AnimatedWordCloud ver 1.0.9

AnimatedWordCloud animates the timelapse of your words vector.

Examples!

Using Elon Musk's tweets.
(C) Elon Musk

Procedure Notebook

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 for details

Using default configuration

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

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()
color_map	str	color map used for coloring words This is based on matplotlib colormap
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
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_width0.75, image_height0.75) which is right bottom.
intermediate_frames_id	str	Static images of each frame of itermediate product will be saved as "{intermediateframes_id}{frame_number}.png". If None(default), this will be set randomly.

Want to contribute?

Look at CONTRIBUTING.md first.

Maintainers

• Konbraphat51: Head Author
  

• SuperHotDogCat: Author
  

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