processing.py

# -*- coding: utf-8 -*-

import numpy as np
import xarray as xr
import metpy.calc as mpcalc
import itertools


from matplotlib import pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature

def populate_object(obj_props, path):
    # obj_props.num_nodes = len(path)
    # fill the properties defined in the .proto file.

    # vertices of path
    min_lat, max_lat, min_lon, max_lon = 90.0, -90.0, 180.0, -180.0
    dist_deg = 0.0
    for v_idx, v in enumerate(path.vertices):
        line_pt = obj_props.line_pts.add()
        line_pt.lon = v[0]
        line_pt.lat = v[1]

        if v[0] < min_lon:
            min_lon = v[0]
        if v[0] > max_lon:
            max_lon = v[0]
        if v[1] < min_lat:
            min_lat = v[1]
        if v[1] > max_lat:
            max_lat = v[1]

        if v_idx > 0:
            dist_deg = dist_deg + (((path.vertices[v_idx - 1][0] - v[0]) ** 2 + (path.vertices[v_idx - 1][1] - v[1]) ** 2) ** 0.5)

    # bounding box
    obj_props.bb.min.lat = min_lat
    obj_props.bb.min.lon = min_lon
    obj_props.bb.max.lat = max_lat
    obj_props.bb.max.lon = max_lon

    obj_props.length_deg = dist_deg

# identify troughs in data (should contain U,V,cv), based on the cv climatology
# def identify_troughs(data, cv_clim, cfg):