404
+ +Page not found
+ + +'+ escapeHtml(title) + '
' + escapeHtml(summary) +'
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ font
+Default fonts: times_new_roman, arial, courier_new, akrobat_bold, xkcd_regular, akrobat_regular, helvetica_bold, helvetica_light, helvetica_regular, roboto_bold, roboto_medium, roboto_regular, roboto_slab_bold, roboto_slab_light, roboto_slab_regular.
+function list_fonts()
+Get all fonts.
+function get_font(font_name: str) -> DataFrame
+from plotnineseqsuite import get_font
+f_df = get_font(font_name='times_new_roman')
+Gets the specified font.
+font_name
+Name of one of the default fonts.
+ +
+
+
+
+ « Previous
+
+
+ Next »
+
+
+
+
+
+
+
+
+
+
+
diff --git a/site/fonts.png b/site/fonts.png
new file mode 100644
index 0000000..519e7e3
Binary files /dev/null and b/site/fonts.png differ
diff --git a/site/geom_alignedSeq/index.html b/site/geom_alignedSeq/index.html
new file mode 100644
index 0000000..409a3a5
--- /dev/null
+++ b/site/geom_alignedSeq/index.html
@@ -0,0 +1,202 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ geom_alignedSeq
+A class that represents the sequence alignment diagram
+class geom_alignedSeq(self,data: Union[list[str], dict, None] = None,seq_names: Optional[list[str]] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,font_col: str = '#FFFFFF',bg_col_scheme: Union[DataFrame, str] = 'AUTO',bg_low_col: str = 'black',bg_high_col: str = 'yellow',bg_na_col: str = '#333333',**kwargs: Any)
+from plotnine import ggplot, coord_fixed
+from plotnineseqsuite import geom_alignedSeq, theme_seq
+from plotnineseqsuite.data import seqs_dna
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed()
+data
+Sequence data or corresponding dict.
+seq_names
+The name corresponding to the sequence data.
+seq_type
+OTHER, AA, DNA, RNA
+namespace
+The letter corresponding to the data.
+font
+Font value
+stack_width
+The ratio of the size of letters to the standard unit width.
+font_col
+The color of the font.
+bg_col_scheme
+Color scheme of the backgrounds.
+bg_low_col
+Continuous color schemes are available.
+bg_high_col
+Continuous color schemes are available.
+bg_na_col
+Used when the background in the corresponding namespace do not have a color matching value defined.
+kwargs
+Other arguments passed on to layer().
+ +
+
+
+
+ « Previous
+
+
+ Next »
+
+
+
+
+
+
+
+
+
+
+
diff --git a/site/geom_logo/index.html b/site/geom_logo/index.html
new file mode 100644
index 0000000..dc25020
--- /dev/null
+++ b/site/geom_logo/index.html
@@ -0,0 +1,202 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ geom_logo
+A class that represents the sequence logo
+class geom_logo(self,data: Union[list[str], ndarray, dict, None] = None,method: str = 'bits',seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.95,rev_stack_order: bool = False,col_scheme: Union[DataFrame, str] = 'AUTO',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any)
+from plotnine import ggplot
+from plotnineseqsuite import geom_logo, theme_seq
+from plotnineseqsuite.data import seqs_dna
+ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq()
+data
+Sequence data or PFM or corresponding dict.
+method
+bits, probability, custom
+seq_type
+OTHER, AA, DNA, RNA
+namespace
+The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray.
+font
+Font value
+stack_width
+The ratio of the size of letters to the standard unit width.
+rev_stack_order
+Order of letter stack is reversed.
+col_scheme
+Color scheme of the letters.
+low_col
+Continuous color schemes are available.
+high_col
+Continuous color schemes are available.
+na_col
+Used when the letters in the corresponding namespace do not have a color matching value defined.
+kwargs
+Other arguments passed on to layer().
+ +
+
+
+
+ « Previous
+
+
+ Next »
+
+
+
+
+
+
+
+
+
+
+
diff --git a/site/geom_seqBar/index.html b/site/geom_seqBar/index.html
new file mode 100644
index 0000000..4d45536
--- /dev/null
+++ b/site/geom_seqBar/index.html
@@ -0,0 +1,198 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ geom_seqBar
+A class that represents the sequence histogram
+class geom_seqBar(self,data: Union[list[str], ndarray, dict, None] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,bar_col_scheme: Union[DataFrame, str] = 'AUTO',font_col: str = '#808080',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any)
+from plotnine import ggplot
+from plotnineseqsuite import geom_seqBar, theme_seq
+from plotnineseqsuite.data import seqs_dna
+ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq()
+data
+Sequence data or PFM or corresponding dict.
+seq_type
+OTHER, AA, DNA, RNA
+namespace
+The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray.
+font
+Font value
+stack_width
+The ratio of the size of letters and the width of bars to the standard unit width.
+bar_col_scheme
+Color scheme of the cylinder.
+font_col
+The color of the font.
+low_col
+Continuous color schemes are available.
+high_col
+Continuous color schemes are available.
+na_col
+Used when the letters in the corresponding namespace do not have a color matching value defined.
+kwargs
+Other arguments passed on to layer().
+ +
+
+
+
+ « Previous
+
+
+ Next »
+
+
+
+
+
+
+
+
+
+
+
diff --git a/site/img/favicon.ico b/site/img/favicon.ico
new file mode 100644
index 0000000..e85006a
Binary files /dev/null and b/site/img/favicon.ico differ
diff --git a/site/index.html b/site/index.html
new file mode 100644
index 0000000..917116a
--- /dev/null
+++ b/site/index.html
@@ -0,0 +1,416 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Getting Started
+Installation
+pip install plotnineseqsuite
Load sample data
+from plotnineseqsuite.data import seqs_dna, seqs_aa ,pfms_dna
+This loads three sample data sets:
+-
+
seqs_dna: dict of binding sites for 12 transcription factors obtained from FASTA files in JASPAR. The keys represent the JASPAR ID.
+pfms_dna: dict of position frequency matrices for four transcription factors obtained from JASPAR. The keys names represent the JASPAR ID.
+seqs_aa: dict of kinase-substrate phosphorylation sites obtained from Wagih et al. The keys represent the names of the kinases associated with the phosphosites.
+
Visualizing aligned sequences
+Plot an aligned sequences
+You can draw an aligned sequences using ggplot function, with geom_alignedSeq. Let’s try this on sequences for one of the transcription factors from JASPAR:
+from plotnine import ggplot, coord_fixed
+from plotnineseqsuite.align import geom_alignedSeq
+from plotnineseqsuite.theme import theme_seq
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed()
+
Accepted input formats
+geom_alignedSeq accepts two types of input, each described in detail below
+-
+
- list: a list of aligned sequences +
- dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list described above +
No background color
+When bg_col_scheme option is None, the picture has no background color.
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font_col='black', bg_col_scheme=None) + theme_seq() + coord_fixed()
+
No sequence letter
+When font option is None, the picture has only the background color.
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font=None) + theme_seq() + coord_fixed()
+
Tagging sequences
+You can set seq_names parameter to identify the name of the sequence.
+names=['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f']
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) + theme_seq() + coord_fixed()
+
Visualizing sequence logo
+Plot a sequence logo
+You can draw a sequence logos using ggplot function, with geom_logo. Let’s try this on sequences for one of the transcription factors from JASPAR:
+from plotnine import ggplot
+from plotnineseqsuite.logo import geom_logo
+from plotnineseqsuite.theme import theme_seq
+ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq()
+
Accepted input formats
+geom_logo accepts three types of input, each described in detail below
+-
+
- list: a list of aligned sequences +
- numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. +
- dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above +
The following generates a sequence logo using a position frequency matrix from the sample data
+ggplot() + geom_logo(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq()
+
Plotting methods
+geom_logo supports two sequence logo methods through the method options: ‘bits’ and ‘probability’. By default, the bits is used.
+ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'bits' ) + theme_seq()
+ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'probability' ) + theme_seq()
+
+
Custom-height logos
+If you have your own height metric for each letter, simply create a matrix where each cell is a the desired height, and set the method to custom. You can even have negative heights. Here’s a simple example:
+import numpy as np
+custom_mat = np.random.randn(4,5)
+ggplot() + geom_logo(custom_mat, method='custom', seq_type='DNA') + theme_seq()
+
Visualizing sequence histogram
+Plot a sequence histogram
+You can draw a conservation bar of aligned sequences using ggplot function, with geom_seqBar. Let’s try this on sequences for one of the transcription factors from JASPAR:
+from plotnineseqsuite.bar import geom_seqBar
+ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq()
+
Accepted input formats
+geom_seqBar accepts three types of input, each described in detail below
+-
+
- list: a list of aligned sequences +
- numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. +
- dict: It is used for plotting more than one sequence histogram at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above +
The following generates a sequence histogram using a position frequency matrix from the sample data
+ggplot() + geom_seqBar(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq()
+
No sequence letter
+When font option is None, the picture has only the bar.
+ggplot() + geom_seqBar(seqs_dna['MA0013.1'], font=None) + theme_seq()
+
Sequence types
+Preset alphabets
+Amino acids, DNA and RNA sequence types are all supported by geom_logo, geom_seqBar and geom_alignedSeq. By default, plotnineSeqSuite will try to guess your sequence type. You can explicitly set the sequence type through the seq_type option.
+Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data:
+ggplot() + geom_logo( seqs_aa['AKT1'], seq_type = 'AA' ) + theme_seq()
+
Custom alphabet
+If you want to define a custom alphabet you can do so by setting namespace with your desired custom alphabet. For example, lets say you wanted a sequence logo of zeros and ones:
+from plotnine.guides import guides
+seqs_numeric = list(map(lambda x: x.replace('A','1').replace('T','2').replace('G','3').replace('C','4'), seqs_dna['MA0001.1']))
+ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['1','2','3','4']) + theme_seq()+guides(fill=False)
+
+Greek letters are also supported:
seqs_numeric = list(map(lambda x: x.replace('A','δ').replace('T','ε').replace('G','ψ').replace('C','λ'), seqs_dna['MA0001.1']))
+ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['δ','ε','ψ','λ']) + theme_seq()+guides(fill=False)
+
Colour schemes
+Preset color schemes
+plotnineSeqSuite has preset color schemes that can be set using the col_scheme parameter in geom_logo, the parameter bar_col_scheme in geom_seqBar and the parameter bg_col_scheme in geom_alignedSeq. By default, the col_scheme is set to AUTO such that the color scheme is automatically chosen based on your sequence type.
+Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data:
+ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme='base_pairing') + theme_seq()
+
Custom color schemes
+If the presets are not enough for you, you can define custom discrete or continuous color schemes using the col_schemes.make_col_scheme function. Here are two examples of discrete and continuous color schemes.
+Discrete color schemes
+from plotnineseqsuite.col_schemes import make_col_scheme
+cs1 = make_col_scheme(chars=['A', 'T', 'C', 'G'], groups=['gr1', 'gr1', 'gr2', 'gr2'],cols=['purple', 'purple', 'blue', 'blue'])
+ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs1) + theme_seq()
+
Continuous color schemes
+cs2 = make_col_scheme(chars=['A', 'T', 'C', 'G'], values=[1,2,3,4])
+ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs2) + theme_seq()
+
Multiple grouped sequences
+You can plot more than one grouped sequences at the same time with the help of facets. plotnineSeqSuite will accept a dict. The keys of the dict will be used as the facet titles. Take geom_logo for example.
+from plotnine import facet_wrap
+ggplot() + geom_logo(seqs_dna)+ theme_seq()+facet_wrap('~seq_group', ncol=4, scales='free_x')
+
Fonts
+You can adjust the font of letters by setting the font parameter. To list all the available color schemes use the font.list_fonts function. Take geom_logo for example.
+from plotnine import ggtitle
+import patchworklib as pw
+from plotnineseqsuite.font import list_fonts
+
+fonts = list_fonts()
+for i in range(0,12,3):
+ g1 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i]) + theme_seq()+ggtitle(fonts[i]))
+ g2 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+1]) + theme_seq() + ggtitle(fonts[i+1]))
+ g3 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+2]) + theme_seq() + ggtitle(fonts[i+2]))
+ if i == 0:
+ allgg = g1|g2|g3
+ else:
+ temp = g1|g2|g3
+ allgg = temp/allgg
+allgg.savefig()
+
Advanced plotnineSeqSuite
+plotnineSeqSuite is based on object-oriented design. The *_data property of class geom_logo and geom_seqBar, geom_alignedSeq is a core feature.
+Combining plots
+Without using any packages like patchwork and cowplot, plotnineSeqSuite can easily plot geom_logo and geom_seqBar, geom_alignedSeq in one figure. I’ll demonstrate with an example plotting probability sequence logo, aligned sequences and sequence histogram in one figure via changed *_data property.
+from plotnine import scale_y_continuous
+names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f']
+seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names)
+logo = geom_logo(seqs_dna['MA0013.1'], method='probability')
+logo.data['y'] = logo.data['y']+6.1
+bar = geom_seqBar(seqs_dna['MA0013.1'], font=None)
+bar.bar_data['y'] = bar.bar_data['y'] - 6.1
+ggplot() + logo + bar + seqs + theme_seq() + scale_y_continuous(breaks=lambda x: [k + 0.5 for k in range(0, len(names))], labels=names)
+
Modify the starting position
+When the input sequence fragment does not start at 1, you can modify the x value of the property to display the correct starting position.
+names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f']
+seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names)
+seqs.bg_data['x'] = seqs.bg_data['x']+3333
+seqs.letter_data['x'] = seqs.letter_data['x']+3333
+ggplot() + seqs + theme_seq()
+
Used concurrently with other functions of plotnine.
+Because plotnineSeqSuite is an extension of plotnine, functions of plotnine can be used without obstacles. Here is an example of drawing rectangles, lines and text.
+from plotnine.geoms import annotate
+ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + annotate('rect', xmin=0.5, xmax=3.5, ymin=-0.05, ymax=6.1,alpha=.1, color='black') + theme_seq()
+
ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + annotate('segment', x=1.5, xend=2.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=4.5, xend=7.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=8.5, xend=11.5, y=0, yend=0,size=2, color='red') + annotate('text', x=6, y=-0.2,label='A is the most', color='red') + theme_seq()
+
+
+
+
+
+ Next »
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/site/index.pdf b/site/index.pdf
new file mode 100644
index 0000000..583e9c3
Binary files /dev/null and b/site/index.pdf differ
diff --git a/site/js/html5shiv.min.js b/site/js/html5shiv.min.js
new file mode 100644
index 0000000..1a01c94
--- /dev/null
+++ b/site/js/html5shiv.min.js
@@ -0,0 +1,4 @@
+/**
+* @preserve HTML5 Shiv 3.7.3 | @afarkas @jdalton @jon_neal @rem | MIT/GPL2 Licensed
+*/
+!function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return c.innerHTML="x",d.insertBefore(c.lastChild,d.firstChild)}function d(){var a=t.elements;return"string"==typeof a?a.split(" "):a}function e(a,b){var c=t.elements;"string"!=typeof c&&(c=c.join(" ")),"string"!=typeof a&&(a=a.join(" ")),t.elements=c+" "+a,j(b)}function f(a){var b=s[a[q]];return b||(b={},r++,a[q]=r,s[r]=b),b}function g(a,c,d){if(c||(c=b),l)return c.createElement(a);d||(d=f(c));var e;return e=d.cache[a]?d.cache[a].cloneNode():p.test(a)?(d.cache[a]=d.createElem(a)).cloneNode():d.createElem(a),!e.canHaveChildren||o.test(a)||e.tagUrn?e:d.frag.appendChild(e)}function h(a,c){if(a||(a=b),l)return a.createDocumentFragment();c=c||f(a);for(var e=c.frag.cloneNode(),g=0,h=d(),i=h.length;i>g;g++)e.createElement(h[g]);return e}function i(a,b){b.cache||(b.cache={},b.createElem=a.createElement,b.createFrag=a.createDocumentFragment,b.frag=b.createFrag()),a.createElement=function(c){return t.shivMethods?g(c,a,b):b.createElem(c)},a.createDocumentFragment=Function("h,f","return function(){var n=f.cloneNode(),c=n.createElement;h.shivMethods&&("+d().join().replace(/[\w\-:]+/g,function(a){return b.createElem(a),b.frag.createElement(a),'c("'+a+'")'})+");return n}")(t,b.frag)}function j(a){a||(a=b);var d=f(a);return!t.shivCSS||k||d.hasCSS||(d.hasCSS=!!c(a,"article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}mark{background:#FF0;color:#000}template{display:none}")),l||i(a,d),a}var k,l,m="3.7.3",n=a.html5||{},o=/^<|^(?:button|map|select|textarea|object|iframe|option|optgroup)$/i,p=/^(?:a|b|code|div|fieldset|h1|h2|h3|h4|h5|h6|i|label|li|ol|p|q|span|strong|style|table|tbody|td|th|tr|ul)$/i,q="_html5shiv",r=0,s={};!function(){try{var a=b.createElement("a");a.innerHTML="
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Search Results
+ + + +
+ Searching...
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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' + 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..94ea4c2 --- /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":"Getting Started Installation pip install plotnineseqsuite Load sample data from plotnineseqsuite.data import seqs_dna, seqs_aa ,pfms_dna This loads three sample data sets: seqs_dna : dict of binding sites for 12 transcription factors obtained from FASTA files in JASPAR . The keys represent the JASPAR ID. pfms_dna : dict of position frequency matrices for four transcription factors obtained from JASPAR . The keys names represent the JASPAR ID. seqs_aa : dict of kinase-substrate phosphorylation sites obtained from Wagih et al. The keys represent the names of the kinases associated with the phosphosites. Visualizing aligned sequences Plot an aligned sequences You can draw an aligned sequences using ggplot function, with geom_alignedSeq. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnine import ggplot, coord_fixed from plotnineseqsuite.align import geom_alignedSeq from plotnineseqsuite.theme import theme_seq ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed() Accepted input formats geom_alignedSeq accepts two types of input, each described in detail below list: a list of aligned sequences dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list described above No background color When bg_col_scheme option is None, the picture has no background color. ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font_col='black', bg_col_scheme=None) + theme_seq() + coord_fixed() No sequence letter When font option is None, the picture has only the background color. ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font=None) + theme_seq() + coord_fixed() Tagging sequences You can set seq_names parameter to identify the name of the sequence. names=['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) + theme_seq() + coord_fixed() Visualizing sequence logo Plot a sequence logo You can draw a sequence logos using ggplot function, with geom_logo. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnine import ggplot from plotnineseqsuite.logo import geom_logo from plotnineseqsuite.theme import theme_seq ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq() Accepted input formats geom_logo accepts three types of input, each described in detail below list: a list of aligned sequences numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above The following generates a sequence logo using a position frequency matrix from the sample data ggplot() + geom_logo(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq() Plotting methods geom_logo supports two sequence logo methods through the method options: \u2018bits\u2019 and \u2018probability\u2019. By default, the bits is used. ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'bits' ) + theme_seq() ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'probability' ) + theme_seq() Custom-height logos If you have your own height metric for each letter, simply create a matrix where each cell is a the desired height, and set the method to custom. You can even have negative heights. Here\u2019s a simple example: import numpy as np custom_mat = np.random.randn(4,5) ggplot() + geom_logo(custom_mat, method='custom', seq_type='DNA') + theme_seq() Visualizing sequence histogram Plot a sequence histogram You can draw a conservation bar of aligned sequences using ggplot function, with geom_seqBar. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnineseqsuite.bar import geom_seqBar ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq() Accepted input formats geom_seqBar accepts three types of input, each described in detail below list: a list of aligned sequences numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. dict: It is used for plotting more than one sequence histogram at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above The following generates a sequence histogram using a position frequency matrix from the sample data ggplot() + geom_seqBar(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq() No sequence letter When font option is None, the picture has only the bar. ggplot() + geom_seqBar(seqs_dna['MA0013.1'], font=None) + theme_seq() Sequence types Preset alphabets Amino acids, DNA and RNA sequence types are all supported by geom_logo, geom_seqBar and geom_alignedSeq. By default, plotnineSeqSuite will try to guess your sequence type. You can explicitly set the sequence type through the seq_type option. Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data: ggplot() + geom_logo( seqs_aa['AKT1'], seq_type = 'AA' ) + theme_seq() Custom alphabet If you want to define a custom alphabet you can do so by setting namespace with your desired custom alphabet. For example, lets say you wanted a sequence logo of zeros and ones: from plotnine.guides import guides seqs_numeric = list(map(lambda x: x.replace('A','1').replace('T','2').replace('G','3').replace('C','4'), seqs_dna['MA0001.1'])) ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['1','2','3','4']) + theme_seq()+guides(fill=False) Greek letters are also supported: seqs_numeric = list(map(lambda x: x.replace('A','\u03b4').replace('T','\u03b5').replace('G','\u03c8').replace('C','\u03bb'), seqs_dna['MA0001.1'])) ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['\u03b4','\u03b5','\u03c8','\u03bb']) + theme_seq()+guides(fill=False) Colour schemes Preset color schemes plotnineSeqSuite has preset color schemes that can be set using the col_scheme parameter in geom_logo, the parameter bar_col_scheme in geom_seqBar and the parameter bg_col_scheme in geom_alignedSeq. By default, the col_scheme is set to AUTO such that the color scheme is automatically chosen based on your sequence type. Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data: ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme='base_pairing') + theme_seq() Custom color schemes If the presets are not enough for you, you can define custom discrete or continuous color schemes using the col_schemes.make_col_scheme function. Here are two examples of discrete and continuous color schemes. Discrete color schemes from plotnineseqsuite.col_schemes import make_col_scheme cs1 = make_col_scheme(chars=['A', 'T', 'C', 'G'], groups=['gr1', 'gr1', 'gr2', 'gr2'],cols=['purple', 'purple', 'blue', 'blue']) ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs1) + theme_seq() Continuous color schemes cs2 = make_col_scheme(chars=['A', 'T', 'C', 'G'], values=[1,2,3,4]) ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs2) + theme_seq() Multiple grouped sequences You can plot more than one grouped sequences at the same time with the help of facets. plotnineSeqSuite will accept a dict. The keys of the dict will be used as the facet titles. Take geom_logo for example. from plotnine import facet_wrap ggplot() + geom_logo(seqs_dna)+ theme_seq()+facet_wrap('~seq_group', ncol=4, scales='free_x') Fonts You can adjust the font of letters by setting the font parameter. To list all the available color schemes use the font.list_fonts function. Take geom_logo for example. from plotnine import ggtitle import patchworklib as pw from plotnineseqsuite.font import list_fonts fonts = list_fonts() for i in range(0,12,3): g1 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i]) + theme_seq()+ggtitle(fonts[i])) g2 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+1]) + theme_seq() + ggtitle(fonts[i+1])) g3 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+2]) + theme_seq() + ggtitle(fonts[i+2])) if i == 0: allgg = g1|g2|g3 else: temp = g1|g2|g3 allgg = temp/allgg allgg.savefig() Advanced plotnineSeqSuite plotnineSeqSuite is based on object-oriented design. The *_data property of class geom_logo and geom_seqBar, geom_alignedSeq is a core feature. Combining plots Without using any packages like patchwork and cowplot, plotnineSeqSuite can easily plot geom_logo and geom_seqBar, geom_alignedSeq in one figure. I\u2019ll demonstrate with an example plotting probability sequence logo, aligned sequences and sequence histogram in one figure via changed *_data property. from plotnine import scale_y_continuous names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) logo = geom_logo(seqs_dna['MA0013.1'], method='probability') logo.data['y'] = logo.data['y']+6.1 bar = geom_seqBar(seqs_dna['MA0013.1'], font=None) bar.bar_data['y'] = bar.bar_data['y'] - 6.1 ggplot() + logo + bar + seqs + theme_seq() + scale_y_continuous(breaks=lambda x: [k + 0.5 for k in range(0, len(names))], labels=names) Modify the starting position When the input sequence fragment does not start at 1, you can modify the x value of the property to display the correct starting position. names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) seqs.bg_data['x'] = seqs.bg_data['x']+3333 seqs.letter_data['x'] = seqs.letter_data['x']+3333 ggplot() + seqs + theme_seq() Used concurrently with other functions of plotnine. Because plotnineSeqSuite is an extension of plotnine, functions of plotnine can be used without obstacles. Here is an example of drawing rectangles, lines and text. from plotnine.geoms import annotate ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + annotate('rect', xmin=0.5, xmax=3.5, ymin=-0.05, ymax=6.1,alpha=.1, color='black') + theme_seq() ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + annotate('segment', x=1.5, xend=2.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=4.5, xend=7.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=8.5, xend=11.5, y=0, yend=0,size=2, color='red') + annotate('text', x=6, y=-0.2,label='A is the most', color='red') + theme_seq()","title":"Getting Started"},{"location":"#getting-started","text":"","title":"Getting Started"},{"location":"#installation","text":"pip install plotnineseqsuite","title":"Installation"},{"location":"#load-sample-data","text":"from plotnineseqsuite.data import seqs_dna, seqs_aa ,pfms_dna This loads three sample data sets: seqs_dna : dict of binding sites for 12 transcription factors obtained from FASTA files in JASPAR . The keys represent the JASPAR ID. pfms_dna : dict of position frequency matrices for four transcription factors obtained from JASPAR . The keys names represent the JASPAR ID. seqs_aa : dict of kinase-substrate phosphorylation sites obtained from Wagih et al. The keys represent the names of the kinases associated with the phosphosites.","title":"Load sample data"},{"location":"#visualizing-aligned-sequences","text":"","title":"Visualizing aligned sequences"},{"location":"#plot-an-aligned-sequences","text":"You can draw an aligned sequences using ggplot function, with geom_alignedSeq. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnine import ggplot, coord_fixed from plotnineseqsuite.align import geom_alignedSeq from plotnineseqsuite.theme import theme_seq ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed()","title":"Plot an aligned sequences"},{"location":"#accepted-input-formats","text":"geom_alignedSeq accepts two types of input, each described in detail below list: a list of aligned sequences dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list described above","title":"Accepted input formats"},{"location":"#no-background-color","text":"When bg_col_scheme option is None, the picture has no background color. ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font_col='black', bg_col_scheme=None) + theme_seq() + coord_fixed()","title":"No background color"},{"location":"#no-sequence-letter","text":"When font option is None, the picture has only the background color. ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], font=None) + theme_seq() + coord_fixed()","title":"No sequence letter"},{"location":"#tagging-sequences","text":"You can set seq_names parameter to identify the name of the sequence. names=['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] ggplot() + geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) + theme_seq() + coord_fixed()","title":"Tagging sequences"},{"location":"#visualizing-sequence-logo","text":"","title":"Visualizing sequence logo"},{"location":"#plot-a-sequence-logo","text":"You can draw a sequence logos using ggplot function, with geom_logo. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnine import ggplot from plotnineseqsuite.logo import geom_logo from plotnineseqsuite.theme import theme_seq ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq()","title":"Plot a sequence logo"},{"location":"#accepted-input-formats_1","text":"geom_logo accepts three types of input, each described in detail below list: a list of aligned sequences numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. dict: It is used for plotting more than one sequence logo at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above The following generates a sequence logo using a position frequency matrix from the sample data ggplot() + geom_logo(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq()","title":"Accepted input formats"},{"location":"#plotting-methods","text":"geom_logo supports two sequence logo methods through the method options: \u2018bits\u2019 and \u2018probability\u2019. By default, the bits is used. ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'bits' ) + theme_seq() ggplot() + geom_logo( seqs_dna['MA0001.1'], method = 'probability' ) + theme_seq()","title":"Plotting methods"},{"location":"#custom-height-logos","text":"If you have your own height metric for each letter, simply create a matrix where each cell is a the desired height, and set the method to custom. You can even have negative heights. Here\u2019s a simple example: import numpy as np custom_mat = np.random.randn(4,5) ggplot() + geom_logo(custom_mat, method='custom', seq_type='DNA') + theme_seq()","title":"Custom-height logos"},{"location":"#visualizing-sequence-histogram","text":"","title":"Visualizing sequence histogram"},{"location":"#plot-a-sequence-histogram","text":"You can draw a conservation bar of aligned sequences using ggplot function, with geom_seqBar. Let\u2019s try this on sequences for one of the transcription factors from JASPAR: from plotnineseqsuite.bar import geom_seqBar ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq()","title":"Plot a sequence histogram"},{"location":"#accepted-input-formats_2","text":"geom_seqBar accepts three types of input, each described in detail below list: a list of aligned sequences numpy.ndarray: a position frequency matrix, where the row is the letter, and column is the position. Note: The order of the rows corresponds to the NAMESPACE one by one. dict: It is used for plotting more than one sequence histogram at the same time with the help of facets, the key of dict is facet value, and the value of dict is list or numpy.ndarray described above The following generates a sequence histogram using a position frequency matrix from the sample data ggplot() + geom_seqBar(pfms_dna['MA0018.2'],seq_type='DNA') + theme_seq()","title":"Accepted input formats"},{"location":"#no-sequence-letter_1","text":"When font option is None, the picture has only the bar. ggplot() + geom_seqBar(seqs_dna['MA0013.1'], font=None) + theme_seq()","title":"No sequence letter"},{"location":"#sequence-types","text":"","title":"Sequence types"},{"location":"#preset-alphabets","text":"Amino acids, DNA and RNA sequence types are all supported by geom_logo, geom_seqBar and geom_alignedSeq. By default, plotnineSeqSuite will try to guess your sequence type. You can explicitly set the sequence type through the seq_type option. Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data: ggplot() + geom_logo( seqs_aa['AKT1'], seq_type = 'AA' ) + theme_seq()","title":"Preset alphabets"},{"location":"#custom-alphabet","text":"If you want to define a custom alphabet you can do so by setting namespace with your desired custom alphabet. For example, lets say you wanted a sequence logo of zeros and ones: from plotnine.guides import guides seqs_numeric = list(map(lambda x: x.replace('A','1').replace('T','2').replace('G','3').replace('C','4'), seqs_dna['MA0001.1'])) ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['1','2','3','4']) + theme_seq()+guides(fill=False) Greek letters are also supported: seqs_numeric = list(map(lambda x: x.replace('A','\u03b4').replace('T','\u03b5').replace('G','\u03c8').replace('C','\u03bb'), seqs_dna['MA0001.1'])) ggplot() + geom_logo(seqs_numeric, method='probability', namespace=['\u03b4','\u03b5','\u03c8','\u03bb']) + theme_seq()+guides(fill=False)","title":"Custom alphabet"},{"location":"#colour-schemes","text":"","title":"Colour schemes"},{"location":"#preset-color-schemes","text":"plotnineSeqSuite has preset color schemes that can be set using the col_scheme parameter in geom_logo, the parameter bar_col_scheme in geom_seqBar and the parameter bg_col_scheme in geom_alignedSeq. By default, the col_scheme is set to AUTO such that the color scheme is automatically chosen based on your sequence type. Lets try generate an amino acid sequence logo using kinase-substrate phosphorylation data: ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme='base_pairing') + theme_seq()","title":"Preset color schemes"},{"location":"#custom-color-schemes","text":"If the presets are not enough for you, you can define custom discrete or continuous color schemes using the col_schemes.make_col_scheme function. Here are two examples of discrete and continuous color schemes.","title":"Custom color schemes"},{"location":"#discrete-color-schemes","text":"from plotnineseqsuite.col_schemes import make_col_scheme cs1 = make_col_scheme(chars=['A', 'T', 'C', 'G'], groups=['gr1', 'gr1', 'gr2', 'gr2'],cols=['purple', 'purple', 'blue', 'blue']) ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs1) + theme_seq()","title":"Discrete color schemes"},{"location":"#continuous-color-schemes","text":"cs2 = make_col_scheme(chars=['A', 'T', 'C', 'G'], values=[1,2,3,4]) ggplot() + geom_logo(seqs_dna['MA0001.1'], col_scheme=cs2) + theme_seq()","title":"Continuous color schemes"},{"location":"#multiple-grouped-sequences","text":"You can plot more than one grouped sequences at the same time with the help of facets. plotnineSeqSuite will accept a dict. The keys of the dict will be used as the facet titles. Take geom_logo for example. from plotnine import facet_wrap ggplot() + geom_logo(seqs_dna)+ theme_seq()+facet_wrap('~seq_group', ncol=4, scales='free_x')","title":"Multiple grouped sequences"},{"location":"#fonts","text":"You can adjust the font of letters by setting the font parameter. To list all the available color schemes use the font.list_fonts function. Take geom_logo for example. from plotnine import ggtitle import patchworklib as pw from plotnineseqsuite.font import list_fonts fonts = list_fonts() for i in range(0,12,3): g1 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i]) + theme_seq()+ggtitle(fonts[i])) g2 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+1]) + theme_seq() + ggtitle(fonts[i+1])) g3 = pw.load_ggplot(ggplot() + geom_logo(data=seqs_dna['MA0001.1'], font=fonts[i+2]) + theme_seq() + ggtitle(fonts[i+2])) if i == 0: allgg = g1|g2|g3 else: temp = g1|g2|g3 allgg = temp/allgg allgg.savefig()","title":"Fonts"},{"location":"#advanced-plotnineseqsuite","text":"plotnineSeqSuite is based on object-oriented design. The *_data property of class geom_logo and geom_seqBar, geom_alignedSeq is a core feature.","title":"Advanced plotnineSeqSuite"},{"location":"#combining-plots","text":"Without using any packages like patchwork and cowplot, plotnineSeqSuite can easily plot geom_logo and geom_seqBar, geom_alignedSeq in one figure. I\u2019ll demonstrate with an example plotting probability sequence logo, aligned sequences and sequence histogram in one figure via changed *_data property. from plotnine import scale_y_continuous names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) logo = geom_logo(seqs_dna['MA0013.1'], method='probability') logo.data['y'] = logo.data['y']+6.1 bar = geom_seqBar(seqs_dna['MA0013.1'], font=None) bar.bar_data['y'] = bar.bar_data['y'] - 6.1 ggplot() + logo + bar + seqs + theme_seq() + scale_y_continuous(breaks=lambda x: [k + 0.5 for k in range(0, len(names))], labels=names)","title":"Combining plots"},{"location":"#modify-the-starting-position","text":"When the input sequence fragment does not start at 1, you can modify the x value of the property to display the correct starting position. names = ['seq-a', 'seq-b', 'seq-c', 'seq-d', 'seq-e', 'seq-f'] seqs = geom_alignedSeq(seqs_dna['MA0013.1'], seq_names=names) seqs.bg_data['x'] = seqs.bg_data['x']+3333 seqs.letter_data['x'] = seqs.letter_data['x']+3333 ggplot() + seqs + theme_seq()","title":"Modify the starting position"},{"location":"#used-concurrently-with-other-functions-of-plotnine","text":"Because plotnineSeqSuite is an extension of plotnine, functions of plotnine can be used without obstacles. Here is an example of drawing rectangles, lines and text. from plotnine.geoms import annotate ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + annotate('rect', xmin=0.5, xmax=3.5, ymin=-0.05, ymax=6.1,alpha=.1, color='black') + theme_seq() ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + annotate('segment', x=1.5, xend=2.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=4.5, xend=7.5, y=0, yend=0, size=2, color='red') + annotate('segment', x=8.5, xend=11.5, y=0, yend=0,size=2, color='red') + annotate('text', x=6, y=-0.2,label='A is the most', color='red') + theme_seq()","title":"Used concurrently with other functions of plotnine."},{"location":"col_schemes/","text":"color schemes Default color schemes: chemistry, chemistry2, hydrophobicity, nucleotide, nucleotide2, base_pairing, clustalx, taylor. function make_col_scheme(name: str = 'Custom Scheme', chars: Optional[list[str]] = None, groups: Optional[list[int]] = None, cols: Optional[list[int]] = None, values: Optional[list[int]] = None) -> dict from plotnineseqsuite.col_schemes import make_col_scheme cs1 = make_col_scheme(chars=['A', 'T', 'C', 'G'], groups=['gr1', 'gr1', 'gr2', 'gr2'],cols=['purple', 'purple', 'blue', 'blue']) cs2 = make_col_scheme(chars=['A', 'T', 'C', 'G'], values=[1,2,3,4]) The function is used to create custom color style themes. name Name of custom scheme. It will display in legend. chars Letters will used to plot. groups Used in a custom discrete color scheme. It groups letters. cols Used in a custom discrete color scheme. It represents the RGB value of the grouped color. values Used in a custom continuous color scheme. It represents the numeric value of the corresponding letter. function get_col_scheme(col_scheme: str, seq_type: str = 'AUTO') -> dict This function is used to get the built-in color theme of the type of the given sequence. from plotnineseqsuite.col_schemes import get_col_scheme col_df = get_col_scheme(col_scheme='chemistry') col_scheme One of the default color schemes. seq_type AA or DNA or RNA","title":"color schemes"},{"location":"col_schemes/#color-schemes","text":"Default color schemes: chemistry, chemistry2, hydrophobicity, nucleotide, nucleotide2, base_pairing, clustalx, taylor.","title":"color schemes"},{"location":"col_schemes/#function-make_col_schemename-str-custom-scheme-chars-optionalliststr-none-groups-optionallistint-none-cols-optionallistint-none-values-optionallistint-none-dict","text":"from plotnineseqsuite.col_schemes import make_col_scheme cs1 = make_col_scheme(chars=['A', 'T', 'C', 'G'], groups=['gr1', 'gr1', 'gr2', 'gr2'],cols=['purple', 'purple', 'blue', 'blue']) cs2 = make_col_scheme(chars=['A', 'T', 'C', 'G'], values=[1,2,3,4]) The function is used to create custom color style themes.","title":"function make_col_scheme(name: str = 'Custom Scheme', chars: Optional[list[str]] = None, groups: Optional[list[int]] = None, cols: Optional[list[int]] = None, values: Optional[list[int]] = None) -> dict"},{"location":"col_schemes/#name","text":"Name of custom scheme. It will display in legend.","title":"name"},{"location":"col_schemes/#chars","text":"Letters will used to plot.","title":"chars"},{"location":"col_schemes/#groups","text":"Used in a custom discrete color scheme. It groups letters.","title":"groups"},{"location":"col_schemes/#cols","text":"Used in a custom discrete color scheme. It represents the RGB value of the grouped color.","title":"cols"},{"location":"col_schemes/#values","text":"Used in a custom continuous color scheme. It represents the numeric value of the corresponding letter.","title":"values"},{"location":"col_schemes/#function-get_col_schemecol_scheme-str-seq_type-str-auto-dict","text":"This function is used to get the built-in color theme of the type of the given sequence. from plotnineseqsuite.col_schemes import get_col_scheme col_df = get_col_scheme(col_scheme='chemistry')","title":"function get_col_scheme(col_scheme: str, seq_type: str = 'AUTO') -> dict"},{"location":"col_schemes/#col_scheme","text":"One of the default color schemes.","title":"col_scheme"},{"location":"col_schemes/#seq_type","text":"AA or DNA or RNA","title":"seq_type"},{"location":"font/","text":"font Default fonts: times_new_roman, arial, courier_new, akrobat_bold, xkcd_regular, akrobat_regular, helvetica_bold, helvetica_light, helvetica_regular, roboto_bold, roboto_medium, roboto_regular, roboto_slab_bold, roboto_slab_light, roboto_slab_regular. function list_fonts() Get all fonts. function get_font(font_name: str) -> DataFrame from plotnineseqsuite import get_font f_df = get_font(font_name='times_new_roman') Gets the specified font. font_name Name of one of the default fonts.","title":"font"},{"location":"font/#font","text":"Default fonts: times_new_roman, arial, courier_new, akrobat_bold, xkcd_regular, akrobat_regular, helvetica_bold, helvetica_light, helvetica_regular, roboto_bold, roboto_medium, roboto_regular, roboto_slab_bold, roboto_slab_light, roboto_slab_regular.","title":"font"},{"location":"font/#function-list_fonts","text":"Get all fonts.","title":"function list_fonts()"},{"location":"font/#function-get_fontfont_name-str-dataframe","text":"from plotnineseqsuite import get_font f_df = get_font(font_name='times_new_roman') Gets the specified font.","title":"function get_font(font_name: str) -> DataFrame"},{"location":"font/#font_name","text":"Name of one of the default fonts.","title":"font_name"},{"location":"geom_alignedSeq/","text":"geom_alignedSeq A class that represents the sequence alignment diagram class geom_alignedSeq(self,data: Union[list[str], dict, None] = None,seq_names: Optional[list[str]] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,font_col: str = '#FFFFFF',bg_col_scheme: Union[DataFrame, str] = 'AUTO',bg_low_col: str = 'black',bg_high_col: str = 'yellow',bg_na_col: str = '#333333',**kwargs: Any) from plotnine import ggplot, coord_fixed from plotnineseqsuite import geom_alignedSeq, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed() data Sequence data or corresponding dict. seq_names The name corresponding to the sequence data. seq_type OTHER, AA, DNA, RNA namespace The letter corresponding to the data. font Font value stack_width The ratio of the size of letters to the standard unit width. font_col The color of the font. bg_col_scheme Color scheme of the backgrounds. bg_low_col Continuous color schemes are available. bg_high_col Continuous color schemes are available. bg_na_col Used when the background in the corresponding namespace do not have a color matching value defined. kwargs Other arguments passed on to layer().","title":"geom_alignedSeq"},{"location":"geom_alignedSeq/#geom_alignedseq","text":"A class that represents the sequence alignment diagram","title":"geom_alignedSeq"},{"location":"geom_alignedSeq/#class-geom_alignedseqselfdata-unionliststr-dict-none-noneseq_names-optionalliststr-noneseq_type-str-autonamespace-optionalliststr-nonefont-str-roboto_mediumstack_width-float-075font_col-str-ffffffbg_col_scheme-uniondataframe-str-autobg_low_col-str-blackbg_high_col-str-yellowbg_na_col-str-333333kwargs-any","text":"from plotnine import ggplot, coord_fixed from plotnineseqsuite import geom_alignedSeq, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_alignedSeq(seqs_dna['MA0013.1']) + theme_seq() + coord_fixed()","title":"class geom_alignedSeq(self,data: Union[list[str], dict, None] = None,seq_names: Optional[list[str]] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,font_col: str = '#FFFFFF',bg_col_scheme: Union[DataFrame, str] = 'AUTO',bg_low_col: str = 'black',bg_high_col: str = 'yellow',bg_na_col: str = '#333333',**kwargs: Any)"},{"location":"geom_alignedSeq/#data","text":"Sequence data or corresponding dict.","title":"data"},{"location":"geom_alignedSeq/#seq_names","text":"The name corresponding to the sequence data.","title":"seq_names"},{"location":"geom_alignedSeq/#seq_type","text":"OTHER, AA, DNA, RNA","title":"seq_type"},{"location":"geom_alignedSeq/#namespace","text":"The letter corresponding to the data.","title":"namespace"},{"location":"geom_alignedSeq/#font","text":"Font value","title":"font"},{"location":"geom_alignedSeq/#stack_width","text":"The ratio of the size of letters to the standard unit width.","title":"stack_width"},{"location":"geom_alignedSeq/#font_col","text":"The color of the font.","title":"font_col"},{"location":"geom_alignedSeq/#bg_col_scheme","text":"Color scheme of the backgrounds.","title":"bg_col_scheme"},{"location":"geom_alignedSeq/#bg_low_col","text":"Continuous color schemes are available.","title":"bg_low_col"},{"location":"geom_alignedSeq/#bg_high_col","text":"Continuous color schemes are available.","title":"bg_high_col"},{"location":"geom_alignedSeq/#bg_na_col","text":"Used when the background in the corresponding namespace do not have a color matching value defined.","title":"bg_na_col"},{"location":"geom_alignedSeq/#kwargs","text":"Other arguments passed on to layer().","title":"kwargs"},{"location":"geom_logo/","text":"geom_logo A class that represents the sequence logo class geom_logo(self,data: Union[list[str], ndarray, dict, None] = None,method: str = 'bits',seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.95,rev_stack_order: bool = False,col_scheme: Union[DataFrame, str] = 'AUTO',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any) from plotnine import ggplot from plotnineseqsuite import geom_logo, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq() data Sequence data or PFM or corresponding dict. method bits, probability, custom seq_type OTHER, AA, DNA, RNA namespace The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray. font Font value stack_width The ratio of the size of letters to the standard unit width. rev_stack_order Order of letter stack is reversed. col_scheme Color scheme of the letters. low_col Continuous color schemes are available. high_col Continuous color schemes are available. na_col Used when the letters in the corresponding namespace do not have a color matching value defined. kwargs Other arguments passed on to layer().","title":"geom_logo"},{"location":"geom_logo/#geom_logo","text":"A class that represents the sequence logo","title":"geom_logo"},{"location":"geom_logo/#class-geom_logoselfdata-unionliststr-ndarray-dict-none-nonemethod-str-bitsseq_type-str-autonamespace-optionalliststr-nonefont-str-roboto_mediumstack_width-float-095rev_stack_order-bool-falsecol_scheme-uniondataframe-str-autolow_col-str-blackhigh_col-str-yellowna_col-str-333333kwargs-any","text":"from plotnine import ggplot from plotnineseqsuite import geom_logo, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_logo(seqs_dna['MA0001.1']) + theme_seq()","title":"class geom_logo(self,data: Union[list[str], ndarray, dict, None] = None,method: str = 'bits',seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.95,rev_stack_order: bool = False,col_scheme: Union[DataFrame, str] = 'AUTO',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any)"},{"location":"geom_logo/#data","text":"Sequence data or PFM or corresponding dict.","title":"data"},{"location":"geom_logo/#method","text":"bits, probability, custom","title":"method"},{"location":"geom_logo/#seq_type","text":"OTHER, AA, DNA, RNA","title":"seq_type"},{"location":"geom_logo/#namespace","text":"The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray.","title":"namespace"},{"location":"geom_logo/#font","text":"Font value","title":"font"},{"location":"geom_logo/#stack_width","text":"The ratio of the size of letters to the standard unit width.","title":"stack_width"},{"location":"geom_logo/#rev_stack_order","text":"Order of letter stack is reversed.","title":"rev_stack_order"},{"location":"geom_logo/#col_scheme","text":"Color scheme of the letters.","title":"col_scheme"},{"location":"geom_logo/#low_col","text":"Continuous color schemes are available.","title":"low_col"},{"location":"geom_logo/#high_col","text":"Continuous color schemes are available.","title":"high_col"},{"location":"geom_logo/#na_col","text":"Used when the letters in the corresponding namespace do not have a color matching value defined.","title":"na_col"},{"location":"geom_logo/#kwargs","text":"Other arguments passed on to layer().","title":"kwargs"},{"location":"geom_seqBar/","text":"geom_seqBar A class that represents the sequence histogram class geom_seqBar(self,data: Union[list[str], ndarray, dict, None] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,bar_col_scheme: Union[DataFrame, str] = 'AUTO',font_col: str = '#808080',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any) from plotnine import ggplot from plotnineseqsuite import geom_seqBar, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq() data Sequence data or PFM or corresponding dict. seq_type OTHER, AA, DNA, RNA namespace The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray. font Font value stack_width The ratio of the size of letters and the width of bars to the standard unit width. bar_col_scheme Color scheme of the cylinder. font_col The color of the font. low_col Continuous color schemes are available. high_col Continuous color schemes are available. na_col Used when the letters in the corresponding namespace do not have a color matching value defined. kwargs Other arguments passed on to layer().","title":"geom_seqBar"},{"location":"geom_seqBar/#geom_seqbar","text":"A class that represents the sequence histogram","title":"geom_seqBar"},{"location":"geom_seqBar/#class-geom_seqbarselfdata-unionliststr-ndarray-dict-none-noneseq_type-str-autonamespace-optionalliststr-nonefont-str-roboto_mediumstack_width-float-075bar_col_scheme-uniondataframe-str-autofont_col-str-808080low_col-str-blackhigh_col-str-yellowna_col-str-333333kwargs-any","text":"from plotnine import ggplot from plotnineseqsuite import geom_seqBar, theme_seq from plotnineseqsuite.data import seqs_dna ggplot() + geom_seqBar(seqs_dna['MA0013.1']) + theme_seq()","title":"class geom_seqBar(self,data: Union[list[str], ndarray, dict, None] = None,seq_type: str = 'AUTO',namespace: Optional[list[str]] = None,font: str = 'roboto_medium',stack_width: float = 0.75,bar_col_scheme: Union[DataFrame, str] = 'AUTO',font_col: str = '#808080',low_col: str = 'black',high_col: str = 'yellow',na_col: str = '#333333',**kwargs: Any)"},{"location":"geom_seqBar/#data","text":"Sequence data or PFM or corresponding dict.","title":"data"},{"location":"geom_seqBar/#seq_type","text":"OTHER, AA, DNA, RNA","title":"seq_type"},{"location":"geom_seqBar/#namespace","text":"The letter corresponding to the data. If the type of data is ndarray, the order of the namespaces must correspond to that of ndarray.","title":"namespace"},{"location":"geom_seqBar/#font","text":"Font value","title":"font"},{"location":"geom_seqBar/#stack_width","text":"The ratio of the size of letters and the width of bars to the standard unit width.","title":"stack_width"},{"location":"geom_seqBar/#bar_col_scheme","text":"Color scheme of the cylinder.","title":"bar_col_scheme"},{"location":"geom_seqBar/#font_col","text":"The color of the font.","title":"font_col"},{"location":"geom_seqBar/#low_col","text":"Continuous color schemes are available.","title":"low_col"},{"location":"geom_seqBar/#high_col","text":"Continuous color schemes are available.","title":"high_col"},{"location":"geom_seqBar/#na_col","text":"Used when the letters in the corresponding namespace do not have a color matching value defined.","title":"na_col"},{"location":"geom_seqBar/#kwargs","text":"Other arguments passed on to layer().","title":"kwargs"},{"location":"theme/","text":"theme function theme_seq() -> theme Default theme. Plain white background.","title":"theme"},{"location":"theme/#theme","text":"","title":"theme"},{"location":"theme/#function-theme_seq-theme","text":"Default theme. Plain white background.","title":"function theme_seq() -> theme"}]} \ 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..067e6dc --- /dev/null +++ b/site/sitemap.xml @@ -0,0 +1,38 @@ + +
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ theme
+function theme_seq() -> theme
+Default theme. Plain white background.
+ +
+
+
+
+ « Previous
+
+
+
+
+
+
+
+
+
+
+
+