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"info": {
"author": "konbraphat51, superhotdogcat",
"author_email": "konbraphat51@gmail.com, siromisochan@gmail.com",
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"Development Status :: 1 - Planning",
"Intended Audience :: Developers",
"Intended Audience :: Information Technology",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Topic :: Multimedia :: Video",
"Topic :: Scientific/Engineering :: Information Analysis",
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"description": "# AnimatedWordCloud ver 1.0.9\n\n![](\"https://api.codeclimate.com/v1/badges/7a03252f77e7af46dc0f/maintainability\")
\n[](https://app.codacy.com/gh/konbraphat51/AnimatedWordCloud/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)\n[](https://github.com/konbraphat51/AnimatedWordCloud/actions/workflows/python-tester.yml)[](https://codecov.io/gh/konbraphat51/AnimatedWordCloud)\n\nAnimatedWordCloud animates the timelapse of your words vector.\n\n## Examples!\n\nUsing [Elon Musk's tweets](https://data.world/adamhelsinger/elon-musk-tweets-until-4-6-17). \n(C) Elon Musk\n\n\n\n[Procedure Notebook](https://github.com/konbraphat51/AnimatedWordCloudExampleElon)\n\n## How to use?\n\n### Requirements\n\nPython (3.8 <= version <= 3.12)\n\n### install\n\n**BE CAREFUL of the name**\n\n\u274cAnimatedWordCloud \n\u2705AnimatedWordCloudTimelapse\n\n```\npip install AnimatedWordCloudTimelapse\n```\n\n### coding\n\nSee [Example Notebook](https://github.com/konbraphat51/AnimatedWordCloudExampleElon) for details\n\n#### Using default configuration\n\n```python\nfrom AnimatedWordCloud import animate\n\n# data must be list[(\"time name\", dict[str, float])]\ntimelapse_wordvector = [\n (\n \"time_0\", #time stamp\n {\n \"hanshin\":0.334, #word -> weight\n \"chiba\":0.226\n }\n ),\n (\n \"time_1\",\n {\n \"hanshin\":0.874,\n \"fujinami\":0.609\n }\n ),\n (\n \"time_2\",\n {\n \"fujinami\":0.9,\n \"major\":0.4\n }\n )\n]\n\n# animate!\n# the animation gif path is in this variable!\npath = animate(timelapse_wordvector)\n```\n\n#### Editing configuration\n\n```python\nfrom AnimatedWordCloud import animate, Config\n\nconfig = Config(\n what_you_want_to_edit = editing_value\n)\n\ntimelapse = # adding time lapse data\n\n#give the config to second parameter\nanimate(timelapse, config)\n```\n\n##### Parameters of `Config`\n\nAll has default value, so just edit what you need\n\n| parameter name | type | meaning |\n| -------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |\n| font_path | str | Path to the font file. |\n| output_path | str | Parh of the output directory |\n| max_words | int | max number of the words in the screen |\n| max_font_size | int | Maximum font size of the word |\n| min_font_size | int | Minimum font size of the word |\n| image_width | int | Width of the image |\n| image_height | int | Height of the image |\n| background_color | str | Background color.
This is based on [Pillow.Image.new()](https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.new) |\n| color_map | str | color map used for coloring words
This is based on [matplotlib colormap](https://matplotlib.org/stable/users/explain/colors/colormaps.html) |\n| allocation_strategy | str(literal) | allocation algorithm method. This will change the allocation of the words in the output.
There is \"magnetic\" now. |\n| image_division | int | precision of allocation calculation. Higher the preciser, but calculation slower |\n| movement_reluctance | float | Reluctance of the movement of the word. If higher, the word tends to stay near to the previous position. |\n| verbosity | str(literal) | logging.
silent: nothing
minor: bars to know the progress
debug: all progress. noisy |\n| transition_symbol | str | written in the image |\n| starting_time_stamp | str | time stamp of the first frame (before the first time stamp in the input timelapse data) |\n| duration_per_interpolation_frame | int | milliseconds per interpolation frame |\n| duration_per_static_frame | int | milliseconds per staic (frame correspond to timestamp of wordvector) frame |\n| n_frames_for_interpolation | int | how many frames will be generated for interpolation between each frames |\n| interpolation_method | str(literal) | The method of making movement
There is \"linear\" now |\n| drawing_time_stamp | bool | Whether to draw time stamp on the image |\n| 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) |\n| time_stamp_font_size | int | Font size of the time stamp.
If None(default), it will be set to 75% of max_font_size |\n| 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. |\n| 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. |\n\n## Want to contribute?\n\nLook at [CONTRIBUTING.md](CONTRIBUTING.md) first.\n\n### Maintainers\n\n- [Konbraphat51](https://github.com/konbraphat51): Head Author \n [](https://github.com/konbraphat51)\n\n- [SuperHotDogCat](https://github.com/SuperHotDogCat): Author \n [](https://github.com/SuperHotDogCat)\n\n## Want to support?\n\n**\u2b50Give this project a star\u2b50** \nThis is our first OSS project, \u2b50**star**\u2b50 would make us very happy\u2b50\u2b50\u2b50\n",
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