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CoolProp/dev/IncompressibleLiquids/LinearAlgebra.ipynb

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{
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{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Linear algebra for multidimensional polynomial fitting"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import itertools\n",
"# A small data set\n",
"#T_in = np.array([20,24,35,40])+273.15\n",
"#x_in = np.array([47,55,70,78,82])/100.0\n",
"#rho_in = np.array([[1047,1033,1020,1000,990],[997,983,970,950,940],[947,933,920,900,895],[987,883,870,850,845]])\n",
"#\n",
"# large data set\n",
"T_in = np.array([ -45 , -40 , -35 , -30 , -25 , -20 , -15 , -10])+273.15 # Kelvin\n",
"x_in = np.array([ 5 , 10 , 15 , 20 , 25 , 30 , 35 ])/100.0 # mass fraction\n",
" \n",
"rho_in = np.array([\n",
" [1064.0, 1054.6, 1045.3, 1036.3, 1027.4, 1018.6, 1010.0],\n",
" [1061.3, 1052.1, 1043.1, 1034.3, 1025.6, 1017.0, 1008.6],\n",
" [1057.6, 1048.8, 1040.1, 1031.5, 1023.1, 1014.8, 1006.7],\n",
" [1053.1, 1044.6, 1036.2, 1028.0, 1019.9, 1012.0, 1004.1],\n",
" [1047.5, 1039.4, 1031.5, 1023.7, 1016.0, 1008.4, 1000.9],\n",
" [1040.7, 1033.2, 1025.7, 1018.4, 1011.2, 1004.0, 997.0],\n",
" [1032.3, 1025.3, 1018.5, 1011.7, 1005.1, 998.5, 992.0],\n",
" [1021.5, 1015.3, 1009.2, 1003.1, 997.1, 991.2, 985.4]]) # kg/m3"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Minimizing the squared error $\\epsilon(\\mathbf{c}) = \\sqrt{\\sum (\\mathbf{z} - \\mathbf{A} \\cdot \\mathbf{c})^2 }$ can be achieved by solving the system of orthogonal equations given by $\\mathbf{A}^\\text{T}\\mathbf{A} \\cdot \\mathbf{c} =\\mathbf{A}^\\text{T}\\mathbf{z}$. Using Python tools, we can leave this to the software and we only have to construct the Van der Monde matrix $\\mathbf{A}$ of the independent variable and equate it with the result vector of the dependent variable."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def getCoeffs1d(x,z,order):\n",
" if (len(x)<order+1): \n",
" raise ValueError(\"You have only {0} elements and try to fit {1} coefficients, please reduce the order.\".format(len(x),order+1))\n",
" A = np.vander(x,order+1)[:,::-1]\n",
" #Anew = np.dot(A.T,A)\n",
" #znew = np.dot(A.T,z)\n",
" #coeffs = np.linalg.solve(Anew, znew)\n",
" coeffs = np.linalg.lstsq(A, z)[0]\n",
" return coeffs\n",
"\n",
"xorder = 2\n",
"x = T_in[0:4]#T_in#T_in[0:4]#\n",
"z = rho_in[0:4,0]#rho_in#rho_in[0:4,0]#\n",
"coeffs = getCoeffs1d(x,z,xorder)\n",
"print coeffs\n",
"zf = np.polynomial.polynomial.polyval(x,coeffs)\n",
"print z[0]\n",
"print zf[0]\n",
"print z[-1]\n",
"print zf[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[ 2.31559095e+02 7.75540000e+00 -1.80000000e-02]\n",
"1064.0\n",
"1064.01\n",
"1053.1\n",
"1053.09\n"
]
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can extend the whole procedure to 2D, given that we have a solution matrix $\\mathbf{Z}$ instead of a vector. Since this potentially involves a large number of coefficients, we disregard the higher order terms in order to avoid overfitting. This is done by discarding terms with a sum of exponents higher than the largest single exponent. The pair of exponents for elements $\\mathbf{x}$ and $\\mathbf{y}$, $i$ and $j$, has to satisfy $ i+j \\leq \\max(k,l)$ with $k$ and $l$ being the highest exponents in $x$ and $y$ direction respectively. The matrix of exponent pairs $\\mathbf{E}$ for $k<l$ is therefore defined as $$ \\mathbf{E}_{i,j} =\n",
" \\begin{pmatrix}\n",
" (0,0) & (0,1) & \\cdots & \\cdots & \\cdots & (0,l) \\\\\n",
" (1,0) & \\ddots & & & (1,l-1) & (0,0) \\\\\n",
" \\vdots & & & \\udots & \\udots & \\vdots \\\\\n",
" (k,0) & \\cdots & (k,l-k) & (0,0) & \\cdots & (0,0) \n",
" \\end{pmatrix}\n",
" \\text{ yielding, for example, }\n",
" \\begin{pmatrix}\n",
" (0,0) & (0,1) & (0,2) & (0,3) & (0,4) \\\\\n",
" (1,0) & (1,1) & (1,2) & (1,3) & (0,0) \\\\\n",
" (2,0) & (2,1) & (2,2) & (0,0) & (0,0) \n",
" \\end{pmatrix}\n",
" \\text{ for $k=2$ and $l=4$. }\n",
" $$\n",
"Following the matrix notation would result in a 4-dimensional functional matrix from the Cartesian product of all elements of $\\mathbf{E}$ and the input vectors $\\mathbf{x}$ and $\\mathbf{y}$. However, having many linear algebra solvers available in 2D, it is more practical to manually reduce the dimensionality of $\\mathbf{A}$ to two. Each row of $\\mathbf{A}$ corresponds to an unique pair elements of the input vectors $\\mathbf{x}$ and $\\mathbf{y}$. Evaluating the resulting expression $x_n^i y_n^j$ for all non-zero entries of $\\mathbf{E}$ fills the columns of $\\mathbf{A}$ with values. Every row of $\\mathbf{A}$ can therefore be mapped to an entry in the solution matrix $\\mathbf{Z}$. A data set consisting of 10 entries in $x$ and 20 in $y$ requires $\\mathbf{Z}$ to have 200 elements and thus $\\mathbf{A}$ to have 200 rows. The example given above, $k=2$ and $l=4$, leads to 10 columns in $\\mathbf{A}$. After minimizing $\\epsilon(\\mathbf{c})$, information from $\\mathbf{E}$ can be used to convert the coefficient vector $\\mathbf{c}$ to a matrix to be used with two-dimensional polynomials."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def getCoeffs2dmatrix(x_in,y_in,z_in,x_order,y_order):\n",
" \n",
" x_order += 1\n",
" y_order += 1\n",
" \n",
" #To avoid overfitting, we only use the upper left triangle of the coefficient matrix\n",
" x_exp = range(x_order)\n",
" y_exp = range(y_order)\n",
" limit = max(x_order,y_order)\n",
" \n",
" xy_exp = []\n",
" \n",
" # Construct the upper left triangle of coefficients \n",
" for i in x_exp:\n",
" for j in y_exp:\n",
" if(i+j<limit): xy_exp.append((i,j))\n",
" \n",
" x_num = len(x_in)\n",
" y_num = len(y_in)\n",
" \n",
" cols = len(xy_exp)\n",
" eqns = x_num * y_num\n",
" #if (eqns<cols):\n",
" # raise ValueError(\"You have only {0} equations and try to fit {1} coefficients, please reduce the order.\".format(eqns,cols)) \n",
" if (x_num<x_order):\n",
" raise ValueError(\"You have only {0} x-entries and try to fit {1} x-coefficients, please reduce the x_order.\".format(x_num,x_order))\n",
" if (y_num<y_order):\n",
" raise ValueError(\"You have only {0} y-entries and try to fit {1} y-coefficients, please reduce the y_order.\".format(y_num,y_order))\n",
" \n",
" #Create functional matrix\n",
" A = np.zeros((x_num,y_num,x_order,y_order))\n",
" for i in range(x_num):\n",
" for j in range(y_num):\n",
" for (xk,yk) in xy_exp:\n",
" A[i][j][xk][yk] = x[i]**xk * y[j]**yk\n",
" \n",
" raise NotImplementedError(\"No 4-dimensional solver implemented\")\n",
" \n",
" \n",
"def getCoeffs2d(x_in,y_in,z_in,x_order,y_order):\n",
" \n",
" x_order += 1\n",
" y_order += 1\n",
" \n",
" #To avoid overfitting, we only use the upper left triangle of the coefficient matrix\n",
" x_exp = range(x_order)\n",
" y_exp = range(y_order)\n",
" limit = max(x_order,y_order)\n",
" \n",
" xy_exp = []\n",
" \n",
" # Construct the upper left triangle of coefficients \n",
" for i in x_exp:\n",
" for j in y_exp:\n",
" if(i+j<limit): xy_exp.append((i,j))\n",
" \n",
" # Construct input pairs \n",
" xx, yy = np.meshgrid(x_in,y_in,indexing='ij')\n",
" xx = np.array(xx.flat)\n",
" yy = np.array(yy.flat)\n",
" zz = np.array(z_in.flat)\n",
" \n",
" x_num = len(x_in)\n",
" y_num = len(y_in)\n",
" \n",
" cols = len(xy_exp)\n",
" eqns = x_num * y_num\n",
" #if (eqns<cols):\n",
" # raise ValueError(\"You have only {0} equations and try to fit {1} coefficients, please reduce the order.\".format(eqns,cols)) \n",
" if (x_num<x_order):\n",
" raise ValueError(\"You have only {0} x-entries and try to fit {1} x-coefficients, please reduce the x_order.\".format(x_num,x_order))\n",
" if (y_num<y_order):\n",
" raise ValueError(\"You have only {0} y-entries and try to fit {1} y-coefficients, please reduce the y_order.\".format(y_num,y_order))\n",
" \n",
" # Build the functional matrix\n",
" A = np.zeros((eqns,cols))\n",
" for i in range(eqns): # row loop\n",
" for j, (xj,yj) in enumerate(xy_exp): # makes columns\n",
" A[i][j] = xx[i]**xj * yy[i]**yj\n",
" \n",
" coeffs = np.linalg.lstsq(A, zz)[0]\n",
" \n",
" #Rearrange coefficients to a matrix shape\n",
" C = np.zeros((x_order,y_order))\n",
" for i, (xi,yi) in enumerate(xy_exp): # makes columns\n",
" C[xi][yi] = coeffs[i]\n",
" \n",
" return C\n",
"\n",
"xorder = 3\n",
"yorder = 3\n",
"\n",
"x = T_in\n",
"y = x_in\n",
"z = rho_in\n",
"\n",
"coeffs = getCoeffs2d(x,y,z,xorder,yorder)\n",
"print coeffs\n",
"\n",
"print z[0][0]\n",
"print np.polynomial.polynomial.polyval2d(x[0],y[0],coeffs)\n",
"\n",
"print z[-1][-1]\n",
"print np.polynomial.polynomial.polyval2d(x[-1],y[-1],coeffs)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[ 4.13353531e+03 1.18712872e+03 1.46361848e+02 -8.33333333e+00]\n",
" [ -4.16716735e+01 -1.29148475e+01 -4.77324263e-01 0.00000000e+00]\n",
" [ 1.91354824e-01 3.00850340e-02 0.00000000e+00 0.00000000e+00]\n",
" [ -2.95815296e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00]]\n",
"1064.0\n",
"1064.01648212\n",
"985.4\n",
"985.391852058\n"
]
}
],
"prompt_number": 42
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline\n",
"import matplotlib\n",
"matplotlib.rcParams['savefig.dpi'] = 2 * matplotlib.rcParams['savefig.dpi']\n",
"from mpl_toolkits.mplot3d import Axes3D\n",
"\n",
"# Construct input pairs \n",
"xx, yy = np.meshgrid(x,y,indexing='ij')\n",
"xx = np.array(xx.flat)\n",
"yy = np.array(yy.flat)\n",
"zz = np.array(z.flat)\n",
"\n",
"zf = np.polynomial.polynomial.polyval2d(xx,yy,coeffs)\n",
"\n",
"fig = plt.figure()\n",
"ax = plt.axes(projection='3d')\n",
"ax.scatter(xx, yy, zz, color='blue', label='Original data')\n",
"ax.scatter(xx, yy, zf, color='red', label='Fitted data')\n",
"#ax.plot(xx[0], yy[0], zs=zz[0], label='Fitted line', zdir='z')\n",
"ax.legend()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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HEwgqzSpEAcwsNsDQjTUwMABVVbU3zmQyqUujZUeAUyKRQCKRQCAQyOkfVC6x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XdZ+PWLSMt64hRB5ItMoih+qtZ1RmJVLsrhjheF1h8YO6JbVlaWcUCpo6MDQRASktja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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0xb0137ec>"
]
}
],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}