MovingBubbles
- D3Blocks.movingbubbles(df, datetime: str = 'datetime', sample_id: str = 'sample_id', state: str = 'state', center: str = None, size=5, color=None, cmap: str = 'Set1', color_method: str = 'state', dt_format: str = '%d-%m-%Y %H:%M:%S', damper: float = 1, fontsize: int = 14, timedelta: str = 'minutes', standardize: str = 'samplewise', speed: dict = {'fast': 50, 'medium': 200, 'slow': 1000}, figsize=[700, 800], note: str = None, time_notes: str = None, title: str = 'Movingbubbles - D3Blocks', filepath: str = 'movingbubbles.html', showfig: bool = True, overwrite: bool = True, notebook: bool = False, save_button: bool = True, return_html: bool = False, reset_properties: bool = True)
Movingbubbles block.
The MovingBubbles provides insights into when one action follows the other across time. It can help to understand the movements of entities, and whether clusters occur at specific time points and state(s). It may not be the most visually efficient method, but it is one of the more visually satisfying ones with force-directed and colliding nodes. The function d3.import_example(‘random_time’) is created to generate a randomized dataset with various states. The input dataset should contain 3 columns;
DateTime column: Describes the data-time when an event occurs.
State column: Describes what the particular state was at that point of time of the specific sample_id.
Sample_id column: A sample can have multiple states at various time points but can not have two states at exactly the same point in time.
- Parameters:
df (Input data, pd.DataFrame()) – Input data.
datetime (str, (default: 'datetime')) – Name of the column with the datetime.
sample_id (str, (default: 'sample_id')) – Name of the column with the sample ids.
state (str, (default: 'state')) – Name of the column with the states.
center (String, (default: None)) – Center this category.
size (int or dictionary. (default: 5) or {sample_id i: size}) –
- Size the nodes by specifying per sample_id the size.
5: set all nodes this this size
{‘0’: 4, ‘1’: 10, ‘2’: 5, ..}: Specify size for each sample_id
color (int or dictionary. (default: '#808080') or {sample_id i: hex-color}) –
- Color the nodes by specifying per sample_id the color.
’#000FFF’: set all nodes to this color.
{‘0’: ‘#808080’, ‘1’: ‘#FFF000’, ‘3’: ‘#000000’, ..}: Specify color for each sample_id
None: Colors are based on sample_id using the cmap.
color_method (str) –
- Coloring of the nodes.
’state’: Use the colors defined per state as (d3.node_properties).
’node’: Use the colors defined in the dataframe (d3.edge_properties).
dt_format (str) –
- Date time format.
’%d-%m-%Y %H:%M:%S’.
damper (float, (default: 1)) –
- Movement of samples. A smaller number is slower/smoother movement.
0.1: min
10: max
fontsize (int, (default: 14)) – Fontsize of the states.
timedelta (String, (default: 'minutes')) –
- The time delta between states. Change accordingly.
’seconds’
’minutes’
’days’
standardize (str. (default: None)) –
- Method to standardize the data.
None: standardize over the entire timeframe. Sample_ids are dependent to each other.
’samplewise’: Standardize per sample_id by substracting the minimum time per sample_id.
’relative’: Standardize across the entire dataframe after sorting on time. Each action is relative to the previous one in time without considering sample_id.
’minimum’: Movements are relative to the minimum time in the dataset.
speed (dict, (default: {"stop": 100000, "slow": 1000, "medium": 200, "fast": 50})) – The final html file contains three buttons for speed movements. The lower the value, the faster the time moves.
note (str, (default: None)) –
- A specific note, such as project description can be put on the html page.
None: Default text will be provided about the simulation, and states.
time_notes (dict, (default: None)) –
- The time notes will be shown between specific time points.
- time_notes = [{“start_minute”: 1,
”stop_minute”: 5, “note”: “Enter your note here and it is shown between 1 min and 5 min.”}]
time_notes.append[{“start_minute”: 6, “stop_minute”: 10, “note”: “Enter your second note here and it is shown between 6 min and 10 min.”}]
cmap (String, (default: 'Set1')) –
- All colors can be reversed with ‘_r’, e.g. ‘binary’ to ‘binary_r’
’tab20c’, ‘Set1’, ‘Set2’
’rainbow’, ‘bwr’, ‘binary’, ‘seismic’
’Blues’, ‘Reds’, ‘Pastel1’, ‘Paired’
’twilight’, ‘hsv’, ‘inferno’
title (String, (default: None)) –
- Title of the figure.
’Movingbubbles’
filepath (String, (Default: user temp directory)) –
- File path to save the output.
Temporarily path: ‘d3blocks.html’
Relative path: ‘./d3blocks.html’
Absolute path: ‘c://temp//d3blocks.html’
None: Return HTML
figsize (tuple) –
- Size of the figure in the browser, [width, height].
[780, 800]
showfig (bool, (default: True)) –
True: Open browser-window.
False: Do not open browser-window.
overwrite (bool, (default: True)) –
True: Overwrite the html in the destination directory.
False: Do not overwrite destination file but show warning instead.
notebook (bool) –
True: Use IPython to show chart in notebook.
False: Do not use IPython.
save_button (bool, (default: True)) –
True: Save button is shown in the HTML to save the image in svg.
False: No save button is shown in the HTML.
return_html (bool, (default: False)) –
True: Return html
False: Nothing is returned
reset_properties (bool, (default: True)) –
True: Reset the node_properties at each run.
False: Use the d3.node_properties()
- Returns:
d3.node_properties (DataFrame of dictionary) – Contains properties of the unique input label/nodes/samples.
d3.edge_properties (DataFrame of dictionary) – Contains properties of the unique input edges/links.
d3.config (dictionary) – Contains configuration properties.
Examples
>>> # Load d3blocks >>> from d3blocks import D3Blocks >>> # >>> # Initialize >>> d3 = D3Blocks() >>> # >>> # Load example data >>> df = d3.import_example('random_time', n=10000, c=300, date_start="1-1-2000 00:10:05", date_stop="1-1-2000 23:59:59") >>> # >>> # Plot >>> d3.movingbubbles(df, speed={"stop": 100000, "slow": 1000, "medium": 200, "fast": 10}, filepath='movingbubbles.html') >>> #
Examples
>>> # Load d3blocks >>> from d3blocks import D3Blocks >>> # >>> # Initialize >>> d3 = D3Blocks(chart='movingbubbles', frame=False) >>> # >>> # Import example >>> df = d3.import_example('random_time', n=1000, c=100, date_start="1-1-2000 00:10:05", date_stop="1-1-2000 23:59:59") >>> # >>> # Coloring the states. >>> d3.set_node_properties(df['state']) >>> print(d3.node_properties) >>> # Color the sleeping state black >>> d3.node_properties.get('Sleeping')['color']='#000000' >>> # >>> d3.set_edge_properties(df) >>> print(d3.edge_properties) >>> # >>> # Show >>> d3.show(title='Movingbubbles with adjusted configurations')
Examples
>>> # Load d3blocks >>> import random >>> from d3blocks import D3Blocks >>> # >>> # Initialize >>> d3 = D3Blocks(chart='movingbubbles') >>> # >>> # Import example >>> df = d3.import_example('random_time', n=10000, c=300, date_start="1-1-2000 00:10:05", date_stop="1-1-2000 23:59:59") >>> # >>> # Specify the colors and node sizes for the specific sample_id or for demonstration, generated randomly >>> # size = {1: 15, 3: 30, 5: 25} >>> size = {i: random.randint(2, 15) for i in range(1, 100)} >>> color = {1: '#FF0000', 3: '#000FFF'} >>> # >>> # Show >>> d3.movingbubbles(df, color=color, size=size)
References
Input Data
The input data is a dataframe that should contain the columns datatime, sample_id and state. If the column names are different, then the column name can be specified.
# datetime sample_id state
# 0 2000-01-01 00:10:32 30 Sick
# 1 2000-01-01 00:10:36 23 Work
# 2 2000-01-01 00:11:16 179 Sleeping
# 3 2000-01-01 00:11:28 122 Sport
# 4 2000-01-01 00:13:02 226 Sleeping
# ... ... ...
# 9994 2000-01-01 23:59:56 300 Sleeping
# 9995 2000-01-01 23:59:57 217 Home
# 9996 2000-01-01 23:59:57 89 Sleeping
# 9997 2000-01-01 23:59:58 42 Sleeping
# 9998 2000-01-01 23:59:58 237 Work
# [9999 rows x 3 columns]