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Package: evprof | ||
Title: Electric Vehicle Charging Sessions Profiling and Modelling | ||
Version: 1.0.0 | ||
Authors@R: | ||
person("Marc", "Cañigueral", , "marc.canigueral@udg.edu", role = c("aut", "cre", "cph"), | ||
comment = c(ORCID = "0000-0001-9724-5829")) | ||
Description: Tools for modelling electric vehicle charging sessions into | ||
generic groups with similar connection patterns called "user profiles", | ||
using Gaussian Mixture Models clustering. The clustering and profiling | ||
methodology is described in Cañigueral and Meléndez (2021, ISBN:0142-0615) | ||
<doi:10.1016/j.ijepes.2021.107195>. | ||
License: GPL-3 | ||
URL: https://github.com/mcanigueral/evprof/ | ||
BugReports: https://github.com/mcanigueral/evprof/issues | ||
Depends: R (>= 3.5.0) | ||
Imports: cowplot, dbscan, dplyr, ggplot2, jsonlite, lubridate, MASS, | ||
mclust, plotly, purrr, rlang, tibble, tidyr | ||
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0), utils | ||
VignetteBuilder: knitr | ||
Config/testthat/edition: 3 | ||
Encoding: UTF-8 | ||
Language: en-US | ||
LazyData: true | ||
RoxygenNote: 7.2.3 | ||
NeedsCompilation: no | ||
Packaged: 2024-01-19 11:38:01 UTC; mcanigueral | ||
Author: Marc Cañigueral [aut, cre, cph] | ||
(<https://orcid.org/0000-0001-9724-5829>) | ||
Maintainer: Marc Cañigueral <marc.canigueral@udg.edu> | ||
Repository: CRAN | ||
Date/Publication: 2024-01-19 15:50:02 UTC |
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9542fcc1b4d5296b1a6f29d242a569be *DESCRIPTION | ||
77d1462cf3a2d535823f8a02329a231c *NAMESPACE | ||
e5128fea3a0d0955928d3a9e663bc647 *NEWS.md | ||
b35c4c551a87ac9ceda5c0e8d2a9ce5e *R/clustering.R | ||
49bfe15a2e9f1bbc4b0b8b8cbcab7acc *R/data.R | ||
3fd6fe919593a7c2e481bd5c7ca4f27e *R/exploration.R | ||
995dfbce0d7751631a9b19bcd91eb43a *R/modelling.R | ||
77bf9b420ca315d87755518b6982c06a *R/package_utils.R | ||
65c8349534a85c122cb2f21f97a9ce27 *R/preprocessing.R | ||
31947b3126783aa2749dc2aef8855a9b *R/profiling.R | ||
9700e5b032e0de253036a562378ce977 *README.md | ||
ca92612c359a079d6fbda517be2ed926 *build/vignette.rds | ||
9de514546ce47535410a55fdae4a27ac *data/california_GMM.rda | ||
989ee4b9448b0ab3f63e58c5e8295ca4 *data/california_ev_model.rda | ||
07c23309b23d7f7aa9371219ac719731 *data/california_ev_sessions.rda | ||
7a2187e38d0480684f7ead3d753bb175 *data/california_ev_sessions_profiles.rda | ||
66b3acfb7bac463b3fe35a5aa5b4414b *data/sessions_feature_names.rda | ||
465992bd9176d7911cc54633e6de098a *data/sessions_summary_feature_names.rda | ||
cc18fa472536fce9db69cc4a3f886edf *inst/doc/evmodel.R | ||
fae2dd11227c21512635f5999303b109 *inst/doc/evmodel.Rmd | ||
13560c2ea5792bba4d219bf549ed87e2 *inst/doc/evmodel.html | ||
7c173a67481270a68ff9101cb21badbd *inst/doc/sessions-format.R | ||
4b6cf81408beeb1904ea368a732a2463 *inst/doc/sessions-format.Rmd | ||
3f89a5e88ba6ec5e97f74c0b714b8ab6 *inst/doc/sessions-format.html | ||
20aff559b2c2c7c635300c0a8032ec75 *man/california_GMM.Rd | ||
8278c42bd4275ab4664f81cdebb96c9b *man/california_ev_model.Rd | ||
8499fe2b32a67660c41d73c83744011d *man/california_ev_sessions.Rd | ||
6adc1aab217604d24f75040593c0d6b4 *man/california_ev_sessions_profiles.Rd | ||
f62a8f36258ce1e21d315be96ecd9fce *man/choose_k_GMM.Rd | ||
375930cb4e20b6232bf9842c542a9c8e *man/cluster_sessions.Rd | ||
1601ef1a40821ea75bf42414a4a0f271 *man/convert_time_dt_to_num.Rd | ||
b9826a4ac900d3b0c408fb2ba69944dd *man/convert_time_dt_to_plot_dt.Rd | ||
e5a89215616c892c14c59d07b20da3ac *man/convert_time_dt_to_plot_num.Rd | ||
cef86402013883c398c0fd22e6bda9d6 *man/convert_time_num_to_chr.Rd | ||
c795f8eda44f53c5f77d8d9f526df4ef *man/convert_time_num_to_period.Rd | ||
9dcb7d83ebc6e2055d716e50948190ed *man/convert_time_num_to_plot_num.Rd | ||
850b0fc612eb7f8df3458afefe5a4839 *man/cut_sessions.Rd | ||
7ba1a91adc1a79ccde559bfb3126e44a *man/define_clusters.Rd | ||
205d838747a3bcefa4cc9d6ce9679c02 *man/detect_outliers.Rd | ||
a4e9e863b1618e957c71256694e15f61 *man/divide_by_disconnection.Rd | ||
10dbf80742caa348f7514eac8762375f *man/divide_by_timecycle.Rd | ||
654de6c9344a1fb74eb1225db24340fc *man/drop_outliers.Rd | ||
749ad31e388a934da20a17773306bbf9 *man/figures/logo.png | ||
236e6df60d74a8b9de2f4918add7beb8 *man/get_charging_rates_distribution.Rd | ||
063a5fb513b2e2312aee23be24aa1ae1 *man/get_connection_model_mclust_object.Rd | ||
4c56fe2a8e10f788e1e25ee370653ace *man/get_connection_model_params.Rd | ||
ae08273d7d7d2214497b1b0db9b2190d *man/get_connection_models.Rd | ||
b90de871f3671e163b9f35499cea2cf0 *man/get_daily_avg_n_sessions.Rd | ||
09249f16969656bdb0cc23f76e0023eb *man/get_daily_n_sessions.Rd | ||
9c1552e45fb2bb48bee340444b3f7580 *man/get_dbscan_params.Rd | ||
7afd96657ccf87b48f157263ac011d0c *man/get_division_line.Rd | ||
55c231dad0c46027b2141b475f0731bb *man/get_energy_model_mclust_object.Rd | ||
040c1f72de82cfb4c5ec69ce0c231e89 *man/get_energy_model_parameters.Rd | ||
aadb8f6bd871a7b3805c74d8b1dec09a *man/get_energy_models.Rd | ||
78af70c7cda525d5ab276409707a3014 *man/get_ev_model.Rd | ||
9b5a555a216fe9dcc6683f78e92ed375 *man/mutate_to_log.Rd | ||
dd51a03c56934d7cdad757ec40ad239a *man/plot_bivarGMM.Rd | ||
9773a0801023f25142f2da012e9319c3 *man/plot_density_2D.Rd | ||
5bc059f1d15a61a60e2912e208618498 *man/plot_density_3D.Rd | ||
c817a28661229bf246d463b777b6c3bb *man/plot_division_lines.Rd | ||
befd767e50965f616887ee3938cd6921 *man/plot_energy_models.Rd | ||
e93eb65d9f82eab786483e123bcca05a *man/plot_histogram.Rd | ||
88bc4d08d677dba1c0bb1f6e13ae2623 *man/plot_histogram_grid.Rd | ||
74acbeac8f0c85bd7ca36e649766a679 *man/plot_kNNdist.Rd | ||
d9222cd6a22185e3734e29291ad4a606 *man/plot_model_clusters.Rd | ||
fdcc22da4e043770c575466a204acaf3 *man/plot_outliers.Rd | ||
b028644e3ccf4f8f466d2471b4079b2f *man/plot_points.Rd | ||
05ef1d2e16e791459e51059adb0aaf71 *man/print.evmodel.Rd | ||
2a9d01c2222f102803efc2cb5517c738 *man/print_connection_models_table.Rd | ||
b3967c1c38725f1e48bf266f45f873cb *man/print_user_profile_energy_models_table.Rd | ||
9229b7aa474b7345c92595ff93e7a313 *man/read_ev_model.Rd | ||
ec4377fa1e8c87847d73f411706c94d2 *man/round_to_half.Rd | ||
dd0c09ca9e5c232accaac33bc91538aa *man/round_to_interval.Rd | ||
b04209585a8adf60ae2d6721e993afb4 *man/save_clustering_iterations.Rd | ||
aedeb23173b2b4024312c6fdfd594dfb *man/save_ev_model.Rd | ||
2fd468136b57e6fc7d3ab59d9b2e978b *man/sessions_feature_names.Rd | ||
dad02fd42d30473859cd09f9089c8ef8 *man/sessions_summary_feature_names.Rd | ||
b9f563e33ab0137ef64ae0173e87b9eb *man/set_profiles.Rd | ||
e48e114ec50c3d992e337e72b9b52e81 *man/summarise_sessions.Rd | ||
0622a97a2aaa3c342f09636052c2d7f5 *tests/spelling.R | ||
c5a8ebd44a1983bb51d26baacb5767b1 *tests/testthat.R | ||
53ffd85407d935d66ba23cc1be247282 *tests/testthat/test-evprof.R | ||
47382bd57b84adeb1c9bc5d776ca65a1 *vignettes/californa_sessions_profiles.RDS | ||
fae2dd11227c21512635f5999303b109 *vignettes/evmodel.Rmd | ||
4b6cf81408beeb1904ea368a732a2463 *vignettes/sessions-format.Rmd |
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# Generated by roxygen2: do not edit by hand | ||
|
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S3method(print,evmodel) | ||
export(choose_k_GMM) | ||
export(cluster_sessions) | ||
export(cut_sessions) | ||
export(define_clusters) | ||
export(detect_outliers) | ||
export(divide_by_disconnection) | ||
export(divide_by_timecycle) | ||
export(drop_outliers) | ||
export(get_charging_rates_distribution) | ||
export(get_connection_models) | ||
export(get_daily_avg_n_sessions) | ||
export(get_daily_n_sessions) | ||
export(get_dbscan_params) | ||
export(get_division_line) | ||
export(get_energy_models) | ||
export(get_ev_model) | ||
export(plot_bivarGMM) | ||
export(plot_density_2D) | ||
export(plot_density_3D) | ||
export(plot_division_lines) | ||
export(plot_energy_models) | ||
export(plot_histogram) | ||
export(plot_histogram_grid) | ||
export(plot_kNNdist) | ||
export(plot_model_clusters) | ||
export(plot_outliers) | ||
export(plot_points) | ||
export(print_connection_models_table) | ||
export(print_user_profile_energy_models_table) | ||
export(read_ev_model) | ||
export(round_to_interval) | ||
export(save_clustering_iterations) | ||
export(save_ev_model) | ||
export(set_profiles) | ||
export(summarise_sessions) | ||
importFrom(MASS,kde2d) | ||
importFrom(cowplot,plot_grid) | ||
importFrom(dbscan,dbscan) | ||
importFrom(dbscan,kNNdist) | ||
importFrom(dplyr,"%>%") | ||
importFrom(dplyr,all_of) | ||
importFrom(dplyr,any_of) | ||
importFrom(dplyr,arrange) | ||
importFrom(dplyr,as_tibble) | ||
importFrom(dplyr,between) | ||
importFrom(dplyr,bind_rows) | ||
importFrom(dplyr,everything) | ||
importFrom(dplyr,filter) | ||
importFrom(dplyr,group_by) | ||
importFrom(dplyr,left_join) | ||
importFrom(dplyr,mutate) | ||
importFrom(dplyr,n) | ||
importFrom(dplyr,pull) | ||
importFrom(dplyr,rename) | ||
importFrom(dplyr,select) | ||
importFrom(dplyr,summarise) | ||
importFrom(dplyr,summarise_all) | ||
importFrom(dplyr,sym) | ||
importFrom(dplyr,tibble) | ||
importFrom(dplyr,ungroup) | ||
importFrom(ggplot2,aes) | ||
importFrom(ggplot2,after_stat) | ||
importFrom(ggplot2,facet_wrap) | ||
importFrom(ggplot2,geom_histogram) | ||
importFrom(ggplot2,geom_line) | ||
importFrom(ggplot2,geom_path) | ||
importFrom(ggplot2,geom_point) | ||
importFrom(ggplot2,ggplot) | ||
importFrom(ggplot2,ggsave) | ||
importFrom(ggplot2,ggtitle) | ||
importFrom(ggplot2,guide_legend) | ||
importFrom(ggplot2,guides) | ||
importFrom(ggplot2,labs) | ||
importFrom(ggplot2,scale_color_discrete) | ||
importFrom(ggplot2,scale_color_manual) | ||
importFrom(ggplot2,scale_fill_viridis_c) | ||
importFrom(ggplot2,scale_x_continuous) | ||
importFrom(ggplot2,scale_x_datetime) | ||
importFrom(ggplot2,scale_y_continuous) | ||
importFrom(ggplot2,stat_density2d) | ||
importFrom(ggplot2,theme) | ||
importFrom(ggplot2,theme_light) | ||
importFrom(ggplot2,unit) | ||
importFrom(ggplot2,vars) | ||
importFrom(ggplot2,xlab) | ||
importFrom(ggplot2,ylab) | ||
importFrom(grDevices,extendrange) | ||
importFrom(graphics,plot) | ||
importFrom(jsonlite,fromJSON) | ||
importFrom(lubridate,"date<-") | ||
importFrom(lubridate,as_datetime) | ||
importFrom(lubridate,date) | ||
importFrom(lubridate,days) | ||
importFrom(lubridate,floor_date) | ||
importFrom(lubridate,hour) | ||
importFrom(lubridate,hours) | ||
importFrom(lubridate,minute) | ||
importFrom(lubridate,minutes) | ||
importFrom(lubridate,month) | ||
importFrom(lubridate,second) | ||
importFrom(lubridate,today) | ||
importFrom(lubridate,wday) | ||
importFrom(lubridate,year) | ||
importFrom(mclust,Mclust) | ||
importFrom(mclust,cdfMclust) | ||
importFrom(mclust,densityMclust) | ||
importFrom(mclust,emControl) | ||
importFrom(mclust,mclustBIC) | ||
importFrom(mclust,predict.densityMclust) | ||
importFrom(plotly,add_surface) | ||
importFrom(plotly,hide_colorbar) | ||
importFrom(plotly,layout) | ||
importFrom(plotly,plot_ly) | ||
importFrom(purrr,map) | ||
importFrom(purrr,map2) | ||
importFrom(purrr,map2_dfr) | ||
importFrom(purrr,map_dbl) | ||
importFrom(purrr,map_dfr) | ||
importFrom(purrr,pmap) | ||
importFrom(purrr,pmap_chr) | ||
importFrom(purrr,pmap_dfr) | ||
importFrom(purrr,set_names) | ||
importFrom(rlang,.data) | ||
importFrom(stats,runif) | ||
importFrom(tibble,tibble) | ||
importFrom(tidyr,nest) |
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# evprof 1.0.0 | ||
|
||
* Added functions to save and read the model in JSON instead of RDS files | ||
* Bug fix in the `evmodel` printing function | ||
* Default `log` value of function `detect_outliers` set to `TRUE` | ||
* Replace all deprecated `aes_string` functions by using `.data[[var]]` | ||
* Remove unused functions | ||
* Remove `days` parameter from function `divide_by_disconnection` | ||
* Print a message with time-cycles' table in function `divide_by_timecycle` | ||
* Complete tests | ||
* Including California EV sessions when loading the package | ||
* Include examples in all exported functions | ||
* CRAN release | ||
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# evprof 0.1.0 | ||
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* First release |
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