viz.yaml: How to write a viz.yaml
In USGS-VIZLAB/vizlab: Utilities for building online data visualizations
Description
See the testviz directory for an example, and see below for a detailed
description.
fetch
The fetch section takes a list of items. Each item is a raw data file.
Items always have a id field. They also always have information,
either explicit or implicit, about how to (1) fetch and (2) read the data
file.
Fields describing (1) fetch include fetcher, which can take the
values file or sciencebase, If sciencebase, then the
remoteItemId field should also be included and should be the
24-digit hexadecimal ScienceBase item ID, and the remoteFilename
should be included and should be the filename as the item is stored on
ScienceBase.
Fields describing (2) read include mimeType, which can take the
values text/csv, text/tab-seperated-values, text/yaml,
or
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet.
If the reader function is unspecified then a default reader will use the
mimeType to determine how to read the data file into R.
Alternatively, the customReader field may be included with a value
describing a custom reading function defined in the scripts|lib folder,
where the function has the name readData.mytype and the value in the
customReader field is mytype. For example, you could define a
custom function called readData.netCDF and give customReader:
netCDF. If both customReader and mimeType are specified, mimeType will be
passed as a second argument to the customReader function.
The export tag is by default true for figures, false for data and
munged. but can be set for any of those classes of items. Any item for
which export=true will be copied to the target directory when the full
visualization is built.
If the customReader argument is ever given, the code will automatically
source all files in scripts/read before trying to run the customReader.
USGS-VIZLAB/vizlab documentation built on July 10, 2019, 12:08 a.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
See the testviz directory for an example, and see below for a detailed description.
fetch
The fetch section takes a list of items. Each item is a raw data file.
Items always have a id field. They also always have information,
either explicit or implicit, about how to (1) fetch and (2) read the data
file.
Fields describing (1) fetch include fetcher, which can take the
values file or sciencebase, If sciencebase, then the
remoteItemId field should also be included and should be the
24-digit hexadecimal ScienceBase item ID, and the remoteFilename
should be included and should be the filename as the item is stored on
ScienceBase.
Fields describing (2) read include mimeType, which can take the
values text/csv, text/tab-seperated-values, text/yaml,
or
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet.
If the reader function is unspecified then a default reader will use the
mimeType to determine how to read the data file into R.
Alternatively, the customReader field may be included with a value
describing a custom reading function defined in the scripts|lib folder,
where the function has the name readData.mytype and the value in the
customReader field is mytype. For example, you could define a
custom function called readData.netCDF and give customReader:
netCDF. If both customReader and mimeType are specified, mimeType will be
passed as a second argument to the customReader function.
The export tag is by default true for figures, false for data and
munged. but can be set for any of those classes of items. Any item for
which export=true will be copied to the target directory when the full
visualization is built.
If the customReader argument is ever given, the code will automatically source all files in scripts/read before trying to run the customReader.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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