{ "cells": [ { "cell_type": "markdown", "id": "cc613597-a097-4666-8828-58a2c4409a61", "metadata": {}, "source": [ "# Superancillary functions\n", "\n", "TODO: object hierarchy\n", "\n", "TODO: rough description of algorithms" ] }, { "cell_type": "code", "execution_count": 1, "id": "e65a1364", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:32.023155Z", "iopub.status.busy": "2025-01-06T11:32:32.022928Z", "iopub.status.idle": "2025-01-06T11:32:32.291923Z", "shell.execute_reply": "2025-01-06T11:32:32.291594Z" } }, "outputs": [], "source": [ "import json\n", "import timeit\n", "import tarfile\n", "import functools\n", "import itertools\n", "from dataclasses import dataclass\n", "\n", "import numpy as np \n", "import matplotlib.pyplot as plt\n", "\n", "import ChebTools\n", "import teqpflsh\n", "import CoolProp.CoolProp as CP" ] }, { "cell_type": "markdown", "id": "75b38e42-6e91-46ed-973d-d759b365806f", "metadata": {}, "source": [ "Build a superancillary function for water\n", "\n", "To begin, load from the provided files:\n", "\n", "* $\\rho'(T)$\n", "* $\\rho''(T)$\n", "* $p(T)$\n", "\n", "And then use the EOS (as implemented in CoolProp, but REFPROP would be fine too) to add\n", "\n", "* $h'(T)$, $h''(T)$\n", "* $s'(T)$, $s''(T)$\n", "* $u'(T)$, $u''(T)$" ] }, { "cell_type": "code", "execution_count": 2, "id": "9df81f71-d329-4b60-b4f0-f9323cad6f04", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:32.293592Z", "iopub.status.busy": "2025-01-06T11:32:32.293480Z", "iopub.status.idle": "2025-01-06T11:32:32.684805Z", "shell.execute_reply": "2025-01-06T11:32:32.684531Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Water has non-monotonic rho'(T). The monotonic intervals are:\n", "(273.16, 277.15003423906836) K\n", "(277.15003423906836, 647.0959999999867) K\n" ] } ], "source": [ "FLD = 'WATER'\n", "with tarfile.open('superancillaryJSON.tar.xz', mode='r:xz') as tar:\n", " # for member in tar.getmembers(): print(member)\n", " j = json.load(tar.extractfile(f'./{FLD}_exps.json'))\n", "sa = teqpflsh.SuperAncillary(json.dumps(j))\n", "\n", "ca = sa.get_approx1d(k='D', q=0)\n", "print('Water has non-monotonic rho\\'(T). The monotonic intervals are:')\n", "for inter in ca.monotonic_intervals:\n", " print(f'({inter.xmin}, {inter.xmax}) K')" ] }, { "cell_type": "code", "execution_count": 3, "id": "17aeac7b-62d5-4b67-b074-2a9919923beb", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:32.686034Z", "iopub.status.busy": "2025-01-06T11:32:32.685945Z", "iopub.status.idle": "2025-01-06T11:32:32.704768Z", "shell.execute_reply": "2025-01-06T11:32:32.704518Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "add_variable(self, *, k: str, caller: collections.abc.Callable[[float, float], float]) -> None\n" ] } ], "source": [ "AS = CP.AbstractState('HEOS', 'Water')\n", "def calc(T, rho, AS, key):\n", " AS.specify_phase(CP.iphase_gas)\n", " AS.update(CP.DmolarT_INPUTS, rho, T)\n", " val = AS.keyed_output(key)\n", " AS.unspecify_phase()\n", " return val\n", "\n", "# Add another thermodynamic variable to the superancillary\n", "# Speed is order of ms per variable, likely MUCH faster in C++\n", "# caller is a callable function that takes temperature and density and returns a value of a given property type\n", "# here we can avoid flash calculations because we take T,rho value from the superancillary and \n", "# get values for the \"other\" variable\n", "sa.add_variable(k='H', caller=functools.partial(calc, AS=AS, key=CP.iHmolar))\n", "sa.add_variable(k='S', caller=functools.partial(calc, AS=AS, key=CP.iSmolar))\n", "sa.add_variable(k='U', caller=functools.partial(calc, AS=AS, key=CP.iUmolar))\n", "\n", "# Here is the call signature for the method\n", "print(sa.add_variable.__doc__)" ] }, { "cell_type": "code", "execution_count": 4, "id": "2b52ebc8", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:32.705908Z", "iopub.status.busy": "2025-01-06T11:32:32.705829Z", "iopub.status.idle": "2025-01-06T11:32:33.010862Z", "shell.execute_reply": "2025-01-06T11:32:33.010578Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The monotonic intervals are:\n", "(273.16, 277.15003423906836) K\n", "(277.15003423906836, 647.0959999999867) K\n", "T at extrema in rho(T): [277.15003423906836] K\n", "and corresponding value 55504.316178396366 mol/m³\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Solving for temperature given saturated liquid density, around the density maximum\n", "# as a challenging test for the rootfinding. The approach works well, even very close(!) \n", "# to the extremum\n", "\n", "ca = sa.get_approx1d(k='D', q=0)\n", "print('The monotonic intervals are:')\n", "for inter in ca.monotonic_intervals:\n", " print(f'({inter.xmin}, {inter.xmax}) K')\n", "\n", "print('T at extrema in rho(T):', ca.x_at_extrema, 'K')\n", "print('and corresponding value', ca.eval(ca.x_at_extrema[0]), 'mol/m³')\n", "\n", "plt.figure()\n", "Trange = np.linspace(-10, 10) + ca.x_at_extrema[0]\n", "plt.plot(Trange, [ca.eval(T) for T in Trange])\n", "plt.gca().set(xlabel=r'$T$ / K', ylabel=r'$\\rho$ / mol/m$^3$')\n", "\n", "# Starting at a density below the extremum, test getting\n", "# very close to the extremum and solving for temperature\n", "\n", "plt.figure()\n", "y_extremum = ca.eval(ca.x_at_extrema[0])\n", "delta = y_extremum - 0.9999*y_extremum\n", "\n", "while delta > 1e-13:\n", " # First output argument is the solution, second is the number of iterations required\n", " Tsoln = ca.get_x_for_y(y=y_extremum-delta)\n", " \n", " if len(Tsoln) != 2:\n", " break\n", " if Tsoln[0][0] > Tsoln[1][0]:\n", " break\n", " \n", " delta /= 1.1\n", " plt.plot(delta, Tsoln[0][0]-ca.x_at_extrema[0], 'ro')\n", " plt.plot(delta, Tsoln[1][0]-ca.x_at_extrema[0], 'bx')\n", " \n", "plt.xscale('log')\n", "plt.yscale('symlog')\n", "plt.gca().set(xlabel=r'$\\rho-\\rho_{\\rm extremum}$ / mol/m$^3$', ylabel=r'$T-T_{\\rm extremum}$ / K')\n", "plt.title(r'$T(\\rho)$ which should have two solutions for all $\\rho < \\rho_{\\rm extremum}$')\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 5, "id": "6bc4219d", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:33.012260Z", "iopub.status.busy": "2025-01-06T11:32:33.012155Z", "iopub.status.idle": "2025-01-06T11:32:34.134759Z", "shell.execute_reply": "2025-01-06T11:32:34.134496Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "rho(T) takes 0.016125665977597237 μs/call\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "T(rho) takes 0.6450482499785721 μs/call\n", "so the inversion is much slower, and here there are two candidate regions, so it is again two times worse than normal fluids, which would be more like:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "T(rho) takes 0.45679099997505546 μs/call when there is only one solution\n" ] } ], "source": [ "# Time forward evalution of a chebyshev expansion\n", "T = np.linspace(273.16, 290, 1000000)\n", "ybuf = np.zeros_like(T)\n", "tic = timeit.default_timer()\n", "ca.eval_many(T, ybuf)\n", "toc = timeit.default_timer()\n", "print('rho(T) takes', (toc-tic)/len(T)*1e6, 'μs/call')\n", "\n", "# Time the rootfinding in the superancillary\n", "tic = timeit.default_timer()\n", "ybuf = np.linspace(55400, 55503, 1000000)\n", "xbuf = np.zeros_like(ybuf)\n", "ca.count_x_for_y_many(ybuf, 64, 100, 1e-10, xbuf)\n", "toc = timeit.default_timer()\n", "print('T(rho) takes', (toc-tic)/len(xbuf)*1e6, 'μs/call')\n", "print('so the inversion is much slower, and here there are two candidate regions, so it is again two times worse than normal fluids, which would be more like:')\n", "\n", "tic = timeit.default_timer()\n", "ybuf = np.linspace(20400, 20503, 1000000)\n", "xbuf = np.zeros_like(ybuf)\n", "ca.count_x_for_y_many(ybuf, 64, 100, 1e-10, xbuf)\n", "toc = timeit.default_timer()\n", "print('T(rho) takes', (toc-tic)/len(xbuf)*1e6, 'μs/call when there is only one solution')" ] }, { "cell_type": "markdown", "id": "938b8f8d-2d82-4395-aadb-efb4f6888c7e", "metadata": {}, "source": [ "Rootfinding is based on the TOMS748 method, which is an advanced version of the Brent method that is bounded and uses the optimal combination of secant, quadratic, and cubic interpolation mixed with bisection." ] }, { "cell_type": "code", "execution_count": 6, "id": "1338ce45-8aa4-4da9-8c3b-ae9a684a8382", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:34.136218Z", "iopub.status.busy": "2025-01-06T11:32:34.136124Z", "iopub.status.idle": "2025-01-06T11:32:34.138184Z", "shell.execute_reply": "2025-01-06T11:32:34.137921Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "7 iterations were required\n" ] } ], "source": [ "T_K, steps = ca.get_x_for_y(y=20250)[0]\n", "print(f'{steps} iterations were required')" ] }, { "cell_type": "markdown", "id": "cc4bcdc8-fb44-4738-99ec-b3b62ca2e684", "metadata": {}, "source": [ "which is about that much higher than the forward evaluation of a superancillary itself" ] }, { "cell_type": "code", "execution_count": 7, "id": "0daccc7c", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:34.139350Z", "iopub.status.busy": "2025-01-06T11:32:34.139275Z", "iopub.status.idle": "2025-01-06T11:32:34.241798Z", "shell.execute_reply": "2025-01-06T11:32:34.241573Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.005306542036123574 μs/call\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ca = sa.get_approx1d(k='D', q=0)\n", "rhoc = ca.monotonic_intervals[1].ymin\n", "\n", "# Pick a density where there is only one possible solution for temperature\n", "for D in [22082.571366851185]:\n", "\n", " # Get the saturation temperature, if possible\n", " Tlims = [_ for _ in ca.get_x_for_y(y=D)]\n", " if len(Tlims) == 1:\n", " Trange = [ca.expansions[0].xmin, Tlims[0][0]]\n", " else:\n", " Trange = [Tlims[0][0], Tlims[1][0]]\n", " \n", " Ts = np.linspace(*Trange, 100000)\n", " # Non-iteratively solve for q for value of density\n", " q = np.array([sa.get_vaporquality(T=T_, propval=D, k='D') for T_ in Ts])\n", "\n", " fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)\n", " # And then plot another property\n", " y = np.zeros_like(q)\n", " tic = timeit.default_timer()\n", " sa.get_yval_many(q=q, T=Ts, k='H', y=y)\n", " toc = timeit.default_timer()\n", " print((toc-tic)/len(T)*1e6, 'μs/call')\n", " ax1.plot(Ts, q,)\n", " ax2.plot(Ts, y, label=D)\n", " ax1.set(ylabel='$q$ (vapor quality)')\n", " ax2.set(xlabel='$T$ / K', ylabel='$h$ / J/mol')" ] }, { "cell_type": "markdown", "id": "0567c710", "metadata": {}, "source": [ "Plot lines of constant quality in the two-phase region according to the superancillary functions" ] }, { "cell_type": "code", "execution_count": 8, "id": "ee4a928e-5e37-4237-afd5-a62ffb35e9d6", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:34.243107Z", "iopub.status.busy": "2025-01-06T11:32:34.243025Z", "iopub.status.idle": "2025-01-06T11:32:34.250042Z", "shell.execute_reply": "2025-01-06T11:32:34.249787Z" } }, "outputs": [], "source": [ "eps = 1e-6\n", "Tt = 273.16\n", "Tc = 647.0959999999867\n", "\n", "for T in np.linspace(Tt, Tc-eps, 10000):\n", " p = sa.get_yval(T=T, q=1, k='P')\n", " Tnew = sa.get_T_from_p(p=p)\n", " DELTAT = Tnew-T\n", " if abs(DELTAT) > 0.001:\n", " print(T, p, Tnew-T)" ] }, { "cell_type": "code", "execution_count": 9, "id": "88ee67da", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:34.251183Z", "iopub.status.busy": "2025-01-06T11:32:34.251103Z", "iopub.status.idle": "2025-01-06T11:32:34.382835Z", "shell.execute_reply": "2025-01-06T11:32:34.382576Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.2694700808656397 17873.7282300601 [(437.3594696512889, 10)]\n", "1.4787499094381928 μs/call from 5.3 steps on average\n", "1.970840385183692 μs/call from 8.17 steps on average\n", "2.230409882031381 μs/call from 9.6 steps on average\n", "2.2991601144894958 μs/call from 10.12 steps on average\n", "2.3312499979510903 μs/call from 10.27 steps on average\n", "2.40708002820611 μs/call from 10.58 steps on average\n", "2.4075002875179052 μs/call from 10.59 steps on average\n", "2.4258403573185205 μs/call from 10.79 steps on average\n", "2.9266695491969585 μs/call from 10.46 steps on average\n", "2.4391600163653493 μs/call from 9.92 steps on average\n", "1.431250129826367 μs/call from 5.23 steps on average\n", "1.4441600069403648 μs/call from 5.32 steps on average\n", "1.497499761171639 μs/call from 5.2 steps on average\n", "1.4208396896719933 μs/call from 5.19 steps on average\n", "1.4154094969853759 μs/call from 5.2 steps on average\n", "1.4266703510656953 μs/call from 5.25 steps on average\n", "1.413749996572733 μs/call from 5.23 steps on average\n", "1.5320797683671117 μs/call from 5.3 steps on average\n", "1.4416599879041314 μs/call from 5.36 steps on average\n", "1.4595797983929515 μs/call from 5.56 steps on average\n", "1.5179102774709463 μs/call from 5.65 steps on average\n", "1.5229103155434132 μs/call from 5.7 steps on average\n", "1.5283300308510661 μs/call from 5.79 steps on average\n", "1.5508296201005578 μs/call from 5.95 steps on average\n", "1.604580320417881 μs/call from 6.03 steps on average\n", "1.5791598707437515 μs/call from 6.08 steps on average\n", "1.590839819982648 μs/call from 6.13 steps on average\n", "1.5712500317022204 μs/call from 6.05 steps on average\n", "1.6354199033230543 μs/call from 6.2 steps on average\n", "1.5858298866078258 μs/call from 6.12 steps on average\n", "1.5791598707437515 μs/call from 6.11 steps on average\n", "1.5845795860514045 μs/call from 6.15 steps on average\n", "1.5899998834356666 μs/call from 6.2 steps on average\n", "1.6104202950373292 μs/call from 6.3 steps on average\n", "1.736659905873239 μs/call from 6.71 steps on average\n", "1.7420802032575011 μs/call from 6.94 steps on average\n", "1.8787500448524952 μs/call from 7.27 steps on average\n", "1.9300001440569758 μs/call from 7.41 steps on average\n", "1.8570898100733757 μs/call from 7.45 steps on average\n", "1.9204203272238374 μs/call from 8.04 steps on average\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "caV = sa.get_approx1d(k='D', q=1)\n", "# for interval in caV.monotonic_intervals:\n", "# print(interval)\n", "# print({k: getattr(interval,k) for k in dir(interval) if not k.startswith('__')})\n", "# for m in interval.expansioninfo:\n", "# print({k: getattr(m,k) for k in dir(m) if not k.startswith('__')})\n", "# print(m.xmin, m.xmax)\n", "print(caV.eval(273.16), caV.eval(647.096), caV.get_x_for_y(y=200))\n", "\n", "# print([0].ymin, caV.monotonic_intervals[0].ymax)\n", "# print(caV.get_x_for_y(y=200))\n", "\n", "ca = sa.get_approx1d(k='D', q=0)\n", "y = ca.eval(ca.x_at_extrema[0])*0.9999\n", "Tlims = [_[0] for _ in ca.get_x_for_y(y=y)]\n", "\n", "Ts = np.linspace(ca.expansions[0].xmin+1e-6, ca.expansions[-1].xmax-1e-6, 100)\n", "# Ts = np.linspace(273.1600001, 280, 10000)\n", "\n", "for Q in np.arange(1e-6, 1.0000, 0.1, dtype=float).tolist() + np.logspace(-8, -1, 30).tolist():\n", " Qs = Q*np.ones_like(Ts)\n", " \n", " rho = np.zeros_like(Ts)\n", " sa.get_yval_many(T=Ts, q=Qs, k='D', y=rho)\n", " \n", " other = np.zeros_like(Ts)\n", " kother = 'S'\n", " sa.get_yval_many(T=Ts, q=Qs, k=kother, y=other)\n", " plt.plot(1/rho, other)\n", " \n", " Tbuf = np.zeros_like(Ts)\n", " qbuf = np.zeros_like(Ts)\n", " countbuf = np.zeros_like(Ts)\n", " tic = timeit.default_timer()\n", " sa.solve_for_Tq_DX_many(rho, other, kother, 64, 100, 1e-10, Tbuf, qbuf, countbuf)\n", " toc = timeit.default_timer()\n", " print((toc-tic)/len(Tbuf)*1e6, 'μs/call from', np.mean(countbuf), 'steps on average')\n", " \n", " for T_goal_, rho_, other_ in zip(Ts, rho, other):\n", " soln = sa.solve_for_Tq_DX(rho_, other_, kother, 64, 100, 1e-10)\n", " try:\n", " T_ = soln.T; q_ = soln.q; count_ = soln.counter\n", " except BaseException as be:\n", " print(rho_, other_)\n", " print(be, T_goal_, Q)\n", " plt.plot(1/rho_, other_, 'o')\n", " \n", "# plt.yscale('log')\n", "plt.xscale('log')" ] }, { "cell_type": "code", "execution_count": 10, "id": "7444ff7e-a446-4b55-860e-346411492b5a", "metadata": { "execution": { "iopub.execute_input": "2025-01-06T11:32:34.384113Z", "iopub.status.busy": "2025-01-06T11:32:34.384011Z", "iopub.status.idle": "2025-01-06T11:32:37.142005Z", "shell.execute_reply": "2025-01-06T11:32:37.141738Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "TwoPhaseResult(Terr=0.0, Qerr=2.795420235938882e-16, elap_us=0.05967111326754093, count=0.0, proppair=['D', 'T'])\n", "TwoPhaseResult(Terr=0.0, Qerr=8.929621463779706e-16, elap_us=0.06645833336127302, count=0.0, proppair=['T', 'U'])\n", "TwoPhaseResult(Terr=0.0, Qerr=1.1279329866925603e-15, elap_us=0.06656027981080115, count=0.0, proppair=['S', 'T'])\n", "TwoPhaseResult(Terr=0.0, Qerr=7.645675477278846e-16, elap_us=0.06656500006405015, count=0.0, proppair=['H', 'T'])\n", "TwoPhaseResult(Terr=7.164476301113609e-13, Qerr=7.684752486105178e-10, elap_us=0.12980527981805304, count=0.0, proppair=['D', 'P'])\n", "TwoPhaseResult(Terr=7.164476301113609e-13, Qerr=7.684694347776641e-10, elap_us=0.1314924998829762, count=0.0, proppair=['P', 'S'])\n", "TwoPhaseResult(Terr=7.164476301113609e-13, Qerr=7.684689638248323e-10, elap_us=0.13159055340414247, count=0.0, proppair=['P', 'U'])\n", "TwoPhaseResult(Terr=7.164476301113609e-13, Qerr=7.684687278664324e-10, elap_us=0.13510666671209037, count=0.0, proppair=['H', 'P'])\n", "TwoPhaseResult(Terr=9.051291272044182e-14, Qerr=2.2156901951207798e-11, elap_us=2.0759752734253807, count=0.0, proppair=['S', 'U'])\n", "TwoPhaseResult(Terr=1.6613512343610638e-13, Qerr=1.0721330329692832e-10, elap_us=2.202141946569706, count=0.0, proppair=['H', 'S'])\n", "TwoPhaseResult(Terr=2.3948511322184155e-14, Qerr=2.2876501559810492e-11, elap_us=2.232273886911571, count=0.0, proppair=['D', 'S'])\n", "TwoPhaseResult(Terr=2.379654991576293e-14, Qerr=1.6898106011334103e-11, elap_us=2.3842438865297786, count=0.0, proppair=['D', 'U'])\n", "TwoPhaseResult(Terr=2.4474881380835237e-14, Qerr=1.7895061607415564e-11, elap_us=2.4198447268766663, count=0.0, proppair=['D', 'H'])\n" ] } ], "source": [ "eps = 1e-6\n", "\n", "Tt = 273.16\n", "Tc = 647.0959999999867\n", "\n", "# A class storing the info for a single two-phase point\n", "@dataclass\n", "class TwoPhasePoint:\n", " T: float\n", " Q: float\n", " D: float\n", " H: float\n", " S: float\n", " U: float\n", " P: float\n", "\n", "@dataclass\n", "class TwoPhaseResult:\n", " Terr: float\n", " Qerr: float\n", " elap_us: float\n", " count: float\n", " proppair: list[str]\n", "\n", "# Build up database of points for two-phase data\n", "points = []\n", "for T in np.linspace(Tt, Tc-eps, 300):\n", " for q in np.linspace(eps, 1-eps, 500):\n", " pt = TwoPhasePoint(\n", " T = T, \n", " Q = q,\n", " P = sa.get_yval(T=T, q=q, k='P'),\n", " D = sa.get_yval(T=T, q=q, k='D'),\n", " H = sa.get_yval(T=T, q=q, k='H'),\n", " S = sa.get_yval(T=T, q=q, k='S'),\n", " U = sa.get_yval(T=T, q=q, k='U')\n", " )\n", " points.append(pt)\n", "\n", "keys = ['D', 'H', 'S', 'U', 'P', 'T']\n", "\n", "results = []\n", "for proppair in itertools.combinations(keys, 2):\n", " proppair = sorted(proppair)\n", " if proppair == ['H', 'U']: continue\n", " if proppair == ['P', 'T']: continue\n", " \n", " val1 = np.array([getattr(pt, proppair[0]) for pt in points])\n", " val2 = np.array([getattr(pt, proppair[1]) for pt in points])\n", " \n", " flash_key = teqpflsh.get_pair_from_chars(*proppair)\n", " tic = timeit.default_timer()\n", " T = np.zeros_like(val1)\n", " q = np.zeros_like(val2)\n", " count = np.zeros_like(val2, dtype=int)\n", " sa.flash_many(flash_key, val1, val2, T, q, count)\n", " toc = timeit.default_timer()\n", " \n", " valQ = np.array([getattr(pt, 'Q') for pt in points])\n", " valT = np.array([getattr(pt, 'T') for pt in points])\n", "\n", " DELTAT = np.abs((valT-T))\n", " badsolns = sum(T < 0) # \n", " \n", " results.append(TwoPhaseResult(\n", " elap_us=(toc-tic)/len(val1)*1e6,\n", " Terr=float(np.mean(np.abs((valT-T)))),\n", " Qerr=float(np.mean(np.abs((valQ-q)))),\n", " count=float(np.mean(count)),\n", " proppair=proppair\n", " ))\n", "\n", "for el in sorted(results, key=lambda x: x.elap_us):\n", " print(el)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 5 }