What is the translation of " NUMPY " in Chinese?

• numpy
• 一个numpy

Examples of using Numpy in English and their translations into Chinese

Numpy indices start with zero.
NumPy数组的下标从0开始。

Let's say that I have the following numpy array:.
比如我有个numpyarray如下：.

I wonder if numpy provides a built-in way to do a partial sort;
我想知道是否numpy提供了一种内置的方式来进行局部排序;

How do you calculate percentiles with Python/ NumPy?
如何计算百分位数与Python/numpy的.

These data structures are built on top of Numpy which means they are fast.
这些数据结构构建在Numpy数组之上，这意味着它们效率很高。

In numpy, some of the operations return in shape(R, 1) but some return(R,).
在numpy中，有些运算返回shape为(R,1)而有些返回(R,)。

How to get indices of N maximum values in a NumPy array?
如何在numpy数组中获取N个最大值的索引？?

NumPy, SciPy and MatPlotLib will be of interest to engineers, but thats just the start.
像NumPy，SciPy和MatPlotLib这样的库将会对工程师有很大帮助，但这些仅仅是一小部分。

To manage this Q table, we will use a NumPy array.
未来管理这个Q表，我们会使用一个NumPy的array列表。

Since we will use the Numpy methods to read and write files, you may skip this chapter at first reading.
由于我们将使用Numpy方法读取和写入文件，你可以在第一次阅读时跳过本章。

Suppose that the input volume is a numpy array X. Then:.
假设输入存储在一个numpyarrayX里，那么：.

This NumPy stack has similar users to other applications such as MATLAB, GNU Octave, and Scilab.
这个NumPy具有与其他应用程序类似的用户，例如MATLAB、GNUOctave和Scilab。

Q39How to get indices of N maximum values in a NumPy array?
Python-如何在NumPy数组中获得N个最大值的索引？?

We can use the randn() NumPy function to generate a sample of random numbers drawn from a Gaussian distribution.
我们可以使用NumPy的randn()函数，生成从高斯分布中抽取的随机数的样本。

Throughout this chapter, and indeed the rest of the book, you will find that this is the way we will import and use NumPy.
在本章以及本书的其余部分中，你会发现这是我们导入和使用NumPy的方式。

If you are a NumPy user who requires ongoing Python2 support in 2020 or later, then please contact your vendor.
如果您是一个NumPy用户，需要在2020年或以后使用python支持，那么请联系您的供应商。

No surprises here, the most popular data science frameworks and libraries are: NumPy, Pandas, Matplotlib, and SciPy.
毫不奇怪，最受欢迎的数据科学框架和库是：NumPy，Pandas，Matplotlib和SciPy。

The Scikit-Learn library uses NumPy arrays in its implementation, so we will use NumPy to load*. csv files.
Scikit-Learn库在它的实现用使用了NumPy数组，所以我们将用NumPy来加载*.csv文件。

Glue is written in Python, and built on top of its standard scientific libraries(i.e., Numpy, Matplotlib, Scipy).
Glue是用Python编写的，并且建立在其标准科学库（即Numpy，Matplotlib，Scipy）之上。

Denis Yarats uses NumPy, pandas, and scikit-learn for general machine learning:“I like their simplicity and transparency.
DenisYarats使用NumPy，pandas和scikit-learn进行一般机器学习：“我喜欢它们的简洁性和透明度。

Python JIT(just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
Numba-PythonJIT(justintime)编译器，针对科学用的Python，由Cython和NumPy的开发者开发.

Traditionally, we start our list with the libraries for scientific applications, and NumPy is one of the principal packages in this area.
传统上，我们从科学应用程序库开始列表，而NumPy是这一领域的主要软件包之一。

IPython notebook and NumPy can be used as a scratchpad for lighter work, while Python is a powerful tool for medium-scale data processing.
IPythonnotebook和NumPy可以用于轻量工作的处理，而Python则是中级规模数据处理的有力工具。

Keras provides a convenient handler for importing the dataset which is also available as a serialized numpy array. npz file to download here.
Keras提供了一个方便的函数来导入该数据集，同时也可以在这里下载一个序列化的numpyarray.npy文件。

However, one of NumPy's important goals is compatibility, so NumPy tries to retain all features supported by either of its predecessors.
但是，NumPy的一个重要目标是兼容性，因此NumPy试图保留其前任任何一个支持的所有功能。

So, the main purpose to develop this language is to emphasize code readability and scientific and mathematical computing(e.g. NumPy, SymPy, Orange).
因此，开发这种语言的主要目的是强调代码的可读性以及科学和数学计算(NumPy，SymPy,Orange)。

Scikit-learn is designed on three other open source projects- matplotlib, NumPy, and SciPy- and it focuses on data mining and data analysis.
Scikit-learn是在另外三个开源项目Matplotlib，NumPy和SciPy上设计的，它专注于数据挖掘和数据分析。

This module allows developers to transparently support these accelerated functions when scipy is available but still support users who have only installed NumPy.
此模块允许开发人员在scipy可用时透明地支持这些加速功能，但仍然支持只安装了Numpy的用户。

Furthermore, our NumPy solution involves both Python-stack recursions and the allocation of many temporary arrays, which adds significant computation time.
此外，我们的NumPy的解决方案，同时涉及的Python堆栈递归和许多临时数组的分配，这显著地增加了计算时间。

PyCharm integrates with Jupyter Notebook, has an interactive Python console, and supports Anaconda as well as multiple scientific packages including Matplotlib and NumPy.
PyCharm与IPythonNotebook集成，具有交互式Python控制台，并支持Anaconda以及多个科学软件包，包括matplotlib和NumPy。