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module myna.database.pelican

Database class for extracting data from MDF Pelican build data

class Pelican

Database of Pelican data for a directed energy deposition build

method Pelican.__init__

__init__()

method Pelican.clean_build_data

clean_build_data(df)

Cleans pelican data to ensure that there are no null rows left in the DataFrame

Args:

  • df: (polars.DataFrame) DataFrame containing "x (mm)", "y (mm)", "z (mm)", "time (s)" and "time" columns

method Pelican.convert_dataframe_to_myna_scanpath

convert_dataframe_to_myna_scanpath(df, power=1)

Converts a polars.DataFrame in the initialize_dataframe() schema to a Myna scan path.

Args:

  • df: (polars.DataFrame)
  • power: (float) Power, in Watts

method Pelican.exists

exists()

method Pelican.get_scan_path

get_scan_path(part, layer)

Extracts the scan path file for the database if needed, then returns the scanpath file path

Args:

  • part: (str) part name to extract data for
  • layer: (int) "layer" corresponding to the time_segment for the part in the Myna input file

method Pelican.get_segment_details

get_segment_details(part, layer)

Gets the start and end time and starting details for the given "layer" in the part. This is a translation layer between the time-segment nature of the Pelican database and the layer structure of the myna.core.workflow.config functionality.

Args:

  • part: (str) part name to extract data for
  • layer: (str) "layer" corresponding to the time_segment for the part in the Myna input file

method Pelican.initialize_dataframe

initialize_dataframe(
    segment_dict=None,
    epoch=datetime.datetime(1970, 1, 1, 0, 0)
)

Loads the raw x, y, z, and time data from the Pelican simulation data directory.

Args:

  • path: (str) path to the Pelican directory
  • segment_dict: (None, {x,y,z,onoff,time}) dictionary describing segment start/end conditions
  • datatype: (str) ["raw", "resampled"] type of data to load from Pelican
  • epoch: (datetime.datetime instance) datetime object to use as the epoch

Returns: polars.DataFrame instance with the columns: - "x (mm)": float, X-coordinate in meters at given time - "y (mm)": float, Y-coordinate in meters at given time - "z (mm)": float, Z-coordinate in meters at given time - "time (s)": float, time in seconds corresponding to the XYZ location - "time": pl.Datetime, time since epoch

method Pelican.load

load(metadata_type, part=None, layer=None)

Load and return a metadata value from the database

Note that layer is never used, because Pelican does not have the layer concept

method Pelican.load_build_data

load_build_data(
    datatype='raw',
    segment_dict=None,
    epoch=datetime.datetime(1970, 1, 1, 0, 0)
)

Loads the raw x, y, z, and time data from the Pelican simulation data directory.

Args:

  • datatype: (str) ["raw", "resampled"] type of data to load from Pelican
  • epoch: (datetime.datetime instance) datetime object to use as the epoch

Returns: polars.DataFrame instance with the columns defined by initialize_dataframe()

method Pelican.set_path

set_path(path)

Set the path to the database

Args:

  • path: filepath to the directory containing Pelican build data

method Pelican.sync

sync(component_type, step_types, output_class, files)

Sync result files to the database using Pelican-style directory and file structure.

Args:

  • component_type: (str) name of workflow component app, i.e., Component.component_application
  • step_types: (list of str) list of workflow component types, i.e., Component.types
  • output_class: class object for the output file, e.g., Component.output_requirement
  • files: List of files to sync for the passed workflow component

Returns:

  • synced_files: list of files that were synced

For each time segment (i.e., "layer"): 1. Open the corresponding data file (CSV?, Arrow?, Parquet?, HDF5?) 2. Get all compatible time-series data from the completed Myna Components 3. Write all time-series data to the file with each row being a unique time and each column corresponding to the variable name (consider overwrite behavior) 4. Close the file stream

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