Core#

seismoviz.core.read_catalog(source, **kwargs)#

Creates a Catalog object from either a CSV file path or a pandas DataFrame.

Parameters:

sourcestr or pd.DataFrame: Either a path to a CSV file containing the seismic catalog or a pandas DataFrame with the catalog data already loaded.
**kwargs: Additional keyword arguments to pass to pandas.read_csv() when source is a file path.

Returns:

Catalog: An instance of the Catalog class with the data loaded.

Examples

From a CSV file:

# Reading a catalog from a CSV file
catalog = sv.read_catalog(
    source='seismic_data.csv'
)

From a DataFrame:

# Creating a catalog from an existing DataFrame
catalog = sv.read_catalog(source=df)

Warning

The input must contain the following columns: lon, lat, time, depth, mag, and id. If any of these columns are missing, an error will be raised.

seismoviz.core.create_cross_section(catalog, center, num_sections, thickness, strike, map_length, depth_range, section_distance=1.0)#

Creates a seismic cross-section from a given Catalog.

Parameters:

catalogCatalog: An instance of the Catalog class containing seismic event data.
centertuple[float, float]: A tuple representing the geographical coordinates (longitude, latitude) of the center of the cross-section.
num_sectionstuple[int, int]: A tuple specifying the number of sections to create to the left and right of the center (e.g., (2, 2) will create 2 sections on each side of the center).
thicknessint: The maximum distance (in km) that events can be from the cross-section plane to be included in the section.
strikeint: The strike angle (in degrees) of the cross-section, measured clockwise from north. Cross section will be computed perpendicular to strike.
map_lengthfloat: The length of the cross-section (in km), which determines the horizontal extent of the plotted data.
depth_rangetuple[float, float]: A tuple specifying the minimum and maximum depth (in km) of events to include in the cross-section.
section_distancefloat, optional: The distance (in km) between adjacent sections. Default is 1.

Returns:

CrossSection: An instance of the CrossSection class with the seismic events that fit the specified parameters.

Examples

cs = sv.create_cross_section(
    catalog=catalog,
    center=(13.12, 42.83),
    num_sections=(2,2),
    thickness=1,
    strike=155,
    map_length=40,
    depth_range=(0, 10),
    section_distance=2
)

The output will be a CrossSection object. To access the data, you can use the cs.data attribute, which is a DataFrame containing all the events within the sections. Each event is labeled with a section_id, allowing you to easily identify which section it belongs to.

seismoviz.select(instance, x=None, y=None, custom=False, section_ids=None, **kwargs)#

Launch an interactive tool to select seismic events.

Note

When custom is True, you can choose which graph to use for the sections by selecting the columns with x and y. Otherwise, the selection is set automatically: a Catalog instance produces a map selection, while a CrossSection instance produces a cross-section selection.

Parameters:

instancetype: An object containing seismic data and plotting configurations.
xstr, optional: The column name for the x-axis variable. Required if custom is True.
ystr, optional: The column name for the y-axis variable. Required if custom is True.
custombool, optional: Flag to indicate if a custom selection should be used. Defaults to False.
section_idsint, list, optional: When the instance is a CrossSection, this parameter allows specifying which section(s) to display. Can be a single section ID (int) or a list of IDs. If specified, only events from the selected section(s) will be displayed.
**kwargsdict, optional: Additional keyword arguments for customizing the selection.

Returns:

An interactive selection object with a confirm_selection() method.

Raises:

ValueError: If custom is True and either x or y is not provided, or if the type of instance is unsupported.

Core#

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