# LinePlot ## Introduction **`LinePlot`** widget in Supervisely is a widget that allows users to display one or more lines of data in a plot. It provides a canvas area that can be customized with various options, such as line smoothing, axis labels, and displaying legends. `LinePlot` widget is useful for visualizing time-series data or data with continuous variables. ## Function signature ```python x1 = list(range(10)) y1 = [random.randint(10, 148) for _ in range(10)] x2 = list(range(30)) y2 = [random.randint(1, 300) for _ in range(30)] line_plot = LinePlot("My Line Plot") line_plot.add_series("Line 1", x1, y1) line_plot.add_series("Line 2", x2, y2) ``` or ```python size1 = 10 x1 = list(range(size1)) y1 = np.random.randint(low=10, high=148, size=size1).tolist() s1 = [{"x": x, "y": y} for x, y in zip(x1, y1)] size2 = 30 x2 = list(range(size2)) y2 = np.random.randint(low=0, high=300, size=size2).tolist() s2 = [{"x": x, "y": y} for x, y in zip(x2, y2)] line_plot = LinePlot( title="My Line Plot", series=[{"name": "Line 1", "data": s1}, {"name": "Line 2", "data": s2}], smoothing_weight=0, group_key=None, show_legend=True, decimals_in_float=2, xaxis_decimals_in_float=None, yaxis_interval=None, widget_id=None, yaxis_autorescale=True, ) ```

### series Determine list of input data series. **type:** `list` **default value:** `[]` ```python size1 = 10 x1 = list(range(size1)) y1 = np.random.randint(low=10, high=148, size=size1).tolist() s1 = [{"x": x, "y": y} for x, y in zip(x1, y1)] size2 = 30 x2 = list(range(size2)) y2 = np.random.randint(low=0, high=300, size=size2).tolist() s2 = [{"x": x, "y": y} for x, y in zip(x2, y2)] line_chart = LinePlot( title="Max vs Denis", series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}], ) ```

### smoothing\_weight Determine `LinePlot` smoothing. **type:** `int` **default value:** `0` ### group\_key Synced `LinePlot` key. **type:** `str` **default value:** `None` ### show\_legend Determine showing legend on `LinePlot`. **type:** `bool` **default value:** `True` ```python line_chart = LinePlot( title="Max vs Denis", series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}], show_legend=False, ) ```

### decimals\_in\_float The number of fractions to display floating values in `Y` axis. **type:** `int` **default value:** `2` ### xaxis\_decimals\_in\_float The number of fractions to display floating values in `X` axis. **type:** `int` **default value:** `None` ```python line_chart = LinePlot( title="Max vs Denis", series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}], xaxis_decimals_in_float=44, ) ```

### yaxis\_interval Determine min and max values on `Y` axis (e.g. \[0, 1]). **type:** `list` **default value:** `None` ```python line_chart = LinePlot( title="Max vs Denis", series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}], yaxis_interval=[0, 200], ) ```

### yaxis\_autorescale Set autoscaling of the `Y` axis. **type:** `bool` **default value:** `True` ### widget\_id ID of the widget. **type:** `str` **default value:** `None` ## Methods and attributes | Attributes and Methods | Description | | :---------------------------------------------------------------------------------------: | ---------------------------------------------- | | `update_y_range(ymin: int, ymax: int)` | Update `LinePlot` data. | | `add_series(name: str, x: list, y: list, send_changes: bool = True)` | Add new series of data in `LinePlot`. | | `add_series_batch(series: list)` | Add new series of data in `LinePlot` by batch. | | `add_to_series(name_or_id: str or int, data: List[tuple] or List[dict] or tuple or dict)` | Add data to existing series. | | `get_series_by_name(name: str)` | Return series data by name. | ## Mini App Example You can find this example in our GitHub repository: [ui-widgets-demos/charts and plots/005\_line\_plot/src/main.py](https://github.com/supervisely-ecosystem/ui-widgets-demos/blob/master/charts%20and%20plots/005_line_plot/src/main.py) ### Import libraries ```python import os import numpy as np import supervisely as sly from supervisely.app.widgets import Card, Container, LinePlot from dotenv import load_dotenv ``` ### Init API client First, we load environment variables with credentials and init API for communicating with Supervisely Instance: ```python load_dotenv("local.env") load_dotenv(os.path.expanduser("~/supervisely.env")) api = sly.Api() ``` ### Prepare series for plot ```python size1 = 10 x1 = list(range(size1)) y1 = np.random.randint(low=10, high=148, size=size1).tolist() s1 = [{"x": x, "y": y} for x, y in zip(x1, y1)] size2 = 30 x2 = list(range(size2)) y2 = np.random.randint(low=0, high=300, size=size2).tolist() s2 = [{"x": x, "y": y} for x, y in zip(x2, y2)] ``` ### Initialize `LinePlot` widget ```python line_chart = LinePlot( title="Max vs Denis", series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}], show_legend=False, ) ``` ### Create app layout Prepare a layout for app using `Card` widget with the `content` parameter and place widget that we've just created in the `Container` widget. ```python card = Card( title="Line Plot", content=line_chart, ) layout = Container(widgets=[card]) ``` ### Create app using layout Create an app object with layout parameter. ```python app = sly.Application(layout=layout) ```

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