqr26N7fCvimd4e5ghtyCEozdcBYL9l/h7OJEJKoKh5vPPvsMq1atQlhYGHR1ddXrO3bsiJiYmCotjohqP3szfWx/2w/BHZ0AAGuOJWDo6kjczebbk0QkjgqHm/j4eHTp0uWp9aampsjOzq6KmohIy+jpSDG//0tY9WZbGCt0EJOUjT5LjuPI1XSxSyOieqjC4cbGxgY3btx4av2JEyfQpEmTKimKiLRT71a22De5M1rbmyL7UTGCfzyDUD6mIqIaVuFwM3bsWEydOhWnT5+GRCLB3bt3sWnTJsyYMQMTJkyojhqJSIs0bmiAHRP8EOTnCABYfSwBr6+ORHLWI5ErI6L6osLhZtasWXjjjTfQo0cP5OXloUuXLhgzZgzefvttTJ48uVJFLF++HE5OTlAoFPD19UVUVNQz2/7444+QSCQai0LB2YqJahO5jgwfD2iFVW96qSff7LvkOMIvpopdGhHVAxUONxKJBHPnzkVWVhYuXryIU6dOISMjA59++mmlpl/YunUrQkJCMH/+fMTExMDd3R0BAQFIT3/2s3oTExPcu3dPvXA2cqLaqXcrG+yb0hkef79NNX5jNObtvYiCYg76R0TVp1Lj3ACAnp4eWrZsCR8fH+jq6mLhwoVwdnau8HEWLlyIsWPHIjg4GC1btsSqVatgYGCAtWvXPnMfiUQCGxsb9WJtbV3Zj0FE1czB3ADbx/vh7S5P+uRtiLyNgcv/wo10zk1FRNWj3OGmsLAQs2fPhre3Nzp06IA9e/YAANatWwdnZ2csWrQI06dPr9DJi4qKEB0dDX9//38Lkkrh7++PyMjIZ+6Xl5cHR0dHODg4YMCAAbh06VKZdefm5mosRFSzdGVSzO7TAj8Gt0NDQz1cTX2I/kv/wtYzSahng6QTUQ0od7iZN28eVq5cCScnJyQmJmLIkCEYN24cFi1ahIULFyIxMRHvv/9+hU6emZkJpVL51J0Xa2trpKaW/my+efPmWLt2Lfbu3YuNGzdCpVKhQ4cOuHPnTqntQ0NDYWpqql4cHBwqVCMRVZ1uza1wYGpndHKxwONiJd7feQGTf45FzuNisUsjojqk3OFm+/bt2LBhA3bs2IFDhw5BqVSipKQE586dw7BhwyCTyaqzTjU/Pz8EBgbCw8MDXbt2xa5du2BpaYnVq1eX2n727NnIyclRL8nJyTVSJxGVzspEgQ2jffB+bzfoSCX47fw99PnuOM4mZoldGhHVEeUON3fu3IGXlxcAoFWrVpDL5Zg+fTokEkmlT25hYQGZTIa0NM35aNLS0mBjY1OuY+jq6sLT07PUsXcAQC6Xw8TERGMhInFJpRJM6NYU28f7obG5AVKyH+P11ZH47vfrKOGYOET0gsodbpRKJfT09NQ/6+jowMjI6IVOrqenBy8vL0RERKjXqVQqREREwM/Pr9x1XbhwAba2ti9UCxHVPM/GDbBvSicM8rSHSgAW/X4Nw8NO4c4DjolDRJWnU96GgiBg1KhRkMvlAICCggKMHz8ehoaGGu127dpVoQJCQkIQFBQEb29v+Pj4YPHixcjPz0dwcDAAIDAwEPb29ggNDQUAfPLJJ2jfvj1cXFyQnZ2Nr7/+Grdv38aYMWMqdF4iqh2MFbpYNNQDXZpZ4MM9l3Am8QFe/u44PhvYCgM87MUuj4i0ULnDTVBQkMbPb775ZpUUMHToUGRkZGDevHlITU2Fh4cHwsPD1Z2Mk5KSIJX+e4PpwYMHGDt2LFJTU9GgQQN4eXnh5MmTaNmyZZXUQ0TiGOTZCF6NzTF1ayxik7IxdUsc/riajk8HtoKJQvf5ByAi+ptEqGfvYebm5sLU1BQ5OTnsf0NUC5UoVVh25AaW/nEDSpUAezN9LBrqAR9nc7FLIyIRVeT7u9KD+BERVQcdmRTT/Jth29v/djYeuiYSX4ZfRVEJOxsT0fMx3BBRreTl2AD7p3bGEK9GEARg5dGbGLj8L1xL48jGRFQ2hhsiqrWM5Dr4eog7Vr3ZFg0MdHH5Xi76LT2BtSduQaWqV0/UiagCGG6IqNbr3coWB6d1QbfmligqUeGT3y5j5NrTuJtd8cl6iajuY7ghIq1gZaLAulHt8OmAl6DQleKvG/cRsPgYdsXc4fxURKSB4YaItIZEIsFIPyccmNoFno3N8LCgBCHbzmHCxhjczysUuzwiqiUYbohI6zhbGGL72354L6A5dGUShF9KRcDiYzh4qfQJd4mofmG4ISKtpCOTYmJ3F+yZ2BHNrY2RmVeEt3+KxvStcch5xFnGieozhhsi0mov2Znil8kdMaFbU0glwO7YFPRa/CeOxKeLXRoRiYThhoi0nlxHhvd7u2HHhA5oYmmItNxCBK87g5k7ziG3gHdxiOobhhsiqjPaNm6A/VM6461OzpBIgG1n7yBg0TEc5V0conqF4YaI6hSFrgwf9muJreP84NTQAPdyCjDq77s4OY95F4eoPmC4IaI6ycfZHAemdsHojpp3cf64miZ2aURUzRhuiKjO0teTYV7/ltj29pO7OKm5BRj941mEbI3Dg/wiscsjomrCcENEdV47pyd3ccZ2doZUAuyKTUHPRX/iwIV7YpdGRNWA4YaI6gV9PRnm9m2JHRM6wMXKCJl5RZiwKQYTNkYj/WGB2OURURViuCGieqVt4wbYN6UTJv/PBTKpBAcupqLnwmPYdjaZc1QR1REMN0RU78h1ZHi3V3P8MqkjWtmbIOdxMWbuOI+RP0Qh6f4jscsjohfEcENE9dZLdqbY805HzH7ZDXIdKU7cyETA4mMIO5aAEqVK7PKIqJIYboioXtORSfF216YIn9YF7ZuY43GxEp/vv4JBK07iYkqO2OURUSUw3BAR4clM45vHtMcXg1vDRKGDCyk5GLD8LyzYfwWPi5Ril0dEFcBwQ0T0N6lUgmE+jfH7u13Rt40tlCoBa44loNfiPzmFA5EWYbghIvp/rIwVWP5GW/wQ5A07UwWSsx5j1LozmPxzLF8bJ9ICDDdERM/Qo4U1Dod0xVudngz+9+u5u+jx7Z/YdPo2VCq+Nk5UWzHcEBGVwVCugw/7tcQvkzqhtb0pHhaUYO7ui3h11UlcvpsrdnlEVAqGGyKicmhlb4o9EztiXr+WMNSTITYpG/2XncBnv11GfmGJ2OUR0X8w3BARlZNMKsHoTs6IeLcb+rS2gVIl4PsTt+C/8E+EX0zlCMdEtQTDDRFRBdmYKrBihBfWBbeDg7k+7uUUYPzGaAT/eAa37+eLXR5RvcdwQ0RUSd2bW+HQtK6Y1N0FujIJjsZnoOeiY1j8+zUUFHNsHCKxMNwQEb0AfT0ZZgQ0R/i0LujkYoGiEhUW/34dAYuP4QjHxiESBcMNEVEVaGpphJ/e8sHS4Z6wMpbj9v1HCF53BmM3nEVyFifjJKpJtSLcLF++HE5OTlAoFPD19UVUVFS59tuyZQskEgkGDhxYvQUSEZWDRCJBf3c7RLzbFWM7O0NHKsHhy2nwX/gnH1UR1SDRw83WrVsREhKC+fPnIyYmBu7u7ggICEB6etm3cxMTEzFjxgx07ty5hiolIiofY4Uu5vZtiQNTO8OvSUMU/v2oqueiP3HoEt+qIqpuEkHkv2W+vr5o164dli1bBgBQqVRwcHDA5MmTMWvWrFL3USqV6NKlC0aPHo3jx48jOzsbe/bsKdf5cnNzYWpqipycHJiYmFTVxyAiKpUgCNh34R4+++0KUnOfTN3QpZkl5vdviaaWRiJXR6Q9KvL9Leqdm6KiIkRHR8Pf31+9TiqVwt/fH5GRkc/c75NPPoGVlRXeeuutmiiTiKjSJBIJ+rV58qhqYvem0JNJcexaBgIWHcOC/VfwsKBY7BKJ6hxRw01mZiaUSiWsra011ltbWyM1NbXUfU6cOIEffvgBYWFh5TpHYWEhcnNzNRYioppmKNfBewFuODS9C3q4WaHk7xnH//ftn9h+NplzVRFVIdH73FTEw4cPMXLkSISFhcHCwqJc+4SGhsLU1FS9ODg4VHOVRETP5mRhiB9GtcO6Ue3gbGGIjIeFeG/HeQxc8Reibz8QuzyiOkHUPjdFRUUwMDDAjh07NN54CgoKQnZ2Nvbu3avRPi4uDp6enpDJZOp1KpUKwJPHWfHx8WjatKnGPoWFhSgsLFT/nJubCwcHB/a5ISLRFZWosP5kIr6LuI68v+enGuBhh/d7u8HOTF/k6ohqF63pc6OnpwcvLy9ERESo16lUKkRERMDPz++p9m5ubrhw4QLi4uLUyyuvvILu3bsjLi6u1LsycrkcJiYmGgsRUW2gpyPF2C5NcGRGN7zu3QgSCbA37i7+9+1RLDp8DY+KOCEnUWXoiF1ASEgIgoKC4O3tDR8fHyxevBj5+fkIDg4GAAQGBsLe3h6hoaFQKBRo1aqVxv5mZmYA8NR6IiJtYWksx1evuWNkeyd88tslnEl8gO8irmPrmWS8/3JzDHC3h1QqEbtMIq0hergZOnQoMjIyMG/ePKSmpsLDwwPh4eHqTsZJSUmQSrWqaxARUaW0bmSKbW/74cDFVCzYfwV3HjzG9K3n8ONfifigX0u0czIXu0QirSD6ODc1jePcEJE2KChWYu1ft7D8jxvIL3oysnGf1jZ4v7cbHBsailwdUc2ryPc3ww0RUS2W8bAQCw9fw9YzSVAJgK5MglEdnDCpuytMDXTFLo+oxjDclIHhhoi00dXUXHy+7wqOX88EAJjq62JKD1eMbO8IPR0+uqe6j+GmDAw3RKStBEHA0WsZCN1/BdfS8gAAjg0NMDPADX1a20AiYadjqrsYbsrAcENE2q5EqcKO6Dv49vA1ZDx8Mo6XZ2MzzH65BXyc2emY6iaGmzIw3BBRXZFfWIKw4wlY/WcCHhc/6XTs38Ias15uDhcrY5GrI6paDDdlYLghoromPbcAi/8eF0epEiCVAK97O2CafzPYmCrELo+oSjDclIHhhojqqhvpefgq/CoOXU4DAMh1pAju6IwJXZvyzSrSegw3ZWC4IaK67mxiFr44cBVn/56I01RfF+90a4qgDk5Q6MqeszdR7cRwUwaGGyKqDwRBQMSVdHx18Kr6zSobEwWm+rtiiFcj6Mj4+jhpF4abMjDcEFF9olQJ2B2bgkWHryEl+zEAwNnCECE9m6Fva1vOWUVag+GmDAw3RFQfFRQrsel0EpYfuYGs/CIAwEt2JpjRqzm6NbfkGDlU6zHclIHhhojqs7zCEvxw/BbCjicgr7AEAODt2ADv9moOv6YNRa6O6NkYbsrAcENEBGTlF2HVnzex/mQiCktUAIBOLhaYEdAcHg5m4hZHVAqGmzIw3BAR/SsttwDL/riBLWeSUKx88nXQw80K03s2Qyt7U5GrI/oXw00ZGG6IiJ6WnPUI30Vcx66YO1D9/a3Q+yUbTO/ZDM1tONoxiY/hpgwMN0REz5aQkYfvIq7jl3N3IQiARAL0bW2Laf6unNKBRMVwUwaGGyKi57uW9hCLf7+G/RdSATwJOf3b2GFKD1e4WBmJXB3VRww3ZWC4ISIqv8t3c/FdxDUcvPRkSgepBHjF3Q6T/seQQzWL4aYMDDdERBV36W4OFv9+HYf/nrfq3zs5LnxcRTWC4aYMDDdERJV3MSUH30Vohpy+rW0xpYcrmlkz5FD1YbgpA8MNEdGLu3Q3B0sirqsfVwFP3q6a9D8XvkJO1YLhpgwMN0REVefy3VwsO3IdBy6m4p9vkx5uVpjcw5WDAVKVYrgpA8MNEVHVu572EMuO3MCv5+6qx8np5GKBid1d0L6JOeeuohfGcFMGhhsiouqTkJGHFUdvYk9sCkr+Tjlejg0wqbsLJ+ikF8JwUwaGGyKi6pec9Qirj93EtrN3UPT33FUtbU3wTvemeLmVLWRShhyqGIabMjDcEBHVnPTcAoQdT8DGU0l4XKwEADhbGGJ81yYY5NkIejpSkSskbcFwUwaGGyKimpeVX4T1JxPx48lE5DwuBgDYmCgwprMzhvk0hpFcR+QKqbZjuCkDww0RkXjyC0vwc1QSwo4nIC23EABgqq+LQD9HjOrghIZGcpErpNqK4aYMDDdEROIrLFFiT2wKVv+ZgITMfACAXEeK170dMKazMxwbGopcIdU2DDdlYLghIqo9lCoBhy+nYuXRmzh3JwfAk/mrXm5li3FdmsCdY+XQ3xhuysBwQ0RU+wiCgMiE+1hzLAFH4zPU69s3Mce4Lk3QrZkVpHzDql5juCkDww0RUe12NTUXa44l4Je4u+qxclysjDCmkzMGetpDoSsTuUISQ0W+v2vFO3jLly+Hk5MTFAoFfH19ERUV9cy2u3btgre3N8zMzGBoaAgPDw/89NNPNVgtERFVJzcbEyx83QPHZnbHuC5NYCTXwY30PMzadQGdvvwDSyKuIyu/SOwyqRYT/c7N1q1bERgYiFWrVsHX1xeLFy/G9u3bER8fDysrq6faHz16FA8ePICbmxv09PTw22+/4d1338W+ffsQEBDw3PPxzg0RkXZ5WFCMrWeSsfbELdzNKQDwpPPxq16NMLqjM1ysjESukGqCVj2W8vX1Rbt27bBs2TIAgEqlgoODAyZPnoxZs2aV6xht27ZF37598emnnz63LcMNEZF2KlaqsP/CPYQdT8DFlFz1+u7NLfFWpybo6NKQ0zvUYVrzWKqoqAjR0dHw9/dXr5NKpfD390dkZORz9xcEAREREYiPj0eXLl2qs1QiIhKZrkyKAR72+HVSJ2wd1x49W1pDIgGOxGfgzR9Oo/fi49h6JgkFf4+ETPWXqENCZmZmQqlUwtraWmO9tbU1rl69+sz9cnJyYG9vj8LCQshkMqxYsQI9e/YstW1hYSEKCwvVP+fm5pbajoiItINEIoFvk4bwbdIQiZn5WPfXLWyPvoP4tId4f+cFfBkejzd8GmOknyOsTRRil0siqBUdiivK2NgYcXFxOHPmDD7//HOEhITg6NGjpbYNDQ2FqampenFwcKjZYomIqNo4WRji4wGtEDm7B+b2aQF7M31k5Rdh2ZEb6PjFH5j8cyxikh6IXSbVMFH73BQVFcHAwAA7duzAwIED1euDgoKQnZ2NvXv3lus4Y8aMQXJyMg4ePPjUttLu3Dg4OLDPDRFRHVSiVOHQ5TT8+FciohKz1OvdHcwwqoMj+rS2hVyHr5JrI63pc6OnpwcvLy9ERESo16lUKkRERMDPz6/cx1GpVBoB5r/kcjlMTEw0FiIiqpt0ZFL0aW2LbeP98NvkTnjNqxH0ZFKcS87G9K3n0PGLP7DwUDxS/37riuom0d+W2rp1K4KCgrB69Wr4+Phg8eLF2LZtG65evQpra2sEBgbC3t4eoaGhAJ48ZvL29kbTpk1RWFiI/fv3Y9asWVi5ciXGjBnz3PPxbSkiovolM68QW6KSsPFUElJzn4QaHakEAa1sENjeET7O5nzLSgtU5Ptb9Dnmhw4dioyMDMybNw+pqanw8PBAeHi4upNxUlISpNJ/bzDl5+fjnXfewZ07d6Cvrw83Nzds3LgRQ4cOFesjEBFRLWZhJMek/7ni7a5NcehSGtaffPLIat/5e9h3/h7cbIzxZntHDPK0h6Fc9K9FqgKi37mpabxzQ0REl+/m4qdTidgTexeP/3513Fiug8Ft7fFme0e4WhuLXCH9f1o1iF9NY7ghIqJ/5Dwuxo7oO9h46jZuZear1/s6m2OknyN6tbSBno5Wvlhc5zDclIHhhoiI/j+VSsCJG5nYeOo2fr+Shr/n64SlsRxDvR0wzMcBjRoYiFtkPcdwUwaGGyIiKsu9nMf4OSoZP0clIePhkzdxJRKgWzNLjPB1RHc3K8ik7IBc0xhuysBwQ0RE5VGsVOH3y2nYdDoJJ25kqtfbmiowtJ0DXvd2gJ2ZvogV1i8MN2VguCEiooq6lZmPn6OSsP1sMh48KgYASCVA9+ZWGO7TGN2aW0JHxr451YnhpgwMN0REVFkFxUocvJSKn6OScCrh3xGQrU3kGOLlgKHtHOBgzr451YHhpgwMN0REVBVuZuRh65lk7Ii+g6z8IvX6Ti4WGNrOAb1esuZUD1WI4aYMDDdERFSVikpUOHw5DVvOJOH49X/75jQw0MVAT3sMbecANxt+37wohpsyMNwQEVF1Sc56hG1nk7H97B31VA8A4N7IFEO8HdDf3Q6m+roiVqi9GG7KwHBDRETVTakScOxaBraeScbvV9JQ8vfAOXIdKV5uZYMh3g7wa9IQUr5SXm4MN2VguCEiopqUmVeI3TEp2B6djGtpeer19mb6eNWrEV5taw/HhoYiVqgdGG7KwHBDRERiEAQB5+/kYHt0MvbG3cXDghL1Nh8nc7zm1Qgvt7aBsYKPrUrDcFMGhhsiIhJbQbEShy6nYUf0HRy/noF/vokVulL0fskGg9s2QkcXC46E/B8MN2VguCEiotrkXs5j7I5NwY7oO0jI+HfyTmsTOQZ62mOwZyM0t+Es5Qw3ZWC4ISKi2kgQBJy7k4Od0Xfwy7m7yHlcrN72kp0JBnna4xUPO1gZK0SsUjwMN2VguCEiotqusESJI1fTsTMmBUfj01GsfPJVLZUAnV0tMdDTDr1a2sBQriNypTWH4aYMDDdERKRNHuQX4bfzd7ErNgWxSdnq9fq6MgS8ZI0Bnvbo5GIB3To+txXDTRkYboiISFvdyszHntgU7I1LQeL9R+r1DQ310LeNLQZ42KFt4waQSOpeR2SGmzIw3BARkbYTBAFxydnYG3cXv567i/v/mduqUQN99He3wwAPuzo17QPDTRkYboiIqC4pUarw18372BuXgoMXU5FfpFRva2ZthP5t7PCKh53WDxTIcFMGhhsiIqqrHhcpEXE1Db/E3cXR+AwUKVXqbe6NTNGvjR36trGFnZm+iFVWDsNNGRhuiIioPsh5XIyDl1Lx67m7+OtGJlT/+bb3dmyAfm1s0ae1LaxMtOPVcoabMjDcEBFRfZOZV4gDF58EnTOJWeoRkSWSJ1M/9Gtji96tbGFpLBe30DIw3JSB4YaIiOqz1JwC7LtwD/vO30XMf14tl0oAH2dz9Glti96tbGrdYIEMN2VguCEiInoiJfsxDly4h9/O30NccrZ6vUQCtHMyR59WNujdyhY2puIHHYabMjDcEBERPe3Og0c4cCEV+y5oBh0AaNvYTH1Hp1EDA1HqY7gpA8MNERFR2f65o3PgYiqibz/Q2Nba3hS9W9mgdysbNLU0qrGaGG7KwHBDRERUfqk5BTh4KRX7L9xD1H86IwOAq5URereyQcBLNnjJzqRaR0ZmuCkDww0REVHlZDwsxO9X0hB+MRUnb2aqJ/QEAHszffR6yRoBL9mgnZM5ZNKqDToMN2VguCEiInpxOY+LEXElDQcvpeLPaxkoKP53wECnhgY4MqNbld7Jqcj3d/2ZK52IiIiqjKm+Lga3bYTBbRvhcZESx65n4OClVERcSYeHg5mok3cy3BAREdEL0deTIeClJ31vipUqPCwoEbUeqahn/9vy5cvh5OQEhUIBX19fREVFPbNtWFgYOnfujAYNGqBBgwbw9/cvsz0RERHVHF2ZFOaGeqLWIHq42bp1K0JCQjB//nzExMTA3d0dAQEBSE9PL7X90aNHMXz4cBw5cgSRkZFwcHBAr169kJKSUsOVExERUW0keodiX19ftGvXDsuWLQMAqFQqODg4YPLkyZg1a9Zz91cqlWjQoAGWLVuGwMDA57Znh2IiIiLtU5Hvb1Hv3BQVFSE6Ohr+/v7qdVKpFP7+/oiMjCzXMR49eoTi4mKYm5uXur2wsBC5ubkaCxEREdVdooabzMxMKJVKWFtba6y3trZGampquY7x/vvvw87OTiMg/VdoaChMTU3Vi4ODwwvXTURERLWX6H1uXsQXX3yBLVu2YPfu3VAoSp/Ua/bs2cjJyVEvycnJNVwlERER1SRRXwW3sLCATCZDWlqaxvq0tDTY2NiUue8333yDL774Ar///jvatGnzzHZyuRxyubxK6iUiIqLaT9Q7N3p6evDy8kJERIR6nUqlQkREBPz8/J6531dffYVPP/0U4eHh8Pb2rolSiYiISEuIPohfSEgIgoKC4O3tDR8fHyxevBj5+fkIDg4GAAQGBsLe3h6hoaEAgC+//BLz5s3D5s2b4eTkpO6bY2RkBCOjmpudlIiIiGon0cPN0KFDkZGRgXnz5iE1NRUeHh4IDw9XdzJOSkqCVPrvDaaVK1eiqKgIr732msZx5s+fj48++qgmSyciIqJaSPRxbmoax7khIiLSPlozzg0RERFRVWO4ISIiojqF4YaIiIjqFNE7FNe0f7oYcRoGIiIi7fHP93Z5ugrXu3Dz8OFDAOA0DERERFro4cOHMDU1LbNNvXtbSqVS4e7duzA2NoZEIqnSY+fm5sLBwQHJycl8E6sa8TrXDF7nmsHrXHN4rWtGdV1nQRDw8OFD2NnZaQwRU5p6d+dGKpWiUaNG1XoOExMT/sWpAbzONYPXuWbwOtccXuuaUR3X+Xl3bP7BDsVERERUpzDcEBERUZ3CcFOF5HI55s+fz1nIqxmvc83gda4ZvM41h9e6ZtSG61zvOhQTERFR3cY7N0RERFSnMNwQERFRncJwQ0RERHUKww0RERHVKQw3VWT58uVwcnKCQqGAr68voqKixC5Jq4SGhqJdu3YwNjaGlZUVBg4ciPj4eI02BQUFmDhxIho2bAgjIyO8+uqrSEtL02iTlJSEvn37wsDAAFZWVnjvvfdQUlJSkx9Fq3zxxReQSCSYNm2aeh2vc9VISUnBm2++iYYNG0JfXx+tW7fG2bNn1dsFQcC8efNga2sLfX19+Pv74/r16xrHyMrKwogRI2BiYgIzMzO89dZbyMvLq+mPUmsplUp8+OGHcHZ2hr6+Ppo2bYpPP/1UY+4hXufKOXbsGPr37w87OztIJBLs2bNHY3tVXdfz58+jc+fOUCgUcHBwwFdffVU1H0CgF7ZlyxZBT09PWLt2rXDp0iVh7NixgpmZmZCWliZ2aVojICBAWLdunXDx4kUhLi5O6NOnj9C4cWMhLy9P3Wb8+PGCg4ODEBERIZw9e1Zo37690KFDB/X2kpISoVWrVoK/v78QGxsr7N+/X7CwsBBmz54txkeq9aKiogQnJyehTZs2wtSpU9XreZ1fXFZWluDo6CiMGjVKOH36tJCQkCAcPHhQuHHjhrrNF198IZiamgp79uwRzp07J7zyyiuCs7Oz8PjxY3Wb3r17C+7u7sKpU6eE48ePCy4uLsLw4cPF+Ei10ueffy40bNhQ+O2334Rbt24J27dvF4yMjITvvvtO3YbXuXL2798vzJ07V9i1a5cAQNi9e7fG9qq4rjk5OYK1tbUwYsQI4eLFi8LPP/8s6OvrC6tXr37h+hluqoCPj48wceJE9c9KpVKws7MTQkNDRaxKu6WnpwsAhD///FMQBEHIzs4WdHV1he3bt6vbXLlyRQAgREZGCoLw5C+jVCoVUlNT1W1WrlwpmJiYCIWFhTX7AWq5hw8fCq6ursLhw4eFrl27qsMNr3PVeP/994VOnTo9c7tKpRJsbGyEr7/+Wr0uOztbkMvlws8//ywIgiBcvnxZACCcOXNG3ebAgQOCRCIRUlJSqq94LdK3b19h9OjRGusGDx4sjBgxQhAEXueq8v/DTVVd1xUrVggNGjTQ+Hfj/fffF5o3b/7CNfOx1AsqKipCdHQ0/P391eukUin8/f0RGRkpYmXaLScnBwBgbm4OAIiOjkZxcbHGdXZzc0Pjxo3V1zkyMhKtW7eGtbW1uk1AQAByc3Nx6dKlGqy+9ps4cSL69u2rcT0BXueq8ssvv8Db2xtDhgyBlZUVPD09ERYWpt5+69YtpKamalxnU1NT+Pr6alxnMzMzeHt7q9v4+/tDKpXi9OnTNfdharEOHTogIiIC165dAwCcO3cOJ06cwMsvvwyA17m6VNV1jYyMRJcuXaCnp6duExAQgPj4eDx48OCFaqx3E2dWtczMTCiVSo1/6AHA2toaV69eFakq7aZSqTBt2jR07NgRrVq1AgCkpqZCT08PZmZmGm2tra2RmpqqblPaf4d/ttETW7ZsQUxMDM6cOfPUNl7nqpGQkICVK1ciJCQEc+bMwZkzZzBlyhTo6ekhKChIfZ1Ku47/vc5WVlYa23V0dGBubs7r/LdZs2YhNzcXbm5ukMlkUCqV+PzzzzFixAgA4HWuJlV1XVNTU+Hs7PzUMf7Z1qBBg0rXyHBDtc7EiRNx8eJFnDhxQuxS6pzk5GRMnToVhw8fhkKhELucOkulUsHb2xsLFiwAAHh6euLixYtYtWoVgoKCRK6u7ti2bRs2bdqEzZs346WXXkJcXBymTZsGOzs7Xud6jo+lXpCFhQVkMtlTb5OkpaXBxsZGpKq016RJk/Dbb7/hyJEjaNSokXq9jY0NioqKkJ2drdH+v9fZxsam1P8O/2yjJ4+d0tPT0bZtW+jo6EBHRwd//vknlixZAh0dHVhbW/M6VwFbW1u0bNlSY12LFi2QlJQE4N/rVNa/GzY2NkhPT9fYXlJSgqysLF7nv7333nuYNWsWhg0bhtatW2PkyJGYPn06QkNDAfA6V5equq7V+W8Jw80L0tPTg5eXFyIiItTrVCoVIiIi4OfnJ2Jl2kUQBEyaNAm7d+/GH3/88dStSi8vL+jq6mpc5/j4eCQlJamvs5+fHy5cuKDxF+rw4cMwMTF56oumvurRowcuXLiAuLg49eLt7Y0RI0ao/8zr/OI6duz41FAG165dg6OjIwDA2dkZNjY2Gtc5NzcXp0+f1rjO2dnZiI6OVrf5448/oFKp4OvrWwOfovZ79OgRpFLNrzGZTAaVSgWA17m6VNV19fPzw7Fjx1BcXKxuc/jwYTRv3vyFHkkB4KvgVWHLli2CXC4XfvzxR+Hy5cvCuHHjBDMzM423SahsEyZMEExNTYWjR48K9+7dUy+PHj1Stxk/frzQuHFj4Y8//hDOnj0r+Pn5CX5+furt/7yi3KtXLyEuLk4IDw8XLC0t+Yryc/z3bSlB4HWuClFRUYKOjo7w+eefC9evXxc2bdokGBgYCBs3blS3+eKLLwQzMzNh7969wvnz54UBAwaU+iqtp6encPr0aeHEiROCq6trvX9F+b+CgoIEe3t79avgu3btEiwsLISZM2eq2/A6V87Dhw+F2NhYITY2VgAgLFy4UIiNjRVu374tCELVXNfs7GzB2tpaGDlypHDx4kVhy5YtgoGBAV8Fr02WLl0qNG7cWNDT0xN8fHyEU6dOiV2SVgFQ6rJu3Tp1m8ePHwvvvPOO0KBBA8HAwEAYNGiQcO/ePY3jJCYmCi+//LKgr68vWFhYCO+++65QXFxcw59Gu/z/cMPrXDV+/fVXoVWrVoJcLhfc3NyENWvWaGxXqVTChx9+KFhbWwtyuVzo0aOHEB8fr9Hm/v37wvDhwwUjIyPBxMRECA4OFh4+fFiTH6NWy83NFaZOnSo0btxYUCgUQpMmTYS5c+dqvFrM61w5R44cKfXf5KCgIEEQqu66njt3TujUqZMgl8sFe3t74YsvvqiS+iWC8J+hHImIiIi0HPvcEBERUZ3CcENERER1CsMNERER1SkMN0RERFSnMNwQERFRncJwQ0RERHUKww0RERHVKQw3RKSVEhMTIZFIEBcXV+F9IyIi0KJFCyiVyqov7D8uX76MRo0aIT8/v1rPQ0SaGG6IqMJGjRoFiUQCiUQCXV1dWFtbo2fPnli7dq16Xp+qPt/AgQOr7HgzZ87EBx98AJlMVmXHLE3Lli3Rvn17LFy4sFrPQ0SaGG6IqFJ69+6Ne/fuITExEQcOHED37t0xdepU9OvXDyUlJWKX90wnTpzAzZs38eqrr9bI+YKDg7Fy5cpafU2I6hqGGyKqFLlcDhsbG9jb26Nt27aYM2cO9u7diwMHDuDHH39Ut8vOzsaYMWNgaWkJExMT/O9//8O5c+fU2z/66CN4eHhg9erVcHBwgIGBAV5//XXk5OSot69fvx579+5V3y06evSoev+EhAR0794dBgYGcHd3R2RkZJl1b9myBT179oRCoVCvK+3O0LRp09CtWzf1z926dcPkyZMxbdo0NGjQANbW1ggLC0N+fj6Cg4NhbGwMFxcXHDhwQOM4PXv2RFZWFv78889yXlkielEMN0RUZf73v//B3d0du3btUq8bMmQI0tPTceDAAURHR6Nt27bo0aMHsrKy1G1u3LiBbdu24ddff0V4eDhiY2PxzjvvAABmzJiB119/XX2n6N69e+jQoYN637lz52LGjBmIi4tDs2bNMHz48DLvkhw/fhze3t6V+nzr16+HhYUFoqKiMHnyZEyYMAFDhgxBhw4dEBMTg169emHkyJF49OiReh89PT14eHjg+PHjlTonEVUcww0RVSk3NzckJiYCePIIKCoqCtu3b4e3tzdcXV3xzTffwMzMDDt27FDvU1BQgA0bNsDDwwNdunTB0qVLsWXLFqSmpsLIyAj6+vrqO0U2NjbQ09NT7ztjxgz07dsXzZo1w8cff4zbt2/jxo0bz6zv9u3bsLOzq9Rnc3d3xwcffABXV1fMnj0bCoUCFhYWGDt2LFxdXTFv3jzcv38f58+f19jPzs4Ot2/frtQ5iajiGG6IqEoJggCJRAIAOHfuHPLy8tCwYUMYGRmpl1u3buHmzZvqfRo3bgx7e3v1z35+flCpVIiPj3/u+dq0aaP+s62tLQAgPT39me0fP36s8UiqIv57LplMhoYNG6J169bqddbW1qWeX19fX+NuDhFVLx2xCyCiuuXKlStwdnYGAOTl5cHW1lajj8w/zMzMquR8urq66j//E6rKemPLwsICDx48eO5xS3tN/L/n+ud85Tl/VlYWmjZt+txzElHVYLghoirzxx9/4MKFC5g+fToAoG3btkhNTYWOjg6cnJyeuV9SUhLu3r2rflx06tQpSKVSNG/eHMCTfitVNSaNp6cnLl++/NT6tLQ0jZ8TEhKq5HwAcPHiRbz22mtVdjwiKhsfSxFRpRQWFiI1NRUpKSmIiYnBggULMGDAAPTr1w+BgYEAAH9/f/j5+WHgwIE4dOgQEhMTcfLkScydOxdnz55VH0uhUCAoKAjnzp3D8ePHMWXKFLz++uuwsbEBADg5OeH8+fOIj49HZmYmiouLK113QEAATpw48dT606dPIywsDAkJCfj+++9x8OBB3Lt3D7du3ar0uYAngw2mpKTA39//hY5DROXHcENElRIeHg5bW1s4OTmhd+/eOHLkCJYsWYK9e/eqB8eTSCTYv38/unTpguDgYDRr1gzDhg3D7du31f1TAMDFxQWDBw9Gnz590KtXL7Rp0wYrVqxQbx87diyaN28Ob29vWFpa4q+//qp03SNGjMClS5ee6s/TvXt37Ny5Ey1atEBYWBjWrVuHe/fu4euvv670uQDg559/Rq9eveDo6PhCxyGi8pMIgiCIXQQR1V8fffQR9uzZU6lpFCrrvffeQ25uLlavXg3gyTg32dnZ2LNnT5Wep6ioCK6urti8eTM6duxYpccmomfjnRsiqnfmzp0LR0fHapkq4r+SkpIwZ84cBhuiGsYOxURU75iZmWHOnDnVfh4XFxe4uLhU+3mISBMfSxEREVGdwsdSREREVKcw3BAREVGdwnBDREREdQrDDREREdUpDDdERERUpzDcEBERUZ3CcENERER1CsMNERER1SkMN0RERFSn/B9BV/zQaOltIgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "depth = numpy.linspace(0, 1000, 100)\n", "res = numpy.exp(-mu*depth*1e-6)\n", "fig, ax = subplots()\n", "ax.plot(depth, res, \"-\")\n", "ax.set_xlabel(\"Depth (µm)\")\n", "ax.set_ylabel(\"Residual signal\")\n", "ax.set_title(\"Silicon @ 17.8 keV\")\n", "pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is consistent with:\n", "http://henke.lbl.gov/optical_constants/filter2.html\n", "\n", "Now we can model the detector\n", "\n", "## Modeling of the detector:\n", "\n", "The detector is seen as a 2D array of voxel. Let vox, voy and voz be the dimention of the detector in the three dimentions.\n", "\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\n", "0.000172 0.000172 0.00045\n" ] } ], "source": [ "detector= pyFAI.detector_factory(calib[\"detector\"])\n", "print(detector)\n", "\n", "vox = detector.pixel2 # this is not a typo\n", "voy = detector.pixel1 # x <--> axis 2\n", "voz = thickness\n", "\n", "print(vox, voy, voz)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The intensity grabbed in this voxel is the triple integral of the absorbed signal coming from this pixel or from the neighboring ones.\n", "\n", "There are 3 ways to perform this intergral:\n", "* Volumetric analytic integral. Looks feasible with a change of variable in the depth\n", "* Slice per slice, the remaining intensity depand on the incidence angle + pixel splitting between neighbooring pixels\n", "* raytracing: the decay can be solved analytically for each ray, one has to throw many ray to average out the signal.\n", "\n", "For sake of simplicity, this integral will be calculated numerically using this raytracing algorithm.\n", "http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.42.3443&rep=rep1&type=pdf\n", "\n", "Knowing the input position for a X-ray on the detector and its propagation vector, this algorithm allows us to calculate the length of the path in all voxel it crosses in a fairly efficient way.\n", "\n", "To speed up the calculation, we will use a few tricks:\n", "* One ray never crosses more than 16 pixels, which is reasonable considering the incidance angle \n", "* we use numba to speed-up the calculation of loops in python\n", "* We will allocate the needed memory by chuncks of 1 million elements\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: numba in /users/kieffer/.venv/py311/lib/python3.11/site-packages (0.58.0)\n", "Requirement already satisfied: llvmlite<0.42,>=0.41.0dev0 in /users/kieffer/.venv/py311/lib/python3.11/site-packages (from numba) (0.41.0)\n", "Requirement already satisfied: numpy<1.26,>=1.21 in /users/kieffer/.venv/py311/lib/python3.11/site-packages (from numba) (1.25.2)\n" ] } ], "source": [ "! pip install numba" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "from numba import jit \n", "\n", "BLOCK_SIZE = 1<<20 # 1 million\n", "BUFFER_SIZE = 16 \n", "BIG = numpy.finfo(numpy.float32).max\n", "\n", "mask = numpy.load(\"mask.npy\").astype(numpy.int8)\n", "from scipy.sparse import csr_matrix, csc_matrix, linalg" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(array([0, 0, 1, 1], dtype=int32), array([0, 1, 1, 2], dtype=int32), array([0.00029791, 0.00029791, 0.00059583, 0.00059583], dtype=float32))\n", "The slowest run took 6.73 times longer than the fastest. This could mean that an intermediate result is being cached.\n", "6.53 µs ± 6.22 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", "6.54 µs ± 272 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)\n" ] } ], "source": [ "@jit(nopython=True)\n", "def calc_one_ray(entx, enty, \n", " kx, ky, kz,\n", " vox, voy, voz):\n", " \"\"\"For a ray, entering at position (entx, enty), with a propagation vector (kx, ky,kz),\n", " calculate the length spent in every voxel where energy is deposited from a bunch of photons comming in the detector \n", " at a given position and and how much energy they deposit in each voxel. \n", " \n", " Direct implementation of http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.42.3443&rep=rep1&type=pdf\n", " \n", " :param entx, enty: coordinate of the entry point in meter (2 components, x,y)\n", " :param kx, ky, kz: vector with the direction of the photon (3 components, x,y,z)\n", " :param vox, voy, voz: size of the voxel in meter (3 components, x,y,z)\n", " :return: coordinates voxels in x, y and length crossed when leaving the associated voxel\n", " \"\"\"\n", " array_x = numpy.empty(BUFFER_SIZE, dtype=numpy.int32)\n", " array_x[:] = -1\n", " array_y = numpy.empty(BUFFER_SIZE, dtype=numpy.int32)\n", " array_y[:] = -1\n", " array_len = numpy.empty(BUFFER_SIZE, dtype=numpy.float32)\n", " \n", " #normalize the input propagation vector\n", " n = numpy.sqrt(kx*kx + ky*ky + kz*kz)\n", " kx /= n\n", " ky /= n\n", " kz /= n\n", " \n", " #assert kz>0\n", " step_X = -1 if kx<0.0 else 1\n", " step_Y = -1 if ky<0.0 else 1\n", " \n", " #assert vox>0\n", " #assert voy>0\n", " #assert voz>0\n", " \n", " X = int(entx//vox)\n", " Y = int(enty//voy)\n", " \n", " if kx>0.0:\n", " t_max_x = ((entx//vox+1)*(vox)-entx)/ kx\n", " elif kx<0.0:\n", " t_max_x = ((entx//vox)*(vox)-entx)/ kx\n", " else:\n", " t_max_x = BIG\n", "\n", " if ky>0.0:\n", " t_max_y = ((enty//voy+1)*(voy)-enty)/ ky\n", " elif ky<0.0:\n", " t_max_y = ((enty//voy)*(voy)-enty)/ ky\n", " else:\n", " t_max_y = BIG\n", " \n", " #Only one case for z as the ray is travelling in one direction only\n", " t_max_z = voz / kz\n", " \n", " t_delta_x = abs(vox/kx) if kx!=0 else BIG\n", " t_delta_y = abs(voy/ky) if ky!=0 else BIG\n", " t_delta_z = voz/kz\n", " \n", " finished = False\n", " last_id = 0\n", " array_x[last_id] = X\n", " array_y[last_id] = Y\n", " \n", " while not finished:\n", " if t_max_x < t_max_y:\n", " if t_max_x < t_max_z:\n", " array_len[last_id] = t_max_x\n", " last_id+=1\n", " X += step_X\n", " array_x[last_id] = X\n", " array_y[last_id] = Y\n", " t_max_x += t_delta_x\n", " else:\n", " array_len[last_id] = t_max_z\n", " finished = True\n", " else:\n", " if t_max_y < t_max_z:\n", " array_len[last_id] = t_max_y\n", " last_id+=1\n", " Y += step_Y\n", " array_x[last_id] = X\n", " array_y[last_id] = Y \n", " t_max_y += t_delta_y\n", " else:\n", " array_len[last_id] = t_max_z\n", " finished = True\n", " if last_id>=array_len.size-1:\n", " print(\"resize arrays\")\n", " old_size = len(array_len)\n", " new_size = (old_size//BUFFER_SIZE+1)*BUFFER_SIZE\n", " new_array_x = numpy.empty(new_size, dtype=numpy.int32)\n", " new_array_x[:] = -1\n", " new_array_y = numpy.empty(new_size, dtype=numpy.int32)\n", " new_array_y[:] = -1\n", " new_array_len = numpy.empty(new_size, dtype=numpy.float32)\n", " new_array_x[:old_size] = array_x\n", " new_array_y[:old_size] = array_y\n", " new_array_len[:old_size] = array_len\n", " array_x = new_array_x\n", " array_y = new_array_y\n", " array_len = new_array_len\n", " return array_x[:last_id], array_y[:last_id], array_len[:last_id]\n", "\n", "print(calc_one_ray(0.0,0.0, 1,1,1, 172e-6, 172e-6, 450e-6))\n", "import random\n", "%timeit calc_one_ray(10+random.random(),11+random.random(),\\\n", " random.random()-0.5,random.random()-0.5,0.5+random.random(), \\\n", " vox, voy, voz)\n", "%timeit calc_one_ray.py_func(10+random.random(),11+random.random(),\\\n", " random.random()-0.5,random.random()-0.5,0.5+random.random(), \\\n", " vox, voy, voz)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we are able to perform raytracing for any ray comming in the detector, we can calculate the contribution to the neighboring pixels, using the absorption law (the length travelled is already known). \n", "To average-out the signal, we will sample a few dozens of rays per pixel to get an approximatation of the volumic integrale. \n", "\n", "Now we need to store the results so that this transformation can be represented as a sparse matrix multiplication:\n", "\n", "b = M.a\n", "\n", "Where b is the recorded image (blurred) and a is the \"perfect\" signal. \n", "M being the sparse matrix where every pixel of a gives a limited number of contribution to b.\n", "\n", "Each pixel in *b* is represented by one line in *M* and we store the indices of *a* of interest with the coefficients of the matrix.\n", "So if a pixel i,j contributes to (i,j), (i+1,j), (i+1,j+1), there are only 3 elements in the line. \n", "This is advantagous for storage.\n", "\n", "We will use the CSR sparse matrix representation:\n", "https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_sparse_row_.28CSR.2C_CRS_or_Yale_format.29\n", "where there are 3 arrays:\n", "* data: containing the actual non zero values\n", "* indices: for a given line, it contains the column number of the assocated data (at the same indice)\n", "* idptr: this array contains the index of the start of every line.\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from numba.experimental import jitclass\n", "from numba import int8, int32, int64, float32, float64\n", "spec = [(\"vox\",float64),(\"voy\",float64),(\"voz\",float64),(\"mu\",float64),\n", " (\"dist\",float64),(\"poni1\",float64),(\"poni2\",float64),\n", " (\"width\", int64),(\"height\", int64),(\"mask\", int8[:,:]),\n", " (\"sampled\", int64), (\"data\", float32[:]),(\"indices\", int32[:]),(\"idptr\", int32[:]),\n", " ]\n", "@jitclass(spec)\n", "class ThickDetector(object):\n", " \"Calculate the point spread function as function of the geometry of the experiment\"\n", " \n", " def __init__(self, vox, voy, thickness, mask, mu, \n", " dist, poni1, poni2):\n", " \"\"\"Constructor of the class:\n", " \n", " :param vox, voy: detector pixel size in the plane\n", " :param thickness: thickness of the sensor in meters\n", " :param mask: \n", " :param mu: absorption coefficient of the sensor material\n", " :param dist: sample detector distance as defined in the geometry-file\n", " :param poni1, poni2: coordinates of the PONI as defined in the geometry \n", " \"\"\"\n", " self.vox = vox\n", " self.voy = voy\n", " self.voz = thickness\n", " self.mu = mu\n", " self.dist=dist\n", " self.poni1 = poni1\n", " self.poni2 = poni2\n", " self.width = mask.shape[-1]\n", " self.height = mask.shape[0]\n", " self.mask = mask\n", " self.sampled = 0\n", " self.data = numpy.zeros(BLOCK_SIZE, dtype=numpy.float32)\n", " self.indices = numpy.zeros(BLOCK_SIZE,dtype=numpy.int32)\n", " self.idptr = numpy.zeros(self.width*self.height+1, dtype=numpy.int32)\n", " \n", " def calc_one_ray(self, entx, enty):\n", " \"\"\"For a ray, entering at position (entx, enty), with a propagation vector (kx, ky,kz),\n", " calculate the length spent in every voxel where energy is deposited from a bunch of photons comming in the detector \n", " at a given position and and how much energy they deposit in each voxel. \n", "\n", " Direct implementation of http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.42.3443&rep=rep1&type=pdf\n", "\n", " :param entx, enty: coordinate of the entry point in meter (2 components, x,y)\n", " :return: coordinates voxels in x, y and length crossed when leaving the associated voxel\n", " \"\"\"\n", " array_x = numpy.empty(BUFFER_SIZE, dtype=numpy.int32)\n", " array_x[:] = -1\n", " array_y = numpy.empty(BUFFER_SIZE, dtype=numpy.int32)\n", " array_y[:] = -1\n", " array_len = numpy.empty(BUFFER_SIZE, dtype=numpy.float32)\n", "\n", " #normalize the input propagation vector\n", " kx = entx - self.poni2\n", " ky = enty - self.poni1\n", " kz = self.dist\n", " n = numpy.sqrt(kx*kx + ky*ky + kz*kz)\n", " kx /= n\n", " ky /= n\n", " kz /= n\n", "\n", " step_X = -1 if kx<0.0 else 1\n", " step_Y = -1 if ky<0.0 else 1\n", "\n", " X = int(entx/self.vox)\n", " Y = int(enty/self.voy)\n", "\n", " if kx>0.0:\n", " t_max_x = ((entx//self.vox+1)*(self.vox)-entx)/ kx\n", " elif kx<0.0:\n", " t_max_x = ((entx//self.vox)*(self.vox)-entx)/ kx\n", " else:\n", " t_max_x = BIG\n", "\n", " if ky>0.0:\n", " t_max_y = ((enty//self.voy+1)*(self.voy)-enty)/ ky\n", " elif ky<0.0:\n", " t_max_y = ((enty//self.voy)*(self.voy)-enty)/ ky\n", " else:\n", " t_max_y = BIG\n", "\n", " #Only one case for z as the ray is travelling in one direction only\n", " t_max_z = self.voz / kz\n", "\n", " t_delta_x = abs(self.vox/kx) if kx!=0 else BIG\n", " t_delta_y = abs(self.voy/ky) if ky!=0 else BIG\n", " t_delta_z = self.voz/kz\n", "\n", " finished = False\n", " last_id = 0\n", " array_x[last_id] = X\n", " array_y[last_id] = Y\n", "\n", " while not finished:\n", " if t_max_x < t_max_y:\n", " if t_max_x < t_max_z:\n", " array_len[last_id] = t_max_x\n", " last_id+=1\n", " X += step_X\n", " array_x[last_id] = X\n", " array_y[last_id] = Y\n", " t_max_x += t_delta_x\n", " else:\n", " array_len[last_id] = t_max_z\n", " last_id+=1\n", " finished = True\n", " else:\n", " if t_max_y < t_max_z:\n", " array_len[last_id] = t_max_y\n", " last_id+=1\n", " Y += step_Y\n", " array_x[last_id] = X\n", " array_y[last_id] = Y \n", " t_max_y += t_delta_y\n", " else:\n", " array_len[last_id] = t_max_z\n", " last_id+=1\n", " finished = True\n", " if last_id>=array_len.size-1:\n", " print(\"resize arrays\")\n", " old_size = len(array_len)\n", " new_size = (old_size//BUFFER_SIZE+1)*BUFFER_SIZE\n", " new_array_x = numpy.empty(new_size, dtype=numpy.int32)\n", " new_array_x[:] = -1\n", " new_array_y = numpy.empty(new_size, dtype=numpy.int32)\n", " new_array_y[:] = -1\n", " new_array_len = numpy.empty(new_size, dtype=numpy.float32)\n", " new_array_x[:old_size] = array_x\n", " new_array_y[:old_size] = array_y\n", " new_array_len[:old_size] = array_len\n", " array_x = new_array_x\n", " array_y = new_array_y\n", " array_len = new_array_len\n", " return array_x[:last_id], array_y[:last_id], array_len[:last_id]\n", "\n", " def one_pixel(self, row, col, sample):\n", " \"\"\"calculate the contribution of one pixel to the sparse matrix and populate it.\n", "\n", " :param row: row index of the pixel of interest\n", " :param col: column index of the pixel of interest\n", " :param sample: Oversampling rate, 10 will thow 10x10 ray per pixel\n", "\n", " :return: the extra number of pixel allocated\n", " \"\"\"\n", " if self.mask[row, col]:\n", " return (numpy.empty(0, dtype=numpy.int32),\n", " numpy.empty(0, dtype=numpy.float32))\n", "\n", " counter = 0\n", " tmp_size = 0\n", " last_buffer_size = BUFFER_SIZE\n", " tmp_idx = numpy.empty(last_buffer_size, dtype=numpy.int32)\n", " tmp_idx[:] = -1\n", " tmp_coef = numpy.zeros(last_buffer_size, dtype=numpy.float32)\n", "\n", " pos = row * self.width + col\n", " start = self.idptr[pos]\n", " for i in range(sample):\n", " posx = (col+1.0*i/sample)*vox\n", " for j in range(sample):\n", " posy = (row+1.0*j/sample)*voy\n", " array_x, array_y, array_len = self.calc_one_ray(posx, posy)\n", "\n", " rem = 1.0\n", " for i in range(array_x.size):\n", " x = array_x[i]\n", " y = array_y[i]\n", " l = array_len[i]\n", " if (x<0) or (y<0) or (y>=self.height) or (x>=self.width):\n", " break\n", " elif (self.mask[y, x]):\n", " continue\n", " idx = x + y*self.width\n", " dos = numpy.exp(-self.mu*l)\n", " value = rem - dos\n", " rem = dos\n", " for j in range(last_buffer_size):\n", " if tmp_size >= last_buffer_size:\n", " #Increase buffer size\n", " new_buffer_size = last_buffer_size + BUFFER_SIZE\n", " new_idx = numpy.empty(new_buffer_size, dtype=numpy.int32)\n", " new_coef = numpy.zeros(new_buffer_size, dtype=numpy.float32)\n", " new_idx[:last_buffer_size] = tmp_idx\n", " new_idx[last_buffer_size:] = -1\n", " new_coef[:last_buffer_size] = tmp_coef\n", " last_buffer_size = new_buffer_size\n", " tmp_idx = new_idx\n", " tmp_coef = new_coef\n", "\n", " if tmp_idx[j] == idx:\n", " tmp_coef[j] += value\n", " break\n", " elif tmp_idx[j] < 0:\n", " tmp_idx[j] = idx\n", " tmp_coef[j] = value\n", " tmp_size +=1\n", " break \n", " return tmp_idx[:tmp_size], tmp_coef[:tmp_size]\n", "\n", " def calc_csr(self, sample):\n", " \"\"\"Calculate the CSR matrix for the whole image\n", " :param sample: Oversampling factor\n", " :return: CSR matrix\n", " \"\"\"\n", " size = self.width * self.height\n", " allocated_size = BLOCK_SIZE\n", " idptr = numpy.zeros(size+1, dtype=numpy.int32) \n", " indices = numpy.zeros(allocated_size, dtype=numpy.int32)\n", " data = numpy.zeros(allocated_size, dtype=numpy.float32)\n", " self.sampled = sample*sample\n", " pos = 0\n", " start = 0\n", " for row in range(self.height):\n", " for col in range(self.width): \n", " line_idx, line_coef = self.one_pixel(row, col, sample)\n", " line_size = line_idx.size\n", " if line_size == 0:\n", " new_size = 0\n", " pos+=1\n", " idptr[pos] = start\n", " continue\n", "\n", " stop = start + line_size\n", " \n", " if stop >= allocated_size:\n", " new_buffer_size = allocated_size + BLOCK_SIZE\n", " new_idx = numpy.zeros(new_buffer_size, dtype=numpy.int32)\n", " new_coef = numpy.zeros(new_buffer_size, dtype=numpy.float32)\n", " new_idx[:allocated_size] = indices\n", " new_coef[:allocated_size] = data\n", " allocated_size = new_buffer_size\n", " indices = new_idx\n", " data = new_coef\n", "\n", " indices[start:stop] = line_idx\n", " data[start:stop] = line_coef\n", " pos+=1\n", " idptr[pos] = stop\n", " start = stop\n", " \n", " last = idptr[-1]\n", " self.data = data\n", " self.indices = indices\n", " self.idptr = idptr\n", " return (self.data[:last]/self.sampled, indices[:last], idptr)\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 3.84 s, sys: 131 ms, total: 3.97 s\n", "Wall time: 3.98 s\n" ] }, { "data": { "text/plain": [ "(array([0., 0., 0., ..., 0., 0., 0.], dtype=float32),\n", " array([ 2, 2, 4, ..., 1023180, 1023181, 1023182],\n", " dtype=int32),\n", " array([ 0, 0, 0, ..., 1902581, 1902582, 1902583],\n", " dtype=int32))" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "thick = ThickDetector(vox,voy, thickness=thickness, mu=mu, dist=dist, poni1=poni1, poni2=poni2, mask=mask)\n", "%time thick.calc_csr(1)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 26.8 s, sys: 210 ms, total: 27 s\n", "Wall time: 26.6 s\n" ] } ], "source": [ "thick = ThickDetector(vox,voy, thickness=thickness, mu=mu, dist=dist, poni1=poni1, poni2=poni2, mask=mask)\n", "%time pre_csr = thick.calc_csr(8)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Validation of the CSR matrix obtained:\n", "\n", "For this we will build a simple 2D image with one pixel in a regular grid and calculate the effect of the transformation calculated previously on it. " ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dummy_image = numpy.ones(mask.shape, dtype=\"float32\")\n", "dummy_image[::5,::5] = 10\n", "#dummy_image[mask] = -1\n", "csr = csr_matrix(pre_csr)\n", "dummy_blurred = csr.T.dot(dummy_image.ravel()).reshape(mask.shape)\n", "fix, ax = subplots(2,2, figsize=(8,8))\n", "ax[0,0].imshow(dummy_image)\n", "ax[0,1].imshow(dummy_blurred)\n", "ax[1,1].imshow(csr.dot(dummy_blurred.ravel()).reshape(mask.shape))\n", "pass" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "ax[0,0].set_xlim(964,981)\n", "ax[0,0].set_ylim(0,16)\n", "ax[0,1].set_xlim(964,981)\n", "ax[0,1].set_ylim(0,16)\n", "ax[1,1].set_xlim(964,981)\n", "ax[1,1].set_ylim(0,16)\n", "pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Least squares refinement of the pseudo-inverse" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 4.2 s, sys: 5.33 s, total: 9.53 s\n", "Wall time: 896 ms\n", "(1, 30, 0.004636807487921894, 0.0005109823651654101, 2.1354865334098925, 4.833787524750339, 2175.5691048676463)\n" ] } ], "source": [ "blured = dummy_blurred.ravel()\n", "\n", "# Invert this matrix: see https://arxiv.org/abs/1006.0758\n", "\n", "%time res = linalg.lsmr(csr.T, blured)\n", "\n", "restored = res[0].reshape(mask.shape)\n", "ax[1,0].imshow(restored)\n", "ax[1,0].set_xlim(964,981)\n", "ax[1,0].set_ylim(0,16)\n", "\n", "print(res[1:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Pseudo inverse with positivitiy constrain and poissonian noise (MLEM)\n", "\n", "The MLEM algorithm was initially developed within the framework of reconstruction of\n", "images in emission tomography [Shepp and Vardi, 1982], [Vardi et al., 1985], [Lange and\n", "Carson, 1984]. Nowadays, this algorithm is employed in numerous tomographic reconstruction\n", "problems and often associated to regularization techniques. It is based on the iterative\n", "maximization of the log-likelihood function." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fix, ax = subplots(2,2, figsize=(8,8))\n", "ax[0,0].imshow(dummy_image)\n", "ax[0,1].imshow(dummy_blurred)\n", "ax[1,1].imshow(csr.dot(dummy_blurred.ravel()).reshape(mask.shape))\n", "ax[0,0].set_xlim(964,981)\n", "ax[0,0].set_ylim(0,16)\n", "ax[0,0].set_title(\"Dummy image\")\n", "ax[0,1].set_xlim(964,981)\n", "ax[0,1].set_ylim(0,16)\n", "ax[0,1].set_title(\"Convolved image (i.e. blurred)\")\n", "ax[1,1].set_xlim(964,981)\n", "ax[1,1].set_ylim(0,16)\n", "ax[1,1].set_title(\"Retro-projected of the blurred\")\n", "ax[1,0].set_title(\"Corrected image\")\n", "pass" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def iterMLEM_scipy(F, M, R):\n", " \"Implement one step of MLEM\"\n", " #res = F * (R.T.dot(M))/R.dot(F)# / M.sum(axis=-1)\n", " norm = 1/R.T.dot(numpy.ones_like(F)) \n", " cor = R.T.dot(M/R.dot(F))\n", " res = norm * F * cor\n", " res[numpy.isnan(res)] = 1.0\n", " return res\n", "\n", "def deconv_MLEM(csr, data, thres=0.2, maxiter=1000):\n", " R = csr.T\n", " msk = data<0\n", " img = data.astype(\"float32\")\n", " img[msk] = 0.0 # set masked values to 0, negative values could induce errors\n", " M = img.ravel()\n", " #F0 = numpy.random.random(data.size)#M#\n", " F0 = R.T.dot(M)\n", " F1 = iterMLEM_scipy(F0, M, R)\n", " delta = abs(F1-F0).max()\n", " for i in range(maxiter):\n", " if delta