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The Database of Odorant Responses (DoOR.functions) #34

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7 of 10 tasks
Dahaniel opened this issue Apr 11, 2016 · 46 comments
Closed
7 of 10 tasks

The Database of Odorant Responses (DoOR.functions) #34

Dahaniel opened this issue Apr 11, 2016 · 46 comments

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@Dahaniel
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Dahaniel commented Apr 11, 2016

    1. What does this package do? (explain in 50 words or less)

Package containing the functions for the DoOR project. DoOR provides a framework to merge heterogeneous response data into a single consensus database, thus creating a comprehensive view on olfactory coding.

    1. Paste the full DESCRIPTION file inside a code block below.
Package: DoOR.functions
Type: Package
Title: Integrating Heterogeneous Odorant Response Data into a Common Response
    Model: A DoOR to the Complete Olfactome
Version: 2.0.0
Date: 2016-02-25
Authors@R: c(
    person("Daniel", "Münch", email = "daniel.muench@uni-konstanz.de", role = c("aut", "cre")),
    person("C. Giovanni", "Galizia", email = "giovanni.galizia@uni-konstanz.de", role = "aut"),
    person("Shouwen", "Ma", role = "aut"),
    person("Martin", "Strauch", role = "aut"),
    person("Anja", "Nissler", role = "aut"),
    person("Wolf", "Huetteroth", role = "ctb"))
URL: http://neuro.uni.kn/DoOR
BugReports: https://github.com/Dahaniel/DoOR.data/issues
Description: This is a function package providing functions to perform data
    manipulations and visualizations for DoOR.data. See http://dx.doi.org/10.1093/chemse/bjq042 for the original publication and http://dx.doi.org/10.1038/srep21841
    regarding version 2.0.
License: GPL-3
Encoding: UTF-8
Imports:
    utils
Depends:
    DoOR.data (>= 2.0.0),
    R (>= 3.2.0)
Remotes: Dahaniel/DoOR.data@v2.0.0
Suggests:
    ggplot2,
    grid,
    gridExtra (>= 2.0.0),
    knitr,
    class,
    rmarkdown
VignetteBuilder: knitr
RoxygenNote: 5.0.1

    1. URL for the package (the development repository, not a stylized html page)

https://github.com/Dahaniel/DoOR.functions

    1. What data source(s) does it work with (if applicable)?

It provides its own data via the DoOR.data package (see corresponding onboarding issue).

    1. Who is the target audience?

Scientists working on olfactory coding, modelers and physiologists.

    1. Are there other R packages that accomplish the same thing? If so, what is different about yours?

No, to our knowledge DoOR is the only project providing this kind of data and using this approach to integrate heterogeneous data.

    1. Check the box next to each policy below, confirming that you agree. These are mandatory.
    • This package does not violate the Terms of Service of any service it interacts with.
    • The repository has continuous integration with Travis CI and/or another service
    • The package contains a vignette
    • The package contains a reasonably complete README with devtools install instructions
    • The package contains unit tests
    • The package only exports functions to the NAMESPACE that are intended for end users
    1. Do you agree to follow the rOpenSci packaging guidelines? These aren't mandatory, but we strongly suggest you follow them. If you disagree with anything, please explain.
    • Are there any package dependencies not on CRAN? - no
    • Do you intend for this package to go on CRAN?
    • Does the package have a CRAN accepted license?
    • Did devtools::check() produce any errors or warnings? If so paste them below. - no
    1. Please add explanations below for any exceptions to the above:
    • Not sure how to implement unit tests but am willing to learn, might need some help.
    1. If this is a resubmission following rejection, please explain the change in circumstances.
@sckott
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sckott commented Apr 11, 2016

Thanks for your submission, seeking reviewers

@noamross
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noamross commented Apr 17, 2016

Reviewers: @RemkoDuursma
Due date: 2016-05-09

@sckott
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sckott commented May 3, 2016

@RemkoDuursma
Due date: 2016-05-09 - hey there, it's been 16 days, please get your review in by May 08, thanks 😺 (ropensci-bot)

@sckott
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sckott commented May 8, 2016

@RemkoDuursma
Due date: 2016-05-09 - hey there, it's been 21 days, please get your review in soon, thanks 😺 (ropensci-bot)

@noamross
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noamross commented May 23, 2016

Hi @RemkoDuursma, just checking in on this review, which was due 2016-05-09. Please get it in soon, thanks!

@sckott
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sckott commented May 23, 2016

@RemkoDuursma
Due date: 2016-05-09 - hey there, it's been 36 days, please get your review in soon, thanks 😺 (ropensci-bot)

@RemkoDuursma
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RemkoDuursma commented May 25, 2016

Apologies for my very slow review.

  • The DoOR.functions package is quite well documented and implemented with good consistency. I did not find any major issues here at all. Again I want to point out that I cannot comment on the usefulness or applicability of the package since this is well outside my expertise.
  • The included vignettes are very useful to get an overview of this rather complicated package.
  • The default.val function is slightly odd, and could be replaced with the more standard use of options to set values for default parameters/flags in a package. The drawback of the current implementation is that new default values cannot be set, this would be a useful feature I think. One option is to have all possible parameters as arguments to the default.val function (e.g. points.cex=1).
  • In the DESCRIPTION file, it is customary to move all URLs to the URL field (there is one in the Description field).
  • Names of functions use camelCase which is fine (though snake_case is preferred by ROpenSci as previously discussed), except CreateDatabase.
  • The package includes examples, but it would be helpful if the examples are commented (at the moment only the code is shown but no information on what the code does).
  • Some functions lack in documentation (e.g. updateOdorInfo).

@sckott
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sckott commented Aug 10, 2016

@Dahaniel can you respond to the review above please

@Dahaniel
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Dahaniel commented Aug 11, 2016

@RemkoDuursma Thank you very much for reviewing the package and apologies for my slow response.

  • It is correct that the default.val() values cannot be changed. default.val() is intended to provide package wide default values for functions, whenever these are called without parameters. In fact users can change the default parameters when calling the individual functions with parameters. So I think changing the values that default.val() provides would not make sense.
    Regarding the suggestion to use options instead: I was not aware of options and have to read about its usage. When this would provide a standard way of achieving what we achieve with default.val() we should use options instead.

We also use default.val to check if the data.frames a function relies on exist in the global environment and if not load the data from the package:

  if (DoOR_default == "DoOR.mappings") {
    if (!exists("DoOR.mappings")) {
      data(DoOR.mappings)
    }
    return(DoOR.mappings)
  } 

The idea is that the user can put modified data into the global environment that will be used when available. Not sure whether this could be implemented with options.

  • I moved the urls to the URL field
  • Function names: see my comment at the DoOR.data thread. I am happy to change function names having a transitional phase where old and new name work and am looking for a way to implement this.
  • Documentation: I will check for missing docs and add descriptions to examples

@sckott
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sckott commented Aug 11, 2016

thanks for your response @Dahaniel on function names, see comment in #35

@Dahaniel
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Dahaniel commented Mar 7, 2017

Hi everyone, apologies that it took me so long to implement the requested changes. But finally today I was able to release v2.0.1 for both packages, implementing all of the above discussed changes.
In detail (I summarize the changes here as most affect both packages):

  • I renamed loadData to load_door_data() to be more descriptive.
  • I warn that data will be loaded to the current environment and forced a user interaction for that.
  • I transform all function names to snake_case and inform about that on package loading. I also kept the old function names working for now.
  • I replaced '.' with '_' in data names.
  • moved all urls to url field in DESCRIPTION.
  • I added documentation to the data sets.
  • I added some descriptions to the examples.
  • I exported all data as csv for better change tracking.
  • I kept default.val() for now (see previous discussion)

@sckott
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sckott commented Mar 7, 2017

thx @Dahaniel

@RemkoDuursma if possible, could you take a look at the changes for this and #35 and let us know if you're happy with the changes? also let us know if you're too busy/etc, and we'll have a look instead

@RemkoDuursma
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RemkoDuursma commented Mar 9, 2017

Sorry I won't have a chance any time soon to look at the changes. If you could have a look, that would be great.

@noamross
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noamross commented Mar 13, 2017

Thanks for the update, @Dahaniel. As @RemkoDuursma is no longer available, we'll have an alternate reviewer or editor look at your changes.

@sckott sckott self-assigned this Apr 11, 2017
@sckott
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sckott commented Apr 17, 2017

@Dahaniel

  • Looks like you still don't have unit tests - please add those
  • You have a circularity problem in your dependencies. DoOR.data is in DEPENDS in this pkg, and DoOR.functions is in Suggests for the DoOR.data package - why is DoOR.data in Depends? there's very few cases in which that's needed, is it here?
  • R check reveals many problems: you need to Rbuildignore .travis.yml/CHANGELOG.md (but you should also have a NEWS.md or NEWS as that's more typical of R packages),

Some of R check output

N  checking R code for possible problems
   default.val: no visible binding for global variable ‘door_AL_map’
   default.val: no visible binding for global variable ‘door_data_format’
   default.val: no visible binding for global variable ‘odor’
   default.val: no visible binding for global variable ‘odor.dist’
   default.val: no visible binding for global variable
     ‘door_global_normalization_weights’
   default.val: no visible binding for global variable
     ‘door_excluded_data’
   default.val: no visible binding for global variable ‘door_mappings’
   default.val: no visible binding for global variable ‘ORs’
   default.val: no visible binding for global variable
     ‘door_response_matrix’
   default.val: no visible binding for global variable
     ‘door_response_range’
   default.val: no visible binding for global variable
     ‘door_response_matrix_non_normalized’
   door_default_values: no visible binding for global variable
     ‘door_AL_map’
   door_default_values: no visible binding for global variable
     ‘door_data_format’
   door_default_values: no visible binding for global variable ‘odor’
   door_default_values: no visible binding for global variable ‘odor.dist’
   door_default_values: no visible binding for global variable
     ‘door_global_normalization_weights’
   door_default_values: no visible binding for global variable
     ‘door_excluded_data’
   door_default_values: no visible binding for global variable
     ‘door_mappings’
   door_default_values: no visible binding for global variable ‘ORs’
   door_default_values: no visible binding for global variable
     ‘door_response_matrix’
   door_default_values: no visible binding for global variable
     ‘door_response_range’
   door_default_values: no visible binding for global variable
     ‘door_response_matrix_non_normalized’
   dplot_ALmap: no visible binding for global variable ‘odor’
   dplot_ALmap: no visible binding for global variable ‘x’
   dplot_ALmap: no visible binding for global variable ‘group’
   dplot_ALmap: no visible binding for global variable ‘glomerulus’
   dplot_ALmap: no visible binding for global variable ‘response’
   dplot_acrossOSNs: no visible binding for global variable ‘sensillum’
   dplot_acrossOSNs: no visible binding for global variable ‘OSN’
   dplot_acrossOSNs: no visible binding for global variable ‘value’
   dplot_acrossOSNs: no visible binding for global variable ‘dataset’
   dplot_acrossOSNs: no visible binding for global variable ‘odorant’
   dplot_acrossReceptors: no visible binding for global variable ‘value’
   dplot_across_osns: no visible binding for global variable ‘sensillum’
   dplot_across_osns: no visible binding for global variable ‘OSN’
   dplot_across_osns: no visible binding for global variable ‘value’
   dplot_across_osns: no visible binding for global variable ‘dataset’
   dplot_across_osns: no visible binding for global variable ‘odorant’
   dplot_across_ru: no visible binding for global variable ‘value’
   dplot_al_map: no visible binding for global variable ‘odor’
   dplot_al_map: no visible binding for global variable ‘x’
   dplot_al_map: no visible binding for global variable ‘group’
   dplot_al_map: no visible binding for global variable ‘glomerulus’
   dplot_al_map: no visible binding for global variable ‘response’
   dplot_compareProfiles: no visible binding for global variable ‘odorant’
   dplot_compareProfiles: no visible binding for global variable ‘value’
   dplot_compareProfiles: no visible binding for global variable ‘dataset’
   dplot_compare_profiles: no visible binding for global variable
     ‘odorant’
   dplot_compare_profiles: no visible binding for global variable ‘value’
   dplot_compare_profiles: no visible binding for global variable
     ‘dataset’
   dplot_responseMatrix: no visible binding for global variable ‘odorant’
   dplot_responseMatrix: no visible binding for global variable ‘dataset’
   dplot_responseMatrix: no visible binding for global variable ‘value’
   dplot_responseProfile: no visible binding for global variable ‘odorant’
   dplot_responseProfile: no visible binding for global variable ‘value’
   dplot_response_matrix: no visible binding for global variable ‘odorant’
   dplot_response_matrix: no visible binding for global variable ‘dataset’
   dplot_response_matrix: no visible binding for global variable ‘value’
   dplot_response_profile: no visible binding for global variable
     ‘odorant’
   dplot_response_profile: no visible binding for global variable ‘value’
   dplot_tuningCurve: no visible binding for global variable ‘odorants’
   dplot_tuningCurve: no visible binding for global variable ‘value’
   dplot_tuningCurve: no visible binding for global variable ‘receptors’
   get_dataset: no visible binding for global variable ‘door_data_format’
   identifySensillum: no visible binding for global variable ‘sensillum’
   identifySensillum: no visible binding for global variable ‘dataset’
   identifySensillum: no visible binding for global variable ‘odorant’
   identifySensillum: no visible binding for global variable ‘value’
   identify_sensillum: no visible binding for global variable ‘sensillum’
   identify_sensillum: no visible binding for global variable ‘dataset’
   identify_sensillum: no visible binding for global variable ‘odorant’
   identify_sensillum: no visible binding for global variable ‘value’
   importNewData: no visible binding for global variable
     ‘door_response_range’
   importNewData: no visible binding for global variable
     ‘door_global_normalization_weights’
   import_new_data: no visible binding for global variable
     ‘door_response_range’
   import_new_data: no visible binding for global variable
     ‘door_global_normalization_weights’
   load2list: no visible binding for global variable ‘ORs’
   privateOdorant: no visible binding for global variable ‘x’
   privateOdorant: no visible binding for global variable ‘n’
   private_odorant: no visible binding for global variable ‘x’
   private_odorant: no visible binding for global variable ‘n’
   rebuild_metadata: no visible binding for global variable ‘ORs’
   updateOdorInfo: no visible binding for global variable ‘ORs’
   updateOdorInfo: no visible binding for global variable ‘odor’
   update_door_odorinfo: no visible binding for global variable ‘ORs’
   update_door_odorinfo: no visible binding for global variable ‘odor’
   Undefined global functions or variables:
     ORs OSN dataset door_AL_map door_data_format door_excluded_data
     door_global_normalization_weights door_mappings door_response_matrix
     door_response_matrix_non_normalized door_response_range glomerulus
     group n odor odor.dist odorant odorants receptors response sensillum
     value x

   Found the following assignments to the global environment:
   File ‘DoOR.functions/R/create_door_database.R’:
     assign("door_response_matrix", frame_data, envir = .GlobalEnv)
     assign("door_response_matrix_non_normalized", frame_data_nn,
       envir = .GlobalEnv)
     assign("door_excluded_data", door_excluded_data, envir = .GlobalEnv)
   File ‘DoOR.functions/R/import_new_data.R’:
     assign(j, target, envir = .GlobalEnv)
     assign(j, target, envir = .GlobalEnv)
     assign(column.name, combine_data(data1 = target, data2 = imported.data,
       by.data2 = column.name, assigned.name = paste(file.name,
           sep = "")), envir = .GlobalEnv)
     assign("door_data_format", dataFormat, envir = .GlobalEnv)
     assign("door_global_normalization_weights", weightGlobNorm, envir = .GlobalEnv)
     assign("door_response_range", responseRange, envir = .GlobalEnv)
     assign("ORs", receptors, envir = .GlobalEnv)
     assign("odor", odor_data, envir = .GlobalEnv)
   File ‘DoOR.functions/R/rebuild_metadata.R’:
     assign("door_global_normalization_weights", wgn, envir = .GlobalEnv)
     assign("door_response_range", rr, envir = .GlobalEnv)
   File ‘DoOR.functions/R/remove_study.R’:
     assign(x, data, envir = .GlobalEnv)
     assign("door_response_range", responseRange, envir = .GlobalEnv)
     assign("door_global_normalization_weights", weightGlobNorm, envir = .GlobalEnv)
   File ‘DoOR.functions/R/update_door_database.R’:
     assign("door_response_matrix_non_normalized", response_matrix_nn,
       envir = .GlobalEnv)
     assign("door_response_matrix", response_matrix, envir = .GlobalEnv)
     assign("door_excluded_data", door_excluded_data, envir = .GlobalEnv)
   File ‘DoOR.functions/R/update_door_odorinfo.R’:
     assign(i, tmp, envir = .GlobalEnv)
     assign("door_data_format", odor[1:5], envir = .GlobalEnv)

   Found the following calls to data() loading into the global environment:
   File ‘DoOR.functions/R/door_default_values.R’:
     data(door_AL_map)
     data(door_data_format)
     data(odor)
     data(odor.dist)
     data(door_global_normalization_weights)
     data(door_excluded_data)
     data(door_mappings)
     data(ORs)
     data(door_response_matrix)
     data(door_response_range)
     data(door_response_matrix_non_normalized)
   See section ‘Good practice’ in ‘?data’.

many problems above:

  • don't assign variables to the global environment
  • see ‘Good practice’ in ‘?data’ for help on data objects
  • you have many Undefined global functions or variables
  • A LOT OF warnings about "no visible binding for global variable' - fix those

@Dahaniel
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Dahaniel commented Apr 19, 2017

Thanks for the comments @sckott

  • Looks like you still don't have unit tests - please add those

That is right, as explained before I do not have a clue about unit testing and
might need some help here. However I read Hadley's piece on testthat and
think I could implement some simple tests like checking against creation of
empty data frames etc.

  • You have a circularity problem in your dependencies. DoOR.data is in DEPENDS
    in this pkg, and DoOR.functions is in Suggests for the DoOR.data package - why
    is DoOR.data in Depends? there's very few cases in which that's needed, is it
    here?

True, in an earlier mail you suggested to put the data package into DEPENDS, I
had it in SUGGESTS before. The reason being that DoOR.functions depends on
some of the data provided in the DoOR.data package. This is also the reason
for the undefined global functions or variables below.

  • R check reveals many problems: you need to Rbuildignore
    .travis.yml/CHANGELOG.md (but you should also have a NEWS.md or NEWS as that's
    more typical of R packages),

ok

  • don't assign variables to the global environment
  • see ‘Good practice’ in ‘?data’ for help on data objects

As discussed in #35 (comment) this is how the package was initially written: "Load data into the
global environment so that it is easily visible and edible for the user". I am
looking into ways to rewrite that (started a branch for that). But this
is not simple as I might need to write lots of helper functions for the user to easily interact
with the data.

As described, my workaround for now was to create a user interaction upon
package loading. I prompt a warning message and the user has to explicitly type
"yes" to load the data.

  • you have many Undefined global functions or variables

These are from the DoOR.data package and that is why I put it to DEPENDS.
Would putting it to SUGGESTS and the using DoOR.data:: work? But then if
e.g. a user modified version of door_response_matrix exists in the global
environment, the function should use this version and not pick the one from the
DoOR.data package, which it would using the package:: annotation, right?

  • A LOT OF warnings about "no visible binding for global variable' - fix those

Many of the arise from using ggplot functions. I just learned about:

## quiets concerns of R CMD check re: the .'s that appear in pipelines
if(getRversion() >= "2.15.1")  utils::globalVariables(c("."))

here STAT545-UBC/Discussion#451

summary

Points 1,3 & 7 I think I can fix. I would need some advice to fix
the circularity in 2/6. For point 4/5 I do not see an easy fix for now and I
hoped the warning and explicit user interaction will be a sufficient
workaround for now.

@sckott
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sckott commented Jun 12, 2017

@Dahaniel okay, let me know when you're done

@mpadge mpadge mentioned this issue Jun 24, 2017
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@sckott
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sckott commented Jul 11, 2017

@Dahaniel anything to report on this?

@Dahaniel
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Dahaniel commented Jul 15, 2017

@sckott I implemented unit testing in the data package, for the functions package I scheduled implementation for 1st half of August.

@sckott
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sckott commented Jul 24, 2017

Okay, thanks much

@sckott
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sckott commented Aug 11, 2017

just checking in @Dahaniel - i'm waiting on this correct:

for the functions package I scheduled implementation for 1st half of August.

@Dahaniel
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Dahaniel commented Aug 16, 2017

@sckott quick update: I am working on this but it'll take a few more days.

@Dahaniel
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Dahaniel commented Aug 25, 2017

Ok, should be done.

I fixed:

  • added basic unit tests to both packages
  • fixed the 'no visible binding for global variable'
  • moved CHANGELOG to NEWS.md
  • added entries to .Rbuildignore

there remains:

  • a NOTE about loading data to the global environment that will stay for now (see The Database of Odorant Responses (DoOR.data) #35 (comment))
  • circularity: Not sure what is the appropriate solution: I kept DoOR.data in Depends as the algorithms in DoOR.functions need data from DoOR.data to run (vignettes and examples would not work without). DoOR.functions is in suggests in DoOR.data as the two packages basically belong together.

@sckott
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sckott commented Sep 5, 2017

@Dahaniel

For the data issue: isn't it possible to do this approach:

  • use the default data.frame in DooR.data package (NOT loaded into the global namespace, but only in the package namespace)
  • optionally, the user can pass in a modified version of the data.frame to a parameter in the function; overriding the default data.frame
  • for the user to get access to the data.frame to modify it, they could simply load via data(..) i think

this should get around the problem of the package loading data into the global namespace

i think we do need to solve this issue as CRAN will likely not accept it as is


I think the circularity thing is actually okay - as long as one has the other in Suggests

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sckott commented Sep 5, 2017

There's a few more things to fix. These are all quite important to fix.

GP DoOR.functions ─────

It is good practice toomit "Date" in DESCRIPTION. It is not required and it
    gets invalid quite often. A build date will be added to the package
    when you perform `R CMD build` on it.avoid long code lines, it is bad for readability. Also,
    many people prefer editor windows that are about 80 characters
    wide. Try make your lines shorter than 80 characters

    R/back_project.R:53:1
    R/back_project.R:56:1
    R/back_project.R:65:1
    R/back_project.R:68:1
    R/back_project.R:69:1
    ... and 434 more linesavoid sapply(), it is not type safe. It might return a
    vector, or a list, depending on the input data. Consider using
    vapply() instead.

    R/calculate_model.R:48:19
    R/get_dataset.R:25:15
    R/get_dataset.R:26:22
    R/get_responses.R:36:36
    R/import_new_data.R:94:29
    ... and 12 more linesavoid 1:length(...), 1:nrow(...), 1:ncol(...),
    1:NROW(...) and 1:NCOL(...) expressions. They are error prone and
    result 1:0 if the expression on the right hand side is zero. Use
    seq_len() or seq_along() instead.

    R/count_studies.R:31:13
    R/door_melt.R:29:13
    R/dplot_tuningCurve.R:82:35
    R/dplot_tuningCurve.R:110:36
    R/get_responses.R:33:13
    ... and 19 more linesavoid 'T' and 'F', as they are just variables which are
    set to the logicals 'TRUE' and 'FALSE' by default, but are not
    reserved words and hence can be overwritten by the user.  Hence,
    one should always use 'TRUE' and 'FALSE' for the logicals.

    R/back_project.R:NA:NA
    R/get_dataset.R:NA:NA
    R/map_receptor.R:NA:NA
    R/rebuild_metadata.R:NA:NA

@Dahaniel
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Dahaniel commented Sep 6, 2017

Thanks @sckott , how can I reproduce the good practice output you posted here?

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sckott commented Sep 6, 2017

install devtools::install_github("MangoTheCat/goodpractice") then run .Sys.setenv(NOT_CRAN = "true"); x = goodpractice::gp(); x

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sckott commented Oct 12, 2017

any thoughts @Dahaniel ?

@Dahaniel
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Dahaniel commented Oct 14, 2017

Hi @sckott , sorry, busy as usual.
I actually startet working on fixing the "good practice" warnings and am done with the data package.
Regarding the data issue: What makes it complicated is that it is actually not a single data.frame which is accessed but many and that there are many functions that need to be updated. So I think this will take some effort for writing as well as testing.
If ok for you I would rather fix the GP issues now for the onboarding and then have CRAN compatibility as a new milestone afterwards.

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sckott commented Nov 10, 2017

@Dahaniel Okay, did you get to fixing these goodpractice problems yet?

@Dahaniel
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Dahaniel commented Nov 17, 2017

@sckott Should be fixed for both packages, shortened code-lines, replaced sapply with vapply etc...

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sckott commented Nov 22, 2017

@Dahaniel thanks, having a look

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sckott commented Feb 9, 2018

Sorry for the very long wait @Dahaniel !

Approved! Thanks again for your submission

  • Please transfer the package to ropensci- I've invited you to a team within our ropensci organization. After you accept you should be able to move it.
  • Make sure to
    • add rOpenSci footer to README
      [![ropensci_footer](https://ropensci.org/public_images/ropensci_footer.png)](https://ropensci.org)
    • Change any needed links, such those for CI badges
    • Travis CI should update to the new location automatically - you may have to update other CI systems manually
  • Add dotgithub files, see https://github.com/ropensci/dotgithubfiles to make sure users report session info, etc. and to give guidance on how to contribute - issue and PR template probably can be used as is, but feel free to modify CONTRIBUTING as you like
  • We're starting to roll out software metadata files to all ropensci pkgs via the Codemeta initiative, see https://github.com/ropensci/codemetar/#codemetar for how to include it in your pkg, after installing the pkg - should be easy as running codemetar::write_codemeta() in the root of your pkg
  • Add the "Peer-reviewed" status badge to your README:
[![](https://badges.ropensci.org/34_status.svg)](https://github.com/ropensci/onboarding/issues/34)

@Dahaniel
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Dahaniel commented Feb 11, 2018

That's awesome news! I'll see to your points in the coming days and I am happy to write a blog-post as well.

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Dahaniel commented Feb 12, 2018

@sckott where should I look for the invitation to the ROpenSci group? Could not find anything on github or in my mails.

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sckott commented Feb 12, 2018

sorry about that, you should see a notification now or soon

@stefaniebutland
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stefaniebutland commented Feb 12, 2018

Hello @Dahaniel. Great to hear you're interested in writing a blog post about this. Here are some technical and editorial notes for contributing a post: https://github.com/ropensci/roweb2#contributing-a-blog-post

We ask that you submit a draft via pull request at least one week prior to the planned publication date. I have two dates open right now. Take your pick:

  1. Tues Feb 20 (draft due Wed Feb 14 if possible)
  2. Tues Mar 20 (draft due Tues Mar 13)

@Dahaniel
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Dahaniel commented Feb 12, 2018

Thanks @stefaniebutland, I pick March 20th then!

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stefaniebutland commented Feb 12, 2018

Let me know if I can help along the way

@Dahaniel
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Dahaniel commented Feb 24, 2018

@stefaniebutland is there a guideline or a specific structure that I should follow when writing the blog post?

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stefaniebutland commented Feb 25, 2018

@Dahaniel No specific structure. The best approach might be to read a few other blog posts about onboarded packages and see which ones you like / which ones have a narrative that grabs you. This blog tag gets you to some posts: https://ropensci.org/tags/review/

Some basic suggestions here: https://github.com/ropensci/roweb2#blog-post-editorial-suggestions

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stefaniebutland commented Feb 25, 2018

If it would help, I could give you feedback on an outline where you identify audience, take home message and key points you want to get across. No obligation to do this

@sckott sckott closed this as completed Mar 6, 2018
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