tests.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/benneti/repos/journalfeed2pdf/src/journalfeed/LaTeX.py:158: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
      "  ret = BeautifulSoup(s, \"html.parser\").get_text(strip=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'$\\\\_$'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.journalfeed.LaTeX import *\n",
    "from bs4 import BeautifulSoup  # used to get rid of HTML stuff\n",
    "# import html2text\n",
    "\n",
    "from src.journalfeed.config import load_config\n",
    "import src.journalfeed.arxiv as arxiv\n",
    "import src.journalfeed.nature as nature\n",
    "import src.journalfeed.science as science\n",
    "import src.journalfeed.aps as aps\n",
    "import datetime\n",
    "\n",
    "# sources, _filter, preamble = load_config()\n",
    "get_arxivarticles = arxiv.get_articles\n",
    "def arxiv_summary(aid, el=True):\n",
    "    return arxiv.get_articles(query=\"\", id_list=aid, ensure_latex=el)[0].summary\n",
    "\n",
    "# enddate = datetime.date.today()\n",
    "# timedelta = datetime.timedelta(days=7)\n",
    "# startdate = enddate - timedelta\n",
    "# naturearticles = nature.get_articles(journals=sources[\"nature\"][\"weekly\"],)\n",
    "elc(\"$\\\\_$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Inspired by previous studies in statistical physics [see, in particular,\\nKozitsky at al., A phase transition in a Curie-Weiss system with binary\\ninteractions, Condens. Matter Phys. 23, 23502 (2020)] we introduce a discrete\\nGauss-Poisson probability distribution function\\n$tag{A1} p_{GP}(n ;z,r)=[R(r;z)]^{-1}\\\\frac{mbox{e}^{zn}}{n!}\\\\,mbox{e}^{-\\\\frac 12\\\\,rn^2} $ with support on $\\\\mathbb N_0$ and parameters\\n$z\\\\in \\\\mathbb R$ and $r\\\\in \\\\mathbb R_+$. The probability mass function $p_{GP}(n ;z,r)$ is normalized by the special function $R(r;z)$, given by the infinite\\nsum $tag{A2} R(r;z)=\\\\sum_{n=0}^{\\\\infty}\\\\frac{mbox{e}^{zn}}{n!}\\\\,mbox{e}^{-\\\\frac 12\\\\,rn^2}, $ possessing extremely intersting mathematical properties. We\\npresent an asymptotic estimate $R^{(rm as)}(r;z\\\\gg 1)$ for the function\\n$R(r;z)$ with large arguments $z$, along with similar formulas for its\\nlogarithm and logarithmic derivative. These functions exhibit very interesting\\noscillatory behavior around their asymptotics, for parameters $r$ above some\\nthreshold value $r^*$. Some implications of our findings are discussed in the\\ncontext of the Curie-Weiss cell model of simple fluids.'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hmm = arxiv_summary(\"2412.05428v1\", el=True)\n",
    "hmm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['\\\\begin{equation}\\\\label{GPD}\\\\tag{A1} p_{GP}(n\\n;z,r)=\\\\left[R(r;z)\\\\right]^{-1}\\\\frac{\\\\mbox{e}^{zn}}{n!}\\\\,\\\\mbox{e}^{-\\\\frac\\n12\\\\,rn^2} \\\\end{equation} with support on $\\\\mathbb N_0$ and parameters\\n$z\\\\in\\\\mathbb R$ and $r\\\\in\\\\mathbb R_+$. The probability mass function $p_{GP}(n\\n;z,r)$ is normalized by the special function $R(r;z)$, given by the infinite\\nsum \\\\begin{equation}\\\\label{R}\\\\tag{A2}\\nR(r;z)=\\\\sum_{n=0}^\\\\infty\\\\frac{\\\\mbox{e}^{zn}}{n!}\\\\,\\\\mbox{e}^{-\\\\frac 12\\\\,rn^2},\\n\\\\end{equation}',\n",
       "  '\\\\begin{equation}',\n",
       "  '\\\\label{GPD}\\\\tag{A1} p_{GP}(n\\n;z,r)=\\\\left[R(r;z)\\\\right]^{-1}\\\\frac{\\\\mbox{e}^{zn}}{n!}\\\\,\\\\mbox{e}^{-\\\\frac\\n12\\\\,rn^2} \\\\end{equation} with support on $\\\\mathbb N_0$ and parameters\\n$z\\\\in\\\\mathbb R$ and $r\\\\in\\\\mathbb R_+$. The probability mass function $p_{GP}(n\\n;z,r)$ is normalized by the special function $R(r;z)$, given by the infinite\\nsum \\\\begin{equation}\\\\label{R}\\\\tag{A2}\\nR(r;z)=\\\\sum_{n=0}^\\\\infty\\\\frac{\\\\mbox{e}^{zn}}{n!}\\\\,\\\\mbox{e}^{-\\\\frac 12\\\\,rn^2},\\n',\n",
       "  '\\\\end{equation}'],\n",
       " ['$R^{(\\\\rm as)}(r;z\\\\gg1)$', '$', 'R^{(\\\\rm as)}(r;z\\\\gg1)', '$'],\n",
       " ['$R(r;z)$', '$', 'R(r;z)', '$'],\n",
       " ['$z$', '$', 'z', '$'],\n",
       " ['$r$', '$', 'r', '$'],\n",
       " ['$r^*$', '$', 'r^*', '$']]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# list(map(len, \n",
    "find_all_math(hmm) \n",
    "        # ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"The closure relation of quantum mechanical projection operators is not\\nentirely true; it can be strictly falsified under unitary transformations in\\nFock states. The angular momentum $J_x$, $J_y$ and $J_z$ are simultaneously\\ndiagonalized under the orthonormal set $\\\\{|\\\\phi_n\\\\rangle\\\\}$ of continuous\\nrotation transformations in Fock states. $\\\\{|\\\\phi_n\\\\rangle\\\\}$'s time reversal\\n$\\\\{ \\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ is the zero point of coordinates q and\\nmomentum p, and its arbitrary translation transformation $\\\\{ \\\\mathcal{D}\\n\\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ diagonalizes both coordinates and momentum\\nsimultaneously. The abstract representation of the Dirac state vector implies\\nthe symmetry breaking of the non-Abelian group unit matrix $\\\\{ \\\\mathcal{U}^\\n\\\\mathcal{H} \\\\mathcal{U} \\\\neq \\\\mathcal{U} \\\\mathcal{U} ^\\\\mathcal{H} \\\\}$. The EPR\\nparadox is merely a fallacy under the reversible diagonalization of physical\\nreality, it is resolved under irreversible diagonalization.\""
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hmm = arxiv_summary(\"2409.15379v1\", el=False)\n",
    "hmm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"The closure relation of quantum mechanical projection operators is not\\nentirely true; it can be strictly falsified under unitary transformations in\\nFock states. The angular momentum $J_x$, $J_y$ and $J_z$ are simultaneously\\ndiagonalized under the orthonormal set $\\\\{|\\\\phi_n\\\\rangle\\\\}$ of continuous\\nrotation transformations in Fock states. $\\\\{|\\\\phi_n\\\\rangle\\\\}$'s time reversal\\n$\\\\{ \\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ is the zero point of coordinates q and\\nmomentum p, and its arbitrary translation transformation $\\\\{ \\\\mathcal{D}\\n\\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ diagonalizes both coordinates and momentum\\nsimultaneously. The abstract representation of the Dirac state vector implies\\nthe symmetry breaking of the non-Abelian group unit matrix $\\\\{ \\\\mathcal{U}^{\\\\mathcal{H}} \\\\mathcal{U} \\\\neq \\\\mathcal{U} \\\\mathcal{U} ^{\\\\mathcal{H}} \\\\}$. The EPR\\nparadox is merely a fallacy under the reversible diagonalization of physical\\nreality, it is resolved under irreversible diagonalization.\""
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.sub(\"([\\\\^_])\\\\s*(\\\\\\\\[a-zA-Z]+(?:\\\\{[^\\\\}]+\\\\})+|\\\\\\\\\"+\"(?:\"+\"|\".join(math_command_whitelist_with_args)+\")\"+\"\\\\s*\\\\S+)\", \"\\\\1{\\\\2}\", hmm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"The closure relation of quantum mechanical projection operators is not\\nentirely true; it can be strictly falsified under unitary transformations in\\nFock states. The angular momentum $J_x$, $J_y$ and $J_z$ are simultaneously\\ndiagonalized under the orthonormal set $\\\\{|\\\\phi_n\\\\rangle \\\\}$ of continuous\\nrotation transformations in Fock states. $\\\\{|\\\\phi_n\\\\rangle \\\\}$'s time reversal\\n$\\\\{ \\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ is the zero point of coordinates q and\\nmomentum p, and its arbitrary translation transformation $\\\\{ \\\\mathcal{D} \\\\mathcal{T} |\\\\phi_n\\\\rangle \\\\}$ diagonalizes both coordinates and momentum\\nsimultaneously. The abstract representation of the Dirac state vector implies\\nthe symmetry breaking of the non-Abelian group unit matrix $\\\\{ \\\\mathcal{U}^{\\\\mathcal{H}} \\\\mathcal{U} neq \\\\mathcal{U} \\\\mathcal{U} ^{\\\\mathcal{H}} \\\\}$. The EPR\\nparadox is merely a fallacy under the reversible diagonalization of physical\\nreality, it is resolved under irreversible diagonalization.\""
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arxiv_summary(\"2409.15379v1\", el=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'chirality \\\\$stackrel{\\\\textasciicircum}{mathbf{n}}⋅(…'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elc('chirality $\\\\stackrel{^}{\\\\mathbf{n}}⋅(\\\\…') # http://link.aps.org/doi/10.1103/PhysRevApplied.22.034042"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The dispersionless limit of the standard Eliashberg theory of\\nsuperconductivity is studied. The effective electron-electron interactions are\\nmediated by Einstein phonons of frequency $\\\\Omega>0$, equipped with\\nelectron-phonon coupling strength $\\\\lambda$. This allows for a detailed\\nevaluation of the general results on $T_c$ for phonons with non-trivial\\ndispersion relation, obtained in a previous paper, (II), by the authors. The\\nvariational principle for the linear stability boundary $\\\\mathscr{S}_{\\\\!c}$ of\\nthe normal state region against perturbations toward the superconducting\\nregion, obtained in (II), simplifies as follows: If\\n$(\\\\lambda,\\\\Omega,T)\\\\in\\\\mathscr{S}_{\\\\!c}$, then $\\\\lambda =\\n1/\\\\mathfrak{h}(\\\\varpi)$, where $\\\\varpi:=\\\\Omega/2\\\\pi T$, and where\\n$\\\\mathfrak{h}(\\\\varpi)>0$ is the largest eigenvalue of a compact self-adjoint\\noperator $\\\\mathfrak{H}(\\\\varpi)$ on $\\\\ell^2$ sequences; $\\\\mathfrak{H}(\\\\varpi)$\\nis the dispersionless limit $P(d\\\\omega)\\\\to\\\\delta(\\\\omega-\\\\Omega)d\\\\omega$ of the\\noperator $\\\\mathfrak{K}(P,T)$ of (II). It is shown that when $\\\\varpi \\\\leq\\n\\\\sqrt{2}$, then the map $\\\\varpi\\\\mapsto\\\\mathfrak{h}(\\\\varpi)$ is invertible. For\\n$\\\\lambda>0.77$ this yields: (i) the existence of a critical temperature\\n$T_c(\\\\lambda,\\\\Omega) = \\\\Omega f(\\\\lambda)$; (ii) a sequence of lower bounds on\\n$f(\\\\lambda)$ that converges to $f(\\\\lambda)$. Also obtained is an upper bound on\\n$T_c(\\\\lambda,\\\\Omega)$, which agrees with the asymptotic behavior\\n$T_c(\\\\lambda,\\\\Omega) \\\\sim C \\\\Omega\\\\sqrt{\\\\lambda}$ for $\\\\lambda\\\\sim\\\\infty$,\\ngiven $\\\\Omega$, though with $C\\\\approx 2.034 C_\\\\infty$, where $C_\\\\infty :=\\n\\\\frac{1}{2\\\\pi}\\\\mathfrak{k}(2)^\\\\frac12 =0.1827262477...$ is the optimal\\nconstant, and $\\\\mathfrak{k}(\\\\gamma)>0$ the largest eigenvalue of a compact\\nself-adjoint operator for the $\\\\gamma$ model, determined in the first paper,\\n(I), on $T_c$ by the authors.'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arxiv_summary(\"2409.02121v1\", el=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The dispersionless limit of the standard Eliashberg theory of\\nsuperconductivity is studied. The effective electron-electron interactions are\\nmediated by Einstein phonons of frequency $Omega>0$, equipped with\\nelectron-phonon coupling strength $\\\\lambda$. This allows for a detailed\\nevaluation of the general results on $T_c$ for phonons with non-trivial\\ndispersion relation, obtained in a previous paper, (II), by the authors. The\\nvariational principle for the linear stability boundary $mathscr{S}_{\\\\!c}$ of\\nthe normal state region against perturbations toward the superconducting\\nregion, obtained in (II), simplifies as follows: If\\n$(lambda,Omega,T)\\\\in mathscr{S}_{\\\\!c}$, then $\\\\lambda = 1/mathfrak{h}(\\\\varpi)$, where $varpi:=\\\\Omega /2\\\\pi T$, and where\\n$mathfrak{h}(\\\\varpi)>0$ is the largest eigenvalue of a compact self-adjoint\\noperator $mathfrak{H}(\\\\varpi)$ on $\\\\ell^2$ sequences; $mathfrak{H}(\\\\varpi)$\\nis the dispersionless limit $P(d\\\\omega)\\\\to \\\\delta(omega-\\\\Omega)d\\\\omega$ of the\\noperator $mathfrak{K}(P,T)$ of (II). It is shown that when $\\\\varpi \\\\leq \\\\sqrt{2}$, then the map $\\\\varpi \\\\mapsto mathfrak{h}(\\\\varpi)$ is invertible. For\\n$lambda>0.77$ this yields: (i) the existence of a critical temperature\\n$T_c(lambda,\\\\Omega) = \\\\Omega f(\\\\lambda)$; (ii) a sequence of lower bounds on\\n$f(\\\\lambda)$ that converges to $f(\\\\lambda)$. Also obtained is an upper bound on\\n$T_c(lambda,\\\\Omega)$, which agrees with the asymptotic behavior\\n$T_c(lambda,\\\\Omega) \\\\sim C \\\\Omega \\\\sqrt{\\\\lambda}$ for $\\\\lambda \\\\sim \\\\infty$,\\ngiven $\\\\Omega$, though with $C\\\\approx 2.034 C_\\\\infty$, where $C_{\\\\infty} := \\\\frac{1}{2\\\\pi}mathfrak{k}(2)^{\\\\frac 12} =0.1827262477...$ is the optimal\\nconstant, and $mathfrak{k}(\\\\gamma)>0$ the largest eigenvalue of a compact\\nself-adjoint operator for the $\\\\gamma$ model, determined in the first paper,\\n(I), on $T_c$ by the authors.'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arxiv_summary(\"2409.02121v1\", el=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ribozymes are catalytic RNAs with diverse functions including self-splicing and polymerization. This work aims to discover natural ribozymes that behave as hydrolytic and sequence-specific DNA endonucleases, which could be repurposed as DNA manipulation tools. Focused on bacterial group II-C introns, we found that many systems without intron-encoded protein propagate multiple copies in their resident genomes. These introns, named HYdrolytic Endonucleolytic Ribozymes (HYERs), cleaved RNA, single-stranded DNA, bubbled double-stranded DNA (dsDNA), and plasmids in vitro. HYER1 generated dsDNA breaks in the mammalian genome. Cryo–electron microscopy analysis revealed a homodimer structure for HYER1, where each monomer contains a Mg2+-dependent hydrolysis pocket and captures DNA complementary to the target recognition site (TRS). Rational designs including TRS extension, recruiting sequence insertion, and heterodimerization yielded engineered HYERs showing improved specificity and flexibility for DNA manipulation.'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.journalfeed.helpers import abstract_from_doi\n",
    "abstract_from_doi(\"10.1126/science.adh4859\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "feed = science.get_articles(journals=[\"sciadv\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://www.science.org/doi/abs/10.1126/sciadv.adj4060?af=R'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feed[1].url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "timedelta = datetime.timedelta(days=7)\n",
    "enddate = datetime.date.today()\n",
    "startdate = enddate - timedelta\n",
    "prarticles = aps.get_articles(journals=[\"prapplied\"],\n",
    "                            enddate=enddate, startdate=startdate, ensure_latex=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'We address the photonic spin-orbit coupling known from nano-optics and plasmonics in the microwave regime. The spin $\\\\mathbf{S}$ and momentum $\\\\mathbf{q}$ of microwaves emitted by an excited magnetic particle are locked by $\\\\mathbf{q}⋅\\\\mathbf{S}=0$ with a fixed chirality $\\\\stackrel{^}{\\\\mathbf{n}}⋅(\\\\…'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "article_match = prarticles[1]\n",
    "for article in prarticles:\n",
    "    if article.match([], [], [\"Spin-orbit-locked coupling of localized microwaves to magnons\"], []):\n",
    "        article_match = article\n",
    "article_match.summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"In usual restriction terms of the Quadratic Unconstrained Binary Optimization\\n(QUBO) hamiltonians, a integer number of logical qubits R, called the Integer\\nRestriction Coefficient (IRC), are forced to stay active. In this paper we\\ngather the well-known methods of implementing these restrictions, as well as\\nsome novel methods that show to be more efficient in some frequently\\nimplemented cases. Moreover, it is mathematically allowed to ask for fractional\\nvalues of $R$. For these Fractionary Restriction Coefficients (FRC) we show how\\nthey can reduce the number of qubits needed to implement the restriction\\nhamiltonian even further. Lastly, we characterize the response of DWave's\\nAdvantage$\\\\_$system4.1 Quantum Annealer (QA) when faced with the implementation\\nof FRCs, and offer a summary guide of the presented methods and the situations\\neach of them is to be used.\""
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_arxivarticles(query=\"\", id_list=\"2306.06943v1\", ensure_latex=False)[0].summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"In usual restriction terms of the Quadratic Unconstrained Binary Optimization\\n(QUBO) hamiltonians, a integer number of logical qubits R, called the Integer\\nRestriction Coefficient (IRC), are forced to stay active. In this paper we\\ngather the well-known methods of implementing these restrictions, as well as\\nsome novel methods that show to be more efficient in some frequently\\nimplemented cases. Moreover, it is mathematically allowed to ask for fractional\\nvalues of $R$. For these Fractionary Restriction Coefficients (FRC) we show how\\nthey can reduce the number of qubits needed to implement the restriction\\nhamiltonian even further. Lastly, we characterize the response of DWave's\\nAdvantage$\\\\_$system4.1 Quantum Annealer (QA) when faced with the implementation\\nof FRCs, and offer a summary guide of the presented methods and the situations\\neach of them is to be used.\""
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_arxivarticles(query=\"\", id_list=\"2306.06943v1\", ensure_latex=True)[0].summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ferroelectricity in sputtered undoped-HfO$_2$ is attractive for composition\\ncontrol for low power and non-volatile memory and logic applications. Unlike\\ndoped HfO$_2$, evolution of ferroelectricity with annealing and film thickness\\neffect in sputter deposited undoped HfO$_2$ on Si is not yet reported. In\\npresent study, we have demonstrated the impact of post metallization annealing\\ntemperature and film thickness on ferroelectric properties in dopant-free\\nsputtered HfO$_2$ on Si-substrate. A rich correlation of polarization with\\nphase, lattice constant, and crystallite size and interface reaction is\\nobserved. First, anneal temperature shows o-phase saturation beyond 600 oC\\nfollowed by interface reaction beyond 700 oC to show an optimal temperature\\nwindow on 600-700 oC. Second, thickness study at the optimal temperature window\\nshows an alluring o-phase crystallite scaling with thickness till a critical\\nthickness of 20 nm indicating that the films are completely o-phase. However,\\nthe lattice constants (volume) are high in the 15-20 nm thickness range which\\ncorrelates with the enhanced value of 2Pr. Beyond 20 nm, crystallite scaling\\nwith thickness saturates with the correlated appearance of m-phase and\\nreduction in 2Pr. The optimal thickness-temperature window range of 15-20 nm\\nfilms annealed at 600-700 oC show 2Pr of ~35.5 micro-C/cm$^2$ is comparable to\\nstate-of-the-art. The robust wakeup-free endurance of ~$10^$8 cycles showcased\\nin the promising temperature-thickness window has been identified\\nsystematically for non-volatile memory applications.'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_arxivarticles(query=\"\", id_list=\"2304.12924v1\", ensure_latex=False)[0].summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "error",
     "evalue": "invalid group reference 3 at position 5",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31merror\u001b[0m                                     Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-59257712e079>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0melc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"$\\\\_$\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/repos/journalfeed2pdf/src/journalfeed/LaTeX.py\u001b[0m in \u001b[0;36melc\u001b[0;34m(s, general_sub, outside_math_sub, inside_math_sub, math_command_whitlist_regex, math_env_whitelist)\u001b[0m\n\u001b[1;32m    165\u001b[0m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"MATH{}MATH\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    166\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mfind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreplace\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minside_math_sub\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 167\u001b[0;31m             \u001b[0mmatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mre\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreplace\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    168\u001b[0m         \u001b[0;31m# try to clever strip \"bad\" backslashes:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    169\u001b[0m         \u001b[0;31m# first insert a space if the command is directly followed by a \\\\ or a number\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/papbnjfxwrdkmz6xfp7v2q7nxyvgcr5l-python3-3.8.6/lib/python3.8/re.py\u001b[0m in \u001b[0;36msub\u001b[0;34m(pattern, repl, string, count, flags)\u001b[0m\n\u001b[1;32m    208\u001b[0m     \u001b[0ma\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mit\u001b[0m\u001b[0;31m'\u001b[0m\u001b[0ms\u001b[0m \u001b[0mpassed\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mMatch\u001b[0m \u001b[0mobject\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mmust\u001b[0m \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m     a replacement string to be used.\"\"\"\n\u001b[0;32m--> 210\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_compile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpattern\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstring\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcount\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    211\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    212\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msubn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpattern\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrepl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstring\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcount\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/papbnjfxwrdkmz6xfp7v2q7nxyvgcr5l-python3-3.8.6/lib/python3.8/re.py\u001b[0m in \u001b[0;36m_subx\u001b[0;34m(pattern, template)\u001b[0m\n\u001b[1;32m    325\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_subx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpattern\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtemplate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    326\u001b[0m     \u001b[0;31m# internal: Pattern.sub/subn implementation helper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 327\u001b[0;31m     \u001b[0mtemplate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_compile_repl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemplate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpattern\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    328\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtemplate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemplate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    329\u001b[0m         \u001b[0;31m# literal replacement\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/papbnjfxwrdkmz6xfp7v2q7nxyvgcr5l-python3-3.8.6/lib/python3.8/re.py\u001b[0m in \u001b[0;36m_compile_repl\u001b[0;34m(repl, pattern)\u001b[0m\n\u001b[1;32m    316\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_compile_repl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpattern\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    317\u001b[0m     \u001b[0;31m# internal: compile replacement pattern\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 318\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0msre_parse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparse_template\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpattern\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    319\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    320\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_expand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpattern\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtemplate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/papbnjfxwrdkmz6xfp7v2q7nxyvgcr5l-python3-3.8.6/lib/python3.8/sre_parse.py\u001b[0m in \u001b[0;36mparse_template\u001b[0;34m(source, state)\u001b[0m\n\u001b[1;32m   1034\u001b[0m                         \u001b[0mlappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1035\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misoctal\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1036\u001b[0;31m                     \u001b[0maddgroup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1037\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1038\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/papbnjfxwrdkmz6xfp7v2q7nxyvgcr5l-python3-3.8.6/lib/python3.8/sre_parse.py\u001b[0m in \u001b[0;36maddgroup\u001b[0;34m(index, pos)\u001b[0m\n\u001b[1;32m    978\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0maddgroup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    979\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroups\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 980\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"invalid group reference %d\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    981\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mliteral\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    982\u001b[0m             \u001b[0mliterals\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mliteral\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31merror\u001b[0m: invalid group reference 3 at position 5"
     ]
    }
   ],
   "source": [
    "elc(\"$\\\\_$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$\\\\_$'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elc(\"$\\_$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$\\\\ _$'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elc(\"$\\\\\\_$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ferroelectricity in sputtered undoped-HfO$_2$ is attractive for composition\\ncontrol for low power and non-volatile memory and logic applications. Unlike\\ndoped HfO$_2$, evolution of ferroelectricity with annealing and film thickness\\neffect in sputter deposited undoped HfO$_2$ on Si is not yet reported. In\\npresent study, we have demonstrated the impact of post metallization annealing\\ntemperature and film thickness on ferroelectric properties in dopant-free\\nsputtered HfO$_2$ on Si-substrate. A rich correlation of polarization with\\nphase, lattice constant, and crystallite size and interface reaction is\\nobserved. First, anneal temperature shows o-phase saturation beyond 600 oC\\nfollowed by interface reaction beyond 700 oC to show an optimal temperature\\nwindow on 600-700 oC. Second, thickness study at the optimal temperature window\\nshows an alluring o-phase crystallite scaling with thickness till a critical\\nthickness of 20 nm indicating that the films are completely o-phase. However,\\nthe lattice constants (volume) are high in the 15-20 nm thickness range which\\ncorrelates with the enhanced value of 2Pr. Beyond 20 nm, crystallite scaling\\nwith thickness saturates with the correlated appearance of m-phase and\\nreduction in 2Pr. The optimal thickness-temperature window range of 15-20 nm\\nfilms annealed at 600-700 oC show 2Pr of ~35.5 micro-C/cm$^2$ is comparable to\\nstate-of-the-art. The robust wakeup-free endurance of ~$10^$8 cycles showcased\\nin the promising temperature-thickness window has been identified\\nsystematically for non-volatile memory applications.'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_arxivarticles(query=\"\", id_list=\"2304.12924v1\", ensure_latex=True)[0].summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading local config \"filter.json\".\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sources, _filter, preamble = load_config()\n",
    "# get_arxivarticles(query=\"\", id_list=\"2111.04167v1\", ensure_latex=False)[0].match(*_filter)\n",
    "journals, authors, title_res, summary_res = _filter\n",
    "get_arxivarticles(query=\"\", id_list=\"2111.04167v1\", ensure_latex=False)[0].match(*_filter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hall effect measurements in doped polymer semiconductors are widely reported,\\nbut are difficult to interpret due to screening of Hall voltages by carriers\\nundergoing incoherent transport. Here, we propose a refined analysis for such\\nHall measurements, based on measuring the Hall coefficient as a function of\\ntemperature, and modelling carriers as existing in a regime of variable\\n\"deflectability\" (i.e. how strongly they \"feel\" the magnetic part of the\\nLorentz force). By linearly interpolating each carrier between the extremes of\\nno deflection and full deflection, we demonstrate that it is possible to\\nextract the (time-averaged) concentration of deflectable charge carriers,\\n$\\\\left<n_d\\\\right>$, the average, temperature-dependent mobility of those\\ncarriers, $\\\\left<\\\\mu_d\\\\right>(T)$, as well as the ratio of conductivity that\\ncomes from such deflectable transport, $d(T)$. Our method was enabled by the\\nconstruction of an improved AC Hall measurement system, as well as an improved\\ndata extraction method. We measured Hall bar devices of ion-exchange doped\\nfilms of PBTTT-C$_{14}$ from 10--300 K. Our analysis provides evidence for the\\nproportion of conductivity arising from deflectable transport, $d(T)$,\\nincreasing with doping level, ranging between 15.4% and 16.4% at room\\ntemperature. When compared to total charge-carrier-density estimates from\\nindependent methods, the values of $\\\\left<n_d\\\\right>$ extracted suggest that\\ncarriers spend $\\\\sim$37% of their time of flight being deflectable in the most\\nhighly doped of the devices measured here. The extracted values of $d(T)$ being\\nless than half this value thus suggest that the limiting factor for\\nconductivity in such highly doped devices is carrier mobility, rather than\\nconcentration.'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = get_arxivarticles(query=\"\", id_list=\"2303.14053v1\", ensure_latex=False)[0].summary\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hall effect measurements in doped polymer semiconductors are widely reported,\\nbut are difficult to interpret due to screening of Hall voltages by carriers\\nundergoing incoherent transport. Here, we propose a refined analysis for such\\nHall measurements, based on measuring the Hall coefficient as a function of\\ntemperature, and modelling carriers as existing in a regime of variable\\n\"deflectability\" (i.e. how strongly they \"feel\" the magnetic part of the\\nLorentz force). By linearly interpolating each carrier between the extremes of\\nno deflection and full deflection, we demonstrate that it is possible to\\nextract the (time-averaged) concentration of deflectable charge carriers,\\n$\\\\left$, the average, temperature-dependent mobility of those carriers,\\n$\\\\left<\\\\mu_d\\\\right>(T)$, as well as the ratio of conductivity that comes from\\nsuch deflectable transport, $d(T)$. Our method was enabled by the construction\\nof an improved AC Hall measurement system, as well as an improved data\\nextraction method. We measured Hall bar devices of ion-exchange doped films of\\nPBTTT-C$_{14}$ from 10--300 K. Our analysis provides evidence for the\\nproportion of conductivity arising from deflectable transport, $d(T)$,\\nincreasing with doping level, ranging between 15.4% and 16.4% at room\\ntemperature. When compared to total charge-carrier-density estimates from\\nindependent methods, the values of $\\\\left$ extracted suggest that carriers\\nspend $\\\\sim$37% of their time of flight being deflectable in the most highly\\ndoped of the devices measured here. The extracted values of $d(T)$ being less\\nthan half this value thus suggest that the limiting factor for conductivity in\\nsuch highly doped devices is carrier mobility, rather than concentration.\\n\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = html2text.html2text(s)\n",
    "# ret = re.sub(\"\\\\$\\\\\\\\require\\\\{[^\\\\]\\\\}]+\\\\}\\\\$\", \"\", ret)\n",
    "# ret = re.sub(\"\\\\\\\\\\\\$\", \"ESCAPEDDOLLAR\", ret)\n",
    "ret\n",
    "# math_matches = find_all_math(ret)\n",
    "# math_matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "FeatureNotFound",
     "evalue": "Couldn't find a tree builder with the features you requested: lxml. Do you need to install a parser library?",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFeatureNotFound\u001b[0m                           Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-911350a2aafb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_arxivarticles\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mid_list\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"2303.14053v1\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mensure_latex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msummary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/repos/journalfeed2pdf/src/journalfeed/arxiv.py\u001b[0m in \u001b[0;36mget_articles\u001b[0;34m(enddate, startdate, query, id_list, **kwargs)\u001b[0m\n\u001b[1;32m     50\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0me\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfeed\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mentries\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m             \u001b[0mpublished\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsed_datetime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpublished_parsed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m             articles.append(Article(e.title.replace(\"\\n\", \"\"), e.link, published,\n\u001b[0m\u001b[1;32m     53\u001b[0m                                          \u001b[0;34m[\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"name\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauthors\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msummary\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     54\u001b[0m                                          \"arXiv\", **kwargs))\n",
      "\u001b[0;32m~/repos/journalfeed2pdf/src/journalfeed/Article.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, title, url, date, authors, summary, journal, ensure_latex)\u001b[0m\n\u001b[1;32m     29\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_elc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     32\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     33\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/repos/journalfeed2pdf/src/journalfeed/Article.py\u001b[0m in \u001b[0;36m_elc\u001b[0;34m(s)\u001b[0m\n\u001b[1;32m     26\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0m_elc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mensure_latex\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0melc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     29\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/repos/journalfeed2pdf/src/journalfeed/LaTeX.py\u001b[0m in \u001b[0;36melc\u001b[0;34m(s, general_sub, outside_math_sub, inside_math_sub, math_command_whitlist_regex, math_env_whitelist)\u001b[0m\n\u001b[1;32m    131\u001b[0m     \u001b[0;31m# first use BeautifulSoup to get rid of html artefacts\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m     \u001b[0;31m# using html because beautifulsoup also strips <expecation values> in this form\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m     \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBeautifulSoup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"lxml\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    134\u001b[0m     \u001b[0;31m# require is used in math by MATHJAX to load additional packages\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    135\u001b[0m     \u001b[0;31m# Strip it because we use real latex and strip all unknown commands in the following\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/nix/store/kzg2s1sa16l7bzda7rsf21g9zwc13v7i-python3-3.8.6-env/lib/python3.8/site-packages/bs4/__init__.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, markup, features, builder, parse_only, from_encoding, exclude_encodings, element_classes, **kwargs)\u001b[0m\n\u001b[1;32m    241\u001b[0m             \u001b[0mbuilder_class\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuilder_registry\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlookup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mbuilder_class\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 243\u001b[0;31m                 raise FeatureNotFound(\n\u001b[0m\u001b[1;32m    244\u001b[0m                     \u001b[0;34m\"Couldn't find a tree builder with the features you \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    245\u001b[0m                     \u001b[0;34m\"requested: %s. Do you need to install a parser library?\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFeatureNotFound\u001b[0m: Couldn't find a tree builder with the features you requested: lxml. Do you need to install a parser library?"
     ]
    }
   ],
   "source": [
    "get_arxivarticles(query=\"\", id_list=\"2303.14053v1\", ensure_latex=True)[0].summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$$'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elc(\"$\\\\left<n_d\\\\right>$\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$<n_d>$'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "math_command_whitlist_regex = \"(\"+\"|\".join(math_command_whitelist)+\")\"\n",
    "test = \"$\\\\left<n_d\\\\right>$\"\n",
    "for find, replace in inside_math_sub:\n",
    "            test = re.sub(find, replace, test)\n",
    "test = re.sub(math_command_whitlist_regex+\"(\\\\\\\\|[0-9]|/)\", \"\\\\1 \\\\2\", test)\n",
    "test = re.sub(\"\\\\\\\\\"+math_command_whitlist_regex+\"(\\\\s|\\\\^|_|\\\\{|\\\\}|\\\\(|\\\\)|\\\\[|\\\\]|=|\\\\Z)\", \"\\\\\\\\\\\\\\\\\\\\1\\\\2\", test)\n",
    "regex = \"(\\\\\\\\begin\\\\{(?P<env>\"+\"|\".join(math_env_whitelist)+\")\\\\*?\\\\})(.+(?!(?P=env)))(\\\\\\\\end\\\\{(?P=env)\\\\*?\\\\})\"\n",
    "test = re.sub(regex, \"\\\\\\\\\\\\1\\\\3\\\\\\\\\\\\4\", test)\n",
    "test = re.sub(\"\\\\\\\\([a-zA-Z0-9])\", \"\\\\1\", test)\n",
    "\n",
    "    \n",
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "enddate = datetime.date(2021, 11, 4)\n",
    "timedelta = datetime.timedelta(days=7)\n",
    "startdate = enddate - timedelta\n",
    "\n",
    "sciencearticles = science.get_articles(journals=$\\\\\\\\sources[\"science\"][\"weekly\"],\n",
    "                                       enddate=enddate, startdate=startdate)\n",
    "len(sciencearticles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'In Other Journals'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sciencearticles[1].title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\\\\\\\textbf\\\\{\\\\}'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "re.escape(\"\\\\textbf{}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\\\{\\\\}'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.escape(\"{}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\\\\\\\'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.escape(\"\\\\\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'x^{\\\\frac\\\\chi\\\\alpha}'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.sub(\"([\\\\^_])(\\\\\\\\frac(\\\\\\\\[0-9a-zA-Z]+|[0-9a-zA-Z]){2})\", \"\\\\1{\\\\2}\", \"x^\\\\frac\\\\chi\\\\alpha\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}