{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "d792b258", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from smpl import plot\n", "from smpl import functions as fff\n", "import scipy" ] }, { "cell_type": "code", "execution_count": 2, "id": "1012faed", "metadata": {}, "outputs": [], "source": [ "\n", "from scipy.misc import derivative\n", "\n", "def trim_domain(f, \n", " fmin = np.finfo(np.float32).min/2,\n", " fmax = np.finfo(np.float32).max/2,\n", " steps=100000,\n", " min_ch=0.001\n", " ):\n", " test = np.linspace(fmin,fmax,steps)\n", " dr = derivative(f,test,dx=1e-06)\n", " m1 = np.abs(dr)>min_ch\n", " bmin=np.argmax(m1)\n", " m2=(np.abs(dr)>min_ch)[::-1]\n", " tbmax=np.argmax(m2)\n", " xmin = test[bmin]\n", " xmax=test[::-1][tbmax]\n", " if bmin == 0 and tbmax ==0 and not m1[0] and not m2[0]:\n", " # trisect\n", " tmin = xmin\n", " tmax = xmax\n", " t1a,t1b = trim_domain(f,tmin+ (tmax-tmin)/3,tmax -(tmax-tmin)/3,min_ch=min_ch)\n", " if np.isclose(t1a,t1b):\n", " t2a,t2b = trim_domain(f,tmin + (tmax-tmin)/3,tmax,min_ch=min_ch)\n", " if np.isclose(t2a,t2b):\n", " t3a,t3b = trim_domain(f,tmin ,tmax- (tmax-tmin)/3,min_ch=min_ch)\n", " if np.isclose(t3a,t3b):\n", " return 0.,0. \n", " else:\n", " return t3a,t3b \n", " else:\n", " return t2a,t2b\n", " else:\n", " return t1a,t1b\n", " return xmin,xmax\n", " \n", "def get_domain(f,\n", " fmin = np.finfo(np.float32).min/2,\n", " fmax = np.finfo(np.float32).max/2,\n", " steps=100000,\n", "):\n", " \"\"\"\n", " Return the domain of the function ``f``.\n", " \"\"\"\n", " \n", " test = np.linspace(fmin,fmax,steps)\n", " \n", " r = f(test)\n", " mask = np.isfinite(r) \n", " tr = test[mask]\n", " if len(tr)>0:\n", " tmin = np.amin(tr)\n", " tmax = np.amax(tr)\n", " test_r = np.linspace(tmin,tmax,steps)\n", " if np.equal(tr.shape , test_r.shape) and np.allclose(test_r,tr):\n", " return tmin,tmax\n", " \n", " # trisect\n", " tmin = fmin\n", " tmax = fmax\n", " t1a,t1b = get_domain(f,tmin+ (tmax-tmin)/3,tmax -(tmax-tmin)/3)\n", " if np.isclose(t1a,t1b):\n", " t2a,t2b = get_domain(f,tmin + (tmax-tmin)/3,tmax)\n", " if np.isclose(t2a,t2b):\n", " t3a,t3b = get_domain(f,tmin ,tmax- (tmax-tmin)/3)\n", " if np.isclose(t3a,t3b):\n", " return 0.,0. \n", " else:\n", " return t3a,t3b \n", " else:\n", " return t2a,t2b\n", " else:\n", " return t1a,t1b" ] }, { "cell_type": "code", "execution_count": 3, "id": "1f26f329", "metadata": {}, "outputs": [], "source": [ "def is_monotone(f,tmin=None,tmax=None,):\n", " \"\"\"\n", " Test if function ``f`` is monotone.\n", "\n", " Parameters\n", " ----------\n", " f : function\n", " Function to be tested.\n", " test : array_like\n", " Test points.\n", "\n", " Returns\n", " -------\n", " bool\n", " True if function is monotone.\n", " \"\"\"\n", " if tmax is None and tmin is None:\n", " tmin,tmax = get_domain(f)\n", " test = np.linspace(tmin,tmax,1000)\n", " return np.all(f(test[1:])>=f(test[:-1]))" ] }, { "cell_type": "code", "execution_count": 4, "id": "2c63a071", "metadata": {}, "outputs": [], "source": [ "def get_interesting_region(f,min_ch = 1e-4):\n", " \"\"\"\n", " Return interesting xmin and xmax of function ``f``.\n", " \"\"\"\n", " omin_x,omax_x = get_domain(f)\n", " if is_monotone(f,omin_x,omax_x):\n", " min_x,max_x=trim_domain(f,omin_x,omax_x,min_ch = min_ch)\n", " #min_x,max_x=omin_x,omax_x\n", " else:\n", " tmax_x= scipy.optimize.minimize(lambda x: -f(x),0.,method='Nelder-Mead',bounds=[(omin_x,omax_x)])\n", " tmin_x= scipy.optimize.minimize(f,0.,method='Nelder-Mead',bounds=[(omin_x,omax_x)])\n", " if tmax_x.success:\n", " tmax_x = tmax_x.x[0]\n", " else:\n", " tmax_x =0.\n", " if tmin_x.success:\n", " tmin_x = tmin_x.x[0]\n", " else:\n", " tmin_x =0.\n", " \n", " if abs(tmax_x) > np.finfo(np.float32).max/10:\n", " tmax_x = 0.\n", " if abs(tmin_x) > np.finfo(np.float32).max/10:\n", " tmin_x = 0.\n", " x_min = min(tmax_x,tmin_x)\n", " x_max = max(tmax_x,tmin_x)\n", " min_x = ((x_max+x_min)/2-(x_max-x_min))\n", " max_x = ((x_max+x_min)/2+(x_max-x_min))\n", " if np.isclose(min_x,max_x):\n", " min_x,max_x=trim_domain(f,omin_x,omax_x,min_ch = min_ch)\n", " \n", " print(min_x,max_x) \n", " return min_x,max_x" ] }, { "cell_type": "code", "execution_count": 5, "id": "496f262b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-1.7976931348623157e+308 1.7976931348623157e+308\n", "(-279.714718534727, 279.714718534727)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_24996/2162550493.py:47: RuntimeWarning: overflow encountered in exp\n", " r = f(test)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "False\n", "True\n" ] } ], "source": [ "f = np.exp\n", "print(np.finfo(np.float64).min,np.finfo(np.float64).max)\n", "print(get_domain(f))\n", "print(np.isclose(*get_domain(f)))\n", "print(is_monotone(f))" ] }, { "cell_type": "code", "execution_count": 6, "id": "a013ea38", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_24996/2086393400.py:2: RuntimeWarning: overflow encountered in exp\n", " return np.exp(x)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "-9.205503442012287 279.714718534727\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return np.exp(x)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 7, "id": "1abc83cc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-3.141625000000003 3.141625000000003\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return np.sin(x)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 8, "id": "9670f7b2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-7110043947.625 7110043947.625\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return x**2\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 9, "id": "b6b2b4b0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-7110043947.625 7110043947.625\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return x\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 10, "id": "c6f2ca25", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-1.5707812500000022 4.712343750000007\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return np.cos(x)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 11, "id": "61e80c0b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-55.056798617355525 55.056798617355525\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return np.arctan(x)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 12, "id": "4bedf8e2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-3.141592653589793 3.141592653589793\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " return np.tan(x)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": 13, "id": "dfa572ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-18.352266205940396 18.352266205707565\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ff(x):\n", " \"\"\"Lorentz\"\"\"\n", " return fff.lorentz(x,0,5,3,0)\n", "xmin,xmax =get_interesting_region(ff)\n", "plot.function(ff,xmin=xmin,xmax = xmax,logy=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "53bcb22c", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "537e7b69", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "6aeab8be", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 14, "id": "737597db", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from smpl import plot\n", "plot.function(lambda x: x**2,)" ] }, { "cell_type": "code", "execution_count": 15, "id": "1c1ad993", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_24996/2310528.py:3: RuntimeWarning: overflow encountered in exp\n", " return np.exp(x)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from smpl import plot\n", "def f(x):\n", " return np.exp(x)\n", "plot.function(f,label=\"exp\")" ] }, { "cell_type": "code", "execution_count": 16, "id": "3ad68d75", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from smpl import plot\n", "from smpl import functions as f\n", "def gauss(x):\n", " \"\"\"Gauss\"\"\"\n", " return f.gauss(x,0,1,3,0)\n", "plot.function(gauss)" ] }, { "cell_type": "code", "execution_count": null, "id": "391d3b01", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "c1cc74bf", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "a4a04f4b", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "92316862", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "ca89ba9f", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "9f9e4095", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "2942dd1e", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "795c3258", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "be81387b", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "63f48230", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "2dd51071", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "4225a289", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.9.13" } }, "nbformat": 4, "nbformat_minor": 5 }