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modelling

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ivan-aksamentov
ivan-aksamentov commented Mar 17, 2020

In order to perform refactoring and to add new features with more confidence, we need unit, integration and end-to-end tests for:

  • algorithm parts. Seesrc/algorithms

  • React parts - components and pages. See src/components and src/pages

  • State management: redux reducers and sagas. See src/state

The infrastructure:

  • jest and @testing-libraryare already set up. Un
xificurC
xificurC commented Oct 24, 2019

Rich talks extensively about making the distinction about a schema and about the required data within a schema when being used. A person can have many things and only some (different) parts of its data will be required in different functions. That's what the new select is about. Is there similar functionality in malli? I see {:optional true} in an

simpeg
BluePyOpt
wvangeit
wvangeit commented Aug 2, 2016

Needs to allow for:

  • hoc code should be read from string (See #143). hoc_path is not necessary anymore. Should be first argument after name.
  • we need a morph_dir argument to specify morphology directory. when this is specified morph filename in hoc can be used.
  • morph_filename, overwrite morph_filename specified in hoc
  • hoc code should not have full path to morpho anymore (only morph_filename
NShaforostov
NShaforostov commented Nov 6, 2019

Describe the bug
When trying to download *.txt document from the pipeline DOCUMENTS tab - the downloaded file contains error instead of the document content

To Reproduce
Steps to reproduce the behavior:

  1. Open any pipeline, select the DOCUMENTS tab
  2. Upload the document with txt extension
  3. Click the Download button next to the uploaded document (or click the doc
davidruegamer
davidruegamer commented Apr 26, 2019
library(mboost)

myiris <- as.list(iris)
myiris$class <- factor(levels(iris$Species)[-nlevels(iris$Species)])

## Now fit the linear array model
mlm <- mboost(Species ~ bols(Sepal.Length, df = 2) %O%
                bols(class, df = 2, contrasts.arg = "contr.dummy"),
              data = myiris,
              family = Multinomial())

# works
predict(mlm)
# gives weird error messa

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