#!/usr/bin/env python3 # A script that takes a segmented graph in the gt format and performs the # non-local cost function calculation where each edge will have a cost # function assigned to it. # Inputs (to be changed within the script): # node_id_param_file # gt graph # shapefiles # Output: a gt graph with cost functions and an xml graph with cost functions import graph_tool import time import json import math from os import path import shapefile import datetime from numpy import loadtxt import report_graph import util_eddies import sys import bisect def calculate_radii_and_rossby(start, end, inc, segment, e_overestim, handlers, array_d_init): radii = 0 #[m] rossby = 0 #[1/s] days_modifier = 0 for i in range(start, end, inc): current_eddy = report_graph.node_to_date_eddy(segment[i], e_overestim) i_SHPC = get_SHPC(array_d_init, current_eddy['date_index']) # calculate the location in the shapefile location = util_eddies.comp_ishape(handlers[i_SHPC], current_eddy['date_index'], current_eddy['eddy_index']) # now that we have the location in the shapefiles, we need to # get the radius and the rossby number shapeRec = handlers[i_SHPC]["readers"]["extremum"].shapeRecord(location) # rossby: lat_in_deg = shapeRec.shape.points[0][1] #[deg] f = 2*2*math.pi/(24*3600)*math.sin(math.radians(lat_in_deg)) # [1/s] V_max = shapeRec.record[4] #[m/s] R_Vmax = handlers[i_SHPC]["readers"]["max_speed_contour"]\ .record(location)['r_eq_area'] * 1000 #[m] if (V_max < 100): # calculate Ro and Delta_Ro Ro = V_max / (f * R_Vmax) #[] else: Ro = 0 days_modifier += 1 ####### RADII ####### radii += R_Vmax # [m] ####### ROSSBY ###### rossby += Ro # [] return {"radii": radii, "rossby": rossby, "days_modifier": days_modifier} def get_SHPC(array_d_ini, date_index): i_SHPC = bisect.bisect(array_d_init, date_index) assert i_SHPC >= 1 return i_SHPC - 1 if len(sys.argv) == 1: sys.exit("Required arguments: SHPC-directory [SHPC-directory] ...") # Grab e_overestim: with open("node_id_param.json") as f: node_id_param = json.load(f) # assign attributes to the whole graphs e_overestim = node_id_param["e_overestim"] ################################################ # set some values needed for the cost function # ################################################ delta_cent_mean = 3.8481 # [km] delta_cent_std = 8.0388 delta_ro_mean = -0.0025965 # [] delta_ro_std = 5.2168 delta_r_mean = -0.0094709 * 1000 #[m] delta_r_std = 8.6953 * 1000 # Load the graph_tool file: t0 = time.perf_counter() timings = open("timings.txt", "w") print('Loading gt file...') g = graph_tool.Graph() try: g.load('segments.gt') except FileNotFoundError: g.load('segments.graphml') t1 = time.perf_counter() print("Input graph:") print("Number of vertices:", g.num_vertices()) print("Number of edges:", g.num_edges()) print("Internal properties:") g.list_properties() print('Loading done...') timings.write(f"loading: {t1 - t0} s\n") timings.close() g.set_fast_edge_removal() g.vp['pos_first'] = g.new_vp('object') g.vp['pos_last'] = g.new_vp('object') g.vp['first_av_rad'] = g.new_vp('float') g.vp['first_av_ros'] = g.new_vp('float') g.vp['last_av_rad'] = g.new_vp('float') g.vp['last_av_ros'] = g.new_vp('float') g.ep['nl_cost_function'] = g.new_ep('float') # Set up the list of SHPC: handlers = [util_eddies.open_shpc(shp_dir) for shp_dir in sys.argv[1:]] array_d_init = [handler["d_init"] for handler in handlers] # (create the list once and for all) # change if there is a change over the number of days to average num_of_days_to_avg = 7 # iterate on the vertices for n in g.vertices(): # Get the segment and the number of days segment = g.vp.segment[n] # calculate the indexes and dates first = report_graph.node_to_date_eddy(segment[0], e_overestim) first_SHPC = get_SHPC(array_d_init, first['date_index']) num_of_days = len(segment) # start processing last = report_graph.node_to_date_eddy(segment[-1], e_overestim) last_SHPC = get_SHPC(array_d_init, last['date_index']) # calculate the location in the shapefile first_loc = util_eddies.comp_ishape(handlers[first_SHPC], first['date_index'], first['eddy_index']) last_loc = util_eddies.comp_ishape(handlers[last_SHPC], last['date_index'], last['eddy_index']) # grab the centers first_pos = handlers[first_SHPC]["readers"]["extremum"]\ .shape(first_loc).points[0] last_pos = handlers[last_SHPC]["readers"]["extremum"]\ .shape(last_loc).points[0] ##### STORE POSITIONS IN THE VPS ###### g.vp.pos_first[n] = first_pos # [deg, deg] g.vp.pos_last[n] = last_pos # [deg, deg] # if the segments are longer than the # of days over which to avg if (num_of_days > num_of_days_to_avg): first_radii = 0 # [m] last_radii = 0 # [m] first_rossby = 0 # [] last_rossby = 0 # [] # First 7 days calculation first_res = calculate_radii_and_rossby(0, num_of_days_to_avg, 1, segment, e_overestim, handlers, array_d_init) # average and assign radii first_radii = first_res['radii'] / num_of_days_to_avg g.vp.first_av_rad[n] = first_radii # grab the days modifier modifier = first_res['days_modifier'] if (num_of_days_to_avg - modifier > 0): # Average and assign the rossbies: first_rossby = first_res['rossby'] / (num_of_days_to_avg - modifier) g.vp.first_av_ros[n] = first_rossby else: # there is division by zero, average rossby is undefinied pass # Last 7 days calculation last_res = calculate_radii_and_rossby(len(segment) - 1, len(segment) - (num_of_days_to_avg + 1), -1, segment, e_overestim, handlers, array_d_init) # Average and assign the last radii last_radii = last_res['radii'] / num_of_days_to_avg g.vp.last_av_rad[n] = last_radii # grab the days modifier modifier = last_res['days_modifier'] if (num_of_days_to_avg - modifier > 0): # Average and assign the rossbies: last_rossby = last_res['rossby'] / (num_of_days_to_avg - modifier) g.vp.last_av_ros[n] = last_rossby else: # there is division by zero, average rossby is undefinied pass # else, the number of eddies in a segment is lower than the # of # days over which to average, the values will be the same except # for the positions else: res = calculate_radii_and_rossby(0, num_of_days, 1, segment, e_overestim, handlers, array_d_init) # grab the days modifier modifier = res['days_modifier'] if (num_of_days - modifier > 0): # Average and assign the rossbies: rossby = res['rossby'] / (num_of_days - modifier) g.vp.first_av_ros[n] = rossby g.vp.last_av_ros[n] = rossby else: # there is division by zero, average rossby is undefinied pass # Average and assign the radii radii = res['radii'] / num_of_days g.vp.first_av_rad[n] = radii g.vp.last_av_rad[n] = radii ############################### # Calculate the cost function # ############################### for edge in g.edges(): source_node = edge.source() target_node = edge.target() cf = -10000 lat_for_conv = (g.vp.pos_last[source_node][1] + g.vp.pos_first[target_node][1]) / 2 # latitude needed for conversion of degrees to kilometers lat_for_conv = math.radians(lat_for_conv) # need to convert to radians # because of the wrapping issue (360° wrapping incorrectly to 0°), we check for that here lon_diff = abs(g.vp.pos_last[source_node][0] - g.vp.pos_first[target_node][0]) if (lon_diff > 300): lon_diff = 360 - lon_diff # calculate Delta_cent: numbers used for conversion obtained from: # https://stackoverflow.com/questions/1253499/simple-calculations-for-working-with-lat-lon-and-km-distance Delta_Cent = math.sqrt(( lon_diff * 111.32 * math.cos(lat_for_conv) )**2 + ( (g.vp.pos_last[source_node][1] - g.vp.pos_first[target_node][1]) * 110.574 )**2) # calculate the first term first_term = ((Delta_Cent - delta_cent_mean)/delta_cent_std) ** 2 # Rossbies: if (g.vp.first_av_ros[target_node] and g.vp.last_av_ros[source_node]): Delta_Ro = g.vp.last_av_ros[source_node] - g.vp.first_av_ros[target_node] else: print("At least one of the rossbies is invalid.") #Delta_Ro = delta_ro_mean Delta_Ro = 0 # Calculate the second term second_term = ((Delta_Ro - delta_ro_mean)/delta_ro_std ) ** 2 # R_Vmax 1 and 2 already exist, just get the delta Delta_R_Vmax = g.vp.last_av_rad[source_node] - g.vp.first_av_rad[target_node] # Calculate the third term third_term = ((Delta_R_Vmax - delta_r_mean)/delta_r_std) ** 2 ############################# # calculate the cost function ############################# cf = math.sqrt(first_term + second_term + third_term) # assign as weight to the edge g.ep.nl_cost_function[edge] = cf ################################ # Writing to an GT Graph File # ################################ #g.save("segments_cyclo_gl_cf.xml") #print("Done writing xml.") print("Done writing gt.") #g.save('segmented_cf.gv', fmt = "dot") #print("Done writing dot file.") g.save('segments_cost_functions.gt') print('All done')