https://github.com/konbraphat51/animatedwordcloud
Animate a timelapse of word cloud
https://github.com/konbraphat51/animatedwordcloud
animation datascience natural-language-processing nlp video visualization wordcloud
Last synced: 5 months ago
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Animate a timelapse of word cloud
- Host: GitHub
- URL: https://github.com/konbraphat51/animatedwordcloud
- Owner: konbraphat51
- License: mit
- Created: 2023-11-15T15:09:24.000Z (over 2 years ago)
- Default Branch: dev
- Last Pushed: 2024-05-02T06:08:27.000Z (about 2 years ago)
- Last Synced: 2025-09-25T07:25:13.490Z (9 months ago)
- Topics: animation, datascience, natural-language-processing, nlp, video, visualization, wordcloud
- Language: Python
- Homepage: https://pypi.org/project/AnimatedWordCloudTimelapse/
- Size: 1.41 MB
- Stars: 18
- Watchers: 1
- Forks: 1
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
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README
# AnimatedWordCloud ver 1.0.9
[](https://app.codacy.com/gh/konbraphat51/AnimatedWordCloud/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
[](https://github.com/konbraphat51/AnimatedWordCloud/actions/workflows/python-tester.yml)[](https://codecov.io/gh/konbraphat51/AnimatedWordCloud)
AnimatedWordCloud animates the timelapse of your words vector.
## Examples!
Using [Elon Musk's tweets](https://data.world/adamhelsinger/elon-musk-tweets-until-4-6-17).
(C) Elon Musk
[Procedure Notebook](https://github.com/konbraphat51/AnimatedWordCloudExampleElon)
## How to use?
### Requirements
Python (3.8 <= version <= 3.12)
### install
**BE CAREFUL of the name**
❌AnimatedWordCloud
✅AnimatedWordCloudTimelapse
```
pip install AnimatedWordCloudTimelapse
```
### coding
See [Example Notebook](https://github.com/konbraphat51/AnimatedWordCloudExampleElon) for details
#### Using default configuration
```python
from AnimatedWordCloud import animate
# data must be list[("time name", dict[str, float])]
timelapse_wordvector = [
(
"time_0", #time stamp
{
"hanshin":0.334, #word -> weight
"chiba":0.226
}
),
(
"time_1",
{
"hanshin":0.874,
"fujinami":0.609
}
),
(
"time_2",
{
"fujinami":0.9,
"major":0.4
}
)
]
# animate!
# the animation gif path is in this variable!
path = animate(timelapse_wordvector)
```
#### Editing configuration
```python
from AnimatedWordCloud import animate, Config
config = Config(
what_you_want_to_edit = editing_value
)
timelapse = # adding time lapse data
#give the config to second parameter
animate(timelapse, config)
```
##### Parameters of `Config`
All has default value, so just edit what you need
| parameter name | type | meaning |
| -------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| font_path | str | Path to the font file. |
| output_path | str | Parh of the output directory |
| max_words | int | max number of the words in the screen |
| max_font_size | int | Maximum font size of the word |
| min_font_size | int | Minimum font size of the word |
| image_width | int | Width of the image |
| image_height | int | Height of the image |
| background_color | str | Background color.
This is based on [Pillow.Image.new()](https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.new) |
| color_map | str | color map used for coloring words
This is based on [matplotlib colormap](https://matplotlib.org/stable/users/explain/colors/colormaps.html) |
| allocation_strategy | str(literal) | allocation algorithm method. This will change the allocation of the words in the output.
There is "magnetic" now. |
| image_division | int | precision of allocation calculation. Higher the preciser, but calculation slower |
| movement_reluctance | float | Reluctance of the movement of the word. If higher, the word tends to stay near to the previous position. |
| verbosity | str(literal) | logging.
silent: nothing
minor: bars to know the progress
debug: all progress. noisy |
| transition_symbol | str | written in the image |
| starting_time_stamp | str | time stamp of the first frame (before the first time stamp in the input timelapse data) |
| duration_per_interpolation_frame | int | milliseconds per interpolation frame |
| duration_per_static_frame | int | milliseconds per staic (frame correspond to timestamp of wordvector) frame |
| n_frames_for_interpolation | int | how many frames will be generated for interpolation between each frames |
| interpolation_method | str(literal) | The method of making movement
There is "linear" now |
| drawing_time_stamp | bool | Whether to draw time stamp on the image |
| time_stamp_color | str | Color of the time stamp. This is based on [`Pillow ImageColor`](https://pillow.readthedocs.io/en/stable/reference/ImageColor.html#color-names) |
| time_stamp_font_size | int | Font size of the time stamp.
If None(default), it will be set to 75% of max_font_size |
| time_stamp_position | tuple[int, int] | Position of the time stamp.
If None(default), it will be set to (image_width*0.75, image_height*0.75) which is right bottom. |
| intermediate_frames_id | str | Static images of each frame of itermediate product will be saved as "{intermediate*frames_id}*{frame_number}.png".
If None(default), this will be set randomly. |
## Want to contribute?
Look at [CONTRIBUTING.md](CONTRIBUTING.md) first.
### Maintainers
- [Konbraphat51](https://github.com/konbraphat51): Head Author
[](https://github.com/konbraphat51)
- [SuperHotDogCat](https://github.com/SuperHotDogCat): Author
[](https://github.com/SuperHotDogCat)
## Want to support?
**⭐Give this project a star⭐**
This is our first OSS project, ⭐**star**⭐ would make us very happy⭐⭐⭐