From 3cd2a26276e55b67a10efc65cf0c4b5788f8e052 Mon Sep 17 00:00:00 2001 From: Peter Killick Date: Thu, 7 Jun 2018 16:23:24 +0100 Subject: [PATCH 1/2] Blurb updates --- docs/iris/src/_templates/index.html | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/docs/iris/src/_templates/index.html b/docs/iris/src/_templates/index.html index 2a9dc7913f..648102710b 100644 --- a/docs/iris/src/_templates/index.html +++ b/docs/iris/src/_templates/index.html @@ -77,38 +77,38 @@

Iris implements a data model based on the CF conventions - giving you a powerful, format-agnostic, interface for working with your data. + giving you a powerful, format-agnostic interface for working with your data. It excels when working with multi-dimensional Earth Science data, where tabular representations become unwieldy and inefficient.

CF Standard names, units, and coordinate metadata - are built-in to Iris, giving you a rich and expressive interface for maintaining - an accurate representation of your data. Its first-class treatment of data and - associated metadata includes: + are built into Iris, giving you a rich and expressive interface for maintaining + an accurate representation of your data. Its treatment of data and + associated metadata as first-class objects includes:

A number of file formats are recognised by Iris, including CF-compliant NetCDF, GRIB, and PP, and it has a plugin architecture to allow other formats to be added seamlessly.

- Building upon numpy and + Building upon NumPy and dask, Iris scales from efficient single-machine workflows right through to multi-core clusters and HPC. - Interoperability with packages from the wider scientific python ecosystem comes from Iris' - use of standard numpy/dask arrays as its underlying data storage. + Interoperability with packages from the wider scientific Python ecosystem comes from Iris' + use of standard NumPy/dask arrays as its underlying data storage.

From dd162550bbd85828070f6638d145c228c492335c Mon Sep 17 00:00:00 2001 From: Peter Killick Date: Thu, 7 Jun 2018 16:41:47 +0100 Subject: [PATCH 2/2] Doc changes replicated in readme --- README.md | 28 ++++++++++++++-------------- docs/iris/src/_templates/index.html | 2 +- 2 files changed, 15 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index fab6b7a459..e4b0fef54f 100644 --- a/README.md +++ b/README.md @@ -50,32 +50,32 @@ # Overview Iris implements a data model based on the [CF conventions](http://cfconventions.org/) -giving you a powerful, format-agnostic, interface for working with your data. +giving you a powerful, format-agnostic interface for working with your data. It excels when working with multi-dimensional Earth Science data, where tabular representations become unwieldy and inefficient. [CF Standard names](http://cfconventions.org/standard-names.html), [units](https://github.com/SciTools/cf_units), and coordinate metadata -are built-in to Iris, giving you a rich and expressive interface for maintaining -an accurate representation of your data. Its first-class treatment of data and -associated metadata includes: +are built into Iris, giving you a rich and expressive interface for maintaining +an accurate representation of your data. Its treatment of data and + associated metadata as first-class objects includes: - * aggregations and reductions (min, max, (area-)weighted mean, etc.) - * interpolation and regridding (nearest-neighbor, linear, area-weighted, etc.) - * operator overloads (``+``, ``-``, ``*``, ``/``, etc.) - * merge and concatenate - * subsetting and extraction - * unit conversion * a visualisation interface based on [matplotlib](https://matplotlib.org/) and - [cartopy](https://scitools.org.uk/cartopy/docs/latest/) + [cartopy](https://scitools.org.uk/cartopy/docs/latest/), + * unit conversion, + * subsetting and extraction, + * merge and concatenate, + * aggregations and reductions (including min, max, mean and weighted averages), + * interpolation and regridding (including nearest-neighbor, linear and area-weighted), and + * operator overloads (``+``, ``-``, ``*``, ``/``, etc.) A number of file formats are recognised by Iris, including CF-compliant NetCDF, GRIB, and PP, and it has a plugin architecture to allow other formats to be added seamlessly. -Building upon [numpy](http://www.numpy.org/) and [dask](https://dask.pydata.org/en/latest/), +Building upon [NumPy](http://www.numpy.org/) and [dask](https://dask.pydata.org/en/latest/), Iris scales from efficient single-machine workflows right through to multi-core clusters and HPC. -Interoperability with packages from the wider scientific python ecosystem comes from Iris' -use of standard numpy/dask arrays as its underlying data storage. +Interoperability with packages from the wider scientific Python ecosystem comes from Iris' +use of standard NumPy/dask arrays as its underlying data storage. # Documentation diff --git a/docs/iris/src/_templates/index.html b/docs/iris/src/_templates/index.html index 648102710b..a58e956c56 100644 --- a/docs/iris/src/_templates/index.html +++ b/docs/iris/src/_templates/index.html @@ -95,7 +95,7 @@
  • subsetting and extraction,
  • merge and concatenate,
  • aggregations and reductions (including min, max, mean and weighted averages),
    • -
  • interpolation and regridding (including nearest-neighbor, linear, area-weighted), and
    • +
  • interpolation and regridding (including nearest-neighbor, linear and area-weighted), and
  • operator overloads (+, -, *, /, etc.).