{ "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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", 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" ] }, "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= 172µm, 172µm\t BottomRight (3)\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 /home/edgar1993a/miniforge3/envs/edgar/lib/python3.11/site-packages (0.60.0)\n", "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /home/edgar1993a/miniforge3/envs/edgar/lib/python3.11/site-packages (from numba) (0.43.0)\n", "Requirement already satisfied: numpy<2.1,>=1.22 in /home/edgar1993a/miniforge3/envs/edgar/lib/python3.11/site-packages (from numba) (1.26.4)\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 8.26 times longer than the fastest. This could mean that an intermediate result is being cached.\n", "7.27 μs ± 7.97 μs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", "8.15 μs ± 183 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 3.12 s, sys: 79.9 ms, total: 3.2 s\n", "Wall time: 3.2 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 30 s, sys: 113 ms, total: 30.1 s\n", "Wall time: 30 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 13.4 s, sys: 46.7 ms, total: 13.5 s\n", "Wall time: 1.08 s\n", "(1, 30, 0.0046368041028449205, 0.0005109819474116924, 2.1354864217638663, 4.833787403420624, 2175.569104133437)\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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", "text/plain": [ "
" ] }, "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