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Move keyfeatures to a grid of cards
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Moving keyfeatures to a grid of cards. This PR is a part of the ongoing work to adopt the styling from pydata-sphinx-theme where possible.
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InessaPawson authored Feb 21, 2024
2 parents 5ae2bd2 + 59cd8bd commit 764ee22
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49 changes: 49 additions & 0 deletions content/en/_index.md
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---
title:
---

{{< grid columns="1 2 2 3" >}}

{{< card >}}
title = 'Powerful N-dimensional arrays'
body = '''
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
'''
{{< /card >}}

{{< card >}}
title = 'Numerical computing tools'
body = '''
NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
'''
{{< /card >}}

{{< card >}}
title = 'Open source'
body = '''
Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/main/LICENSE.txt), NumPy is developed and maintained [publicly on GitHub](https://github.com/numpy/numpy) by a vibrant, responsive, and diverse [community](/community).
'''
{{< /card >}}

{{< card >}}
title = 'Interoperable'
body = '''
NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
'''
{{< /card >}}

{{< card >}}
title = 'Performant'
body = '''
The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
'''
{{< /card >}}

{{< card >}}
title = 'Easy to use'
body = '''
NumPy's high level syntax makes it accessible and productive for programmers from any background or experience level.
'''
{{< /card >}}

{{< /grid >}}
15 changes: 0 additions & 15 deletions content/en/config.yaml
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Expand Up @@ -50,21 +50,6 @@ params:
alttext: Cheetah pose analysis
url: /case-studies/deeplabcut-dnn

keyfeatures:
features:
- title: Powerful N-dimensional arrays
text: Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
- title: Numerical computing tools
text: NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
- title: Open source
text: Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/main/LICENSE.txt), NumPy is developed and maintained [publicly on GitHub](https://github.com/numpy/numpy) by a vibrant, responsive, and diverse [community](/community).
- title: Interoperable
text: NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
- title: Performant
text: The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
- title: Easy to use
text: NumPy's high level syntax makes it accessible and productive for programmers from any background or experience level.

tabs:
title: ECOSYSTEM

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52 changes: 52 additions & 0 deletions content/ja/_index.md
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---
title:
---

{{< grid columns="1 2 2 3" >}}

{{< card >}}
title = '強力な多次元配列'
body = '''
NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタ>ンダードです。
'''
{{< /card >}}

{{< card >}}
title = '数値計算ツール群'
body = '''
NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。
'''
{{< /card >}}

{{< card >}}
title = '相互運用性'
body = '''
NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対
応しています。
'''
{{< /card >}}

{{< card >}}
title = '高パフォーマンス'
body = '''
NumPyの大部分は最適化されたC言語のコードで構成されています。これによりPythonの柔軟性とコンパイルされたコードの高速性の両方
を享受できます。
'''
{{< /card >}}

{{< card >}}
title = '使いやすさ'
body = '''
NumPyの高水準なシンタックスは、どんなバックグラウンドや経験を持つのプログラマーでも簡単に利用することができ、生産性を高め>ることができます。
'''
{{< /card >}}

{{< card >}}
title = 'オープンソース'
body = '''
NumPyは、寛容な[BSDライセンス](https://github.com/numpy/numpy/blob/main/LICENSE.txt)で公開されています。NumPyは活発で、互>いを尊重し、多様性を認め合う[コミュニティ](/ja/community)によって、 [GitHub](https://github.com/numpy/numpy)上でオープンに開発されていま
す.
'''
{{< /card >}}

{{< /grid >}}
20 changes: 0 additions & 20 deletions content/ja/config.yaml
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Expand Up @@ -50,26 +50,6 @@ params:
img: /images/content_images/case_studies/deeplabcut.png
alttext: チータの姿勢推定
url: /ja/case-studies/deeplabcut-dnn
keyfeatures:
features:
-
title: 強力な多次元配列
text: NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタンダードです。
-
title: 数値計算ツール群
text: NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。
-
title: 相互運用性
text: NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対応しています。
-
title: 高パフォーマンス
text: NumPyの大部分は最適化されたC言語のコードで構成されています。これによりPythonの柔軟性とコンパイルされたコードの高速性の両方を享受できます。
-
title: 使いやすさ
text: NumPyの高水準なシンタックスは、どんなバックグラウンドや経験を持つのプログラマーでも簡単に利用することができ、生産性を高めることができます。
-
title: オープンソース
text: NumPyは、寛容な[BSDライセンス](https://github.com/numpy/numpy/blob/main/LICENSE.txt)で公開されています。NumPyは活発で、互いを尊重し、多様性を認め合う[コミュニティ](/ja/community)によって、 [GitHub](https://github.com/numpy/numpy)上でオープンに開発されています.
tabs:
title: NumPyのエコシステム
section5: false
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49 changes: 49 additions & 0 deletions content/pt/_index.md
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@@ -0,0 +1,49 @@
---
title:
---

{{< grid columns="1 2 2 3" >}}

{{< card >}}
title = 'Arrays n-dimensionais poderosas'
body = '''
Rápidos e versáteis, os conceitos de vetorização, indexação e broadcasting do NumPy são, na prática, o padrão em computação com arrays.
'''
{{< /card >}}

{{< card >}}
title = 'Ferramentas de computação numérica'
body = '''
O NumPy oferece um conjunto completo de funções matemáticas, geradores de números aleatórios, rotinas de álgebra linear, transformadas de Fourier, e mais.
'''
{{< /card >}}

{{< card >}}
title = 'Interoperabilidade'
body = '''
O NumPy suporta um grande número de plataformas de hardware e computação, e pode ser combinado com bibliotecas de computação com arrays esparsas, distribuidas ou em GPUs.
'''
{{< /card >}}

{{< card >}}
title = 'Alto desempenho'
body = '''
O núcleo do NumPy é feito de código otimizado em C. Experimente a flexibilidade do Python com a velocidade de código compilado.
'''
{{< /card >}}

{{< card >}}
title = 'Fácil de usar'
body = '''
A sintaxe de alto nível do NumPy torna-o acessível e produtivo para programadores de qualquer nível de experiência e formação.
'''
{{< /card >}}

{{< card >}}
title = 'Código aberto'
body = '''
Distribuido com uma [licença BSD](https://github.com/numpy/numpy/blob/main/LICENSE.txt) liberal, o NumPy é desenvolvido e mantido [publicamente no GitHub](https://github.com/numpy/numpy) por uma [comunidade](/pt/community) vibrante, responsiva, e diversa.
'''
{{< /card >}}

{{< /grid >}}
20 changes: 0 additions & 20 deletions content/pt/config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -50,26 +50,6 @@ params:
img: /images/content_images/case_studies/deeplabcut.png
alttext: Análise de pose de um guepardo
url: /pt/case-studies/deeplabcut-dnn
keyfeatures:
features:
-
title: Arrays n-dimensionais poderosas
text: Rápidos e versáteis, os conceitos de vetorização, indexação e broadcasting do NumPy são, na prática, o padrão em computação com arrays.
-
title: Ferramentas de computação numérica
text: O NumPy oferece um conjunto completo de funções matemáticas, geradores de números aleatórios, rotinas de álgebra linear, transformadas de Fourier, e mais.
-
title: Interoperabilidade
text: O NumPy suporta um grande número de plataformas de hardware e computação, e pode ser combinado com bibliotecas de computação com arrays esparsas, distribuidas ou em GPUs.
-
title: Alto desempenho
text: O núcleo do NumPy é feito de código otimizado em C. Experimente a flexibilidade do Python com a velocidade de código compilado.
-
title: Fácil de usar
text: A sintaxe de alto nível do NumPy torna-o acessível e produtivo para programadores de qualquer nível de experiência e formação.
-
title: Código aberto
text: Distribuido com uma [licença BSD](https://github.com/numpy/numpy/blob/main/LICENSE.txt) liberal, o NumPy é desenvolvido e mantido [publicamente no GitHub](https://github.com/numpy/numpy) por uma [comunidade](/pt/community) vibrante, responsiva, e diversa.
tabs:
title: ECOSSISTEMA
section5: false
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