{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Rename all BibTeX keys using JabRef"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Use JabRef, open the bib file -> Quality -> Autogenerate BibTeX keys.\n",
"* Commit the changes.\n",
"* `git diff @~1 master > changes`\n",
"* Use Sublime to get the dict below"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Supercurrent orbitalfield\n",
"replace = {\n",
" \"Gramacy2004\": \"gramacy2004parameter\",\n",
" \"Visvalingam1990\": \"visvalingam1990douglas\",\n",
" \"DeRose1998\": \"derose1998subdivision\",\n",
" \"Alliez2003\": \"alliez2003anisotropic\",\n",
" \"Nijholt2019\": \"Nijholt2019a\",\n",
" \"WolframResearch\": \"Mathematica\",\n",
" \"Nijholt\": \"adaptive_docs\",\n",
" \"Vuik2018\": \"vuik2018reproducing\",\n",
" \"Laeven2019\": \"laeven2019enhanced\",\n",
" \"Bommer2019\": \"bommer2019spin\",\n",
" \"Melo2019\": \"melo2019supercurrent\",\n",
" \"Chen2017\": \"chen2017intelligent\",\n",
" \"Takhtaganov2018\": \"takhtaganov2018adaptive\",\n",
" \"Emery1998\": \"emery1998optimal\",\n",
" \"Gonnet2010\": \"gonnet2010increasing\",\n",
" \"Galassi1996\": \"galassi1996gnu\",\n",
" \"Klein1999\": \"klein1999star\",\n",
" \"Berger1989\": \"berger1989local\",\n",
" \"Berger1984\": \"berger1984adaptive\",\n",
" \"Nijholt2016\": \"nijholt2016orbital\",\n",
" \"Dyn1990\": \"dyn1990data\",\n",
" \"Clenshaw1960\": \"clenshaw1960method\",\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fname = \"paper.md\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with open(fname, 'r') as f:\n",
" text = f.readlines()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"text = ''.join(text)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for old, new in replace.items():\n",
" text = text.replace(new, old)\n",
"\n",
"print(text)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# bibtex to yaml"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"\n",
"def doi2bib(doi):\n",
" \"\"\"Return a bibTeX string of metadata for a given DOI.\"\"\"\n",
" url = \"http://dx.doi.org/\" + doi\n",
" headers = {\"accept\": \"application/x-bibtex\"}\n",
" r = requests.get(url, headers=headers)\n",
" return r.text"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create the yaml files and `not_on_crossref.bib` files"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import glob\n",
"\n",
"bibs = [f for f in glob.glob('*bib') if 'not_on_crossref' not in f]\n",
"bibs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Go over the above bib files and fix the DOI problems and then create the `yaml`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fname = 'paper.bib'\n",
"yamls = []\n",
"folder, name = os.path.split(fname)\n",
"new = os.path.join(folder, \"tmp.yaml\")\n",
"yamls.append(new)\n",
"cmd = f\"pandoc-citeproc --bib2yaml {fname} > {new}\"\n",
"print(cmd)\n",
"os.system(cmd)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import yaml\n",
"\n",
"with open(new, 'r') as f:\n",
" try:\n",
" bibs = yaml.safe_load(f)\n",
" except yaml.YAMLError as exc:\n",
" print(exc)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"start = '@article{'\n",
"entries = {}\n",
"for d in bibs['references']:\n",
" key = d['id']\n",
" doi = d.get('DOI')\n",
" if doi is None:\n",
" bib = None\n",
" by_hand = True\n",
" else:\n",
" bib = doi2bib(doi)\n",
" if not bib.startswith(\"@\"):\n",
" bib = \"MANUALLY_ADD\"\n",
" by_hand = True\n",
" else:\n",
" by_hand = False\n",
" entries[key] = dict(doi=doi, bib=bib, by_hand=by_hand)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for k, d in entries.items():\n",
" if d['bib'] == \"MANUALLY_ADD\":\n",
" print(k)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for k, d in entries.items():\n",
" if d['bib'] is None:\n",
" print(k)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"entries['Nijholt2016']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def replace_key(key, bib_entry):\n",
" bib_type, *_ = bib_entry.split('{')\n",
" _, *rest = bib_entry.split(',')\n",
" rest = ','.join(rest)\n",
" result = bib_type + '{' + key + ',' + rest\n",
"\n",
" # XXX: I am not sure whether these substitutions are needed.\n",
" # the problem seemed to be the utf-8 `requests.get` encoding.\n",
" to_replace = [(\"ö\", r\"\\\"{o}\"), (\"ü\", r\"\\\"{u}\"), (\"ë\", r\"\\\"{e}\"), (\"ï\", r\"\\\"{i}\") ]\n",
" for old, new in to_replace:\n",
" result = result.replace(old.upper(), new.upper())\n",
" result = result.replace(old.lower(), new.lower())\n",
"\n",
" print(result, \"\\n\")\n",
" return result\n",
"\n",
"entries = dict(sorted(entries.items()))\n",
"for key, d in entries.items():\n",
" if d['bib'] is not None and d['bib'].startswith(\"@\"):\n",
" replace_key(key, d['bib'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import parse\n",
"bib = entries[\"Nijholt2019\"][\"bib\"]\n",
"bib_type, *_ = bib.split('{')\n",
"_, *rest = bib.split(',')\n",
"rest = ','.join(rest)\n",
"new_bib = bib_type + '{' + \"new\" + ',' + rest"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(new_bib)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Try to fix the above entries with the correct DOI"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from toolz.dicttoolz import dissoc\n",
"\n",
"with open(fname[:-3] + \"yaml\", 'w') as f:\n",
" data = {k: dissoc(v, \"bib\") for k, v in entries.items()}\n",
" yaml.dump(data, f)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Go from yamls to bib files"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Check for double entries and fix them! "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import glob\n",
"\n",
"bibs = [f for f in glob.glob('*/*yaml') if 'tmp.yaml' not in f]\n",
"bibs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import yaml\n",
"mapping = {}\n",
"for fname in bibs:\n",
" with open(fname) as f:\n",
" mapping[fname] = yaml.safe_load(f)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from collections import defaultdict\n",
"items = defaultdict(list)\n",
"for fname, info in mapping.items():\n",
" for k, v in info.items():\n",
" if v is not None:\n",
" v = tuple(v.items())\n",
" items[k].append(v)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for k, v in items.items():\n",
" if len(set(v)) >= 2:\n",
" print(k, v)\n",
" print()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When there are no more entries above here, go to the next step"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Combine everything into one yaml"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# see create_bib_file.py"
]
}
],
"metadata": {
"language_info": {
"name": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}