diff --git a/Makefile b/Makefile index 7d4e560..f014cf7 100644 --- a/Makefile +++ b/Makefile @@ -1,5 +1,5 @@ format: - black --line-length 79 . + black . lint: flake8 . @@ -20,4 +20,13 @@ twine-upload: twine upload dist/* remove-dist: - rm -rf dist/* \ No newline at end of file + rm -rf dist/* + +generate-cli-docs: + python3 scripts/generate_docs.py + +serve-docs: generate-cli-docs + mkdocs serve + +install-docs: + pip install '.[docs]' \ No newline at end of file diff --git a/SSDraw.ipynb b/SSDraw.ipynb deleted file mode 100644 index 23391da..0000000 --- a/SSDraw.ipynb +++ /dev/null @@ -1,1303 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "id": "view-in-github" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "HEuP5CG7g9ak" - }, - "outputs": [], - "source": [ - "%%capture\n", - "#@title SSDraw\n", - "#@markdown Installing the necessary dependencies can take 1-2 minutes.\n", - "\n", - "import os\n", - "cwd=os.getcwd()\n", - "print(cwd)\n", - "os.chdir(\"/content/\")\n", - "cwd=os.getcwd()\n", - "print(cwd)\n", - "\n", - "# first install dssp\n", - "#!sudo yes | apt-get install dssp\n", - "!git clone https://github.com/ethanchen1301/SSDraw.git\n", - "!tar -zxvf SSDraw/dssp-2.3.0.tar.gz\n", - "%cd dssp-2.3.0\n", - "!./autogen.sh\n", - "!./configure\n", - "!make\n", - "!make mkdssp\n", - "!sudo make install\n", - "%cd ../\n", - "!mkdssp --version\n", - "\n", - "# install necessary dependencies\n", - "!pip install Bio\n", - "!pip install matplotlib\n", - "!pip install numpy\n", - "\n", - "import matplotlib.patches as mpatch\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.collections import PatchCollection\n", - "import matplotlib.path as mpath\n", - "import matplotlib\n", - "import numpy as np\n", - "import warnings\n", - "from Bio import BiopythonDeprecationWarning\n", - "warnings.simplefilter('ignore',BiopythonDeprecationWarning)\n", - "from Bio import pairwise2\n", - "import sys, os, string, math, re\n", - "from matplotlib import rcParams\n", - "import argparse\n", - "from Bio.PDB import PDBParser\n", - "from Bio.PDB.DSSP import DSSP\n", - "from Bio.Align import substitution_matrices\n", - "from Bio import AlignIO\n", - "import matplotlib.colors as mcolors\n", - "from matplotlib.colors import ListedColormap\n", - "from Bio.SeqUtils import seq1\n", - "import warnings, textwrap\n", - "from Bio import BiopythonWarning\n", - "from Bio.PDB.PDBExceptions import PDBConstructionWarning\n", - "\n", - "def read_r4s(inputfile):\n", - " # algorithm to convert raw scores to grades is taken from consurf:\n", - " # https://github.com/Rostlab/ConSurf\n", - " seq = \"\"\n", - " scores = []\n", - "\n", - " pattern = r\"^\\s*?\\d+\\s+(\\w)\\s+(\\S+)\\s+\\[\\s*\\S+,\\s*\\S+\\]\\s+\\S+\\s+\\d+\\/\\d+\"\n", - " with open(inputfile) as READ:\n", - " for line in READ:\n", - " line = line.strip()\n", - " if re.match(pattern, line):\n", - " match = re.match(pattern, line)\n", - " seq+=match.group(1)\n", - " scores.append(eval(match.group(2)))\n", - "\n", - " max_cons = min(scores)\n", - "\n", - " # 9 steps from -|max_cons| to |max_cons|, midpoint is 0\n", - " ConsGradeUnity = max_cons / 4.5 * -1\n", - " if max_cons >= 0:\n", - " ConsGradeUnity = max_cons\n", - "\n", - " grades = []\n", - " for score in scores:\n", - " grades.append(max(1, 9-int((score-max_cons)/ConsGradeUnity)))\n", - "\n", - " return seq, grades\n", - "\n", - "def read_consurf_grad(inputfile):\n", - "\n", - " grades = []\n", - " seq = \"\"\n", - " pattern = r\"^\\s*?\\d+\\s+(\\w)\\s+\\S+\\s+\\S+\\s+(\\d)\\S*\\s+-?\\d+.\\d+,\\s+-?\\d+.\\d+\\s+\\d,\\d\\s+\\d+\\/\\d+\\s+\\S+\"\n", - " with open(inputfile, \"r\") as f:\n", - " for line in f:\n", - " if re.match(pattern, line):\n", - " match = re.match(pattern,line)\n", - " seq += match.group(1)\n", - " grades.append(match.group(2))\n", - "\n", - " return seq,grades\n", - "\n", - "def check_consurf_file(file):\n", - " consurf_pattern = r\"^\\s*?\\d+\\s+(\\w)\\s+\\S+\\s+\\S+\\s+(\\d)\\S*\\s+-?\\d+.\\d+,\\s+-?\\d+.\\d+\\s+\\d,\\d\\s+\\d+\\/\\d+\\s+\\S+\"\n", - " r4s_pattern = r\"^\\s*?\\d+\\s+(\\w)\\s+(\\S+)\\s+\\[\\s*\\S+,\\s*\\S+\\]\\s+\\S+\\s+\\d+\\/\\d+\"\n", - " with open(file, \"r\") as f:\n", - " for line in f:\n", - " if re.match(consurf_pattern, line):\n", - " return \"consurf\"\n", - " if re.match(r4s_pattern, line):\n", - " return \"r4s\"\n", - "\n", - "def gap_sequence(seq, extra_gaps):\n", - " # seq can be a list or a string, anything that can be indexed\n", - " # extra gaps is a list of length two [x,y],\n", - " # where x is the number of characters to remove from the beginning\n", - " # and y the number of characters to remove from the end\n", - " new_seq = seq\n", - " if extra_gaps[1] != 0:\n", - " new_seq = new_seq[:-extra_gaps[1]]\n", - " return new_seq[extra_gaps[0]:]\n", - "\n", - "def NormalizeData(data):\n", - " if np.min(data) == np.max(data):\n", - " warnings.warn(\"Warning: scores are the same for all residues\")\n", - " return data\n", - " return (data - np.min(data)) / (np.max(data) - np.min(data))\n", - "\n", - "def coords2path(coord_set1):\n", - "\n", - " coords_f1 = []\n", - " instructions1 = []\n", - "\n", - " for c in coord_set1:\n", - " for n in range(len(c)):\n", - " coords_f1.append(c[n])\n", - " if n == 0:\n", - " instructions1.append(1)\n", - " else:\n", - " instructions1.append(2)\n", - "\n", - " return coords_f1, instructions1\n", - "\n", - "def build_loop(loop,idx,ssidx,loop_coords,linelen,nlines,prev_ss,next_ss,\n", - " z=1,clr='r',mat=0,size=75):\n", - "\n", - " # if loop is smaller than 3 residues and has gaps on both sides, don't draw\n", - " if prev_ss == \"B\" and next_ss == \"B\" and loop[1]-loop[0] < 2:\n", - " return\n", - "\n", - " i0 = loop[0]\n", - " if loop[0] != 0 and prev_ss != \"B\":\n", - " i0 = loop[0]-1\n", - " elif i0 == 0:\n", - " i0 = 0.06\n", - " else:\n", - " i0 = loop[0]\n", - " i1 = loop[1]+2\n", - " if loop[1] == linelen-1:\n", - " i1 += 2\n", - "\n", - " o = 2\n", - " if idx == nlines-1:\n", - " o = 0\n", - " if next_ss == \"B\":\n", - " o = -1.5\n", - " if next_ss == None:\n", - " o=-4.1\n", - "\n", - " rectangle = mpatch.Rectangle((i0/6.0,-0.25-5.5*idx+2.0*ssidx),\n", - " (i1-i0+o)/6.0,0.5,\n", - " fc=clr,ec='k',zorder=0)\n", - "\n", - " plt.gca().add_patch(rectangle)\n", - "\n", - " xy = rectangle.get_xy()\n", - " w = rectangle.get_width()\n", - " h = rectangle.get_height()\n", - " loop_coords.append(np.array([[xy[0],xy[1]],\n", - " [xy[0],xy[1]+h],\n", - " [xy[0]+w,xy[1]+h],\n", - " [xy[0]+w,xy[1]],\n", - " [xy[0],xy[1]]]))\n", - "\n", - "def build_strand(strand,idx,ssidx,strand_coords,next_ss,z=1,clr='r',\n", - " imagemat=0,size=75):\n", - "\n", - " delta = 0 if next_ss == None else 1\n", - "\n", - " arrow=mpatch.FancyArrow(((strand[0]+delta-1)/6.0),-5.5*idx+2.0*ssidx,\n", - " (strand[1]-strand[0]+1)/6.0,0,\n", - " width=1.0,fc=clr,linewidth=0.5,ec='k',\n", - " zorder=z,head_width=2.0,\n", - " length_includes_head=True,head_length=2.0/6.0)\n", - "\n", - " plt.gca().add_patch(arrow)\n", - "\n", - " strand_coords.append(arrow.get_xy())\n", - "\n", - "\n", - "def build_helix(helix,idx,ssidx,coord_set1, coord_set2, clr='r',size=37.5,\n", - " z=1,bkg=(0.195,0,0.051),imagemat=0):\n", - "\n", - " i = helix\n", - " l = i[1]-i[0]+1\n", - " points = [[i[0]/6.0,-0.25-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+1.0/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+2.0/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+1.0/6,-0.25-5.5*idx+2.0*ssidx]]\n", - " #hlx = plt.Polygon(points,fc=clr,ec='k',zorder=1,linewidth=2)\n", - " #coords= hlx.get_xy()\n", - " #coord_set2.append(coords)\n", - " coord_set2.append(points+[points[0]])\n", - "\n", - " for j in range((l-2)-1):\n", - " if j % 2 == 0:\n", - " points = [[i[0]/6.0+(1.0+j)/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(2.0+j)/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(3.0+j)/6,-0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(2.0+j)/6,-0.75-5.5*idx+2.0*ssidx]]\n", - " coord_set1.append(points+[points[0]])\n", - " #hlx = mpatch.Polygon(points,fc=bkg,zorder=z)\n", - "\n", - " else:\n", - " points = [[i[0]/6.0+(1.0+j)/6,-0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(2.0+j)/6,-0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(3.0+j)/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[0]/6.0+(2.0+j)/6,0.75-5.5*idx+2.0*ssidx]]\n", - " coord_set2.append(points+[points[0]])\n", - " #hlx = mpatch.Polygon(points,fc=clr,zorder=0)\n", - "\n", - "\n", - " if (l-2-1)%2 == 1:\n", - "\n", - " points = [[i[1]/6.0-1.0/6,-0.75-5.5*idx+2.0*ssidx],\\\n", - " [i[1]/6.0,-0.75-5.5*idx+2.0*ssidx],\\\n", - " [i[1]/6.0+1.0/6,0.25-5.5*idx+2.0*ssidx],\n", - " [i[1]/6.0,0.25-5.5*idx+2.0*ssidx]]\n", - "\n", - " coord_set2.append(points+[points[0]])\n", - " #hlx = mpatch.Polygon(points,fc=clr,zorder=0)\n", - "\n", - " else:\n", - " points = [[i[1]/6.0-1.0/6,0.75-5.5*idx+2.0*ssidx],\n", - " [i[1]/6.0,0.75-5.5*idx+2.0*ssidx],\\\n", - " [i[1]/6.0+1.0/6,-0.25-5.5*idx+2.0*ssidx],\n", - " [i[1]/6.0,-0.25-5.5*idx+2.0*ssidx]]\n", - " coord_set1.append(points+[points[0]])\n", - "\n", - " #hlx = plt.Polygon(points,fc=bkg,zorder=10)\n", - "\n", - "def SS_breakdown(ss):\n", - "\n", - " i = 0\n", - " curSS = ''\n", - " jstart = -1\n", - " jend = -1\n", - "\n", - " strand = []\n", - " loop = []\n", - " helix = []\n", - " ssbreak = []\n", - "\n", - " ss_order = []\n", - " ss_bounds = []\n", - "\n", - " last_ss = ''\n", - "\n", - " SS_equivalencies = {'H':['H'],\n", - " '-':['-'],\n", - " 'S':[' ','S','C','T','G','I','P'],\n", - " ' ':[' ','S','C','T','G','I','P'],\n", - " 'C':[' ','S','C','T','G','I','P'],\n", - " 'T':[' ','S','C','T','G','I','P'],\n", - " 'G':[' ','S','C','T','G','I','P'],\n", - " 'I':[' ','S','C','T','G','I','P'],\n", - " 'P':[' ','S','C','T','G','I','P'],\n", - " 'E':['E','B'],\n", - " 'B':['E','B']}\n", - "\n", - " cur_SSDict = {'H':'helix',\n", - " '-':'break',\n", - " 'E':'strand',\n", - " 'B':'strand'}\n", - "\n", - " for i in range(len(ss)):\n", - "\n", - " if i == 0:\n", - " curSS = SS_equivalencies[ss[i]]\n", - " jstart = i\n", - " if ss[i] in cur_SSDict.keys():\n", - " last_ss = cur_SSDict[ss[i]]\n", - " else:\n", - " last_ss = 'loop'\n", - " continue\n", - "\n", - " if ss[i] in curSS:\n", - " jend = i\n", - "\n", - " if ss[i] not in curSS or i == len(ss)-1:\n", - " if 'E' in curSS and jend-jstart+1 >= 3:\n", - " strand.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('E')\n", - " last_ss = 'strand'\n", - " elif 'H' in curSS and jend-jstart+1 >=4:\n", - " helix.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('H')\n", - " last_ss = 'helix'\n", - " elif ' ' in curSS and last_ss !='loop':\n", - " if jend < jstart:\n", - " jend = jstart\n", - " loop.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('L')\n", - " last_ss = 'loop'\n", - " elif '-' in curSS:\n", - " if jend < jstart:\n", - " jend = jstart\n", - " ssbreak.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('B')\n", - " last_ss = 'break'\n", - " elif last_ss == 'loop':\n", - " if jend < jstart:\n", - " jend = jstart\n", - " if len(loop) > 0:\n", - " jstart = loop[-1][0]\n", - " loop = loop[0:-1]\n", - " ss_bounds = ss_bounds[0:-1]\n", - " ss_order = ss_order[0:-1]\n", - " loop.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('L')\n", - " last_ss = 'loop'\n", - " else:\n", - " if jend < jstart:\n", - " jend = jstart\n", - " loop.append((jstart,jend))\n", - " ss_bounds.append((jstart,jend))\n", - " ss_order.append('L')\n", - " last_ss = 'loop'\n", - "\n", - "\n", - " jstart = i\n", - " curSS = SS_equivalencies[ss[i]]\n", - "\n", - " return strand,loop,helix, ssbreak, ss_order, ss_bounds\n", - "\n", - "\n", - "def updateSS(ss,seq,alignment,ref_align):\n", - "\n", - " ss_u = ''\n", - "\n", - " j = 0\n", - "\n", - " for i in range(len(alignment)):\n", - " if alignment[i] == '-':\n", - " if ref_align[i] == '-':\n", - " ss_u += '-'\n", - " else:\n", - " ss_u += 'C'\n", - " else:\n", - " ss_u += ss[j]\n", - " j += 1\n", - "\n", - " return ss_u\n", - "\n", - "\n", - "def SS_align(alignment,ID,seq,ss,i_start,i_end):\n", - "\n", - " a_seq = ''\n", - " seq_found = 0\n", - "\n", - " for i in alignment:\n", - "\n", - " if seq_found and i[0] == '>':\n", - " break\n", - "\n", - " if i[0] == '>' and bool(re.search(ID.lower(), i.lower())):\n", - " seq_found = 1\n", - " continue\n", - "\n", - " if seq_found and i[0] != '>':\n", - " a_seq += i\n", - "\n", - " if i_end != 0:\n", - " i_end = len(a_seq)-i_end-1\n", - "\n", - " a_seq = gap_sequence(a_seq, [i_start,i_end])\n", - "\n", - "\n", - " a = pairwise2.align.localxs(seq,a_seq,-1,-0.5)\n", - "\n", - " # check if the dssp annotation has any extra residues not in the alignment\n", - " if a[0][1] != a_seq:\n", - " print(\"extra residues in pdb found\\n\")\n", - "\n", - " # check how many gap marks are at the end and beginning of the alignment\n", - " # (a_seq) and compare to the amount found in a[0][1]\n", - " a_seq_gaps = [0,0]\n", - " new_aln_gaps = [0,0]\n", - " for i in range(len(a_seq)):\n", - " if a_seq[i] == \"-\":\n", - " a_seq_gaps[0] += 1\n", - " else:\n", - " break\n", - " for i in range(len(a_seq)-1, -1, -1):\n", - " if a_seq[i] == \"-\":\n", - " a_seq_gaps[1] += 1\n", - " else:\n", - " break\n", - "\n", - " for i in range(len(a[0][1])):\n", - " if a[0][1][i] == \"-\":\n", - " new_aln_gaps[0] += 1\n", - " else:\n", - " break\n", - " for i in range(len(a[0][1])-1, -1, -1):\n", - " if a[0][1][i] == \"-\":\n", - " new_aln_gaps[1] += 1\n", - " else:\n", - " break\n", - "\n", - " extra_gaps = [new_aln_gaps[0]-a_seq_gaps[0], new_aln_gaps[1]-a_seq_gaps[1]]\n", - "\n", - " SS_updated = updateSS(ss,seq,a[0][0],a[0][1])\n", - "\n", - " SS_updated_new = gap_sequence(SS_updated, extra_gaps)\n", - " a_new = gap_sequence(a[0][1], extra_gaps)\n", - "\n", - " return SS_updated_new, a_new, extra_gaps, i_start, i_end\n", - "\n", - "\n", - "def plot_coords(coords_all,mat,sz,CMAP):\n", - "\n", - " for i,coords in enumerate(coords_all):\n", - "\n", - " if not coords:\n", - " continue\n", - "\n", - " coords_f1, instructions1 = coords2path(coords)\n", - "\n", - " #If loop or bottom helix layer, zorder = 0\n", - " if i in [0,1]:\n", - " z = 0\n", - " else:\n", - " z = 10\n", - "\n", - " path = mpath.Path(np.array(coords_f1),np.array(instructions1))\n", - " patch = mpatch.PathPatch(path, facecolor='none',zorder=z)\n", - " plt.gca().add_patch(patch)\n", - " im = plt.imshow(mat,extent=[0.0,sz,0.5,3.0],cmap=CMAP,interpolation='none',zorder=z)\n", - " im.set_clip_path(patch)\n", - "\n", - "\n", - "def run_dssp(pdb_path, id, chain_id, dssp_exe='mkdssp'):\n", - "\n", - " dssp_mode = \"dssp\"\n", - " ss_seq = \"\"\n", - " aa_seq = \"\"\n", - " #Suppress Biopython PDBParser warning\n", - " with warnings.catch_warnings(record=True) as w:\n", - " warnings.simplefilter(\"always\", PDBConstructionWarning)\n", - " p = PDBParser()\n", - " structure = p.get_structure(id, pdb_path)\n", - " model = structure[0]\n", - "\n", - " dssp = DSSP(model, pdb_path, dssp=dssp_exe)\n", - "\n", - "\n", - " if dssp_mode == \"dssp\":\n", - " a_key = list(dssp.keys())\n", - " for key in a_key:\n", - " if key[0] == chain_id:\n", - " aa_seq+=dssp[key][1]\n", - " if dssp[key][2] == \"-\":\n", - " ss_seq+=\"C\"\n", - " else:\n", - " ss_seq+=dssp[key][2]\n", - "\n", - " return [ss_seq,aa_seq]\n", - "\n", - "def convert2horiz(dssp_file, pdbseq):\n", - "\n", - " ss_seq = \"\"\n", - " aa_seq = \"\"\n", - "\n", - " with open(dssp_file, \"r\") as f:\n", - " lines = f.readlines()\n", - "\n", - " dssp_ext = dssp_file.split(\".\")[-1]\n", - "\n", - " if dssp_ext == \"horiz\":\n", - " ss_seq = lines[0].rstrip('\\n')\n", - " aa_seq = lines[1].rstrip('\\n')\n", - "\n", - " elif dssp_ext == \"dssp\":\n", - " start_read = False\n", - " for line in lines:\n", - " if start_read:\n", - " if line[13] == \"!\":\n", - " start_read = False\n", - " continue\n", - " ss_seq += line[16]\n", - " aa_seq += line[13]\n", - " if line.split()[0] == \"#\":\n", - " start_read = True\n", - "\n", - " else:\n", - " raise Exception(\"DSSP file extension not recognized: must be in .dssp or .horiz format\")\n", - "\n", - " return [ss_seq,aa_seq]\n", - "\n", - "def score_column(msa_col, threshold=0):\n", - "\n", - " blosum62 = substitution_matrices.load(\"BLOSUM62\")\n", - " # find consensus of the column\n", - " aa_count = {\"A\": 0, \"R\": 0, \"N\": 0, \"D\": 0, \"C\": 0, \"Q\": 0, \"E\": 0,\n", - " \"G\": 0, \"H\": 0, \"I\": 0, \"L\": 0, \"K\": 0, \"M\": 0, \"F\": 0,\n", - " \"P\": 0, \"S\": 0, \"T\": 0, \"W\": 0, \"Y\": 0, \"V\": 0}\n", - " for i in msa_col:\n", - " try:\n", - " aa_count[i] += 1\n", - " except:\n", - " pass\n", - " consensus_aa = max(zip(aa_count.values(), aa_count.keys()))[1]\n", - "\n", - " conservation_count = 0\n", - " for i in msa_col:\n", - " if i in aa_count.keys():\n", - " if blosum62[consensus_aa][i] >= 0:\n", - " conservation_count += 1\n", - "\n", - " return conservation_count/len(msa_col)\n", - "\n", - "def parse_color(args,seq_wgaps,pdbseq,bfactors,msa,extra_gaps):\n", - " CMAP = \"\"\n", - " if args.color in mcolors.BASE_COLORS.keys() or \\\n", - " args.color in mcolors.CSS4_COLORS.keys() or \\\n", - " args.color in mcolors.XKCD_COLORS.keys():\n", - " CMAP = ListedColormap([args.color])\n", - " elif args.color[0] == \"#\":\n", - " CMAP = ListedColormap([args.color])\n", - " if args.conservation_score or args.bfactor or args.scoring_file:\n", - " if len(args.color_map) == 1:\n", - " CMAP = args.color_map[0]\n", - " else:\n", - " CMAP = ListedColormap(args.color_map)\n", - "\n", - " #bvals are to make the colormap; taken from input PDB\n", - " bvals = []\n", - "\n", - " if args.mview:\n", - " mview_colors = {\"A\": 0, \"G\": 0, \"I\": 0, \"L\": 0, \"M\": 0, \"P\": 0, \"V\": 0,\n", - " \"F\": 1, \"H\": 1, \"W\": 1, \"Y\": 1,\n", - " \"K\": 2, \"R\": 2,\n", - " \"D\": 3, \"E\": 3,\n", - " \"S\": 4, \"T\": 4,\n", - " \"N\": 5, \"Q\": 5,\n", - " \"C\": 6}\n", - " mview_colors_hit = [0,0,0,0,0,0,0]\n", - "\n", - " mview_color_map = [\"#33cc00\",\"#009900\",\"#cb0000\",\"#0133ff\",\"#0299fe\",\n", - " \"#6601cc\",\"#ffff00\",\"#808080\"]\n", - "\n", - " for i in range(len(seq_wgaps)):\n", - " try:\n", - " m = mview_colors[seq_wgaps[i]]\n", - " bvals.append(m)\n", - " mview_colors_hit[m]+=1\n", - " except:\n", - " bvals.append(7)\n", - "\n", - " # remove colors of residues not in sequence\n", - " for i in range(len(mview_colors_hit)):\n", - " if mview_colors_hit[i] == 0:\n", - " mview_color_map.pop(i)\n", - " for j in range(len(bvals)):\n", - " if bvals[j] > i:\n", - " bvals[j] -= 1\n", - "\n", - " CMAP = ListedColormap(mview_color_map)\n", - "\n", - " elif args.consurf:\n", - " # read in a rate4site output file or consurf score file\n", - " # if rate4site output file, convert raw scores to 1-9 scores\n", - " consurf_color_map = [\"#10C8D1\", \"#8CFFFF\", \"#D7FFFF\", \"#EAFFFF\", \"#FFFFFF\",\n", - " \"#FCEDF4\", \"#FAC9DE\", \"#F07DAB\", \"#A02560\"]\n", - "\n", - " scoring_seq = \"\"\n", - " bvals_tmp = []\n", - " consurf_mode = check_consurf_file(args.consurf)\n", - " if consurf_mode == \"consurf\":\n", - " scoring_seq,bvals_tmp = read_consurf_grad(args.consurf)\n", - " elif consurf_mode == \"r4s\":\n", - " scoring_seq,bvals_tmp = read_r4s(args.consurf)\n", - "\n", - "\n", - " # remove colors of residues not in sequence\n", - " for i in reversed(range(1,10)):\n", - " if i not in bvals_tmp:\n", - " consurf_color_map.pop(i-1)\n", - " for j in range(len(bvals_tmp)):\n", - " if bvals_tmp[j] > i:\n", - " bvals_tmp[j] -= 1\n", - "\n", - " CMAP = ListedColormap(consurf_color_map)\n", - "\n", - " score_align = pairwise2.align.localxs(pdbseq,scoring_seq,-1,-0.5)\n", - "\n", - " j = 0\n", - " for i in range(len(score_align[0][1])):\n", - " if score_align[0][0][i] != \"-\":\n", - " if score_align[0][1][i] != \"-\":\n", - " bvals.append(bvals_tmp[j])\n", - " j+=1\n", - " else:\n", - " bvals.append(min(bvals_tmp))\n", - "\n", - " elif args.scoring_file: # use custom scoring by residue\n", - " # read in scoring file\n", - " bvals_tmp = []\n", - " scoring_seq = \"\"\n", - " with open(args.scoring_file, \"r\") as g:\n", - " lines = g.readlines()\n", - "\n", - " if lines[0] == '\\t Amino Acid Conservation Scores\\n': # read in consurf file\n", - " for line in lines:\n", - " if len(line.split()) > 0:\n", - " if line.split()[0].isdigit():\n", - " scoring_seq += line.split()[1]\n", - " bvals_tmp.append(float(line.split()[4]))\n", - "\n", - " else: # read in custom scoring file\n", - " for line in lines:\n", - " scoring_seq += line.split()[0]\n", - " bvals_tmp.append(float(line.split()[1]))\n", - "\n", - " score_align = pairwise2.align.localxs(pdbseq,scoring_seq,-1,-0.5)\n", - "\n", - " j = 0\n", - " for i in range(len(score_align[0][1])):\n", - " if score_align[0][0][i] != \"-\":\n", - " if score_align[0][1][i] != \"-\":\n", - " bvals.append(bvals_tmp[j])\n", - " j+=1\n", - " else:\n", - " bvals.append(min(bvals_tmp))\n", - "\n", - "\n", - " elif args.bfactor: # score by bfactor\n", - " bvals = [b for b in bfactors]\n", - "\n", - " elif args.conservation_score: # score by conservation score\n", - " bvals = []\n", - " for i in range(len(msa[0])):\n", - " bvals.append(score_column([msa[j][i] for j in range(len(msa))]))\n", - "\n", - " else: # solid color\n", - " bvals = [i for i in range(len(msa[0]))]\n", - "\n", - " if len(bvals) == len(pdbseq):\n", - " # remove extra residues\n", - " pdbseq = gap_sequence(pdbseq, extra_gaps)\n", - " bvals = gap_sequence(bvals, extra_gaps)\n", - "\n", - " j = 0\n", - " bvalsf = []\n", - " bvals_align = pairwise2.align.localxs(seq_wgaps,pdbseq,-1,-0.5)\n", - " if bvals_align[0][0] != seq_wgaps:\n", - " print(\"Error in alignment or pdb sequence\")\n", - " sys.exit()\n", - " for i in range(len(seq_wgaps)):\n", - " if seq_wgaps[i] == \"-\" or bvals_align[0][1][i] == \"-\":\n", - " if j >= len(bvals):\n", - " bvalsf.append(bvals[j-1])\n", - " else:\n", - " bvalsf.append(bvals[j])\n", - " elif seq_wgaps[i] == bvals_align[0][1][i]:\n", - " bvalsf.append(bvals[j])\n", - " j+=1\n", - "\n", - " bvals = bvalsf\n", - "\n", - " return CMAP, bvals\n", - "\n", - "def read_pdb(id,args):\n", - " pdbseq = ''\n", - " #Suppress Biopython PDBParser warning\n", - " with warnings.catch_warnings(record=True) as w:\n", - " warnings.simplefilter(\"always\", PDBConstructionWarning)\n", - " p = PDBParser()\n", - " bfactors = []\n", - " structure = p.get_structure(id, args.pdb)\n", - " model = structure[0]\n", - " for chain in model:\n", - " if chain.get_id() == args.chain_id:\n", - " for residue in chain:\n", - " for atom in residue:\n", - " if atom.name == \"CA\":\n", - " bfactors.append(atom.bfactor)\n", - " pdbseq += seq1(residue.get_resname())\n", - " break\n", - " sys.stdout = sys.__stdout__\n", - "\n", - " return bfactors, pdbseq\n", - "\n", - "description='''\n", - "----------------\n", - "\n", - "SSDraw is a program that generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring.\n", - "\n", - "SSDraw also has a colab notebook available at https://github.com/ethanchen1301/SSDraw/blob/main/SSDraw.ipynb\n", - "\n", - "\n", - "\n", - "Installation:\n", - "\n", - "SSDraw requires the biopython module:\n", - " pip install biopython\n", - "\n", - "SSDraw also requires the DSSP program to be installed in order to generate secondary structure annotations.\n", - " sudo apt-get install dssp\n", - "\n", - "Alternatively, you can install DSSP either through conda (conda install -c salilab dssp), or you can follow the instructions on their github page to make a local installation:\n", - "https://github.com/cmbi/dssp.\n", - "\n", - "\n", - "\n", - "Instructions:\n", - "SSDraw requires 4 arguments:\n", - "1. --fasta: the file name sequence or alignment file in fasta format.\n", - "2. --name: the id of the sequence in the fasta file corresponding to your protein of interest.\n", - "3. --pdb: the file name of the pdb file of your protein\n", - "4. --output: the output file name to use\n", - "\n", - "Example 1:\n", - " python3 ../SSDraw.py --fasta 1ndd.fasta --name 1ndd --pdb 1ndd.pdb --output 1ndd_out\n", - "\n", - "Coloring options:\n", - "SSDraw uses a gradient to color each position in the alignment by a certain score. The user can choose which scoring system to use, and they can also choose which colormap.\n", - "\n", - "Scoring:\n", - "-conservation_score: score each position in the alignment by conservation score.\n", - "-bfactor: score each residue in the pdb by B-factor\n", - "-scoring_file: score each residue by a custom scoring file prepared by the user\n", - "-mview: color each residue by the mview coloring system\n", - "\n", - "Example 2: Score by conservation\n", - " python3 ../SSDraw.py --fasta aligned.fasta --name 1ndd --pdb 1ndd.pdb --output 1ndd_conservation -conservation_score\n", - "\n", - "Example 3: Score by B-factor\n", - " python3 ../SSDraw.py --fasta 1ndd.fasta --name 1ndd --pdb 1ndd.pdb --output 1ndd_bfactor -bfactor\n", - "\n", - "Choosing a colormap:\n", - "The default colormap for SSDraw is inferno. The user can select one of the matplotlib library color maps or simply list a set of colors they'd like to use with the --color_map option. Alternatively, the user can select a single color with the --color option and SSDraw will use that color on the whole image.\n", - "\n", - "Example 4: Custom scoring file with custom color map\n", - " python3 ../SSDraw.py --fasta 2kdl.fasta --name 2kdl --pdb 2kdl.pdb --output 2kdl_out --scoring_file 2kdl_scoring.txt --color_map black cyan\n", - "\n", - "DSSP files:\n", - "Normally, SSDraw will generate a DSSP annotation from the PDB file, but if you have a DSSP file you would like to use, you can upload it and input the file name in Options.\n", - "\n", - "--start and --end:\n", - "If you want SSDraw to draw only a portion of your alignment, you can specify the start and/or end points using the --start and --end options respectively. The argument for these options correspond to the index of the alignment position, not to the residue position numbers.\n", - "\n", - "Example 5: Choose subregion of alignment to run SSDraw on\n", - " python3 ../SSDraw.py --fasta aligned.fasta --name 1ndd --pdb 1ndd.pdb --output 1ndd_conservation_cropped -conservation_score --start 80 --end 132\n", - "\n", - "Running on multiple pdbs:\n", - "In order to rapidly generate multiple images with SSDraw, we recommend writing shell scripts comprised of commands like those shown in the above examples. For examples of such shell scripts, see one of the shell scripts in /figures/.\n", - "----------------\n", - "\n", - "'''" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2kRtLMtIo7HF" - }, - "source": [ - "←\n", - "\n", - "←\n", - "\n", - "You will need to upload the sequence and pdb files to this session.\n", - "Click on the Files icon to the left then choose 'upload to session storage'\n", - "\n", - "Once the files are uploaded type the file names below.\n", - "\n", - "←\n", - "\n", - "←" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "EoaVx2yihGke" - }, - "outputs": [], - "source": [ - "#%%capture\n", - "\n", - "## allow user to upload from their computer\n", - "\n", - "from google.colab import files\n", - "#@title Define variables\n", - "#@markdown ##Required:\n", - "#@markdown Please input the following arguments:\n", - "fasta_file = \"\" #@param {type:\"string\"}\n", - "#@markdown - The filename of the input sequence/alignment file (must be in fasta format).\n", - "name = '' #@param {type:\"string\"}\n", - "#@markdown - The fasta identifier of target protein (what follows the \">\" character in the fasta file).\n", - "pdb_file = \"\" #@param {type:\"string\"}\n", - "#@markdown - The filename of the input pdb file.\n", - "output = \"\" #@param {type:\"string\"}\n", - "#@markdown - The desired name of the output file (default image type is png).\n", - "chain_id = 'A' #@param {type:\"string\"}\n", - "#@markdown - The chain id in the pdb file (default \"A\")\n", - "\n", - "#@markdown For more information please see [instructions](#Instructions) at the bottom of the page.\n", - "\n", - "salign = open(fasta_file).read().splitlines() # every line from the alignment\n", - "\n", - "#@markdown ##Options:\n", - "#@markdown These are optional parameters you can use to further customize the generated image. You should not need to modify any of these to get the code to run.\n", - "coloring = \"solid\" #@param [\"solid\", \"gradient\", \"mview\"]\n", - "#@markdown - Choose whether to color the image by a gradient or with a solid coloring.\n", - "scoring = \"by conservation score\" #@param [\"by conservation score\",\"by bfactor\", \"consurf\",\"custom\"]\n", - "#@markdown - If coloring by gradient, the image will be colored according to the chosen scoring system.\n", - "consurf = \"\" #@param {type: \"string\"}\n", - "#@markdown - If you want to color by consurf grades, type in the name of your consurf file here\n", - "scoring_file = \"\" #@param {type: \"string\"}\n", - "#@markdown - If custom scoring was selected, please input the filename of the scoring file.\n", - "gradient_color_map = \"inferno\" #@param {type: \"string\"}\n", - "#@markdown - Choose which gradient color map to use (default is inferno). You can use any built-in colormap from matplotlib. You can also input a list of space-delimited colors (eg. \"black cyan red\").\n", - "solid_color = \"white\" #@param {type:\"string\"}\n", - "#@markdown - If coloring by solid, this is the color that will be used.\n", - "dssp_file =\"\" #@param {type:\"string\"}\n", - "#@markdown - If desired, one can choose to input their own secondary structure annotation for SSDraw to use. File must be in .dssp or .horiz format. Using this option is not recommended for most cases, as SSDraw already computes the secondary structure with DSSP from the given PDB file.\n", - "ticks=0 #@param [0,5,10,20]\n", - "#@markdown - Add ticks at every nth position to the output image. If this option is set to zero, ticks will not be added to the image.\n", - "output_file_type = \"png\" #@param [\"png\", \"ps\", \"eps\", \"tif\", \"svg\"] {type:\"string\"}\n", - "image_dpi = 600 #@param {type:\"raw\"}\n", - "\n", - "\n", - "id = name\n", - "color = solid_color\n", - "color_map = gradient_color_map\n", - "\n", - "f = run_dssp(pdb_file, id, chain_id)\n", - "\n", - "# custom arg parse for colab notebook\n", - "class ArgParser():\n", - " def __init__(self, fasta, name, pdb, output, dssp=None,\n", - " chain_id = \"A\", color_map=[\"inferno\"], scoring_file=None,\n", - " color=\"white\", conservation_score=False, output_file_type=\"png\",\n", - " bfactor=False,mview=False,dpi=600,start=0,end=0,ticks=0):\n", - " self.fasta = fasta\n", - " self.name = name\n", - " self.pdb = pdb\n", - " self.output = output\n", - " self.dssp = dssp\n", - " self.chain_id = chain_id\n", - " self.color_map = color_map\n", - " self.scoring_file = scoring_file\n", - " self.color = color\n", - " self.conservation_score = conservation_score\n", - " self.output_file_type = output_file_type\n", - " self.bfactor = bfactor\n", - " self.mview = mview\n", - " self.dpi = dpi\n", - " self.start = start\n", - " self.end = end\n", - " self.ticks = int(ticks)\n", - " self.consurf = \"\"\n", - "\n", - "# parse arguments\n", - "args = ArgParser(fasta_file,name,pdb_file,output,dssp=dssp_file,\n", - " chain_id=chain_id,color_map=gradient_color_map,\n", - " scoring_file=None, color=solid_color,\n", - " conservation_score=False, output_file_type=output_file_type,\n", - " bfactor=False,mview=False,dpi=600,start=0,end=0,ticks=ticks)\n", - "\n", - "# parse coloring and scoring\n", - "if coloring != \"solid\":\n", - " args.color_map = gradient_color_map.split()\n", - " if coloring == \"mview\":\n", - " args.mview = True\n", - " elif scoring == \"consurf\":\n", - " args.consurf = consurf\n", - " elif scoring == \"by conservation score\":\n", - " args.conservation_score = True\n", - " elif scoring == \"by bfactor\":\n", - " args.bfactor = True\n", - " elif scoring == \"custom\":\n", - " args.scoring_file = scoring_file" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "id3iqycepcxe" - }, - "outputs": [], - "source": [ - "#@title Choose subregion of alignment to run SSDraw on\n", - "#@markdown If you want to run SSDraw on the entire alignment, run this cell, but leave these sliders unchanged.\n", - "\n", - "#@markdown IMPORTANT: These are the numberings based on the alignment, not on the numbering in the pdb file.\n", - "## Change numbering to the numbering in the pdb\n", - "\n", - "# alignment subsection\n", - "from ipywidgets import interact, interactive, fixed, interact_manual\n", - "import ipywidgets as widgets\n", - "from IPython.display import display\n", - "\n", - "display_seq = \"\"\n", - "display_seq_found = False\n", - "for i in salign:\n", - " if display_seq_found and i[0] == '>':\n", - " break\n", - " if i[0] == '>' and bool(re.search(id.lower(), i.lower())):\n", - " display_seq_found = True\n", - " continue\n", - "\n", - " if display_seq_found and i[0] != '>':\n", - " display_seq += i\n", - "\n", - "def aln_sub(start=0,end=len(display_seq)):\n", - " display(display_seq[start:end+1])\n", - " return [start,end]\n", - "\n", - "w = interactive(aln_sub, start=(0,len(display_seq)), end=(0,len(display_seq)))\n", - "display(w)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 106 - }, - "id": "apdnrtPLXcId", - "outputId": "6fadee26-5a9a-45ea-9918-80364c0dfd89" - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#@title Run SSDraw\n", - "\n", - "# parse start and end\n", - "start,end = w.result\n", - "args.start = start\n", - "if end == len(display_seq):\n", - " args.end = 0\n", - "else:\n", - " args.end = end\n", - "\n", - "def get_args():\n", - "\n", - " parser = argparse.ArgumentParser(\n", - " formatter_class=argparse.RawDescriptionHelpFormatter,\n", - " description = description,\n", - " epilog=\"\")\n", - " parser.add_argument(\"-f\", \"--fasta\", help=\"(required) sequence/alignment file in fasta format\")\n", - " parser.add_argument(\"-p\", \"--pdb\", help=\"(required) pdb file\")\n", - " parser.add_argument(\"-n\", \"--name\", help=\"(required) id of the protein in the alignment file\")\n", - " parser.add_argument(\"-o\", \"--output\", help=\"(required) name for output file\")\n", - " parser.add_argument(\"--dssp\", default=None, help=\"secondary structure annotation in DSSP or .horiz format. If this option is not provided, SSDraw will compute secondary structure from the given PDB file with DSSP.\")\n", - " parser.add_argument(\"--chain_id\", default=\"A\", help=\"chain id to use in pdb. Defaults to chain A.\")\n", - " parser.add_argument(\"--color_map\", default=[\"inferno\"], nargs=\"*\", help=\"color map to use for heat map\")\n", - " parser.add_argument(\"--scoring_file\",default=None,help=\"custom scoring file for alignment\")\n", - " parser.add_argument(\"--color\", default=\"white\", help=\"color for the image. Can be a color name (eg. white, black, green), or a hex code\")\n", - " parser.add_argument(\"-conservation_score\", action='store_true', help=\"score alignment by conservation score\")\n", - " parser.add_argument(\"--output_file_type\", default=\"png\")\n", - " parser.add_argument(\"-bfactor\", action='store_true', help=\"score by B-factor\")\n", - " parser.add_argument(\"-mview\", action=\"store_true\", help=\"color by mview color map\")\n", - " parser.add_argument(\"--dpi\", default=600, type=int, help=\"dpi to use for final plot\")\n", - " parser.add_argument(\"--start\", default=0, type=int)\n", - " parser.add_argument(\"--end\", default=0,type=int)\n", - " parser.add_argument(\"--consurf\", default=\"\", help=\"consurf or rate4site file to color image with. If rate4site file is given, SSDraw will convert raw scores to grades.\")\n", - "\n", - " args = parser.parse_args()\n", - "\n", - " return args, parser\n", - "\n", - "def initialize(args):\n", - " #args, parser = get_args()\n", - "\n", - " '''if not args.fasta or not args.pdb or not args.output or not args.name:\n", - " parser.print_help(sys.stderr)\n", - " sys.exit(1)'''\n", - "\n", - " # preface run\n", - " id = args.name\n", - " chain_id = args.chain_id\n", - " print(\"\\nRunning for: \"+id)\n", - "\n", - " # read in amino acid sequence from PDB\n", - " bfactors, pdbseq = read_pdb(id,args)\n", - "\n", - " if args.dssp:\n", - " # get secondary structure from pre-existing DSSP annotation\n", - " f = convert2horiz(args.dssp,pdbseq)\n", - " else:\n", - " # run the dssp executable\n", - " f = run_dssp(args.pdb, id, chain_id)\n", - "\n", - " nlines = 1\n", - " salign = open(args.fasta).read().splitlines()\n", - "\n", - " if args.start > args.end and args.end != 0:\n", - " raise Exception(\"--start cannot be greater than --end\")\n", - "\n", - " #####Align secondary structure to match input sequence alignment\n", - " ss_wgaps,seq_wgaps,extra_gaps,i_start,i_end = SS_align(salign,args.name,f[1],f[0],args.start,args.end)\n", - "\n", - " #Break down secondary structure classifications in to continuous\n", - " #chunks of helix, strand, and coil\n", - " strand,loop,helix,ss_break,ss_order,ss_bounds = SS_breakdown(ss_wgaps)\n", - "\n", - " msa = [gap_sequence(a, [i_start, i_end]) for a in AlignIO.read(open(args.fasta), \"fasta\")]\n", - "\n", - " return args,pdbseq,bfactors,msa,ss_wgaps,seq_wgaps,extra_gaps,i_start,i_end,strand,loop,helix,ss_break,ss_order,ss_bounds\n", - "\n", - "def SSDraw(args):\n", - "\n", - " args,pdbseq,bfactors,msa,ss_wgaps,seq_wgaps,extra_gaps,i_start,i_end,strand,loop,helix,ss_break,ss_order,ss_bounds=initialize(args)\n", - " nlines = 1\n", - "\n", - " #Parse color and scoring args\n", - " CMAP, bvals = parse_color(args,seq_wgaps,pdbseq,bfactors,msa,extra_gaps)\n", - "\n", - " mat = np.tile(NormalizeData(bvals), (100,1))\n", - "\n", - " #set figure parameters\n", - " sz = 0\n", - " c = 'none'\n", - " bc = 'none'\n", - "\n", - " #set sizes of SS chunks\n", - " ss_prev = 0\n", - " for i in range(len(ss_order)):\n", - "\n", - " if ss_order[i] == 'H':\n", - " ss_prev = ss_bounds[i][1]/6.0+1/6.0\n", - " else:\n", - " ss_prev = ss_bounds[i][1]/6.0\n", - "\n", - " if ss_order[-1] == 'H':\n", - " sz = ss_bounds[-1][1]/6.0+1/6.0\n", - " elif ss_order[-1] in ['E','B']:\n", - " sz = ss_bounds[-1][1]/6.0\n", - " elif ss_order[-1] == 'L':\n", - " sz = (ss_bounds[-1][1])/6.0\n", - "\n", - " #Plot secondary structure chunks\n", - " strand_coords = []\n", - " loop_coords = []\n", - " helix_coords1 = []\n", - " helix_coords2 = []\n", - "\n", - " fig, ax = plt.subplots(ncols=1, figsize=(25,2+1.5*(nlines-1)))\n", - "\n", - " for i in range(len(ss_order)):\n", - " prev_ss = None\n", - " next_ss = None\n", - " if i != 0:\n", - " prev_ss = ss_order[i-1]\n", - " if i != len(ss_order)-1:\n", - " next_ss = ss_order[i+1]\n", - "\n", - " if ss_order[i] == 'L':\n", - " build_loop(ss_bounds[i],0,1,loop_coords,len(ss_wgaps),1,prev_ss,next_ss,z=0,clr=c,mat=mat,size=sz)\n", - " elif ss_order[i] == 'H':\n", - " build_helix(ss_bounds[i],0,1,helix_coords1,helix_coords2,z=i,clr=c,bkg=bc,imagemat=mat,size=sz)\n", - " elif ss_order[i] == 'E':\n", - " build_strand(ss_bounds[i],0,1,strand_coords,next_ss,z=i,clr=c,imagemat=mat,size=sz)\n", - "\n", - "\n", - " plot_coords([loop_coords,helix_coords2,strand_coords,helix_coords1],mat,sz,CMAP)\n", - "\n", - " plt.ylim([0.5,3])\n", - "\n", - " # remove spines and yticks\n", - " ax.spines['top'].set_visible(False)\n", - " ax.spines['right'].set_visible(False)\n", - " ax.spines['bottom'].set_visible(False)\n", - " ax.spines['left'].set_visible(False)\n", - " ax.get_yaxis().set_ticks([])\n", - "\n", - " if args.ticks == 0:\n", - " ax.get_xaxis().set_ticks([])\n", - " else:\n", - " res_x = 0.1646\n", - " ticks = []\n", - " labels = []\n", - " i = 0\n", - " label_i = 1\n", - " while label_i <= len(bvals):\n", - " ticks.append(i)\n", - " labels.append(str(label_i))\n", - " i+=res_x*args.ticks\n", - " label_i+=args.ticks\n", - " ax.get_xaxis().set_ticks(ticks,labels=labels)\n", - " ax.xaxis.set_ticks_position('top')\n", - "\n", - " ax.set_aspect(0.5)\n", - "\n", - " print(\"Saving output to output/{:}.{:}...\".format(args.output, args.output_file_type))\n", - " if not os.path.exists(\"output\"):\n", - " os.makedirs(\"output\")\n", - " plt.savefig(\"output/\"+args.output+\".\"+args.output_file_type,bbox_inches='tight',dpi=args.dpi,transparent=True)\n", - "\n", - "\n", - "SSDraw(args)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 17 - }, - "id": "PxZS0WpKshib", - "outputId": "f3609058-e9c6-4f6d-dca8-8d117f03ffe9" - }, - "outputs": [ - { - "data": { - "application/javascript": "\n async function download(id, filename, size) {\n if (!google.colab.kernel.accessAllowed) {\n return;\n }\n const div = document.createElement('div');\n const label = document.createElement('label');\n label.textContent = `Downloading \"${filename}\": `;\n div.appendChild(label);\n const progress = document.createElement('progress');\n progress.max = size;\n div.appendChild(progress);\n document.body.appendChild(div);\n\n const buffers = [];\n let downloaded = 0;\n\n const channel = await google.colab.kernel.comms.open(id);\n // Send a message to notify the kernel that we're ready.\n channel.send({})\n\n for await (const message of channel.messages) {\n // Send a message to notify the kernel that we're ready.\n channel.send({})\n if (message.buffers) {\n for (const buffer of message.buffers) {\n buffers.push(buffer);\n downloaded += buffer.byteLength;\n progress.value = downloaded;\n }\n }\n }\n const blob = new Blob(buffers, {type: 'application/binary'});\n const a = document.createElement('a');\n a.href = window.URL.createObjectURL(blob);\n a.download = filename;\n div.appendChild(a);\n a.click();\n div.remove();\n }\n ", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": "download(\"download_347d0a21-14b5-4e1d-8ba1-07578cdbf254\", \"output.zip\", 147368)", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#@title Download output files\n", - "\n", - "!zip -r output.zip output # first, zip files\n", - "files.download(\"output.zip\")# Then download zipped file" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yUC0X28sDRBJ" - }, - "source": [ - "## Optional: Creating a composite image\n", - "If running SSDraw on multiple pdbs, you can use the code block below to combine your images into a composite image." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "PEfc9neUHZYN" - }, - "outputs": [], - "source": [ - "#@title Create composite image\n", - "# create list and order all outputs by creation time.\n", - "# then combine images together\n", - "from PIL import Image\n", - "\n", - "img_names = [\"output/\"+img for img in os.listdir(\"output/\") if img != \"composite.png\"]\n", - "img_names.sort(key = lambda x: os.path.getctime(x))\n", - "\n", - "imgs = [Image.open(img_name) for img_name in img_names]\n", - "\n", - "# combine SSDraw images into a composite image\n", - "def combine_images(imgs):\n", - "\n", - " height = min([img.height for img in imgs])\n", - " width = min([img.width for img in imgs])\n", - " pic = Image.new('RGB', (width, height*len(imgs)))\n", - "\n", - " height_i = 0\n", - "\n", - " for img in imgs:\n", - " x = img.crop((0,0,width,height))\n", - " pic.paste(x, (0, height_i))\n", - " height_i+=height\n", - " return pic\n", - "\n", - "combine_images(imgs).save(\"output/composite.png\")\n", - "im = Image.open(\"output/composite.png\")\n", - "im" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "vToOLIiTxHmp" - }, - "source": [ - "# Instructions \n", - "**Quick start**\n", - "1. Upload a pdb file and a sequence file in fasta format. To do this, click the folder icon on the left tab, and select the \"upload files\" option.\n", - "2. Run the first cell block titled \"SSDraw\". This will download and install the necessary dependencies. It should take around 1-2 minutes.\n", - "3. Fill out the arguments in the required section of \"Define Variables.\" Input the sequence file name, name of the protein used in the fasta file, pdb file name, and output file name into their respective prompts. Leave the other options unchanged and run this cell block.\n", - "4. Run the two cell blocks \"Choose subregion to run SSDraw on\" and \"run SSDraw\". You should see an output image in the window.\n", - "5. To download the results, run \"Download output files\".\n", - "**Running on multiple PDBs**\n", - "\n", - "Run the first cell titled \"SSDraw\". Then fill in the required inputs for your first pdb, and run the next three cells: \"Define variables\", \"Choose subregion...\", and \"Run SSDraw\". That will generate an image for your first PDB. To run again for the next pdb, edit the input section and rerun the same three cells \"Define variables, \"Choose subregion...\", and \"Run SSDraw\". You do not need to rerun the first cell, since it is just for installing and importing the required libraries. Repeat this step for all PDBs.\n", - "Each time you run SSDraw, the resulting image will be saved to the directory named \"output\". Run the final cell titled \"Download output files\" to download a zip file of the output directory.\n", - "\n", - "*Note*: If you are running SSDraw for multiple pdbs on a subregion of the alignment, you can skip rerunning the \"Choose subregion...\" cell. This will fix the subregion for all of your runs.\n", - "\n", - "**File formats:**\n", - "\n", - "The alignment file you use must be in fasta format.\n", - "\n", - "If you use a custom file to score residues, write the file in the following format: every line includes first the one-letter amino acid code of the residue, followed by a space, and then the score for that residue.\n", - "\n", - "**DSSP files:**\n", - "\n", - "Normally, SSDraw will generate a DSSP annotation from the PDB file, but if you have a DSSP file you would like to use, you can upload it and input the file name in Options.\n", - "\n", - "**Coloring:**\n", - "\n", - "SSDraw provides both solid and gradient coloring. If you choose solid, you can pick which solid color to use by either typing a color name contained in matplotlib's color library or a hexcode (with a preceding #). If you choose gradient, SSDraw will use the gradient color map selected in the options section. The image will be colored in based on a per-residue score (see Scoring). SSDraw also provides the option to color based on the mview color map, which colors residues by their chemical property.\n", - "\n", - "**Scoring**:\n", - "\n", - "There are two scoring methods built into SSDraw: scoring by conservation score or scoring by b-factor. There are also two ways to use a custom scoring method. First, you can upload a scoring file following this file format: every line includes first a one-letter amino acid code, followed by a space, and then the score of that residue. Another way to use a custom scoring is to edit the b-factors of the C-alpha carbons in your pdb file, then choose score by b-factor." - ] - } - ], - "metadata": { - "colab": { - "authorship_tag": "ABX9TyO8RdggjFDXk0MtbvTRLOGN", - "include_colab_link": true, - "provenance": [] - }, - "kernelspec": { - "display_name": "env", - "language": "python", - "name": "python3" - }, - "language_info": { - "name": "python", - "version": "3.14.0" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/docs/commands/multi.md b/docs/commands/multi.md new file mode 100644 index 0000000..faa2678 --- /dev/null +++ b/docs/commands/multi.md @@ -0,0 +1,12 @@ +# SSDraw multi Command + +This section documents the `ssdraw multi` command. + +```bash +usage: generate_docs.py multi [-h] -i INPUT -o OUTPUT + +options: + -h, --help show this help message and exit + -i, --input INPUT Name of input script + -o, --output OUTPUT Name of output directory +``` diff --git a/docs/commands/single.md b/docs/commands/single.md new file mode 100644 index 0000000..5162ba7 --- /dev/null +++ b/docs/commands/single.md @@ -0,0 +1,39 @@ +# SSDraw single Command + +This section documents the `ssdraw single` command. + +```bash +usage: generate_docs.py single [-h] [-f FASTA] [-p PDB] [-n NAME] [-o OUTPUT] [--SS SS] [--chain_id CHAIN_ID] [--color_map [COLOR_MAP ...]] + [--scoring_file SCORING_FILE] [--color COLOR] [-conservation_score] [--output_file_type OUTPUT_FILE_TYPE] [-bfactor] + [-mview] [--dpi DPI] [--ticks TICKS] [--start START] [--end END] [--dssp_exe DSSP_EXE] [--consurf CONSURF] + [--fontsize FONTSIZE] [--fontcolor FONTCOLOR] + +options: + -h, --help show this help message and exit + -f, --fasta FASTA (required) sequence/alignment file in fasta format + -p, --pdb PDB (required) pdb file + -n, --name NAME (required) id of the protein in the alignment file + -o, --output OUTPUT (required) name for output file + --SS SS secondary structure annotation in DSSP or .horiz format. If this option is not provided, SSDraw will compute secondary structure + from the given PDB file with DSSP. + --chain_id CHAIN_ID chain id to use in pdb. Defaults to chain A. + --color_map [COLOR_MAP ...] + color map to use for heat map + --scoring_file SCORING_FILE + custom scoring file for alignment + --color COLOR color for the image. Can be a color name (eg. white, black, green), or a hex code + -conservation_score score alignment by conservation score + --output_file_type OUTPUT_FILE_TYPE + output file type. Options: png, ps, eps, tif, svg + -bfactor score by B-factor + -mview color by mview color map + --dpi DPI dpi to use for final plot + --ticks TICKS set ticks at every nth position + --start START + --end END + --dssp_exe DSSP_EXE The path to your dssp executable. Default: mkdssp + --consurf CONSURF consurf or rate4site file to color image with. If rate4site file is given, SSDraw will convert raw scores to grades. + --fontsize FONTSIZE font size for residue numbers + --fontcolor FONTCOLOR + font color for residue numbers +``` diff --git a/docs/getting-started.md b/docs/getting-started.md new file mode 100644 index 0000000..7ad5cff --- /dev/null +++ b/docs/getting-started.md @@ -0,0 +1,9 @@ +## Installation + +The easiest way to install SSDraw is via pip: + +```bash +pip install SSDraw +``` + +You can find the package on PyPi [here](https://pypi.org/project/SSDraw/). \ No newline at end of file diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..c3f32fb --- /dev/null +++ b/docs/index.md @@ -0,0 +1,4 @@ +# SSDraw +SSDraw is a program that generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. + +SSDraw also has a **colab notebook** available (only usable for Chrome). The notebook can be accessed [here](https://colab.research.google.com/github/ethanchen1301/SSDraw/blob/main/SSDraw.ipynb). \ No newline at end of file diff --git a/docs/troubleshooting.md b/docs/troubleshooting.md new file mode 100644 index 0000000..8a08629 --- /dev/null +++ b/docs/troubleshooting.md @@ -0,0 +1,32 @@ +# Troubleshooting & Common Issues + +This section addresses frequently encountered problems and provides solutions. + +*** + +## Issue: Amino Acid Sequence Overlap/Jumbling + +### Problem +When the secondary structure diagram is **quite long** (i.e., for large proteins), the residue numbering and/or **amino acid sequence often overlaps or becomes jumbled** together, making it unreadable. + +### Solution +You can adjust the size of the residue numbers and sequence labels by changing the default font size. Use the **`--fontsize`** flag followed by a numerical value. The default size is **12**, which may be too large for high-density diagrams. Try reducing it (e.g., `--fontsize 8`) until the text is clearly separated. + +* **Example:** `ssdraw single ... --fontsize 8` + +*** + +## Issue: Saving Secondary Structure to a Specific File Format + +### Problem +I need to save the generated secondary structure diagram in a **high-quality vector format** (like SVG or EPS) or a specific raster format (like TIFF) instead of the default PNG. + +### Solution +You can specify the desired output file type using the **`--output_file_type`** flag. This is particularly useful for generating **publication-quality figures**. + +The supported output file types are: **`png`**, **`ps`**, **`eps`**, **`tif`**, and **`svg`**. + +* **To save as a vector graphic:** `ssdraw single ... --output_file_type svg` +* **To save as a high-resolution image:** `ssdraw single ... --output_file_type tif` + +*** \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 0000000..0e02827 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,11 @@ +site_name: SSDraw + +nav: + - Home: 'index.md' + - Getting Started: 'getting-started.md' + - Modules: + - single: 'commands/single.md' + - multi: 'commands/multi.md' + - Troubleshooting: 'troubleshooting.md' + +theme: readthedocs \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index cf5bed1..02bfcfc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,8 +23,8 @@ dependencies = [ ] [project.optional-dependencies] -tests = [ - "pytest" +docs = [ + "mkdocs", ] [project.scripts] diff --git a/scripts/generate_docs.py b/scripts/generate_docs.py new file mode 100644 index 0000000..6f4369d --- /dev/null +++ b/scripts/generate_docs.py @@ -0,0 +1,29 @@ +import io + +from contextlib import redirect_stdout +from SSDraw.cli import get_args + + +def generate_help(command, filename): + f = io.StringIO() + with redirect_stdout(f): + try: + get_args(argv=[command, "--help"]) + except SystemExit: + pass + + help_output = f.getvalue() + + with open(f"docs/commands/{filename}.md", "w") as doc_file: + doc_file.write(f"# SSDraw {command} Command\n\n") + doc_file.write(f"This section documents the `ssdraw {command}` command.\n\n") + doc_file.write("```bash\n") + doc_file.write(help_output) + doc_file.write("```\n") + + +if __name__ == "__main__": + generate_help("single", "single") + generate_help("multi", "multi") + + print("CLI documentation updated in docs/commands/") diff --git a/site/404.html b/site/404.html new file mode 100644 index 0000000..39f1e59 --- /dev/null +++ b/site/404.html @@ -0,0 +1,116 @@ + + + + + + + + SSDraw + + + + + + + + + + + +
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SSDraw multi Command

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This section documents the ssdraw multi command.

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usage: generate_docs.py multi [-h] -i INPUT -o OUTPUT
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+options:
+  -h, --help           show this help message and exit
+  -i, --input INPUT    Name of input script
+  -o, --output OUTPUT  Name of output directory
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  • single
    • +
  • +
    • +
+
+
+
+
+ +

SSDraw single Command

+

This section documents the ssdraw single command.

+
usage: generate_docs.py single [-h] [-f FASTA] [-p PDB] [-n NAME] [-o OUTPUT] [--SS SS] [--chain_id CHAIN_ID] [--color_map [COLOR_MAP ...]]
+                               [--scoring_file SCORING_FILE] [--color COLOR] [-conservation_score] [--output_file_type OUTPUT_FILE_TYPE] [-bfactor]
+                               [-mview] [--dpi DPI] [--ticks TICKS] [--start START] [--end END] [--dssp_exe DSSP_EXE] [--consurf CONSURF]
+                               [--fontsize FONTSIZE] [--fontcolor FONTCOLOR]
+
+options:
+  -h, --help            show this help message and exit
+  -f, --fasta FASTA     (required) sequence/alignment file in fasta format
+  -p, --pdb PDB         (required) pdb file
+  -n, --name NAME       (required) id of the protein in the alignment file
+  -o, --output OUTPUT   (required) name for output file
+  --SS SS               secondary structure annotation in DSSP or .horiz format. If this option is not provided, SSDraw will compute secondary structure
+                        from the given PDB file with DSSP.
+  --chain_id CHAIN_ID   chain id to use in pdb. Defaults to chain A.
+  --color_map [COLOR_MAP ...]
+                        color map to use for heat map
+  --scoring_file SCORING_FILE
+                        custom scoring file for alignment
+  --color COLOR         color for the image. Can be a color name (eg. white, black, green), or a hex code
+  -conservation_score   score alignment by conservation score
+  --output_file_type OUTPUT_FILE_TYPE
+                        output file type. Options: png, ps, eps, tif, svg
+  -bfactor              score by B-factor
+  -mview                color by mview color map
+  --dpi DPI             dpi to use for final plot
+  --ticks TICKS         set ticks at every nth position
+  --start START
+  --end END
+  --dssp_exe DSSP_EXE   The path to your dssp executable. Default: mkdssp
+  --consurf CONSURF     consurf or rate4site file to color image with. If rate4site file is given, SSDraw will convert raw scores to grades.
+  --fontsize FONTSIZE   font size for residue numbers
+  --fontcolor FONTCOLOR
+                        font color for residue numbers
+
+ +
+
+ +
+
+ +
+ +
+ +
+ + + + « Previous + + + Next » + + +
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https://github.com/mkdocs/mkdocs/issues/233 + * https://github.com/mkdocs/mkdocs/issues/834 + */ +.rst-content code { + white-space: pre-wrap; + word-wrap: break-word; + padding: 2px 5px; +} + +/** + * Make code blocks display as blocks and give them the appropriate + * font size and padding. + * + * https://github.com/mkdocs/mkdocs/issues/855 + * https://github.com/mkdocs/mkdocs/issues/834 + * https://github.com/mkdocs/mkdocs/issues/233 + */ +.rst-content pre code { + white-space: pre; + word-wrap: normal; + display: block; + padding: 12px; + font-size: 12px; +} + +/** + * Fix code colors + * + * https://github.com/mkdocs/mkdocs/issues/2027 + */ +.rst-content code { + color: #E74C3C; +} + +.rst-content pre code { + color: #000; + background: #f8f8f8; +} + +/* + * Fix link colors when the link text is inline code. + * + * https://github.com/mkdocs/mkdocs/issues/718 + */ +a code { + color: #2980B9; +} +a:hover code { + color: #3091d1; +} +a:visited code { + color: #9B59B6; +} + +/* + * The CSS classes from highlight.js seem to clash with the + * ReadTheDocs theme causing some code to be incorrectly made + * bold and italic. + * + * https://github.com/mkdocs/mkdocs/issues/411 + */ +pre .cs, pre .c { + font-weight: inherit; + font-style: inherit; +} + +/* + * Fix some issues with the theme and non-highlighted code + * samples. Without and highlighting styles attached the + * formatting is broken. + * + * https://github.com/mkdocs/mkdocs/issues/319 + */ +.rst-content .no-highlight { + display: block; + padding: 0.5em; + color: #333; +} + + +/* + * Additions specific to the search functionality provided by MkDocs + */ + +.search-results { + margin-top: 23px; +} + +.search-results article { + border-top: 1px solid #E1E4E5; + padding-top: 24px; +} + +.search-results article:first-child { + border-top: none; +} + +form .search-query { + width: 100%; + border-radius: 50px; + padding: 6px 12px; + border-color: #D1D4D5; +} + +/* + * Improve inline code blocks within admonitions. + * + * https://github.com/mkdocs/mkdocs/issues/656 + */ + .rst-content .admonition code { + color: #404040; + border: 1px solid #c7c9cb; + border: 1px solid rgba(0, 0, 0, 0.2); + background: #f8fbfd; + background: rgba(255, 255, 255, 0.7); +} + +/* + * Account for wide tables which go off the side. + * Override borders to avoid weirdness on narrow tables. + * + * https://github.com/mkdocs/mkdocs/issues/834 + * https://github.com/mkdocs/mkdocs/pull/1034 + */ +.rst-content .section .docutils { + width: 100%; + overflow: auto; + display: block; + border: none; +} + +td, th { + border: 1px solid #e1e4e5 !important; + border-collapse: collapse; +} + +/* + * Without the following amendments, the navigation in the theme will be + * slightly cut off. This is due to the fact that the .wy-nav-side has a + * padding-bottom of 2em, which must not necessarily align with the font-size of + * 90 % on the .rst-current-version container, combined with the padding of 12px + * above and below. These amendments fix this in two steps: First, make sure the + * .rst-current-version container has a fixed height of 40px, achieved using + * line-height, and then applying a padding-bottom of 40px to this container. In + * a second step, the items within that container are re-aligned using flexbox. + * + * https://github.com/mkdocs/mkdocs/issues/2012 + */ + .wy-nav-side { + padding-bottom: 40px; +} + +/* For section-index only */ +.wy-menu-vertical .current-section p { + background-color: #e3e3e3; + color: #404040; +} + +/* + * The second step of above amendment: Here we make sure the items are aligned + * correctly within the .rst-current-version container. 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The easiest way to install SSDraw is via pip:

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You can find the package on PyPi here.

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SSDraw

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SSDraw is a program that generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring.

+

SSDraw also has a colab notebook available (only usable for Chrome). The notebook can be accessed here.

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+ + + + + +
+ + + + + + + + + diff --git a/site/search/lunr.js b/site/search/lunr.js new file mode 100644 index 0000000..aca0a16 --- /dev/null +++ b/site/search/lunr.js @@ -0,0 +1,3475 @@ +/** + * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9 + * Copyright (C) 2020 Oliver Nightingale + * @license MIT + */ + +;(function(){ + +/** + * A convenience function for configuring and constructing + * a new lunr Index. + * + * A lunr.Builder instance is created and the pipeline setup + * with a trimmer, stop word filter and stemmer. + * + * This builder object is yielded to the configuration function + * that is passed as a parameter, allowing the list of fields + * and other builder parameters to be customised. + * + * All documents _must_ be added within the passed config function. + * + * @example + * var idx = lunr(function () { + * this.field('title') + * this.field('body') + * this.ref('id') + * + * documents.forEach(function (doc) { + * this.add(doc) + * }, this) + * }) + * + * @see {@link lunr.Builder} + * @see {@link lunr.Pipeline} + * @see {@link lunr.trimmer} + * @see {@link lunr.stopWordFilter} + * @see {@link lunr.stemmer} + * @namespace {function} lunr + */ +var lunr = function (config) { + var builder = new lunr.Builder + + builder.pipeline.add( + lunr.trimmer, + lunr.stopWordFilter, + lunr.stemmer + ) + + builder.searchPipeline.add( + lunr.stemmer + ) + + config.call(builder, builder) + return builder.build() +} + +lunr.version = "2.3.9" +/*! + * lunr.utils + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A namespace containing utils for the rest of the lunr library + * @namespace lunr.utils + */ +lunr.utils = {} + +/** + * Print a warning message to the console. + * + * @param {String} message The message to be printed. + * @memberOf lunr.utils + * @function + */ +lunr.utils.warn = (function (global) { + /* eslint-disable no-console */ + return function (message) { + if (global.console && console.warn) { + console.warn(message) + } + } + /* eslint-enable no-console */ +})(this) + +/** + * Convert an object to a string. + * + * In the case of `null` and `undefined` the function returns + * the empty string, in all other cases the result of calling + * `toString` on the passed object is returned. + * + * @param {Any} obj The object to convert to a string. + * @return {String} string representation of the passed object. + * @memberOf lunr.utils + */ +lunr.utils.asString = function (obj) { + if (obj === void 0 || obj === null) { + return "" + } else { + return obj.toString() + } +} + +/** + * Clones an object. + * + * Will create a copy of an existing object such that any mutations + * on the copy cannot affect the original. + * + * Only shallow objects are supported, passing a nested object to this + * function will cause a TypeError. + * + * Objects with primitives, and arrays of primitives are supported. + * + * @param {Object} obj The object to clone. + * @return {Object} a clone of the passed object. + * @throws {TypeError} when a nested object is passed. + * @memberOf Utils + */ +lunr.utils.clone = function (obj) { + if (obj === null || obj === undefined) { + return obj + } + + var clone = Object.create(null), + keys = Object.keys(obj) + + for (var i = 0; i < keys.length; i++) { + var key = keys[i], + val = obj[key] + + if (Array.isArray(val)) { + clone[key] = val.slice() + continue + } + + if (typeof val === 'string' || + typeof val === 'number' || + typeof val === 'boolean') { + clone[key] = val + continue + } + + throw new TypeError("clone is not deep and does not support nested objects") + } + + return clone +} +lunr.FieldRef = function (docRef, fieldName, stringValue) { + this.docRef = docRef + this.fieldName = fieldName + this._stringValue = stringValue +} + +lunr.FieldRef.joiner = "/" + +lunr.FieldRef.fromString = function (s) { + var n = s.indexOf(lunr.FieldRef.joiner) + + if (n === -1) { + throw "malformed field ref string" + } + + var fieldRef = s.slice(0, n), + docRef = s.slice(n + 1) + + return new lunr.FieldRef (docRef, fieldRef, s) +} + +lunr.FieldRef.prototype.toString = function () { + if (this._stringValue == undefined) { + this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef + } + + return this._stringValue +} +/*! + * lunr.Set + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A lunr set. + * + * @constructor + */ +lunr.Set = function (elements) { + this.elements = Object.create(null) + + if (elements) { + this.length = elements.length + + for (var i = 0; i < this.length; i++) { + this.elements[elements[i]] = true + } + } else { + this.length = 0 + } +} + +/** + * A complete set that contains all elements. + * + * @static + * @readonly + * @type {lunr.Set} + */ +lunr.Set.complete = { + intersect: function (other) { + return other + }, + + union: function () { + return this + }, + + contains: function () { + return true + } +} + +/** + * An empty set that contains no elements. + * + * @static + * @readonly + * @type {lunr.Set} + */ +lunr.Set.empty = { + intersect: function () { + return this + }, + + union: function (other) { + return other + }, + + contains: function () { + return false + } +} + +/** + * Returns true if this set contains the specified object. + * + * @param {object} object - Object whose presence in this set is to be tested. + * @returns {boolean} - True if this set contains the specified object. + */ +lunr.Set.prototype.contains = function (object) { + return !!this.elements[object] +} + +/** + * Returns a new set containing only the elements that are present in both + * this set and the specified set. + * + * @param {lunr.Set} other - set to intersect with this set. + * @returns {lunr.Set} a new set that is the intersection of this and the specified set. + */ + +lunr.Set.prototype.intersect = function (other) { + var a, b, elements, intersection = [] + + if (other === lunr.Set.complete) { + return this + } + + if (other === lunr.Set.empty) { + return other + } + + if (this.length < other.length) { + a = this + b = other + } else { + a = other + b = this + } + + elements = Object.keys(a.elements) + + for (var i = 0; i < elements.length; i++) { + var element = elements[i] + if (element in b.elements) { + intersection.push(element) + } + } + + return new lunr.Set (intersection) +} + +/** + * Returns a new set combining the elements of this and the specified set. + * + * @param {lunr.Set} other - set to union with this set. + * @return {lunr.Set} a new set that is the union of this and the specified set. + */ + +lunr.Set.prototype.union = function (other) { + if (other === lunr.Set.complete) { + return lunr.Set.complete + } + + if (other === lunr.Set.empty) { + return this + } + + return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements))) +} +/** + * A function to calculate the inverse document frequency for + * a posting. This is shared between the builder and the index + * + * @private + * @param {object} posting - The posting for a given term + * @param {number} documentCount - The total number of documents. + */ +lunr.idf = function (posting, documentCount) { + var documentsWithTerm = 0 + + for (var fieldName in posting) { + if (fieldName == '_index') continue // Ignore the term index, its not a field + documentsWithTerm += Object.keys(posting[fieldName]).length + } + + var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5) + + return Math.log(1 + Math.abs(x)) +} + +/** + * A token wraps a string representation of a token + * as it is passed through the text processing pipeline. + * + * @constructor + * @param {string} [str=''] - The string token being wrapped. + * @param {object} [metadata={}] - Metadata associated with this token. + */ +lunr.Token = function (str, metadata) { + this.str = str || "" + this.metadata = metadata || {} +} + +/** + * Returns the token string that is being wrapped by this object. + * + * @returns {string} + */ +lunr.Token.prototype.toString = function () { + return this.str +} + +/** + * A token update function is used when updating or optionally + * when cloning a token. + * + * @callback lunr.Token~updateFunction + * @param {string} str - The string representation of the token. + * @param {Object} metadata - All metadata associated with this token. + */ + +/** + * Applies the given function to the wrapped string token. + * + * @example + * token.update(function (str, metadata) { + * return str.toUpperCase() + * }) + * + * @param {lunr.Token~updateFunction} fn - A function to apply to the token string. + * @returns {lunr.Token} + */ +lunr.Token.prototype.update = function (fn) { + this.str = fn(this.str, this.metadata) + return this +} + +/** + * Creates a clone of this token. Optionally a function can be + * applied to the cloned token. + * + * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token. + * @returns {lunr.Token} + */ +lunr.Token.prototype.clone = function (fn) { + fn = fn || function (s) { return s } + return new lunr.Token (fn(this.str, this.metadata), this.metadata) +} +/*! + * lunr.tokenizer + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A function for splitting a string into tokens ready to be inserted into + * the search index. Uses `lunr.tokenizer.separator` to split strings, change + * the value of this property to change how strings are split into tokens. + * + * This tokenizer will convert its parameter to a string by calling `toString` and + * then will split this string on the character in `lunr.tokenizer.separator`. + * Arrays will have their elements converted to strings and wrapped in a lunr.Token. + * + * Optional metadata can be passed to the tokenizer, this metadata will be cloned and + * added as metadata to every token that is created from the object to be tokenized. + * + * @static + * @param {?(string|object|object[])} obj - The object to convert into tokens + * @param {?object} metadata - Optional metadata to associate with every token + * @returns {lunr.Token[]} + * @see {@link lunr.Pipeline} + */ +lunr.tokenizer = function (obj, metadata) { + if (obj == null || obj == undefined) { + return [] + } + + if (Array.isArray(obj)) { + return obj.map(function (t) { + return new lunr.Token( + lunr.utils.asString(t).toLowerCase(), + lunr.utils.clone(metadata) + ) + }) + } + + var str = obj.toString().toLowerCase(), + len = str.length, + tokens = [] + + for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) { + var char = str.charAt(sliceEnd), + sliceLength = sliceEnd - sliceStart + + if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) { + + if (sliceLength > 0) { + var tokenMetadata = lunr.utils.clone(metadata) || {} + tokenMetadata["position"] = [sliceStart, sliceLength] + tokenMetadata["index"] = tokens.length + + tokens.push( + new lunr.Token ( + str.slice(sliceStart, sliceEnd), + tokenMetadata + ) + ) + } + + sliceStart = sliceEnd + 1 + } + + } + + return tokens +} + +/** + * The separator used to split a string into tokens. Override this property to change the behaviour of + * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens. + * + * @static + * @see lunr.tokenizer + */ +lunr.tokenizer.separator = /[\s\-]+/ +/*! + * lunr.Pipeline + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.Pipelines maintain an ordered list of functions to be applied to all + * tokens in documents entering the search index and queries being ran against + * the index. + * + * An instance of lunr.Index created with the lunr shortcut will contain a + * pipeline with a stop word filter and an English language stemmer. Extra + * functions can be added before or after either of these functions or these + * default functions can be removed. + * + * When run the pipeline will call each function in turn, passing a token, the + * index of that token in the original list of all tokens and finally a list of + * all the original tokens. + * + * The output of functions in the pipeline will be passed to the next function + * in the pipeline. To exclude a token from entering the index the function + * should return undefined, the rest of the pipeline will not be called with + * this token. + * + * For serialisation of pipelines to work, all functions used in an instance of + * a pipeline should be registered with lunr.Pipeline. Registered functions can + * then be loaded. If trying to load a serialised pipeline that uses functions + * that are not registered an error will be thrown. + * + * If not planning on serialising the pipeline then registering pipeline functions + * is not necessary. + * + * @constructor + */ +lunr.Pipeline = function () { + this._stack = [] +} + +lunr.Pipeline.registeredFunctions = Object.create(null) + +/** + * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token + * string as well as all known metadata. A pipeline function can mutate the token string + * or mutate (or add) metadata for a given token. + * + * A pipeline function can indicate that the passed token should be discarded by returning + * null, undefined or an empty string. This token will not be passed to any downstream pipeline + * functions and will not be added to the index. + * + * Multiple tokens can be returned by returning an array of tokens. Each token will be passed + * to any downstream pipeline functions and all will returned tokens will be added to the index. + * + * Any number of pipeline functions may be chained together using a lunr.Pipeline. + * + * @interface lunr.PipelineFunction + * @param {lunr.Token} token - A token from the document being processed. + * @param {number} i - The index of this token in the complete list of tokens for this document/field. + * @param {lunr.Token[]} tokens - All tokens for this document/field. + * @returns {(?lunr.Token|lunr.Token[])} + */ + +/** + * Register a function with the pipeline. + * + * Functions that are used in the pipeline should be registered if the pipeline + * needs to be serialised, or a serialised pipeline needs to be loaded. + * + * Registering a function does not add it to a pipeline, functions must still be + * added to instances of the pipeline for them to be used when running a pipeline. + * + * @param {lunr.PipelineFunction} fn - The function to check for. + * @param {String} label - The label to register this function with + */ +lunr.Pipeline.registerFunction = function (fn, label) { + if (label in this.registeredFunctions) { + lunr.utils.warn('Overwriting existing registered function: ' + label) + } + + fn.label = label + lunr.Pipeline.registeredFunctions[fn.label] = fn +} + +/** + * Warns if the function is not registered as a Pipeline function. + * + * @param {lunr.PipelineFunction} fn - The function to check for. + * @private + */ +lunr.Pipeline.warnIfFunctionNotRegistered = function (fn) { + var isRegistered = fn.label && (fn.label in this.registeredFunctions) + + if (!isRegistered) { + lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\n', fn) + } +} + +/** + * Loads a previously serialised pipeline. + * + * All functions to be loaded must already be registered with lunr.Pipeline. + * If any function from the serialised data has not been registered then an + * error will be thrown. + * + * @param {Object} serialised - The serialised pipeline to load. + * @returns {lunr.Pipeline} + */ +lunr.Pipeline.load = function (serialised) { + var pipeline = new lunr.Pipeline + + serialised.forEach(function (fnName) { + var fn = lunr.Pipeline.registeredFunctions[fnName] + + if (fn) { + pipeline.add(fn) + } else { + throw new Error('Cannot load unregistered function: ' + fnName) + } + }) + + return pipeline +} + +/** + * Adds new functions to the end of the pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline. + */ +lunr.Pipeline.prototype.add = function () { + var fns = Array.prototype.slice.call(arguments) + + fns.forEach(function (fn) { + lunr.Pipeline.warnIfFunctionNotRegistered(fn) + this._stack.push(fn) + }, this) +} + +/** + * Adds a single function after a function that already exists in the + * pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. + * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. + */ +lunr.Pipeline.prototype.after = function (existingFn, newFn) { + lunr.Pipeline.warnIfFunctionNotRegistered(newFn) + + var pos = this._stack.indexOf(existingFn) + if (pos == -1) { + throw new Error('Cannot find existingFn') + } + + pos = pos + 1 + this._stack.splice(pos, 0, newFn) +} + +/** + * Adds a single function before a function that already exists in the + * pipeline. + * + * Logs a warning if the function has not been registered. + * + * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. + * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. + */ +lunr.Pipeline.prototype.before = function (existingFn, newFn) { + lunr.Pipeline.warnIfFunctionNotRegistered(newFn) + + var pos = this._stack.indexOf(existingFn) + if (pos == -1) { + throw new Error('Cannot find existingFn') + } + + this._stack.splice(pos, 0, newFn) +} + +/** + * Removes a function from the pipeline. + * + * @param {lunr.PipelineFunction} fn The function to remove from the pipeline. + */ +lunr.Pipeline.prototype.remove = function (fn) { + var pos = this._stack.indexOf(fn) + if (pos == -1) { + return + } + + this._stack.splice(pos, 1) +} + +/** + * Runs the current list of functions that make up the pipeline against the + * passed tokens. + * + * @param {Array} tokens The tokens to run through the pipeline. + * @returns {Array} + */ +lunr.Pipeline.prototype.run = function (tokens) { + var stackLength = this._stack.length + + for (var i = 0; i < stackLength; i++) { + var fn = this._stack[i] + var memo = [] + + for (var j = 0; j < tokens.length; j++) { + var result = fn(tokens[j], j, tokens) + + if (result === null || result === void 0 || result === '') continue + + if (Array.isArray(result)) { + for (var k = 0; k < result.length; k++) { + memo.push(result[k]) + } + } else { + memo.push(result) + } + } + + tokens = memo + } + + return tokens +} + +/** + * Convenience method for passing a string through a pipeline and getting + * strings out. This method takes care of wrapping the passed string in a + * token and mapping the resulting tokens back to strings. + * + * @param {string} str - The string to pass through the pipeline. + * @param {?object} metadata - Optional metadata to associate with the token + * passed to the pipeline. + * @returns {string[]} + */ +lunr.Pipeline.prototype.runString = function (str, metadata) { + var token = new lunr.Token (str, metadata) + + return this.run([token]).map(function (t) { + return t.toString() + }) +} + +/** + * Resets the pipeline by removing any existing processors. + * + */ +lunr.Pipeline.prototype.reset = function () { + this._stack = [] +} + +/** + * Returns a representation of the pipeline ready for serialisation. + * + * Logs a warning if the function has not been registered. + * + * @returns {Array} + */ +lunr.Pipeline.prototype.toJSON = function () { + return this._stack.map(function (fn) { + lunr.Pipeline.warnIfFunctionNotRegistered(fn) + + return fn.label + }) +} +/*! + * lunr.Vector + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A vector is used to construct the vector space of documents and queries. These + * vectors support operations to determine the similarity between two documents or + * a document and a query. + * + * Normally no parameters are required for initializing a vector, but in the case of + * loading a previously dumped vector the raw elements can be provided to the constructor. + * + * For performance reasons vectors are implemented with a flat array, where an elements + * index is immediately followed by its value. E.g. [index, value, index, value]. This + * allows the underlying array to be as sparse as possible and still offer decent + * performance when being used for vector calculations. + * + * @constructor + * @param {Number[]} [elements] - The flat list of element index and element value pairs. + */ +lunr.Vector = function (elements) { + this._magnitude = 0 + this.elements = elements || [] +} + + +/** + * Calculates the position within the vector to insert a given index. + * + * This is used internally by insert and upsert. If there are duplicate indexes then + * the position is returned as if the value for that index were to be updated, but it + * is the callers responsibility to check whether there is a duplicate at that index + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @returns {Number} + */ +lunr.Vector.prototype.positionForIndex = function (index) { + // For an empty vector the tuple can be inserted at the beginning + if (this.elements.length == 0) { + return 0 + } + + var start = 0, + end = this.elements.length / 2, + sliceLength = end - start, + pivotPoint = Math.floor(sliceLength / 2), + pivotIndex = this.elements[pivotPoint * 2] + + while (sliceLength > 1) { + if (pivotIndex < index) { + start = pivotPoint + } + + if (pivotIndex > index) { + end = pivotPoint + } + + if (pivotIndex == index) { + break + } + + sliceLength = end - start + pivotPoint = start + Math.floor(sliceLength / 2) + pivotIndex = this.elements[pivotPoint * 2] + } + + if (pivotIndex == index) { + return pivotPoint * 2 + } + + if (pivotIndex > index) { + return pivotPoint * 2 + } + + if (pivotIndex < index) { + return (pivotPoint + 1) * 2 + } +} + +/** + * Inserts an element at an index within the vector. + * + * Does not allow duplicates, will throw an error if there is already an entry + * for this index. + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @param {Number} val - The value to be inserted into the vector. + */ +lunr.Vector.prototype.insert = function (insertIdx, val) { + this.upsert(insertIdx, val, function () { + throw "duplicate index" + }) +} + +/** + * Inserts or updates an existing index within the vector. + * + * @param {Number} insertIdx - The index at which the element should be inserted. + * @param {Number} val - The value to be inserted into the vector. + * @param {function} fn - A function that is called for updates, the existing value and the + * requested value are passed as arguments + */ +lunr.Vector.prototype.upsert = function (insertIdx, val, fn) { + this._magnitude = 0 + var position = this.positionForIndex(insertIdx) + + if (this.elements[position] == insertIdx) { + this.elements[position + 1] = fn(this.elements[position + 1], val) + } else { + this.elements.splice(position, 0, insertIdx, val) + } +} + +/** + * Calculates the magnitude of this vector. + * + * @returns {Number} + */ +lunr.Vector.prototype.magnitude = function () { + if (this._magnitude) return this._magnitude + + var sumOfSquares = 0, + elementsLength = this.elements.length + + for (var i = 1; i < elementsLength; i += 2) { + var val = this.elements[i] + sumOfSquares += val * val + } + + return this._magnitude = Math.sqrt(sumOfSquares) +} + +/** + * Calculates the dot product of this vector and another vector. + * + * @param {lunr.Vector} otherVector - The vector to compute the dot product with. + * @returns {Number} + */ +lunr.Vector.prototype.dot = function (otherVector) { + var dotProduct = 0, + a = this.elements, b = otherVector.elements, + aLen = a.length, bLen = b.length, + aVal = 0, bVal = 0, + i = 0, j = 0 + + while (i < aLen && j < bLen) { + aVal = a[i], bVal = b[j] + if (aVal < bVal) { + i += 2 + } else if (aVal > bVal) { + j += 2 + } else if (aVal == bVal) { + dotProduct += a[i + 1] * b[j + 1] + i += 2 + j += 2 + } + } + + return dotProduct +} + +/** + * Calculates the similarity between this vector and another vector. + * + * @param {lunr.Vector} otherVector - The other vector to calculate the + * similarity with. + * @returns {Number} + */ +lunr.Vector.prototype.similarity = function (otherVector) { + return this.dot(otherVector) / this.magnitude() || 0 +} + +/** + * Converts the vector to an array of the elements within the vector. + * + * @returns {Number[]} + */ +lunr.Vector.prototype.toArray = function () { + var output = new Array (this.elements.length / 2) + + for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) { + output[j] = this.elements[i] + } + + return output +} + +/** + * A JSON serializable representation of the vector. + * + * @returns {Number[]} + */ +lunr.Vector.prototype.toJSON = function () { + return this.elements +} +/* eslint-disable */ +/*! + * lunr.stemmer + * Copyright (C) 2020 Oliver Nightingale + * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt + */ + +/** + * lunr.stemmer is an english language stemmer, this is a JavaScript + * implementation of the PorterStemmer taken from http://tartarus.org/~martin + * + * @static + * @implements {lunr.PipelineFunction} + * @param {lunr.Token} token - The string to stem + * @returns {lunr.Token} + * @see {@link lunr.Pipeline} + * @function + */ +lunr.stemmer = (function(){ + var step2list = { + "ational" : "ate", + "tional" : "tion", + "enci" : "ence", + "anci" : "ance", + "izer" : "ize", + "bli" : "ble", + "alli" : "al", + "entli" : "ent", + "eli" : "e", + "ousli" : "ous", + "ization" : "ize", + "ation" : "ate", + "ator" : "ate", + "alism" : "al", + "iveness" : "ive", + "fulness" : "ful", + "ousness" : "ous", + "aliti" : "al", + "iviti" : "ive", + "biliti" : "ble", + "logi" : "log" + }, + + step3list = { + "icate" : "ic", + "ative" : "", + "alize" : "al", + "iciti" : "ic", + "ical" : "ic", + "ful" : "", + "ness" : "" + }, + + c = "[^aeiou]", // consonant + v = "[aeiouy]", // vowel + C = c + "[^aeiouy]*", // consonant sequence + V = v + "[aeiou]*", // vowel sequence + + mgr0 = "^(" + C + ")?" + V + C, // [C]VC... is m>0 + meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$", // [C]VC[V] is m=1 + mgr1 = "^(" + C + ")?" + V + C + V + C, // [C]VCVC... is m>1 + s_v = "^(" + C + ")?" + v; // vowel in stem + + var re_mgr0 = new RegExp(mgr0); + var re_mgr1 = new RegExp(mgr1); + var re_meq1 = new RegExp(meq1); + var re_s_v = new RegExp(s_v); + + var re_1a = /^(.+?)(ss|i)es$/; + var re2_1a = /^(.+?)([^s])s$/; + var re_1b = /^(.+?)eed$/; + var re2_1b = /^(.+?)(ed|ing)$/; + var re_1b_2 = /.$/; + var re2_1b_2 = /(at|bl|iz)$/; + var re3_1b_2 = new RegExp("([^aeiouylsz])\\1$"); + var re4_1b_2 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + + var re_1c = /^(.+?[^aeiou])y$/; + var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + + var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + + var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + var re2_4 = /^(.+?)(s|t)(ion)$/; + + var re_5 = /^(.+?)e$/; + var re_5_1 = /ll$/; + var re3_5 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + + var porterStemmer = function porterStemmer(w) { + var stem, + suffix, + firstch, + re, + re2, + re3, + re4; + + if (w.length < 3) { return w; } + + firstch = w.substr(0,1); + if (firstch == "y") { + w = firstch.toUpperCase() + w.substr(1); + } + + // Step 1a + re = re_1a + re2 = re2_1a; + + if (re.test(w)) { w = w.replace(re,"$1$2"); } + else if (re2.test(w)) { w = w.replace(re2,"$1$2"); } + + // Step 1b + re = re_1b; + re2 = re2_1b; + if (re.test(w)) { + var fp = re.exec(w); + re = re_mgr0; + if (re.test(fp[1])) { + re = re_1b_2; + w = w.replace(re,""); + } + } else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = re_s_v; + if (re2.test(stem)) { + w = stem; + re2 = re2_1b_2; + re3 = re3_1b_2; + re4 = re4_1b_2; + if (re2.test(w)) { w = w + "e"; } + else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,""); } + else if (re4.test(w)) { w = w + "e"; } + } + } + + // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say) + re = re_1c; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + w = stem + "i"; + } + + // Step 2 + re = re_2; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = re_mgr0; + if (re.test(stem)) { + w = stem + step2list[suffix]; + } + } + + // Step 3 + re = re_3; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = re_mgr0; + if (re.test(stem)) { + w = stem + step3list[suffix]; + } + } + + // Step 4 + re = re_4; + re2 = re2_4; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = re_mgr1; + if (re.test(stem)) { + w = stem; + } + } else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = re_mgr1; + if (re2.test(stem)) { + w = stem; + } + } + + // Step 5 + re = re_5; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = re_mgr1; + re2 = re_meq1; + re3 = re3_5; + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) { + w = stem; + } + } + + re = re_5_1; + re2 = re_mgr1; + if (re.test(w) && re2.test(w)) { + re = re_1b_2; + w = w.replace(re,""); + } + + // and turn initial Y back to y + + if (firstch == "y") { + w = firstch.toLowerCase() + w.substr(1); + } + + return w; + }; + + return function (token) { + return token.update(porterStemmer); + } +})(); + +lunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer') +/*! + * lunr.stopWordFilter + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.generateStopWordFilter builds a stopWordFilter function from the provided + * list of stop words. + * + * The built in lunr.stopWordFilter is built using this generator and can be used + * to generate custom stopWordFilters for applications or non English languages. + * + * @function + * @param {Array} token The token to pass through the filter + * @returns {lunr.PipelineFunction} + * @see lunr.Pipeline + * @see lunr.stopWordFilter + */ +lunr.generateStopWordFilter = function (stopWords) { + var words = stopWords.reduce(function (memo, stopWord) { + memo[stopWord] = stopWord + return memo + }, {}) + + return function (token) { + if (token && words[token.toString()] !== token.toString()) return token + } +} + +/** + * lunr.stopWordFilter is an English language stop word list filter, any words + * contained in the list will not be passed through the filter. + * + * This is intended to be used in the Pipeline. If the token does not pass the + * filter then undefined will be returned. + * + * @function + * @implements {lunr.PipelineFunction} + * @params {lunr.Token} token - A token to check for being a stop word. + * @returns {lunr.Token} + * @see {@link lunr.Pipeline} + */ +lunr.stopWordFilter = lunr.generateStopWordFilter([ + 'a', + 'able', + 'about', + 'across', + 'after', + 'all', + 'almost', + 'also', + 'am', + 'among', + 'an', + 'and', + 'any', + 'are', + 'as', + 'at', + 'be', + 'because', + 'been', + 'but', + 'by', + 'can', + 'cannot', + 'could', + 'dear', + 'did', + 'do', + 'does', + 'either', + 'else', + 'ever', + 'every', + 'for', + 'from', + 'get', + 'got', + 'had', + 'has', + 'have', + 'he', + 'her', + 'hers', + 'him', + 'his', + 'how', + 'however', + 'i', + 'if', + 'in', + 'into', + 'is', + 'it', + 'its', + 'just', + 'least', + 'let', + 'like', + 'likely', + 'may', + 'me', + 'might', + 'most', + 'must', + 'my', + 'neither', + 'no', + 'nor', + 'not', + 'of', + 'off', + 'often', + 'on', + 'only', + 'or', + 'other', + 'our', + 'own', + 'rather', + 'said', + 'say', + 'says', + 'she', + 'should', + 'since', + 'so', + 'some', + 'than', + 'that', + 'the', + 'their', + 'them', + 'then', + 'there', + 'these', + 'they', + 'this', + 'tis', + 'to', + 'too', + 'twas', + 'us', + 'wants', + 'was', + 'we', + 'were', + 'what', + 'when', + 'where', + 'which', + 'while', + 'who', + 'whom', + 'why', + 'will', + 'with', + 'would', + 'yet', + 'you', + 'your' +]) + +lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter') +/*! + * lunr.trimmer + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.trimmer is a pipeline function for trimming non word + * characters from the beginning and end of tokens before they + * enter the index. + * + * This implementation may not work correctly for non latin + * characters and should either be removed or adapted for use + * with languages with non-latin characters. + * + * @static + * @implements {lunr.PipelineFunction} + * @param {lunr.Token} token The token to pass through the filter + * @returns {lunr.Token} + * @see lunr.Pipeline + */ +lunr.trimmer = function (token) { + return token.update(function (s) { + return s.replace(/^\W+/, '').replace(/\W+$/, '') + }) +} + +lunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer') +/*! + * lunr.TokenSet + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * A token set is used to store the unique list of all tokens + * within an index. Token sets are also used to represent an + * incoming query to the index, this query token set and index + * token set are then intersected to find which tokens to look + * up in the inverted index. + * + * A token set can hold multiple tokens, as in the case of the + * index token set, or it can hold a single token as in the + * case of a simple query token set. + * + * Additionally token sets are used to perform wildcard matching. + * Leading, contained and trailing wildcards are supported, and + * from this edit distance matching can also be provided. + * + * Token sets are implemented as a minimal finite state automata, + * where both common prefixes and suffixes are shared between tokens. + * This helps to reduce the space used for storing the token set. + * + * @constructor + */ +lunr.TokenSet = function () { + this.final = false + this.edges = {} + this.id = lunr.TokenSet._nextId + lunr.TokenSet._nextId += 1 +} + +/** + * Keeps track of the next, auto increment, identifier to assign + * to a new tokenSet. + * + * TokenSets require a unique identifier to be correctly minimised. + * + * @private + */ +lunr.TokenSet._nextId = 1 + +/** + * Creates a TokenSet instance from the given sorted array of words. + * + * @param {String[]} arr - A sorted array of strings to create the set from. + * @returns {lunr.TokenSet} + * @throws Will throw an error if the input array is not sorted. + */ +lunr.TokenSet.fromArray = function (arr) { + var builder = new lunr.TokenSet.Builder + + for (var i = 0, len = arr.length; i < len; i++) { + builder.insert(arr[i]) + } + + builder.finish() + return builder.root +} + +/** + * Creates a token set from a query clause. + * + * @private + * @param {Object} clause - A single clause from lunr.Query. + * @param {string} clause.term - The query clause term. + * @param {number} [clause.editDistance] - The optional edit distance for the term. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.fromClause = function (clause) { + if ('editDistance' in clause) { + return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance) + } else { + return lunr.TokenSet.fromString(clause.term) + } +} + +/** + * Creates a token set representing a single string with a specified + * edit distance. + * + * Insertions, deletions, substitutions and transpositions are each + * treated as an edit distance of 1. + * + * Increasing the allowed edit distance will have a dramatic impact + * on the performance of both creating and intersecting these TokenSets. + * It is advised to keep the edit distance less than 3. + * + * @param {string} str - The string to create the token set from. + * @param {number} editDistance - The allowed edit distance to match. + * @returns {lunr.Vector} + */ +lunr.TokenSet.fromFuzzyString = function (str, editDistance) { + var root = new lunr.TokenSet + + var stack = [{ + node: root, + editsRemaining: editDistance, + str: str + }] + + while (stack.length) { + var frame = stack.pop() + + // no edit + if (frame.str.length > 0) { + var char = frame.str.charAt(0), + noEditNode + + if (char in frame.node.edges) { + noEditNode = frame.node.edges[char] + } else { + noEditNode = new lunr.TokenSet + frame.node.edges[char] = noEditNode + } + + if (frame.str.length == 1) { + noEditNode.final = true + } + + stack.push({ + node: noEditNode, + editsRemaining: frame.editsRemaining, + str: frame.str.slice(1) + }) + } + + if (frame.editsRemaining == 0) { + continue + } + + // insertion + if ("*" in frame.node.edges) { + var insertionNode = frame.node.edges["*"] + } else { + var insertionNode = new lunr.TokenSet + frame.node.edges["*"] = insertionNode + } + + if (frame.str.length == 0) { + insertionNode.final = true + } + + stack.push({ + node: insertionNode, + editsRemaining: frame.editsRemaining - 1, + str: frame.str + }) + + // deletion + // can only do a deletion if we have enough edits remaining + // and if there are characters left to delete in the string + if (frame.str.length > 1) { + stack.push({ + node: frame.node, + editsRemaining: frame.editsRemaining - 1, + str: frame.str.slice(1) + }) + } + + // deletion + // just removing the last character from the str + if (frame.str.length == 1) { + frame.node.final = true + } + + // substitution + // can only do a substitution if we have enough edits remaining + // and if there are characters left to substitute + if (frame.str.length >= 1) { + if ("*" in frame.node.edges) { + var substitutionNode = frame.node.edges["*"] + } else { + var substitutionNode = new lunr.TokenSet + frame.node.edges["*"] = substitutionNode + } + + if (frame.str.length == 1) { + substitutionNode.final = true + } + + stack.push({ + node: substitutionNode, + editsRemaining: frame.editsRemaining - 1, + str: frame.str.slice(1) + }) + } + + // transposition + // can only do a transposition if there are edits remaining + // and there are enough characters to transpose + if (frame.str.length > 1) { + var charA = frame.str.charAt(0), + charB = frame.str.charAt(1), + transposeNode + + if (charB in frame.node.edges) { + transposeNode = frame.node.edges[charB] + } else { + transposeNode = new lunr.TokenSet + frame.node.edges[charB] = transposeNode + } + + if (frame.str.length == 1) { + transposeNode.final = true + } + + stack.push({ + node: transposeNode, + editsRemaining: frame.editsRemaining - 1, + str: charA + frame.str.slice(2) + }) + } + } + + return root +} + +/** + * Creates a TokenSet from a string. + * + * The string may contain one or more wildcard characters (*) + * that will allow wildcard matching when intersecting with + * another TokenSet. + * + * @param {string} str - The string to create a TokenSet from. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.fromString = function (str) { + var node = new lunr.TokenSet, + root = node + + /* + * Iterates through all characters within the passed string + * appending a node for each character. + * + * When a wildcard character is found then a self + * referencing edge is introduced to continually match + * any number of any characters. + */ + for (var i = 0, len = str.length; i < len; i++) { + var char = str[i], + final = (i == len - 1) + + if (char == "*") { + node.edges[char] = node + node.final = final + + } else { + var next = new lunr.TokenSet + next.final = final + + node.edges[char] = next + node = next + } + } + + return root +} + +/** + * Converts this TokenSet into an array of strings + * contained within the TokenSet. + * + * This is not intended to be used on a TokenSet that + * contains wildcards, in these cases the results are + * undefined and are likely to cause an infinite loop. + * + * @returns {string[]} + */ +lunr.TokenSet.prototype.toArray = function () { + var words = [] + + var stack = [{ + prefix: "", + node: this + }] + + while (stack.length) { + var frame = stack.pop(), + edges = Object.keys(frame.node.edges), + len = edges.length + + if (frame.node.final) { + /* In Safari, at this point the prefix is sometimes corrupted, see: + * https://github.com/olivernn/lunr.js/issues/279 Calling any + * String.prototype method forces Safari to "cast" this string to what + * it's supposed to be, fixing the bug. */ + frame.prefix.charAt(0) + words.push(frame.prefix) + } + + for (var i = 0; i < len; i++) { + var edge = edges[i] + + stack.push({ + prefix: frame.prefix.concat(edge), + node: frame.node.edges[edge] + }) + } + } + + return words +} + +/** + * Generates a string representation of a TokenSet. + * + * This is intended to allow TokenSets to be used as keys + * in objects, largely to aid the construction and minimisation + * of a TokenSet. As such it is not designed to be a human + * friendly representation of the TokenSet. + * + * @returns {string} + */ +lunr.TokenSet.prototype.toString = function () { + // NOTE: Using Object.keys here as this.edges is very likely + // to enter 'hash-mode' with many keys being added + // + // avoiding a for-in loop here as it leads to the function + // being de-optimised (at least in V8). From some simple + // benchmarks the performance is comparable, but allowing + // V8 to optimize may mean easy performance wins in the future. + + if (this._str) { + return this._str + } + + var str = this.final ? '1' : '0', + labels = Object.keys(this.edges).sort(), + len = labels.length + + for (var i = 0; i < len; i++) { + var label = labels[i], + node = this.edges[label] + + str = str + label + node.id + } + + return str +} + +/** + * Returns a new TokenSet that is the intersection of + * this TokenSet and the passed TokenSet. + * + * This intersection will take into account any wildcards + * contained within the TokenSet. + * + * @param {lunr.TokenSet} b - An other TokenSet to intersect with. + * @returns {lunr.TokenSet} + */ +lunr.TokenSet.prototype.intersect = function (b) { + var output = new lunr.TokenSet, + frame = undefined + + var stack = [{ + qNode: b, + output: output, + node: this + }] + + while (stack.length) { + frame = stack.pop() + + // NOTE: As with the #toString method, we are using + // Object.keys and a for loop instead of a for-in loop + // as both of these objects enter 'hash' mode, causing + // the function to be de-optimised in V8 + var qEdges = Object.keys(frame.qNode.edges), + qLen = qEdges.length, + nEdges = Object.keys(frame.node.edges), + nLen = nEdges.length + + for (var q = 0; q < qLen; q++) { + var qEdge = qEdges[q] + + for (var n = 0; n < nLen; n++) { + var nEdge = nEdges[n] + + if (nEdge == qEdge || qEdge == '*') { + var node = frame.node.edges[nEdge], + qNode = frame.qNode.edges[qEdge], + final = node.final && qNode.final, + next = undefined + + if (nEdge in frame.output.edges) { + // an edge already exists for this character + // no need to create a new node, just set the finality + // bit unless this node is already final + next = frame.output.edges[nEdge] + next.final = next.final || final + + } else { + // no edge exists yet, must create one + // set the finality bit and insert it + // into the output + next = new lunr.TokenSet + next.final = final + frame.output.edges[nEdge] = next + } + + stack.push({ + qNode: qNode, + output: next, + node: node + }) + } + } + } + } + + return output +} +lunr.TokenSet.Builder = function () { + this.previousWord = "" + this.root = new lunr.TokenSet + this.uncheckedNodes = [] + this.minimizedNodes = {} +} + +lunr.TokenSet.Builder.prototype.insert = function (word) { + var node, + commonPrefix = 0 + + if (word < this.previousWord) { + throw new Error ("Out of order word insertion") + } + + for (var i = 0; i < word.length && i < this.previousWord.length; i++) { + if (word[i] != this.previousWord[i]) break + commonPrefix++ + } + + this.minimize(commonPrefix) + + if (this.uncheckedNodes.length == 0) { + node = this.root + } else { + node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child + } + + for (var i = commonPrefix; i < word.length; i++) { + var nextNode = new lunr.TokenSet, + char = word[i] + + node.edges[char] = nextNode + + this.uncheckedNodes.push({ + parent: node, + char: char, + child: nextNode + }) + + node = nextNode + } + + node.final = true + this.previousWord = word +} + +lunr.TokenSet.Builder.prototype.finish = function () { + this.minimize(0) +} + +lunr.TokenSet.Builder.prototype.minimize = function (downTo) { + for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) { + var node = this.uncheckedNodes[i], + childKey = node.child.toString() + + if (childKey in this.minimizedNodes) { + node.parent.edges[node.char] = this.minimizedNodes[childKey] + } else { + // Cache the key for this node since + // we know it can't change anymore + node.child._str = childKey + + this.minimizedNodes[childKey] = node.child + } + + this.uncheckedNodes.pop() + } +} +/*! + * lunr.Index + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * An index contains the built index of all documents and provides a query interface + * to the index. + * + * Usually instances of lunr.Index will not be created using this constructor, instead + * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be + * used to load previously built and serialized indexes. + * + * @constructor + * @param {Object} attrs - The attributes of the built search index. + * @param {Object} attrs.invertedIndex - An index of term/field to document reference. + * @param {Object} attrs.fieldVectors - Field vectors + * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens. + * @param {string[]} attrs.fields - The names of indexed document fields. + * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms. + */ +lunr.Index = function (attrs) { + this.invertedIndex = attrs.invertedIndex + this.fieldVectors = attrs.fieldVectors + this.tokenSet = attrs.tokenSet + this.fields = attrs.fields + this.pipeline = attrs.pipeline +} + +/** + * A result contains details of a document matching a search query. + * @typedef {Object} lunr.Index~Result + * @property {string} ref - The reference of the document this result represents. + * @property {number} score - A number between 0 and 1 representing how similar this document is to the query. + * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match. + */ + +/** + * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple + * query language which itself is parsed into an instance of lunr.Query. + * + * For programmatically building queries it is advised to directly use lunr.Query, the query language + * is best used for human entered text rather than program generated text. + * + * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported + * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello' + * or 'world', though those that contain both will rank higher in the results. + * + * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can + * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding + * wildcards will increase the number of documents that will be found but can also have a negative + * impact on query performance, especially with wildcards at the beginning of a term. + * + * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term + * hello in the title field will match this query. Using a field not present in the index will lead + * to an error being thrown. + * + * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term + * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported + * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2. + * Avoid large values for edit distance to improve query performance. + * + * Each term also supports a presence modifier. By default a term's presence in document is optional, however + * this can be changed to either required or prohibited. For a term's presence to be required in a document the + * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and + * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not + * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'. + * + * To escape special characters the backslash character '\' can be used, this allows searches to include + * characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead + * of attempting to apply a boost of 2 to the search term "foo". + * + * @typedef {string} lunr.Index~QueryString + * @example Simple single term query + * hello + * @example Multiple term query + * hello world + * @example term scoped to a field + * title:hello + * @example term with a boost of 10 + * hello^10 + * @example term with an edit distance of 2 + * hello~2 + * @example terms with presence modifiers + * -foo +bar baz + */ + +/** + * Performs a search against the index using lunr query syntax. + * + * Results will be returned sorted by their score, the most relevant results + * will be returned first. For details on how the score is calculated, please see + * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}. + * + * For more programmatic querying use lunr.Index#query. + * + * @param {lunr.Index~QueryString} queryString - A string containing a lunr query. + * @throws {lunr.QueryParseError} If the passed query string cannot be parsed. + * @returns {lunr.Index~Result[]} + */ +lunr.Index.prototype.search = function (queryString) { + return this.query(function (query) { + var parser = new lunr.QueryParser(queryString, query) + parser.parse() + }) +} + +/** + * A query builder callback provides a query object to be used to express + * the query to perform on the index. + * + * @callback lunr.Index~queryBuilder + * @param {lunr.Query} query - The query object to build up. + * @this lunr.Query + */ + +/** + * Performs a query against the index using the yielded lunr.Query object. + * + * If performing programmatic queries against the index, this method is preferred + * over lunr.Index#search so as to avoid the additional query parsing overhead. + * + * A query object is yielded to the supplied function which should be used to + * express the query to be run against the index. + * + * Note that although this function takes a callback parameter it is _not_ an + * asynchronous operation, the callback is just yielded a query object to be + * customized. + * + * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query. + * @returns {lunr.Index~Result[]} + */ +lunr.Index.prototype.query = function (fn) { + // for each query clause + // * process terms + // * expand terms from token set + // * find matching documents and metadata + // * get document vectors + // * score documents + + var query = new lunr.Query(this.fields), + matchingFields = Object.create(null), + queryVectors = Object.create(null), + termFieldCache = Object.create(null), + requiredMatches = Object.create(null), + prohibitedMatches = Object.create(null) + + /* + * To support field level boosts a query vector is created per + * field. An empty vector is eagerly created to support negated + * queries. + */ + for (var i = 0; i < this.fields.length; i++) { + queryVectors[this.fields[i]] = new lunr.Vector + } + + fn.call(query, query) + + for (var i = 0; i < query.clauses.length; i++) { + /* + * Unless the pipeline has been disabled for this term, which is + * the case for terms with wildcards, we need to pass the clause + * term through the search pipeline. A pipeline returns an array + * of processed terms. Pipeline functions may expand the passed + * term, which means we may end up performing multiple index lookups + * for a single query term. + */ + var clause = query.clauses[i], + terms = null, + clauseMatches = lunr.Set.empty + + if (clause.usePipeline) { + terms = this.pipeline.runString(clause.term, { + fields: clause.fields + }) + } else { + terms = [clause.term] + } + + for (var m = 0; m < terms.length; m++) { + var term = terms[m] + + /* + * Each term returned from the pipeline needs to use the same query + * clause object, e.g. the same boost and or edit distance. The + * simplest way to do this is to re-use the clause object but mutate + * its term property. + */ + clause.term = term + + /* + * From the term in the clause we create a token set which will then + * be used to intersect the indexes token set to get a list of terms + * to lookup in the inverted index + */ + var termTokenSet = lunr.TokenSet.fromClause(clause), + expandedTerms = this.tokenSet.intersect(termTokenSet).toArray() + + /* + * If a term marked as required does not exist in the tokenSet it is + * impossible for the search to return any matches. We set all the field + * scoped required matches set to empty and stop examining any further + * clauses. + */ + if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) { + for (var k = 0; k < clause.fields.length; k++) { + var field = clause.fields[k] + requiredMatches[field] = lunr.Set.empty + } + + break + } + + for (var j = 0; j < expandedTerms.length; j++) { + /* + * For each term get the posting and termIndex, this is required for + * building the query vector. + */ + var expandedTerm = expandedTerms[j], + posting = this.invertedIndex[expandedTerm], + termIndex = posting._index + + for (var k = 0; k < clause.fields.length; k++) { + /* + * For each field that this query term is scoped by (by default + * all fields are in scope) we need to get all the document refs + * that have this term in that field. + * + * The posting is the entry in the invertedIndex for the matching + * term from above. + */ + var field = clause.fields[k], + fieldPosting = posting[field], + matchingDocumentRefs = Object.keys(fieldPosting), + termField = expandedTerm + "/" + field, + matchingDocumentsSet = new lunr.Set(matchingDocumentRefs) + + /* + * if the presence of this term is required ensure that the matching + * documents are added to the set of required matches for this clause. + * + */ + if (clause.presence == lunr.Query.presence.REQUIRED) { + clauseMatches = clauseMatches.union(matchingDocumentsSet) + + if (requiredMatches[field] === undefined) { + requiredMatches[field] = lunr.Set.complete + } + } + + /* + * if the presence of this term is prohibited ensure that the matching + * documents are added to the set of prohibited matches for this field, + * creating that set if it does not yet exist. + */ + if (clause.presence == lunr.Query.presence.PROHIBITED) { + if (prohibitedMatches[field] === undefined) { + prohibitedMatches[field] = lunr.Set.empty + } + + prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet) + + /* + * Prohibited matches should not be part of the query vector used for + * similarity scoring and no metadata should be extracted so we continue + * to the next field + */ + continue + } + + /* + * The query field vector is populated using the termIndex found for + * the term and a unit value with the appropriate boost applied. + * Using upsert because there could already be an entry in the vector + * for the term we are working with. In that case we just add the scores + * together. + */ + queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b }) + + /** + * If we've already seen this term, field combo then we've already collected + * the matching documents and metadata, no need to go through all that again + */ + if (termFieldCache[termField]) { + continue + } + + for (var l = 0; l < matchingDocumentRefs.length; l++) { + /* + * All metadata for this term/field/document triple + * are then extracted and collected into an instance + * of lunr.MatchData ready to be returned in the query + * results + */ + var matchingDocumentRef = matchingDocumentRefs[l], + matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field), + metadata = fieldPosting[matchingDocumentRef], + fieldMatch + + if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) { + matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata) + } else { + fieldMatch.add(expandedTerm, field, metadata) + } + + } + + termFieldCache[termField] = true + } + } + } + + /** + * If the presence was required we need to update the requiredMatches field sets. + * We do this after all fields for the term have collected their matches because + * the clause terms presence is required in _any_ of the fields not _all_ of the + * fields. + */ + if (clause.presence === lunr.Query.presence.REQUIRED) { + for (var k = 0; k < clause.fields.length; k++) { + var field = clause.fields[k] + requiredMatches[field] = requiredMatches[field].intersect(clauseMatches) + } + } + } + + /** + * Need to combine the field scoped required and prohibited + * matching documents into a global set of required and prohibited + * matches + */ + var allRequiredMatches = lunr.Set.complete, + allProhibitedMatches = lunr.Set.empty + + for (var i = 0; i < this.fields.length; i++) { + var field = this.fields[i] + + if (requiredMatches[field]) { + allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field]) + } + + if (prohibitedMatches[field]) { + allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field]) + } + } + + var matchingFieldRefs = Object.keys(matchingFields), + results = [], + matches = Object.create(null) + + /* + * If the query is negated (contains only prohibited terms) + * we need to get _all_ fieldRefs currently existing in the + * index. This is only done when we know that the query is + * entirely prohibited terms to avoid any cost of getting all + * fieldRefs unnecessarily. + * + * Additionally, blank MatchData must be created to correctly + * populate the results. + */ + if (query.isNegated()) { + matchingFieldRefs = Object.keys(this.fieldVectors) + + for (var i = 0; i < matchingFieldRefs.length; i++) { + var matchingFieldRef = matchingFieldRefs[i] + var fieldRef = lunr.FieldRef.fromString(matchingFieldRef) + matchingFields[matchingFieldRef] = new lunr.MatchData + } + } + + for (var i = 0; i < matchingFieldRefs.length; i++) { + /* + * Currently we have document fields that match the query, but we + * need to return documents. The matchData and scores are combined + * from multiple fields belonging to the same document. + * + * Scores are calculated by field, using the query vectors created + * above, and combined into a final document score using addition. + */ + var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]), + docRef = fieldRef.docRef + + if (!allRequiredMatches.contains(docRef)) { + continue + } + + if (allProhibitedMatches.contains(docRef)) { + continue + } + + var fieldVector = this.fieldVectors[fieldRef], + score = queryVectors[fieldRef.fieldName].similarity(fieldVector), + docMatch + + if ((docMatch = matches[docRef]) !== undefined) { + docMatch.score += score + docMatch.matchData.combine(matchingFields[fieldRef]) + } else { + var match = { + ref: docRef, + score: score, + matchData: matchingFields[fieldRef] + } + matches[docRef] = match + results.push(match) + } + } + + /* + * Sort the results objects by score, highest first. + */ + return results.sort(function (a, b) { + return b.score - a.score + }) +} + +/** + * Prepares the index for JSON serialization. + * + * The schema for this JSON blob will be described in a + * separate JSON schema file. + * + * @returns {Object} + */ +lunr.Index.prototype.toJSON = function () { + var invertedIndex = Object.keys(this.invertedIndex) + .sort() + .map(function (term) { + return [term, this.invertedIndex[term]] + }, this) + + var fieldVectors = Object.keys(this.fieldVectors) + .map(function (ref) { + return [ref, this.fieldVectors[ref].toJSON()] + }, this) + + return { + version: lunr.version, + fields: this.fields, + fieldVectors: fieldVectors, + invertedIndex: invertedIndex, + pipeline: this.pipeline.toJSON() + } +} + +/** + * Loads a previously serialized lunr.Index + * + * @param {Object} serializedIndex - A previously serialized lunr.Index + * @returns {lunr.Index} + */ +lunr.Index.load = function (serializedIndex) { + var attrs = {}, + fieldVectors = {}, + serializedVectors = serializedIndex.fieldVectors, + invertedIndex = Object.create(null), + serializedInvertedIndex = serializedIndex.invertedIndex, + tokenSetBuilder = new lunr.TokenSet.Builder, + pipeline = lunr.Pipeline.load(serializedIndex.pipeline) + + if (serializedIndex.version != lunr.version) { + lunr.utils.warn("Version mismatch when loading serialised index. Current version of lunr '" + lunr.version + "' does not match serialized index '" + serializedIndex.version + "'") + } + + for (var i = 0; i < serializedVectors.length; i++) { + var tuple = serializedVectors[i], + ref = tuple[0], + elements = tuple[1] + + fieldVectors[ref] = new lunr.Vector(elements) + } + + for (var i = 0; i < serializedInvertedIndex.length; i++) { + var tuple = serializedInvertedIndex[i], + term = tuple[0], + posting = tuple[1] + + tokenSetBuilder.insert(term) + invertedIndex[term] = posting + } + + tokenSetBuilder.finish() + + attrs.fields = serializedIndex.fields + + attrs.fieldVectors = fieldVectors + attrs.invertedIndex = invertedIndex + attrs.tokenSet = tokenSetBuilder.root + attrs.pipeline = pipeline + + return new lunr.Index(attrs) +} +/*! + * lunr.Builder + * Copyright (C) 2020 Oliver Nightingale + */ + +/** + * lunr.Builder performs indexing on a set of documents and + * returns instances of lunr.Index ready for querying. + * + * All configuration of the index is done via the builder, the + * fields to index, the document reference, the text processing + * pipeline and document scoring parameters are all set on the + * builder before indexing. + * + * @constructor + * @property {string} _ref - Internal reference to the document reference field. + * @property {string[]} _fields - Internal reference to the document fields to index. + * @property {object} invertedIndex - The inverted index maps terms to document fields. + * @property {object} documentTermFrequencies - Keeps track of document term frequencies. + * @property {object} documentLengths - Keeps track of the length of documents added to the index. + * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing. + * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing. + * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index. + * @property {number} documentCount - Keeps track of the total number of documents indexed. + * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75. + * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2. + * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space. + * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index. + */ +lunr.Builder = function () { + this._ref = "id" + this._fields = Object.create(null) + this._documents = Object.create(null) + this.invertedIndex = Object.create(null) + this.fieldTermFrequencies = {} + this.fieldLengths = {} + this.tokenizer = lunr.tokenizer + this.pipeline = new lunr.Pipeline + this.searchPipeline = new lunr.Pipeline + this.documentCount = 0 + this._b = 0.75 + this._k1 = 1.2 + this.termIndex = 0 + this.metadataWhitelist = [] +} + +/** + * Sets the document field used as the document reference. Every document must have this field. + * The type of this field in the document should be a string, if it is not a string it will be + * coerced into a string by calling toString. + * + * The default ref is 'id'. + * + * The ref should _not_ be changed during indexing, it should be set before any documents are + * added to the index. Changing it during indexing can lead to inconsistent results. + * + * @param {string} ref - The name of the reference field in the document. + */ +lunr.Builder.prototype.ref = function (ref) { + this._ref = ref +} + +/** + * A function that is used to extract a field from a document. + * + * Lunr expects a field to be at the top level of a document, if however the field + * is deeply nested within a document an extractor function can be used to extract + * the right field for indexing. + * + * @callback fieldExtractor + * @param {object} doc - The document being added to the index. + * @returns {?(string|object|object[])} obj - The object that will be indexed for this field. + * @example Extracting a nested field + * function (doc) { return doc.nested.field } + */ + +/** + * Adds a field to the list of document fields that will be indexed. Every document being + * indexed should have this field. Null values for this field in indexed documents will + * not cause errors but will limit the chance of that document being retrieved by searches. + * + * All fields should be added before adding documents to the index. Adding fields after + * a document has been indexed will have no effect on already indexed documents. + * + * Fields can be boosted at build time. This allows terms within that field to have more + * importance when ranking search results. Use a field boost to specify that matches within + * one field are more important than other fields. + * + * @param {string} fieldName - The name of a field to index in all documents. + * @param {object} attributes - Optional attributes associated with this field. + * @param {number} [attributes.boost=1] - Boost applied to all terms within this field. + * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document. + * @throws {RangeError} fieldName cannot contain unsupported characters '/' + */ +lunr.Builder.prototype.field = function (fieldName, attributes) { + if (/\//.test(fieldName)) { + throw new RangeError ("Field '" + fieldName + "' contains illegal character '/'") + } + + this._fields[fieldName] = attributes || {} +} + +/** + * A parameter to tune the amount of field length normalisation that is applied when + * calculating relevance scores. A value of 0 will completely disable any normalisation + * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b + * will be clamped to the range 0 - 1. + * + * @param {number} number - The value to set for this tuning parameter. + */ +lunr.Builder.prototype.b = function (number) { + if (number < 0) { + this._b = 0 + } else if (number > 1) { + this._b = 1 + } else { + this._b = number + } +} + +/** + * A parameter that controls the speed at which a rise in term frequency results in term + * frequency saturation. The default value is 1.2. Setting this to a higher value will give + * slower saturation levels, a lower value will result in quicker saturation. + * + * @param {number} number - The value to set for this tuning parameter. + */ +lunr.Builder.prototype.k1 = function (number) { + this._k1 = number +} + +/** + * Adds a document to the index. + * + * Before adding fields to the index the index should have been fully setup, with the document + * ref and all fields to index already having been specified. + * + * The document must have a field name as specified by the ref (by default this is 'id') and + * it should have all fields defined for indexing, though null or undefined values will not + * cause errors. + * + * Entire documents can be boosted at build time. Applying a boost to a document indicates that + * this document should rank higher in search results than other documents. + * + * @param {object} doc - The document to add to the index. + * @param {object} attributes - Optional attributes associated with this document. + * @param {number} [attributes.boost=1] - Boost applied to all terms within this document. + */ +lunr.Builder.prototype.add = function (doc, attributes) { + var docRef = doc[this._ref], + fields = Object.keys(this._fields) + + this._documents[docRef] = attributes || {} + this.documentCount += 1 + + for (var i = 0; i < fields.length; i++) { + var fieldName = fields[i], + extractor = this._fields[fieldName].extractor, + field = extractor ? extractor(doc) : doc[fieldName], + tokens = this.tokenizer(field, { + fields: [fieldName] + }), + terms = this.pipeline.run(tokens), + fieldRef = new lunr.FieldRef (docRef, fieldName), + fieldTerms = Object.create(null) + + this.fieldTermFrequencies[fieldRef] = fieldTerms + this.fieldLengths[fieldRef] = 0 + + // store the length of this field for this document + this.fieldLengths[fieldRef] += terms.length + + // calculate term frequencies for this field + for (var j = 0; j < terms.length; j++) { + var term = terms[j] + + if (fieldTerms[term] == undefined) { + fieldTerms[term] = 0 + } + + fieldTerms[term] += 1 + + // add to inverted index + // create an initial posting if one doesn't exist + if (this.invertedIndex[term] == undefined) { + var posting = Object.create(null) + posting["_index"] = this.termIndex + this.termIndex += 1 + + for (var k = 0; k < fields.length; k++) { + posting[fields[k]] = Object.create(null) + } + + this.invertedIndex[term] = posting + } + + // add an entry for this term/fieldName/docRef to the invertedIndex + if (this.invertedIndex[term][fieldName][docRef] == undefined) { + this.invertedIndex[term][fieldName][docRef] = Object.create(null) + } + + // store all whitelisted metadata about this token in the + // inverted index + for (var l = 0; l < this.metadataWhitelist.length; l++) { + var metadataKey = this.metadataWhitelist[l], + metadata = term.metadata[metadataKey] + + if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) { + this.invertedIndex[term][fieldName][docRef][metadataKey] = [] + } + + this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata) + } + } + + } +} + +/** + * Calculates the average document length for this index + * + * @private + */ +lunr.Builder.prototype.calculateAverageFieldLengths = function () { + + var fieldRefs = Object.keys(this.fieldLengths), + numberOfFields = fieldRefs.length, + accumulator = {}, + documentsWithField = {} + + for (var i = 0; i < numberOfFields; i++) { + var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), + field = fieldRef.fieldName + + documentsWithField[field] || (documentsWithField[field] = 0) + documentsWithField[field] += 1 + + accumulator[field] || (accumulator[field] = 0) + accumulator[field] += this.fieldLengths[fieldRef] + } + + var fields = Object.keys(this._fields) + + for (var i = 0; i < fields.length; i++) { + var fieldName = fields[i] + accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName] + } + + this.averageFieldLength = accumulator +} + +/** + * Builds a vector space model of every document using lunr.Vector + * + * @private + */ +lunr.Builder.prototype.createFieldVectors = function () { + var fieldVectors = {}, + fieldRefs = Object.keys(this.fieldTermFrequencies), + fieldRefsLength = fieldRefs.length, + termIdfCache = Object.create(null) + + for (var i = 0; i < fieldRefsLength; i++) { + var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), + fieldName = fieldRef.fieldName, + fieldLength = this.fieldLengths[fieldRef], + fieldVector = new lunr.Vector, + termFrequencies = this.fieldTermFrequencies[fieldRef], + terms = Object.keys(termFrequencies), + termsLength = terms.length + + + var fieldBoost = this._fields[fieldName].boost || 1, + docBoost = this._documents[fieldRef.docRef].boost || 1 + + for (var j = 0; j < termsLength; j++) { + var term = terms[j], + tf = termFrequencies[term], + termIndex = this.invertedIndex[term]._index, + idf, score, scoreWithPrecision + + if (termIdfCache[term] === undefined) { + idf = lunr.idf(this.invertedIndex[term], this.documentCount) + termIdfCache[term] = idf + } else { + idf = termIdfCache[term] + } + + score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf) + score *= fieldBoost + score *= docBoost + scoreWithPrecision = Math.round(score * 1000) / 1000 + // Converts 1.23456789 to 1.234. + // Reducing the precision so that the vectors take up less + // space when serialised. Doing it now so that they behave + // the same before and after serialisation. Also, this is + // the fastest approach to reducing a number's precision in + // JavaScript. + + fieldVector.insert(termIndex, scoreWithPrecision) + } + + fieldVectors[fieldRef] = fieldVector + } + + this.fieldVectors = fieldVectors +} + +/** + * Creates a token set of all tokens in the index using lunr.TokenSet + * + * @private + */ +lunr.Builder.prototype.createTokenSet = function () { + this.tokenSet = lunr.TokenSet.fromArray( + Object.keys(this.invertedIndex).sort() + ) +} + +/** + * Builds the index, creating an instance of lunr.Index. + * + * This completes the indexing process and should only be called + * once all documents have been added to the index. + * + * @returns {lunr.Index} + */ +lunr.Builder.prototype.build = function () { + this.calculateAverageFieldLengths() + this.createFieldVectors() + this.createTokenSet() + + return new lunr.Index({ + invertedIndex: this.invertedIndex, + fieldVectors: this.fieldVectors, + tokenSet: this.tokenSet, + fields: Object.keys(this._fields), + pipeline: this.searchPipeline + }) +} + +/** + * Applies a plugin to the index builder. + * + * A plugin is a function that is called with the index builder as its context. + * Plugins can be used to customise or extend the behaviour of the index + * in some way. A plugin is just a function, that encapsulated the custom + * behaviour that should be applied when building the index. + * + * The plugin function will be called with the index builder as its argument, additional + * arguments can also be passed when calling use. The function will be called + * with the index builder as its context. + * + * @param {Function} plugin The plugin to apply. + */ +lunr.Builder.prototype.use = function (fn) { + var args = Array.prototype.slice.call(arguments, 1) + args.unshift(this) + fn.apply(this, args) +} +/** + * Contains and collects metadata about a matching document. + * A single instance of lunr.MatchData is returned as part of every + * lunr.Index~Result. + * + * @constructor + * @param {string} term - The term this match data is associated with + * @param {string} field - The field in which the term was found + * @param {object} metadata - The metadata recorded about this term in this field + * @property {object} metadata - A cloned collection of metadata associated with this document. + * @see {@link lunr.Index~Result} + */ +lunr.MatchData = function (term, field, metadata) { + var clonedMetadata = Object.create(null), + metadataKeys = Object.keys(metadata || {}) + + // Cloning the metadata to prevent the original + // being mutated during match data combination. + // Metadata is kept in an array within the inverted + // index so cloning the data can be done with + // Array#slice + for (var i = 0; i < metadataKeys.length; i++) { + var key = metadataKeys[i] + clonedMetadata[key] = metadata[key].slice() + } + + this.metadata = Object.create(null) + + if (term !== undefined) { + this.metadata[term] = Object.create(null) + this.metadata[term][field] = clonedMetadata + } +} + +/** + * An instance of lunr.MatchData will be created for every term that matches a + * document. However only one instance is required in a lunr.Index~Result. This + * method combines metadata from another instance of lunr.MatchData with this + * objects metadata. + * + * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one. + * @see {@link lunr.Index~Result} + */ +lunr.MatchData.prototype.combine = function (otherMatchData) { + var terms = Object.keys(otherMatchData.metadata) + + for (var i = 0; i < terms.length; i++) { + var term = terms[i], + fields = Object.keys(otherMatchData.metadata[term]) + + if (this.metadata[term] == undefined) { + this.metadata[term] = Object.create(null) + } + + for (var j = 0; j < fields.length; j++) { + var field = fields[j], + keys = Object.keys(otherMatchData.metadata[term][field]) + + if (this.metadata[term][field] == undefined) { + this.metadata[term][field] = Object.create(null) + } + + for (var k = 0; k < keys.length; k++) { + var key = keys[k] + + if (this.metadata[term][field][key] == undefined) { + this.metadata[term][field][key] = otherMatchData.metadata[term][field][key] + } else { + this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key]) + } + + } + } + } +} + +/** + * Add metadata for a term/field pair to this instance of match data. + * + * @param {string} term - The term this match data is associated with + * @param {string} field - The field in which the term was found + * @param {object} metadata - The metadata recorded about this term in this field + */ +lunr.MatchData.prototype.add = function (term, field, metadata) { + if (!(term in this.metadata)) { + this.metadata[term] = Object.create(null) + this.metadata[term][field] = metadata + return + } + + if (!(field in this.metadata[term])) { + this.metadata[term][field] = metadata + return + } + + var metadataKeys = Object.keys(metadata) + + for (var i = 0; i < metadataKeys.length; i++) { + var key = metadataKeys[i] + + if (key in this.metadata[term][field]) { + this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key]) + } else { + this.metadata[term][field][key] = metadata[key] + } + } +} +/** + * A lunr.Query provides a programmatic way of defining queries to be performed + * against a {@link lunr.Index}. + * + * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method + * so the query object is pre-initialized with the right index fields. + * + * @constructor + * @property {lunr.Query~Clause[]} clauses - An array of query clauses. + * @property {string[]} allFields - An array of all available fields in a lunr.Index. + */ +lunr.Query = function (allFields) { + this.clauses = [] + this.allFields = allFields +} + +/** + * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause. + * + * This allows wildcards to be added to the beginning and end of a term without having to manually do any string + * concatenation. + * + * The wildcard constants can be bitwise combined to select both leading and trailing wildcards. + * + * @constant + * @default + * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour + * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists + * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists + * @see lunr.Query~Clause + * @see lunr.Query#clause + * @see lunr.Query#term + * @example query term with trailing wildcard + * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING }) + * @example query term with leading and trailing wildcard + * query.term('foo', { + * wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING + * }) + */ + +lunr.Query.wildcard = new String ("*") +lunr.Query.wildcard.NONE = 0 +lunr.Query.wildcard.LEADING = 1 +lunr.Query.wildcard.TRAILING = 2 + +/** + * Constants for indicating what kind of presence a term must have in matching documents. + * + * @constant + * @enum {number} + * @see lunr.Query~Clause + * @see lunr.Query#clause + * @see lunr.Query#term + * @example query term with required presence + * query.term('foo', { presence: lunr.Query.presence.REQUIRED }) + */ +lunr.Query.presence = { + /** + * Term's presence in a document is optional, this is the default value. + */ + OPTIONAL: 1, + + /** + * Term's presence in a document is required, documents that do not contain + * this term will not be returned. + */ + REQUIRED: 2, + + /** + * Term's presence in a document is prohibited, documents that do contain + * this term will not be returned. + */ + PROHIBITED: 3 +} + +/** + * A single clause in a {@link lunr.Query} contains a term and details on how to + * match that term against a {@link lunr.Index}. + * + * @typedef {Object} lunr.Query~Clause + * @property {string[]} fields - The fields in an index this clause should be matched against. + * @property {number} [boost=1] - Any boost that should be applied when matching this clause. + * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be. + * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline. + * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended. + * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents. + */ + +/** + * Adds a {@link lunr.Query~Clause} to this query. + * + * Unless the clause contains the fields to be matched all fields will be matched. In addition + * a default boost of 1 is applied to the clause. + * + * @param {lunr.Query~Clause} clause - The clause to add to this query. + * @see lunr.Query~Clause + * @returns {lunr.Query} + */ +lunr.Query.prototype.clause = function (clause) { + if (!('fields' in clause)) { + clause.fields = this.allFields + } + + if (!('boost' in clause)) { + clause.boost = 1 + } + + if (!('usePipeline' in clause)) { + clause.usePipeline = true + } + + if (!('wildcard' in clause)) { + clause.wildcard = lunr.Query.wildcard.NONE + } + + if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) { + clause.term = "*" + clause.term + } + + if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) { + clause.term = "" + clause.term + "*" + } + + if (!('presence' in clause)) { + clause.presence = lunr.Query.presence.OPTIONAL + } + + this.clauses.push(clause) + + return this +} + +/** + * A negated query is one in which every clause has a presence of + * prohibited. These queries require some special processing to return + * the expected results. + * + * @returns boolean + */ +lunr.Query.prototype.isNegated = function () { + for (var i = 0; i < this.clauses.length; i++) { + if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) { + return false + } + } + + return true +} + +/** + * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause} + * to the list of clauses that make up this query. + * + * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion + * to a token or token-like string should be done before calling this method. + * + * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an + * array, each term in the array will share the same options. + * + * @param {object|object[]} term - The term(s) to add to the query. + * @param {object} [options] - Any additional properties to add to the query clause. + * @returns {lunr.Query} + * @see lunr.Query#clause + * @see lunr.Query~Clause + * @example adding a single term to a query + * query.term("foo") + * @example adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard + * query.term("foo", { + * fields: ["title"], + * boost: 10, + * wildcard: lunr.Query.wildcard.TRAILING + * }) + * @example using lunr.tokenizer to convert a string to tokens before using them as terms + * query.term(lunr.tokenizer("foo bar")) + */ +lunr.Query.prototype.term = function (term, options) { + if (Array.isArray(term)) { + term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this) + return this + } + + var clause = options || {} + clause.term = term.toString() + + this.clause(clause) + + return this +} +lunr.QueryParseError = function (message, start, end) { + this.name = "QueryParseError" + this.message = message + this.start = start + this.end = end +} + +lunr.QueryParseError.prototype = new Error +lunr.QueryLexer = function (str) { + this.lexemes = [] + this.str = str + this.length = str.length + this.pos = 0 + this.start = 0 + this.escapeCharPositions = [] +} + +lunr.QueryLexer.prototype.run = function () { + var state = lunr.QueryLexer.lexText + + while (state) { + state = state(this) + } +} + +lunr.QueryLexer.prototype.sliceString = function () { + var subSlices = [], + sliceStart = this.start, + sliceEnd = this.pos + + for (var i = 0; i < this.escapeCharPositions.length; i++) { + sliceEnd = this.escapeCharPositions[i] + subSlices.push(this.str.slice(sliceStart, sliceEnd)) + sliceStart = sliceEnd + 1 + } + + subSlices.push(this.str.slice(sliceStart, this.pos)) + this.escapeCharPositions.length = 0 + + return subSlices.join('') +} + +lunr.QueryLexer.prototype.emit = function (type) { + this.lexemes.push({ + type: type, + str: this.sliceString(), + start: this.start, + end: this.pos + }) + + this.start = this.pos +} + +lunr.QueryLexer.prototype.escapeCharacter = function () { + this.escapeCharPositions.push(this.pos - 1) + this.pos += 1 +} + +lunr.QueryLexer.prototype.next = function () { + if (this.pos >= this.length) { + return lunr.QueryLexer.EOS + } + + var char = this.str.charAt(this.pos) + this.pos += 1 + return char +} + +lunr.QueryLexer.prototype.width = function () { + return this.pos - this.start +} + +lunr.QueryLexer.prototype.ignore = function () { + if (this.start == this.pos) { + this.pos += 1 + } + + this.start = this.pos +} + +lunr.QueryLexer.prototype.backup = function () { + this.pos -= 1 +} + +lunr.QueryLexer.prototype.acceptDigitRun = function () { + var char, charCode + + do { + char = this.next() + charCode = char.charCodeAt(0) + } while (charCode > 47 && charCode < 58) + + if (char != lunr.QueryLexer.EOS) { + this.backup() + } +} + +lunr.QueryLexer.prototype.more = function () { + return this.pos < this.length +} + +lunr.QueryLexer.EOS = 'EOS' +lunr.QueryLexer.FIELD = 'FIELD' +lunr.QueryLexer.TERM = 'TERM' +lunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE' +lunr.QueryLexer.BOOST = 'BOOST' +lunr.QueryLexer.PRESENCE = 'PRESENCE' + +lunr.QueryLexer.lexField = function (lexer) { + lexer.backup() + lexer.emit(lunr.QueryLexer.FIELD) + lexer.ignore() + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexTerm = function (lexer) { + if (lexer.width() > 1) { + lexer.backup() + lexer.emit(lunr.QueryLexer.TERM) + } + + lexer.ignore() + + if (lexer.more()) { + return lunr.QueryLexer.lexText + } +} + +lunr.QueryLexer.lexEditDistance = function (lexer) { + lexer.ignore() + lexer.acceptDigitRun() + lexer.emit(lunr.QueryLexer.EDIT_DISTANCE) + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexBoost = function (lexer) { + lexer.ignore() + lexer.acceptDigitRun() + lexer.emit(lunr.QueryLexer.BOOST) + return lunr.QueryLexer.lexText +} + +lunr.QueryLexer.lexEOS = function (lexer) { + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } +} + +// This matches the separator used when tokenising fields +// within a document. These should match otherwise it is +// not possible to search for some tokens within a document. +// +// It is possible for the user to change the separator on the +// tokenizer so it _might_ clash with any other of the special +// characters already used within the search string, e.g. :. +// +// This means that it is possible to change the separator in +// such a way that makes some words unsearchable using a search +// string. +lunr.QueryLexer.termSeparator = lunr.tokenizer.separator + +lunr.QueryLexer.lexText = function (lexer) { + while (true) { + var char = lexer.next() + + if (char == lunr.QueryLexer.EOS) { + return lunr.QueryLexer.lexEOS + } + + // Escape character is '\' + if (char.charCodeAt(0) == 92) { + lexer.escapeCharacter() + continue + } + + if (char == ":") { + return lunr.QueryLexer.lexField + } + + if (char == "~") { + lexer.backup() + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } + return lunr.QueryLexer.lexEditDistance + } + + if (char == "^") { + lexer.backup() + if (lexer.width() > 0) { + lexer.emit(lunr.QueryLexer.TERM) + } + return lunr.QueryLexer.lexBoost + } + + // "+" indicates term presence is required + // checking for length to ensure that only + // leading "+" are considered + if (char == "+" && lexer.width() === 1) { + lexer.emit(lunr.QueryLexer.PRESENCE) + return lunr.QueryLexer.lexText + } + + // "-" indicates term presence is prohibited + // checking for length to ensure that only + // leading "-" are considered + if (char == "-" && lexer.width() === 1) { + lexer.emit(lunr.QueryLexer.PRESENCE) + return lunr.QueryLexer.lexText + } + + if (char.match(lunr.QueryLexer.termSeparator)) { + return lunr.QueryLexer.lexTerm + } + } +} + +lunr.QueryParser = function (str, query) { + this.lexer = new lunr.QueryLexer (str) + this.query = query + this.currentClause = {} + this.lexemeIdx = 0 +} + +lunr.QueryParser.prototype.parse = function () { + this.lexer.run() + this.lexemes = this.lexer.lexemes + + var state = lunr.QueryParser.parseClause + + while (state) { + state = state(this) + } + + return this.query +} + +lunr.QueryParser.prototype.peekLexeme = function () { + return this.lexemes[this.lexemeIdx] +} + +lunr.QueryParser.prototype.consumeLexeme = function () { + var lexeme = this.peekLexeme() + this.lexemeIdx += 1 + return lexeme +} + +lunr.QueryParser.prototype.nextClause = function () { + var completedClause = this.currentClause + this.query.clause(completedClause) + this.currentClause = {} +} + +lunr.QueryParser.parseClause = function (parser) { + var lexeme = parser.peekLexeme() + + if (lexeme == undefined) { + return + } + + switch (lexeme.type) { + case lunr.QueryLexer.PRESENCE: + return lunr.QueryParser.parsePresence + case lunr.QueryLexer.FIELD: + return lunr.QueryParser.parseField + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expected either a field or a term, found " + lexeme.type + + if (lexeme.str.length >= 1) { + errorMessage += " with value '" + lexeme.str + "'" + } + + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } +} + +lunr.QueryParser.parsePresence = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + switch (lexeme.str) { + case "-": + parser.currentClause.presence = lunr.Query.presence.PROHIBITED + break + case "+": + parser.currentClause.presence = lunr.Query.presence.REQUIRED + break + default: + var errorMessage = "unrecognised presence operator'" + lexeme.str + "'" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + var errorMessage = "expecting term or field, found nothing" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.FIELD: + return lunr.QueryParser.parseField + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expecting term or field, found '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseField = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + if (parser.query.allFields.indexOf(lexeme.str) == -1) { + var possibleFields = parser.query.allFields.map(function (f) { return "'" + f + "'" }).join(', '), + errorMessage = "unrecognised field '" + lexeme.str + "', possible fields: " + possibleFields + + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.fields = [lexeme.str] + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + var errorMessage = "expecting term, found nothing" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + return lunr.QueryParser.parseTerm + default: + var errorMessage = "expecting term, found '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseTerm = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + parser.currentClause.term = lexeme.str.toLowerCase() + + if (lexeme.str.indexOf("*") != -1) { + parser.currentClause.usePipeline = false + } + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseEditDistance = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + var editDistance = parseInt(lexeme.str, 10) + + if (isNaN(editDistance)) { + var errorMessage = "edit distance must be numeric" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.editDistance = editDistance + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + +lunr.QueryParser.parseBoost = function (parser) { + var lexeme = parser.consumeLexeme() + + if (lexeme == undefined) { + return + } + + var boost = parseInt(lexeme.str, 10) + + if (isNaN(boost)) { + var errorMessage = "boost must be numeric" + throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) + } + + parser.currentClause.boost = boost + + var nextLexeme = parser.peekLexeme() + + if (nextLexeme == undefined) { + parser.nextClause() + return + } + + switch (nextLexeme.type) { + case lunr.QueryLexer.TERM: + parser.nextClause() + return lunr.QueryParser.parseTerm + case lunr.QueryLexer.FIELD: + parser.nextClause() + return lunr.QueryParser.parseField + case lunr.QueryLexer.EDIT_DISTANCE: + return lunr.QueryParser.parseEditDistance + case lunr.QueryLexer.BOOST: + return lunr.QueryParser.parseBoost + case lunr.QueryLexer.PRESENCE: + parser.nextClause() + return lunr.QueryParser.parsePresence + default: + var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" + throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) + } +} + + /** + * export the module via AMD, CommonJS or as a browser global + * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js + */ + ;(function (root, factory) { + if (typeof define === 'function' && define.amd) { + // AMD. Register as an anonymous module. + define(factory) + } else if (typeof exports === 'object') { + /** + * Node. Does not work with strict CommonJS, but + * only CommonJS-like environments that support module.exports, + * like Node. + */ + module.exports = factory() + } else { + // Browser globals (root is window) + root.lunr = factory() + } + }(this, function () { + /** + * Just return a value to define the module export. + * This example returns an object, but the module + * can return a function as the exported value. + */ + return lunr + })) +})(); diff --git a/site/search/main.js b/site/search/main.js new file mode 100644 index 0000000..a5e469d --- /dev/null +++ b/site/search/main.js @@ -0,0 +1,109 @@ +function getSearchTermFromLocation() { + var sPageURL = window.location.search.substring(1); + var sURLVariables = sPageURL.split('&'); + for (var i = 0; i < sURLVariables.length; i++) { + var sParameterName = sURLVariables[i].split('='); + if (sParameterName[0] == 'q') { + return decodeURIComponent(sParameterName[1].replace(/\+/g, '%20')); + } + } +} + +function joinUrl (base, path) { + if (path.substring(0, 1) === "/") { + // path starts with `/`. Thus it is absolute. + return path; + } + if (base.substring(base.length-1) === "/") { + // base ends with `/` + return base + path; + } + return base + "/" + path; +} + +function escapeHtml (value) { + return value.replace(/&/g, '&') + .replace(/"/g, '"') + .replace(//g, '>'); +} + +function formatResult (location, title, summary) { + return ''; +} + +function displayResults (results) { + var search_results = document.getElementById("mkdocs-search-results"); + while (search_results.firstChild) { + search_results.removeChild(search_results.firstChild); + } + if (results.length > 0){ + for (var i=0; i < results.length; i++){ + var result = results[i]; + var html = formatResult(result.location, result.title, result.summary); + search_results.insertAdjacentHTML('beforeend', html); + } + } else { + var noResultsText = search_results.getAttribute('data-no-results-text'); + if (!noResultsText) { + noResultsText = "No results found"; + } + search_results.insertAdjacentHTML('beforeend', '

' + noResultsText + '

'); + } +} + +function doSearch () { + var query = document.getElementById('mkdocs-search-query').value; + if (query.length > min_search_length) { + if (!window.Worker) { + displayResults(search(query)); + } else { + searchWorker.postMessage({query: query}); + } + } else { + // Clear results for short queries + displayResults([]); + } +} + +function initSearch () { + var search_input = document.getElementById('mkdocs-search-query'); + if (search_input) { + search_input.addEventListener("keyup", doSearch); + } + var term = getSearchTermFromLocation(); + if (term) { + search_input.value = term; + doSearch(); + } +} + +function onWorkerMessage (e) { + if (e.data.allowSearch) { + initSearch(); + } else if (e.data.results) { + var results = e.data.results; + displayResults(results); + } else if (e.data.config) { + min_search_length = e.data.config.min_search_length-1; + } +} + +if (!window.Worker) { + console.log('Web Worker API not supported'); + // load index in main thread + $.getScript(joinUrl(base_url, "search/worker.js")).done(function () { + console.log('Loaded worker'); + init(); + window.postMessage = function (msg) { + onWorkerMessage({data: msg}); + }; + }).fail(function (jqxhr, settings, exception) { + console.error('Could not load worker.js'); + }); +} else { + // Wrap search in a web worker + var searchWorker = new Worker(joinUrl(base_url, "search/worker.js")); + searchWorker.postMessage({init: true}); + searchWorker.onmessage = onWorkerMessage; +} diff --git a/site/search/search_index.json b/site/search/search_index.json new file mode 100644 index 0000000..8f1ff51 --- /dev/null +++ b/site/search/search_index.json @@ -0,0 +1 @@ +{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"SSDraw SSDraw is a program that generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. SSDraw also has a colab notebook available (only usable for Chrome). The notebook can be accessed here .","title":"Home"},{"location":"#ssdraw","text":"SSDraw is a program that generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. SSDraw also has a colab notebook available (only usable for Chrome). The notebook can be accessed here .","title":"SSDraw"},{"location":"getting-started/","text":"Installation The easiest way to install SSDraw is via pip: pip install SSDraw You can find the package on PyPi here .","title":"Getting Started"},{"location":"getting-started/#installation","text":"The easiest way to install SSDraw is via pip: pip install SSDraw You can find the package on PyPi here .","title":"Installation"},{"location":"commands/multi/","text":"SSDraw multi Command This section documents the ssdraw multi command. usage: generate_docs.py multi [-h] -i INPUT -o OUTPUT options: -h, --help show this help message and exit -i, --input INPUT Name of input script -o, --output OUTPUT Name of output directory","title":"multi"},{"location":"commands/multi/#ssdraw-multi-command","text":"This section documents the ssdraw multi command. usage: generate_docs.py multi [-h] -i INPUT -o OUTPUT options: -h, --help show this help message and exit -i, --input INPUT Name of input script -o, --output OUTPUT Name of output directory","title":"SSDraw multi Command"},{"location":"commands/single/","text":"SSDraw single Command This section documents the ssdraw single command. usage: generate_docs.py single [-h] [-f FASTA] [-p PDB] [-n NAME] [-o OUTPUT] [--SS SS] [--chain_id CHAIN_ID] [--color_map [COLOR_MAP ...]] [--scoring_file SCORING_FILE] [--color COLOR] [-conservation_score] [--output_file_type OUTPUT_FILE_TYPE] [-bfactor] [-mview] [--dpi DPI] [--ticks TICKS] [--start START] [--end END] [--dssp_exe DSSP_EXE] [--consurf CONSURF] [--fontsize FONTSIZE] [--fontcolor FONTCOLOR] options: -h, --help show this help message and exit -f, --fasta FASTA (required) sequence/alignment file in fasta format -p, --pdb PDB (required) pdb file -n, --name NAME (required) id of the protein in the alignment file -o, --output OUTPUT (required) name for output file --SS SS secondary structure annotation in DSSP or .horiz format. If this option is not provided, SSDraw will compute secondary structure from the given PDB file with DSSP. --chain_id CHAIN_ID chain id to use in pdb. Defaults to chain A. --color_map [COLOR_MAP ...] color map to use for heat map --scoring_file SCORING_FILE custom scoring file for alignment --color COLOR color for the image. Can be a color name (eg. white, black, green), or a hex code -conservation_score score alignment by conservation score --output_file_type OUTPUT_FILE_TYPE output file type. Options: png, ps, eps, tif, svg -bfactor score by B-factor -mview color by mview color map --dpi DPI dpi to use for final plot --ticks TICKS set ticks at every nth position --start START --end END --dssp_exe DSSP_EXE The path to your dssp executable. Default: mkdssp --consurf CONSURF consurf or rate4site file to color image with. If rate4site file is given, SSDraw will convert raw scores to grades. --fontsize FONTSIZE font size for residue numbers --fontcolor FONTCOLOR font color for residue numbers","title":"single"},{"location":"commands/single/#ssdraw-single-command","text":"This section documents the ssdraw single command. usage: generate_docs.py single [-h] [-f FASTA] [-p PDB] [-n NAME] [-o OUTPUT] [--SS SS] [--chain_id CHAIN_ID] [--color_map [COLOR_MAP ...]] [--scoring_file SCORING_FILE] [--color COLOR] [-conservation_score] [--output_file_type OUTPUT_FILE_TYPE] [-bfactor] [-mview] [--dpi DPI] [--ticks TICKS] [--start START] [--end END] [--dssp_exe DSSP_EXE] [--consurf CONSURF] [--fontsize FONTSIZE] [--fontcolor FONTCOLOR] options: -h, --help show this help message and exit -f, --fasta FASTA (required) sequence/alignment file in fasta format -p, --pdb PDB (required) pdb file -n, --name NAME (required) id of the protein in the alignment file -o, --output OUTPUT (required) name for output file --SS SS secondary structure annotation in DSSP or .horiz format. If this option is not provided, SSDraw will compute secondary structure from the given PDB file with DSSP. --chain_id CHAIN_ID chain id to use in pdb. Defaults to chain A. --color_map [COLOR_MAP ...] color map to use for heat map --scoring_file SCORING_FILE custom scoring file for alignment --color COLOR color for the image. Can be a color name (eg. white, black, green), or a hex code -conservation_score score alignment by conservation score --output_file_type OUTPUT_FILE_TYPE output file type. Options: png, ps, eps, tif, svg -bfactor score by B-factor -mview color by mview color map --dpi DPI dpi to use for final plot --ticks TICKS set ticks at every nth position --start START --end END --dssp_exe DSSP_EXE The path to your dssp executable. Default: mkdssp --consurf CONSURF consurf or rate4site file to color image with. If rate4site file is given, SSDraw will convert raw scores to grades. --fontsize FONTSIZE font size for residue numbers --fontcolor FONTCOLOR font color for residue numbers","title":"SSDraw single Command"}]} \ No newline at end of file diff --git a/site/search/worker.js b/site/search/worker.js new file mode 100644 index 0000000..8628dbc --- /dev/null +++ b/site/search/worker.js @@ -0,0 +1,133 @@ +var base_path = 'function' === typeof importScripts ? '.' : '/search/'; +var allowSearch = false; +var index; +var documents = {}; +var lang = ['en']; +var data; + +function getScript(script, callback) { + console.log('Loading script: ' + script); + $.getScript(base_path + script).done(function () { + callback(); + }).fail(function (jqxhr, settings, exception) { + console.log('Error: ' + exception); + }); +} + +function getScriptsInOrder(scripts, callback) { + if (scripts.length === 0) { + callback(); + return; + } + getScript(scripts[0], function() { + getScriptsInOrder(scripts.slice(1), callback); + }); +} + +function loadScripts(urls, callback) { + if( 'function' === typeof importScripts ) { + importScripts.apply(null, urls); + callback(); + } else { + getScriptsInOrder(urls, callback); + } +} + +function onJSONLoaded () { + data = JSON.parse(this.responseText); + var scriptsToLoad = ['lunr.js']; + if (data.config && data.config.lang && data.config.lang.length) { + lang = data.config.lang; + } + if (lang.length > 1 || lang[0] !== "en") { + scriptsToLoad.push('lunr.stemmer.support.js'); + if (lang.length > 1) { + scriptsToLoad.push('lunr.multi.js'); + } + if (lang.includes("ja") || lang.includes("jp")) { + scriptsToLoad.push('tinyseg.js'); + } + for (var i=0; i < lang.length; i++) { + if (lang[i] != 'en') { + scriptsToLoad.push(['lunr', lang[i], 'js'].join('.')); + } + } + } + loadScripts(scriptsToLoad, onScriptsLoaded); +} + +function onScriptsLoaded () { + console.log('All search scripts loaded, building Lunr index...'); + if (data.config && data.config.separator && data.config.separator.length) { + lunr.tokenizer.separator = new RegExp(data.config.separator); + } + + if (data.index) { + index = lunr.Index.load(data.index); + data.docs.forEach(function (doc) { + documents[doc.location] = doc; + }); + console.log('Lunr pre-built index loaded, search ready'); + } else { + index = lunr(function () { + if (lang.length === 1 && lang[0] !== "en" && lunr[lang[0]]) { + this.use(lunr[lang[0]]); + } else if (lang.length > 1) { + this.use(lunr.multiLanguage.apply(null, lang)); // spread operator not supported in all browsers: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Spread_operator#Browser_compatibility + } + this.field('title'); + this.field('text'); + this.ref('location'); + + for (var i=0; i < data.docs.length; i++) { + var doc = data.docs[i]; + this.add(doc); + documents[doc.location] = doc; + } + }); + console.log('Lunr index built, search ready'); + } + allowSearch = true; + postMessage({config: data.config}); + postMessage({allowSearch: allowSearch}); +} + +function init () { + var oReq = new XMLHttpRequest(); + oReq.addEventListener("load", onJSONLoaded); + var index_path = base_path + '/search_index.json'; + if( 'function' === typeof importScripts ){ + index_path = 'search_index.json'; + } + oReq.open("GET", index_path); + oReq.send(); +} + +function search (query) { + if (!allowSearch) { + console.error('Assets for search still loading'); + return; + } + + var resultDocuments = []; + var results = index.search(query); + for (var i=0; i < results.length; i++){ + var result = results[i]; + doc = documents[result.ref]; + doc.summary = doc.text.substring(0, 200); + resultDocuments.push(doc); + } + return resultDocuments; +} + +if( 'function' === typeof importScripts ) { + onmessage = function (e) { + if (e.data.init) { + init(); + } else if (e.data.query) { + postMessage({ results: search(e.data.query) }); + } else { + console.error("Worker - Unrecognized message: " + e); + } + }; +} diff --git a/site/sitemap.xml b/site/sitemap.xml new file mode 100644 index 0000000..0f8724e --- /dev/null +++ b/site/sitemap.xml @@ -0,0 +1,3 @@ + + + \ No newline at end of file diff --git a/site/sitemap.xml.gz b/site/sitemap.xml.gz new file mode 100644 index 0000000..7d10608 Binary files /dev/null and b/site/sitemap.xml.gz differ diff --git a/ssdraw.yml b/ssdraw.yml deleted file mode 100644 index 4975420..0000000 --- a/ssdraw.yml +++ /dev/null @@ -1,16 +0,0 @@ -name: ssdraw_venv - -channels: - - salilab - -dependencies: - - python=3.10 - - pip=23.0 - - dssp=2.2.1 - - pip: - - biopython==1.81 - - numpy==1.24 - - matplotlib==3.7 - - torch==2.0.1 - - pydssp - - nomkl