https://github.com/maciejkula/dynarray

Dynamic Numpy arrays
https://github.com/maciejkula/dynarray

Last synced: about 1 month ago
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Dynamic Numpy arrays

• Host: GitHub
• URL: https://github.com/maciejkula/dynarray
• Owner: maciejkula
• License: mit
• Created: 2016-09-19T04:11:30.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-02-26T22:48:11.000Z (over 7 years ago)
• Last Synced: 2024-08-10T10:52:40.311Z (3 months ago)
• Language: Python
• Size: 14.6 KB
• Stars: 13
• Watchers: 3
• Forks: 2
• Open Issues: 2
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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README

        
# Dynarray

[![CircleCI](https://circleci.com/gh/maciejkula/dynarray.svg?style=svg)](https://circleci.com/gh/maciejkula/dynarray)

Dynamically growable Numpy arrays. They function exactly like normal numpy arrays, but support appending new elements.

# Installation

Simply install from PyPI: `pip install dynarray`

# Quickstart

Create an empty one-dimensional array and append elements to it:

```python

from dynarray import DynamicArray

array = DynamicArray()

for element in range(10):

    array.append(element)

```

Create a multidimensional array and append rows:

```python

from dynarray import DynamicArray

# The leading dimension is None to denote that this is

# the dynamic dimension

array = DynamicArray((None, 20, 10))

array.append(np.random.random((20, 10)))

array.extend(np.random.random((100, 20, 10)))

print(array.shape)  # (101, 20, 10)

```

Slice and perform arithmetic like with normal numpy arrays:

```python

from dynarray import DynamicArray

array = DynamicArray(np.ones((100, 10)), dtype=np.float16)

assert array[10:11].sum() == 10.0

print(array[10])

array[10] *= 0.0

assert array[10].sum() == 0.0

```

Shrink to fit to minimize memory usage when no further resizing is needed:

```python

from dynarray import DynamicArray

array = DynamicArray(np.ones((100, 10)), dtype=np.float16)

array.extend(np.ones((50, 10)))

assert array.capacity == 200

array.shrink_to_fit()

assert array.capacity == 150

```