ssscoring.mapview

  1# See: https://github.com/pr3d4t0r/SSScoring/blob/master/LICENSE.txt
  2
  3from geopy import distance
  4from ssscoring.datatypes import JumpResults
  5
  6import pandas as pd
  7import pydeck as pdk
  8
  9
 10# *** constants ***
 11
 12DISTANCE_FROM_MIDDLE = 400.0
 13"""
 14The distance in meters from the middle of the skydive to the outer bounding box
 15for the initial view of a new rendered map.
 16"""
 17
 18
 19# *** implementation ***
 20
 21def viewPointBox(data: pd.DataFrame) -> pd.DataFrame:
 22    """
 23    Calculate the NW and SE corners of a "box" delimiting the viewport area
 24    `DISTANCE_FROM_MIDDLE` meters away from the middle of the speed skydive.
 25
 26    Arguments
 27    ---------
 28        data
 29    A SSScoring dataframe with jump data.
 30
 31    Returns
 32    -------
 33    The NW and SE corners of the box, as terrestrial coordinates, in a dataframe
 34    with these columns:
 35
 36    - `latitude`
 37    - `lontigude`
 38
 39    See
 40    ---
 41    `ssscoring.calc.convertFlySight2SSScoring`
 42    """
 43    mid = len(data)//2
 44    datum = data.iloc[mid]
 45    origin = (datum.latitude, datum.longitude)
 46    pointNW = distance.distance(meters=DISTANCE_FROM_MIDDLE).destination(origin, bearing=315)
 47    pointSE = distance.distance(meters=DISTANCE_FROM_MIDDLE).destination(origin, bearing=135)
 48    data = list(zip([ pointNW[0], pointSE[0], ], [ pointNW[1], pointSE[1], ]))
 49    result = pd.DataFrame(data, columns=[ 'latitude', 'longitude', ])
 50    return result
 51
 52
 53def _resolveMaxSpeedTimeFrom(jumpResult: JumpResults) -> float:
 54    plotTime = jumpResult.scores[jumpResult.score]
 55
 56    return plotTime
 57
 58
 59def speedJumpTrajectory(jumpResult: JumpResults) -> pdk.Deck:
 60    """
 61    Build the layers for a PyDeck map showing a jumper's trajectory.
 62
 63    Arguments
 64    ---------
 65        jumpResult
 66    A SSScoring `JumpResults` instance with the results of the jump.
 67
 68    Returns
 69    -------
 70    A PyDeck `deck` instance ready for rendering using PyDeck or Streamlit
 71    mapping facilities.
 72
 73    See
 74    ---
 75    `st.pydeck_chart`
 76    `st.map`
 77    """
 78    workData = jumpResult.data.copy()
 79    maxSpeedTime = _resolveMaxSpeedTimeFrom(jumpResult)
 80    layers = [
 81        pdk.Layer(
 82            'ScatterplotLayer',
 83            data=workData,
 84            # get_color=[ 0, 160, 0, 128 ],
 85            get_color=[ 0, 192, 0, 255 ],
 86            get_position=[ 'longitude', 'latitude', ],
 87            t_radius=4),
 88        pdk.Layer(
 89            'ScatterplotLayer',
 90            data=workData.head(1),
 91            get_color=[ 255, 126, 0, 255 ],
 92            get_position=[ 'longitude', 'latitude', ],
 93            get_radius=8),
 94        pdk.Layer(
 95            'ScatterplotLayer',
 96            data=workData.tail(1),
 97            get_color=[ 0, 192, 0, 160 ],
 98            get_position=[ 'longitude', 'latitude', ],
 99            get_radius=8),
100        pdk.Layer(
101            'ScatterplotLayer',
102            data=workData[workData.plotTime == maxSpeedTime],
103            get_color=[ 0, 255, 0, ],
104            get_position=[ 'longitude', 'latitude', ],
105            get_radius=12),
106    ]
107    viewBox = viewPointBox(workData)
108    deck = pdk.Deck(
109        map_style = None,
110        initial_view_state=pdk.data_utils.compute_view(viewBox[['longitude', 'latitude',]]),
111        layers=layers
112    )
113    return deck