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ARCCSS Data Archive Tools

Project description

ARCCSS Data Access Tools

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For full documentation please see


### Raijin

The stable version of ARCCSSive is available on Rajin in the `analysis27` Anaconda environment:

raijin $ module use /g/data3/hh5/public/modules
raijin $ module load conda/analysis27

and is also available as a module:

raijin $ module use ~access/modules
raijin $ module load pythonlib/ARCCSSive

### NCI Virtual Desktops

NCI's virtual desktops allow you to use ARCCSSive from a Jupyter notebook. For
details on how to use virtual desktops see

ARCCSSive can be accessed on VDI using the Anaconda environments:

vdi $ module use /g/data3/hh5/public/modules
vdi $ module load conda/analysis27

### Local Install

You can install ARCCSSive locally using either Anaconda or Pip. You will need
to copy the database file from Raijin

$ pip install ARCCSSive
# or
$ conda install -c coecms arccssive

$ scp raijin:/g/data1/ua6/unofficial-ESG-replica/tmp/tree/cmip5_raijin_latest.db $PWD/cmip5.db
$ export CMIP5_DB=sqlite:///$PWD/cmip5.db

### Development Version

To install the current development version with a test database:

$ pip install --user git+
$ export CMIP5_DB=sqlite:///$HOME/cmip5.db


Query and access the CMIP5 data from Raijin

from ARCCSSive import CMIP5

cmip = CMIP5.DB.connect()
for output in cmip.outputs(model='ACCESS1-0'):
variable = output.variable
files = output.filenames()

to filter and sort the data files.

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