From c98be0367de19451e8468c50545c687653bb6cda Mon Sep 17 00:00:00 2001 From: jefferis Date: Sat, 8 Jul 2023 08:28:16 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20natverse?= =?UTF-8?q?/coconat@c695b39b5e9684a7f59bd5faaa0363bf8f57a5f6=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pkgdown.yml | 2 +- reference/add_cluster_info.html | 127 ++++++++++++++++++++++++++++++++ reference/index.html | 5 ++ search.json | 2 +- sitemap.xml | 3 + 5 files changed, 137 insertions(+), 2 deletions(-) create mode 100644 reference/add_cluster_info.html diff --git a/pkgdown.yml b/pkgdown.yml index a23f1ad..1956dc6 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.0.7 pkgdown_sha: ~ articles: identifiers-and-datasets: identifiers-and-datasets.html -last_built: 2023-07-08T07:22Z +last_built: 2023-07-08T08:27Z urls: reference: https://natverse.org/coconat/reference article: https://natverse.org/coconat/articles diff --git a/reference/add_cluster_info.html b/reference/add_cluster_info.html new file mode 100644 index 0000000..ef82817 --- /dev/null +++ b/reference/add_cluster_info.html @@ -0,0 +1,127 @@ + +Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info • coconat + Skip to contents + + +
+
+
+ +
+

Add dataframe columns detailing ordering and groups from a dendrogram

+
+ +
+

Usage

+
add_cluster_info(
+  df,
+  dend,
+  h = NULL,
+  k = NULL,
+  colnames = NULL,
+  idcol = c("id", "root_id", "bodyid")
+)
+
+ +
+

Arguments

+
df
+

A dataframe e.g. as returned by coconatfly::cf_meta

+ + +
dend
+

A dendrogram or hclust object

+ + +
h
+

A height to cut the dendrogram

+ + +
k
+

A number of clusters to cut the dendrogram

+ + +
colnames
+

The names of the two new columns

+ + +
idcol
+

The name of the column containing id information. If you do not +provide this argument then the function will choose the first of three +default columns present in df (with a warning when >1 column +present).

+ +
+
+

Value

+ + +

A copy of df with one or two extra columns called

+

+

dendid and e.g. group_h2.

+
+ +
+ + +
+ + + +
+ + + + + + + diff --git a/reference/index.html b/reference/index.html index 9512753..44fad57 100644 --- a/reference/index.html +++ b/reference/index.html @@ -62,6 +62,11 @@

All functionsadd_cluster_info() + +
Add dataframe columns detailing ordering and groups from a dendrogram
+
+ cosine_sim()
Efficient calculation of cosine similarity for sparse or dense matrices
diff --git a/search.json b/search.json index 545e247..38ac2d7 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://natverse.org/coconat/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://natverse.org/coconat/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. General Public Licenses designed make sure freedom distribute copies free software (charge wish), receive source code can get want , can change software use pieces new free programs, know can things. protect rights, need prevent others denying rights asking surrender rights. Therefore, certain responsibilities distribute copies software, modify : responsibilities respect freedom others. example, distribute copies program, whether gratis fee, must pass recipients freedoms received. must make sure , , receive can get source code. must show terms know rights. 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Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://natverse.org/coconat/articles/identifiers-and-datasets.html","id":"datasets","dir":"Articles","previous_headings":"","what":"datasets","title":"identifiers-and-datasets","text":"coconat needs able handle range datasets. dataset record long name short name (2 characters [-z0-9]) use refer . can tell coconat new dataset :","code":"register_dataset('flywire', shortname = 'fw', species = 'Drosophila melanogaster', sex = 'F')"},{"path":"https://natverse.org/coconat/articles/identifiers-and-datasets.html","id":"identifiers-and-keys","dir":"Articles","previous_headings":"","what":"identifiers and keys","title":"identifiers-and-datasets","text":"dataset unique identifiers neurons contains. connectomics data sources currently work identifiers within 64 bit integer range, reason contain additional characters. ensure interoperability, default handling identifiers character vectors (strings) even native form package providing access dataset king numeric. introduce notion key form \":\" second point vital since numeric identifier can used different datasets refer different neurons. provide number functions assist . basic level id2char()convert numeric ids character representation taking care issues like fact .character(1e5)=1e+05 can cause trouble.","code":"id2char(1000) #> [1] \"1000\" id2char(1e5) #> [1] \"100000\" id2char(NA) #> [1] NA id2char(bit64::as.integer64('12345678901234')) #> [1] \"12345678901234\""},{"path":"https://natverse.org/coconat/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Gregory Jefferis. Author, maintainer.","code":""},{"path":"https://natverse.org/coconat/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Jefferis G (2023). coconat: Core Connectomics Utilities Natverse. https://github.com/natverse/coconat, http://natverse.org/coconat/.","code":"@Manual{, title = {coconat: Core Connectomics Utilities for the Natverse}, author = {Gregory Jefferis}, year = {2023}, note = {https://github.com/natverse/coconat, http://natverse.org/coconat/}, }"},{"path":"https://natverse.org/coconat/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Core Connectomics Utilities for the Natverse","text":"can install development version coconat GitHub :","code":"# install.packages(\"devtools\") devtools::install_github(\"natverse/coconat\")"},{"path":"https://natverse.org/coconat/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Core Connectomics Utilities for the Natverse","text":"basic example shows solve common problem: Now can also cosine cluster can inputs (5 PNs look much ) outputs course useful based richer set inputs","code":"library(coconat) # da2ds=neuprintr::neuprint_connection_table('DA2_lPN', details=TRUE, partners='out', conn = hbconn) da2ds=readRDS(system.file('sampledata/da2ds.rds', package = 'coconat')) head(da2ds) #> bodyid partner prepost weight name type #> 1 1796817841 5812982273 1 28 KCg-m_R KCg-m #> 2 1796817841 574377845 1 28 LHAV3f1_R LHAV3f1 #> 3 1797505019 1202410042 1 27 KCg-m_R KCg-m #> 4 1796818119 632402333 1 26 KCg-m_R KCg-m #> 5 1827516355 5813055865 1 26 LHAD1f2_R LHAD1f2 #> 6 1796818119 5813080766 1 24 KCg-m_R KCg-m library(Matrix) am=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'partner') image(am) am2=partner_summary2adjacency_matrix(subset(da2ds, weight>=15), inputcol = 'bodyid', outputcol = 'partner') image(am2) heatmap(cosine_sim(am, transpose = T)) heatmap(cosine_sim(am))"},{"path":"https://natverse.org/coconat/reference/coconat-package.html","id":null,"dir":"Reference","previous_headings":"","what":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","title":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","text":"Provides data source agnostic utility functions support analysis connectomics data Neuroanatomy Toolbox (natverse) suite packages.","code":""},{"path":[]},{"path":"https://natverse.org/coconat/reference/coconat-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","text":"Maintainer: Gregory Jefferis jefferis@gmail.com (ORCID)","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":null,"dir":"Reference","previous_headings":"","what":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"Efficient calculation cosine similarity sparse dense matrices","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"","code":"cosine_sim(x, sparse = FALSE, transpose = FALSE)"},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"x data matrix suitable clustering sparse Whether return sparse dense matrix (default dense) transpose F (default) calculates cosine distance columns. T calculates distance rows.","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"square matrix, dense unless sparse=TRUE x sparse.","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"much faster e.g. lsa::cosine added benefit works sparse input matrices","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"","code":"da2ds15=readRDS(system.file('sampledata/da2ds15.rds', package = 'coconat')) am=partner_summary2adjacency_matrix(da2ds15, inputcol = 'partner', outputcol = 'bodyid') cosine_sim(am) #> 1796817841 1797505019 1796818119 1827516355 818983130 #> 1796817841 1.00000000 0.09631851 0.00000000 0.0000000 0.03509041 #> 1797505019 0.09631851 1.00000000 0.00000000 0.0000000 0.09507157 #> 1796818119 0.00000000 0.00000000 1.00000000 0.0000000 0.07046832 #> 1827516355 0.00000000 0.00000000 0.00000000 1.0000000 0.20027384 #> 818983130 0.03509041 0.09507157 0.07046832 0.2002738 1.00000000 if (FALSE) { fam_pnkc2=flywire_adjacency_matrix2( inputids = 'class:ALPN_R', outputids = 'class:Kenyon_Cell_R', sparse=T , threshold = 2) kckc.cos=cosine_sim(fam_pnkc2) pnpn.cos=cosine_sim(fam_pnkc2, transpose=T) }"},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Return dataset names either all or those matching a query — dataset_names","title":"Return dataset names either all or those matching a query — dataset_names","text":"Return dataset names either matching query","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return dataset names either all or those matching a query — dataset_names","text":"","code":"dataset_names( query = NULL, return.short = FALSE, match = c(\"both\", \"long\", \"short\"), namespace = \"default\" )"},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return dataset names either all or those matching a query — dataset_names","text":"query character vector partially matched dataset names return.short Whether return long short name match Whether query match long short forms dataset name. namespace Optional character vector specifying namespace used organise datasets (advanced use ).","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return dataset names either all or those matching a query — dataset_names","text":"character vector names","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return dataset names either all or those matching a query — dataset_names","text":"","code":"dataset_names() #> character(0)"},{"path":"https://natverse.org/coconat/reference/id2char.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert any id into a character vector — id2char","title":"Convert any id into a character vector — id2char","text":"Convert id character vector","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert any id into a character vector — id2char","text":"","code":"id2char(x)"},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert any id into a character vector — id2char","text":"x character numeric vector ids","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert any id into a character vector — id2char","text":"character vector","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert any id into a character vector — id2char","text":"","code":"id2char(1000) #> [1] \"1000\" id2char(\"1000\") #> [1] \"1000\" id2char(1e5) #> [1] \"100000\""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"Convert partner summary table adjacency matrix","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"","code":"partner_summary2adjacency_matrix( x, sparse = TRUE, inputcol = \"pre_id\", outputcol = \"post_id\", inputids = NULL, outputids = NULL, standardise_input = T )"},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"x dataframe produced flywire_partner_summary, neuprint_connection_table equivalent. sparse Whether return sparse matrix (default TRUE case making big one) inputcol, outputcol Character vector specifying columns containing input output identifiers. See details section information. inputids, outputids Optional vectors input/output ids ensure present output matrix. Alternatively may contain function takes dataframe x input returns grouping vector. See details section information. standardise_input whether standardise column names/types input dataframe. default work flywire fafbseg neuprintr input ensure identify appropriate pre_id/post_id columns.","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"matrix inputs rows outputs (downstream neurons) columns","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"inputcol outputcol arguments can name columns containing values besides unique numerical identifiers neurons. example can refer cell type column, thereby generating grouped connectivity matrix. useful bringing together neurons similar connectivity patterns across brain hemispheres individuals. Passing function inputids /outputids allows partner neurons grouped maximum flexibility. input function dataframe x (standardisation requested). output must single vector can interpreted factor group partner neurons.","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"","code":"if (FALSE) { da2ds=neuprintr::neuprint_connection_table('DA2_lPN', details=TRUE, partners='out', threshold=5) am=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'partner') library(Matrix) image(am, ylab='DA2 PNs', xlab='outputs') amg=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'type') image(amg, ylab='DA2 PNs', xlab='output cell types') }"},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Cosine matrix utility functions — prepare_cosine_matrix","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"functions intended use package authors rather end users.","code":""},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"","code":"prepare_cosine_matrix( x, partners = c(\"inputs\", \"outputs\"), action = c(\"zero\", \"drop\") )"},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"x matrix named list input/output matrices partners Whether select input output matrices available action Whether zero drop NA values cosine matrix (may present columns entries)","code":""},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"matrix. inputs outputs used weighted total number input output synapses.","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":null,"dir":"Reference","previous_headings":"","what":"Register a dataset for use with coconat and related packages — register_dataset","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"Register dataset use coconat related packages","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"","code":"register_dataset( name, shortname = NULL, species = NULL, sex = c(\"F\", \"M\", \"H\", \"U\"), age = NULL, idfun = NULL, metafun = NULL, partnerfun = NULL, namespace = \"default\", ... )"},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"name long name dataset; must unique shortname abbreviation dataset - used construct keys plot labels etc species binomial name species sex Female, Male, Hermaphrodite Uncertain age description stage (e.g. adult L1 P19) idfun function function name fetch ids based query specification. metafun function function name fetch metadata set ids dataset. partnerfun function function name fetch connections ids dataset. namespace Expert use . Can used define separate namespaces across dataset names keys unique. Currently used testing purposes. ... Additional named arguments specifying properties dataset","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"return value. Called side effect.","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"","code":"if (FALSE) { # partial example. metafun and partnerfun are pretty important to specify register_dataset(\"flywire\", shortname='fw', species='Drosophila melanogaster', sex='F', age=\"adult\") }"},{"path":[]},{"path":"https://natverse.org/coconat/news/index.html","id":"coconat-011","dir":"Changelog","previous_headings":"","what":"coconat 0.1.1","title":"coconat 0.1.1","text":"Added NEWS.md file track changes package. Add support interactive heatmap @jefferis https://github.com/natverse/coconat/pull/2 Dev version @jefferis https://github.com/natverse/coconat/pull/3 interactive heatmap improvements @jefferis https://github.com/natverse/coconat/pull/4 Full Changelog: https://github.com/natverse/coconat/compare/v0.1.0…v0.1.1","code":""},{"path":"https://natverse.org/coconat/news/index.html","id":"coconat-010","dir":"Changelog","previous_headings":"","what":"coconat 0.1.0","title":"coconat 0.1.0","text":"First released version","code":""}] +[{"path":"https://natverse.org/coconat/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://natverse.org/coconat/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://natverse.org/coconat/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://natverse.org/coconat/articles/identifiers-and-datasets.html","id":"datasets","dir":"Articles","previous_headings":"","what":"datasets","title":"identifiers-and-datasets","text":"coconat needs able handle range datasets. dataset record long name short name (2 characters [-z0-9]) use refer . can tell coconat new dataset :","code":"register_dataset('flywire', shortname = 'fw', species = 'Drosophila melanogaster', sex = 'F')"},{"path":"https://natverse.org/coconat/articles/identifiers-and-datasets.html","id":"identifiers-and-keys","dir":"Articles","previous_headings":"","what":"identifiers and keys","title":"identifiers-and-datasets","text":"dataset unique identifiers neurons contains. connectomics data sources currently work identifiers within 64 bit integer range, reason contain additional characters. ensure interoperability, default handling identifiers character vectors (strings) even native form package providing access dataset king numeric. introduce notion key form \":\" second point vital since numeric identifier can used different datasets refer different neurons. provide number functions assist . basic level id2char()convert numeric ids character representation taking care issues like fact .character(1e5)=1e+05 can cause trouble.","code":"id2char(1000) #> [1] \"1000\" id2char(1e5) #> [1] \"100000\" id2char(NA) #> [1] NA id2char(bit64::as.integer64('12345678901234')) #> [1] \"12345678901234\""},{"path":"https://natverse.org/coconat/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Gregory Jefferis. Author, maintainer.","code":""},{"path":"https://natverse.org/coconat/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Jefferis G (2023). coconat: Core Connectomics Utilities Natverse. https://github.com/natverse/coconat, http://natverse.org/coconat/.","code":"@Manual{, title = {coconat: Core Connectomics Utilities for the Natverse}, author = {Gregory Jefferis}, year = {2023}, note = {https://github.com/natverse/coconat, http://natverse.org/coconat/}, }"},{"path":"https://natverse.org/coconat/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Core Connectomics Utilities for the Natverse","text":"can install development version coconat GitHub :","code":"# install.packages(\"devtools\") devtools::install_github(\"natverse/coconat\")"},{"path":"https://natverse.org/coconat/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Core Connectomics Utilities for the Natverse","text":"basic example shows solve common problem: Now can also cosine cluster can inputs (5 PNs look much ) outputs course useful based richer set inputs","code":"library(coconat) # da2ds=neuprintr::neuprint_connection_table('DA2_lPN', details=TRUE, partners='out', conn = hbconn) da2ds=readRDS(system.file('sampledata/da2ds.rds', package = 'coconat')) head(da2ds) #> bodyid partner prepost weight name type #> 1 1796817841 5812982273 1 28 KCg-m_R KCg-m #> 2 1796817841 574377845 1 28 LHAV3f1_R LHAV3f1 #> 3 1797505019 1202410042 1 27 KCg-m_R KCg-m #> 4 1796818119 632402333 1 26 KCg-m_R KCg-m #> 5 1827516355 5813055865 1 26 LHAD1f2_R LHAD1f2 #> 6 1796818119 5813080766 1 24 KCg-m_R KCg-m library(Matrix) am=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'partner') image(am) am2=partner_summary2adjacency_matrix(subset(da2ds, weight>=15), inputcol = 'bodyid', outputcol = 'partner') image(am2) heatmap(cosine_sim(am, transpose = T)) heatmap(cosine_sim(am))"},{"path":"https://natverse.org/coconat/reference/add_cluster_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info","title":"Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info","text":"Add dataframe columns detailing ordering groups dendrogram","code":""},{"path":"https://natverse.org/coconat/reference/add_cluster_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info","text":"","code":"add_cluster_info( df, dend, h = NULL, k = NULL, colnames = NULL, idcol = c(\"id\", \"root_id\", \"bodyid\") )"},{"path":"https://natverse.org/coconat/reference/add_cluster_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info","text":"df dataframe e.g. returned coconatfly::cf_meta dend dendrogram hclust object h height cut dendrogram k number clusters cut dendrogram colnames names two new columns idcol name column containing id information. provide argument function choose first three default columns present df (warning >1 column present).","code":""},{"path":"https://natverse.org/coconat/reference/add_cluster_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add dataframe columns detailing ordering and groups from a dendrogram — add_cluster_info","text":"copy df one two extra columns called dendid e.g. group_h2.","code":""},{"path":"https://natverse.org/coconat/reference/coconat-package.html","id":null,"dir":"Reference","previous_headings":"","what":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","title":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","text":"Provides data source agnostic utility functions support analysis connectomics data Neuroanatomy Toolbox (natverse) suite packages.","code":""},{"path":[]},{"path":"https://natverse.org/coconat/reference/coconat-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"coconat: Core Connectomics Utilities for the Natverse — coconat-package","text":"Maintainer: Gregory Jefferis jefferis@gmail.com (ORCID)","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":null,"dir":"Reference","previous_headings":"","what":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"Efficient calculation cosine similarity sparse dense matrices","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"","code":"cosine_sim(x, sparse = FALSE, transpose = FALSE)"},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"x data matrix suitable clustering sparse Whether return sparse dense matrix (default dense) transpose F (default) calculates cosine distance columns. T calculates distance rows.","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"square matrix, dense unless sparse=TRUE x sparse.","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"much faster e.g. lsa::cosine added benefit works sparse input matrices","code":""},{"path":"https://natverse.org/coconat/reference/cosine_sim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Efficient calculation of cosine similarity for sparse or dense matrices — cosine_sim","text":"","code":"da2ds15=readRDS(system.file('sampledata/da2ds15.rds', package = 'coconat')) am=partner_summary2adjacency_matrix(da2ds15, inputcol = 'partner', outputcol = 'bodyid') cosine_sim(am) #> 1796817841 1797505019 1796818119 1827516355 818983130 #> 1796817841 1.00000000 0.09631851 0.00000000 0.0000000 0.03509041 #> 1797505019 0.09631851 1.00000000 0.00000000 0.0000000 0.09507157 #> 1796818119 0.00000000 0.00000000 1.00000000 0.0000000 0.07046832 #> 1827516355 0.00000000 0.00000000 0.00000000 1.0000000 0.20027384 #> 818983130 0.03509041 0.09507157 0.07046832 0.2002738 1.00000000 if (FALSE) { fam_pnkc2=flywire_adjacency_matrix2( inputids = 'class:ALPN_R', outputids = 'class:Kenyon_Cell_R', sparse=T , threshold = 2) kckc.cos=cosine_sim(fam_pnkc2) pnpn.cos=cosine_sim(fam_pnkc2, transpose=T) }"},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Return dataset names either all or those matching a query — dataset_names","title":"Return dataset names either all or those matching a query — dataset_names","text":"Return dataset names either matching query","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return dataset names either all or those matching a query — dataset_names","text":"","code":"dataset_names( query = NULL, return.short = FALSE, match = c(\"both\", \"long\", \"short\"), namespace = \"default\" )"},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return dataset names either all or those matching a query — dataset_names","text":"query character vector partially matched dataset names return.short Whether return long short name match Whether query match long short forms dataset name. namespace Optional character vector specifying namespace used organise datasets (advanced use ).","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return dataset names either all or those matching a query — dataset_names","text":"character vector names","code":""},{"path":"https://natverse.org/coconat/reference/dataset_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return dataset names either all or those matching a query — dataset_names","text":"","code":"dataset_names() #> character(0)"},{"path":"https://natverse.org/coconat/reference/id2char.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert any id into a character vector — id2char","title":"Convert any id into a character vector — id2char","text":"Convert id character vector","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert any id into a character vector — id2char","text":"","code":"id2char(x)"},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert any id into a character vector — id2char","text":"x character numeric vector ids","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert any id into a character vector — id2char","text":"character vector","code":""},{"path":"https://natverse.org/coconat/reference/id2char.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert any id into a character vector — id2char","text":"","code":"id2char(1000) #> [1] \"1000\" id2char(\"1000\") #> [1] \"1000\" id2char(1e5) #> [1] \"100000\""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"Convert partner summary table adjacency matrix","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"","code":"partner_summary2adjacency_matrix( x, sparse = TRUE, inputcol = \"pre_id\", outputcol = \"post_id\", inputids = NULL, outputids = NULL, standardise_input = T )"},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"x dataframe produced flywire_partner_summary, neuprint_connection_table equivalent. sparse Whether return sparse matrix (default TRUE case making big one) inputcol, outputcol Character vector specifying columns containing input output identifiers. See details section information. inputids, outputids Optional vectors input/output ids ensure present output matrix. Alternatively may contain function takes dataframe x input returns grouping vector. See details section information. standardise_input whether standardise column names/types input dataframe. default work flywire fafbseg neuprintr input ensure identify appropriate pre_id/post_id columns.","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"matrix inputs rows outputs (downstream neurons) columns","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"inputcol outputcol arguments can name columns containing values besides unique numerical identifiers neurons. example can refer cell type column, thereby generating grouped connectivity matrix. useful bringing together neurons similar connectivity patterns across brain hemispheres individuals. Passing function inputids /outputids allows partner neurons grouped maximum flexibility. input function dataframe x (standardisation requested). output must single vector can interpreted factor group partner neurons.","code":""},{"path":"https://natverse.org/coconat/reference/partner_summary2adjacency_matrix.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a partner summary table into an adjacency matrix — partner_summary2adjacency_matrix","text":"","code":"if (FALSE) { da2ds=neuprintr::neuprint_connection_table('DA2_lPN', details=TRUE, partners='out', threshold=5) am=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'partner') library(Matrix) image(am, ylab='DA2 PNs', xlab='outputs') amg=partner_summary2adjacency_matrix(da2ds, inputcol = 'bodyid', outputcol = 'type') image(amg, ylab='DA2 PNs', xlab='output cell types') }"},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Cosine matrix utility functions — prepare_cosine_matrix","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"functions intended use package authors rather end users.","code":""},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"","code":"prepare_cosine_matrix( x, partners = c(\"inputs\", \"outputs\"), action = c(\"zero\", \"drop\") )"},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"x matrix named list input/output matrices partners Whether select input output matrices available action Whether zero drop NA values cosine matrix (may present columns entries)","code":""},{"path":"https://natverse.org/coconat/reference/prepare_cosine_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cosine matrix utility functions — prepare_cosine_matrix","text":"matrix. inputs outputs used weighted total number input output synapses.","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":null,"dir":"Reference","previous_headings":"","what":"Register a dataset for use with coconat and related packages — register_dataset","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"Register dataset use coconat related packages","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"","code":"register_dataset( name, shortname = NULL, species = NULL, sex = c(\"F\", \"M\", \"H\", \"U\"), age = NULL, idfun = NULL, metafun = NULL, partnerfun = NULL, namespace = \"default\", ... )"},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"name long name dataset; must unique shortname abbreviation dataset - used construct keys plot labels etc species binomial name species sex Female, Male, Hermaphrodite Uncertain age description stage (e.g. adult L1 P19) idfun function function name fetch ids based query specification. metafun function function name fetch metadata set ids dataset. partnerfun function function name fetch connections ids dataset. namespace Expert use . Can used define separate namespaces across dataset names keys unique. Currently used testing purposes. ... Additional named arguments specifying properties dataset","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"return value. Called side effect.","code":""},{"path":"https://natverse.org/coconat/reference/register_dataset.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register a dataset for use with coconat and related packages — register_dataset","text":"","code":"if (FALSE) { # partial example. metafun and partnerfun are pretty important to specify register_dataset(\"flywire\", shortname='fw', species='Drosophila melanogaster', sex='F', age=\"adult\") }"},{"path":[]},{"path":"https://natverse.org/coconat/news/index.html","id":"coconat-011","dir":"Changelog","previous_headings":"","what":"coconat 0.1.1","title":"coconat 0.1.1","text":"Added NEWS.md file track changes package. Add support interactive heatmap @jefferis https://github.com/natverse/coconat/pull/2 Dev version @jefferis https://github.com/natverse/coconat/pull/3 interactive heatmap improvements @jefferis https://github.com/natverse/coconat/pull/4 Full Changelog: https://github.com/natverse/coconat/compare/v0.1.0…v0.1.1","code":""},{"path":"https://natverse.org/coconat/news/index.html","id":"coconat-010","dir":"Changelog","previous_headings":"","what":"coconat 0.1.0","title":"coconat 0.1.0","text":"First released version","code":""}] diff --git a/sitemap.xml b/sitemap.xml index 27bce4f..8c2580a 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -21,6 +21,9 @@ https://natverse.org/coconat/news/index.html + + https://natverse.org/coconat/reference/add_cluster_info.html + https://natverse.org/coconat/reference/coconat-package.html