add adddemand_nodes2nodes2 and adddemand_area2area2`

tests/test_other_functions.py

@@ -413,27 +413,27 @@ def test_shortest_path_costs():
     assert spd["orig", "mid2"] == 1000
     assert spd["mid1", "dest"] == 2000
     assert spd["mid2", "dest"] == 1000
-    assert spd["dest", "orig"] == np.Inf
+    assert spd["dest", "orig"] == np.inf
     assert spd[orig, dest] == 2000
-    assert spd[dest, orig] == np.Inf
+    assert spd[dest, orig] == np.inf
 
     spd = get_shortest_path_distance_between_all_nodes(W, return_matrix=True)
     assert spd[0, 3] == 2000
-    assert spd[3, 0] == np.Inf
+    assert spd[3, 0] == np.inf
 
     spt = get_shortest_path_instantaneous_travel_time_between_all_nodes(W)
     assert equal_tolerance(spt["orig", "dest"], 150)
     assert equal_tolerance(spt["orig", "mid1"], 50, rel_tol=0.2)
     assert equal_tolerance(spt["orig", "mid2"], 150)
     assert equal_tolerance(spt["mid1", "dest"], 100)
     assert equal_tolerance(spt["mid2", "dest"], 50, rel_tol=0.2)
-    assert spt["dest", "orig"] == np.Inf
+    assert spt["dest", "orig"] == np.inf
     assert equal_tolerance(spt[orig, dest], 150)
-    assert spt[dest, orig] == np.Inf
+    assert spt[dest, orig] == np.inf
 
     spt = get_shortest_path_instantaneous_travel_time_between_all_nodes(W, return_matrix=True)
     assert equal_tolerance(spt[0, 3], 150)
-    assert spt[3, 0] == np.Inf
+    assert spt[3, 0] == np.inf
 
     spt0 = get_shortest_path_instantaneous_travel_time_between_all_nodes_on_t(W,0)
     assert equal_tolerance(spt0["orig", "dest"], 100)
@@ -458,7 +458,7 @@ def test_shortest_path_costs():
 
     spt600_mat = get_shortest_path_instantaneous_travel_time_between_all_nodes_on_t(W, 600, return_matrix=True)
     assert equal_tolerance(spt600_mat[0, 3], 150)
-    assert spt600_mat[3, 0] == np.Inf
+    assert spt600_mat[3, 0] == np.inf
 
 def test_util_catch_exceptions_and_warn():
     with pytest.warns(UserWarning, match=r".*network().*"):
@@ -592,6 +592,111 @@ def test_area2area_demand_and_stats():
     assert df["average_free_travel_time"][(df["origin_area"] == "areaNW") & (df["destination_area"] == "areaSE")].values[0] == 400.0
     assert df["average_shortest_distance"][(df["origin_area"] == "areaNW") & (df["destination_area"] == "areaSE")].values[0] == 8000.0
 
+def test_adddemand_area2area2_nodes2nodes2():
+    W = World(
+        name="",
+        deltan=5,
+        tmax=7200,
+        print_mode=1, save_mode=1, show_mode=0,
+        random_seed=0
+    )
+
+    # scenario
+    #automated network generation
+    #deploy nodes as an imax x jmax grid
+    imax = 5
+    jmax = 5
+    nodes = {}
+    for i in range(imax):
+        for j in range(jmax):
+            nodes[i,j] = W.addNode(f"n{(i,j)}", i, j)
+
+    #create links between neighborhood nodes
+    links = {}
+    for i in range(imax):
+        for j in range(jmax):
+            if i != imax-1:
+                links[i,j,i+1,j] = W.addLink(f"l{(i,j,i+1,j)}", nodes[i,j], nodes[i+1,j], length=1000, free_flow_speed=20, jam_density=0.2)
+            if i != 0:
+                links[i,j,i-1,j] = W.addLink(f"l{(i,j,i-1,j)}", nodes[i,j], nodes[i-1,j], length=1000, free_flow_speed=20, jam_density=0.2)
+            if j != jmax-1:
+                links[i,j,i,j+1] = W.addLink(f"l{(i,j,i,j+1)}", nodes[i,j], nodes[i,j+1], length=1000, free_flow_speed=20, jam_density=0.2)
+            if j != 0:
+                links[i,j,i,j-1] = W.addLink(f"l{(i,j,i,j-1)}", nodes[i,j], nodes[i,j-1], length=1000, free_flow_speed=20, jam_density=0.2)
+
+    W.adddemand_nodes2nodes2(nodes.values(), nodes.values(), 0, 3600, volume=5000)
+    W.adddemand_area2area2(0, 0, 1.1, 5, 5, 1.1, 0, 3600, volume=5000)
+
+    W.finalize_scenario()
+
+    W.exec_simulation()
+
+    W.analyzer.print_simple_stats()
+
+    assert equal_tolerance(10000, len(W.VEHICLES)*W.DELTAT)
+
+def test_adddemand_area2area2_nodes2nodes2_scenario():
+    # simulation world
+    W = World(
+        name="",
+        deltan=5,
+        tmax=7200,
+        print_mode=1, save_mode=1, show_mode=0,
+        random_seed=0
+    )
+
+    # scenario
+    #automated network generation
+    #deploy nodes as an imax x jmax grid
+    imax = 5
+    jmax = 5
+    nodes = {}
+    for i in range(imax):
+        for j in range(jmax):
+            nodes[i,j] = W.addNode(f"n{(i,j)}", i, j)
+
+    #create links between neighborhood nodes
+    links = {}
+    for i in range(imax):
+        for j in range(jmax):
+            if i != imax-1:
+                links[i,j,i+1,j] = W.addLink(f"l{(i,j,i+1,j)}", nodes[i,j], nodes[i+1,j], length=1000, free_flow_speed=20, jam_density=0.2)
+            if i != 0:
+                links[i,j,i-1,j] = W.addLink(f"l{(i,j,i-1,j)}", nodes[i,j], nodes[i-1,j], length=1000, free_flow_speed=20, jam_density=0.2)
+            if j != jmax-1:
+                links[i,j,i,j+1] = W.addLink(f"l{(i,j,i,j+1)}", nodes[i,j], nodes[i,j+1], length=1000, free_flow_speed=20, jam_density=0.2)
+            if j != 0:
+                links[i,j,i,j-1] = W.addLink(f"l{(i,j,i,j-1)}", nodes[i,j], nodes[i,j-1], length=1000, free_flow_speed=20, jam_density=0.2)
+
+    W.adddemand_nodes2nodes2(nodes.values(), nodes.values(), 0, 3600, volume=5000)
+    W.adddemand_area2area2(0, 0, 1.1, 5, 5, 1.1, 0, 3600, volume=5000)
+
+    W.save_scenario("out/demandtest.uxsim_scenario")
+
+    W.exec_simulation()
+
+    W.analyzer.print_simple_stats()
+
+    #W.analyzer.network_fancy(animation_speed_inverse=15, sample_ratio=0.2, interval=5, trace_length=10,  figsize=6, antialiasing=False)
+    #display_image_in_notebook("out/anim_network_fancy.gif") 
+
+
+    ### ITER2
+
+    W2 = World(
+        name="",
+        deltan=5,
+        tmax=7200,
+        print_mode=1, save_mode=1, show_mode=0,
+        random_seed=0
+    )
+
+    W2.load_scenario("out/demandtest.uxsim_scenario")
+
+    W2.exec_simulation()
+    W2.analyzer.print_simple_stats()
+
+    assert W.analyzer.average_travel_time == W2.analyzer.average_travel_time
 
 @pytest.mark.flaky(reruns=10)
 def test_area_stats():

uxsim/__init__.py

@@ -3,7 +3,7 @@
 from .analyzer import *
 from .scenario_reader_writer import *
 
-__version__ = "1.6.0"
+__version__ = "1.7.0"
 __author__ = "Toru Seo"
 __copyright__ = "Copyright (c) 2023 Toru Seo"
 __license__ = "MIT License"

uxsim/scenario_reader_writer.py

@@ -202,10 +202,24 @@ def load_scenario(W, fname, network=True, demand=True):
                 for dem in dat[demand_type]:
                     W.adddemand_point2point(**dem)
                 print(f" Number of loaded `{demand_type}`s:", len( dat[demand_type]))
-            if demand_type == 'adddemand_area2area':
+            elif demand_type == 'adddemand_area2area':
                 for dem in dat[demand_type]:
                     W.adddemand_area2area(**dem)
                 print(f" Number of loaded `{demand_type}`s:", len( dat[demand_type]))
+            elif demand_type == 'adddemand_nodes2nodes':
+                for dem in dat[demand_type]:
+                    W.adddemand_nodes2nodes(**dem)
+                print(f" Number of loaded `{demand_type}`s:", len( dat[demand_type]))
+            elif demand_type == 'adddemand_area2area2':
+                for dem in dat[demand_type]:
+                    W.adddemand_area2area2(**dem)
+                print(f" Number of loaded `{demand_type}`s:", len( dat[demand_type]))
+            elif demand_type == 'adddemand_nodes2nodes2':
+                for dem in dat[demand_type]:
+                    W.adddemand_nodes2nodes2(**dem)
+                print(f" Number of loaded `{demand_type}`s:", len( dat[demand_type]))
+            else:
+                pass
 
 
 

uxsim/uxsim.py

@@ -6,6 +6,7 @@
 import csv, time, math, string, warnings, copy
 from collections import deque, OrderedDict
 from collections import defaultdict as ddict
+import warnings
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -941,7 +942,7 @@ def __init__(s, W, orig, dest, departure_time, name=None, route_pref=None, route
         else:
             s.route_pref = {l.id:route_pref[l] for l in route_pref.keys()}
 
-        #好むリンクと避けるリンク（近視眼的）1
+        #好むリンクと避けるリンク（近視眼的）
         s.links_prefer = [s.W.get_link(l) for l in links_prefer]
         s.links_avoid = [s.W.get_link(l) for l in links_avoid]
 
@@ -1777,7 +1778,7 @@ def adddemand_point2point(W, x_orig, y_orig, x_dest, y_dest, t_start, t_end, flo
     @demand_info_record
     def adddemand_area2area(W, x_orig, y_orig,  radious_orig, x_dest, y_dest, radious_dest, t_start, t_end, flow=-1, volume=-1, attribute=None, direct_call=True):
         """
-        Generate vehicles by specifying time-dependent origin-destination demand by specifying circular areas.
+        Generate vehicles by specifying time-dependent origin-destination demand by specifying circular areas. `adddemand_area2area()` is not recommended as it may truncate demand. Consider to use new `adddemand_area2area2()` which is more accurate, smooth, and fast.
 
         Parameters
         ----------
@@ -1804,6 +1805,11 @@ def adddemand_area2area(W, x_orig, y_orig,  radious_orig, x_dest, y_dest, radiou
         attribute : any, optinonal
             Additional (meta) attributes defined by users.
         """
+        warnings.warn(
+            "`adddemand_area2area()` is not recommended as it may truncate demand. Consider to use new `adddemand_area2area2()` which is more accurate, smooth, and fast.",
+            FutureWarning
+        )
+
         origs = W.get_nodes_in_area(x_orig, y_orig, radious_orig)
         dests = W.get_nodes_in_area(x_dest, y_dest, radious_dest)
 
@@ -1830,9 +1836,10 @@ def adddemand_area2area(W, x_orig, y_orig,  radious_orig, x_dest, y_dest, radiou
             for d in dests:
                 W.adddemand(o, d, t_start, t_end, flow, volume, attribute, direct_call=False)
 
-    def adddemand_nodes2nodes(W, origs, dests, t_start, t_end, flow=-1, volume=-1, attribute=None):
+    @demand_info_record
+    def adddemand_nodes2nodes(W, origs, dests, t_start, t_end, flow=-1, volume=-1, attribute=None, direct_call=True):
         """
-        Generate vehicles by specifying time-dependent origin-destination demand by specifying origin area (i.e., list of nodes) and destination one.
+        Generate vehicles by specifying time-dependent origin-destination demand by specifying origin area (i.e., list of nodes) and destination one. `adddemand_nodes2nodes()` is not recommended as it may truncate demand. Consider to use new `adddemand_nodes2nodes2() which is more accurate, smooth, and fast.
 
         Parameters
         ----------
@@ -1851,6 +1858,10 @@ def adddemand_nodes2nodes(W, origs, dests, t_start, t_end, flow=-1, volume=-1, a
         attribute : any, optinonal
             Additional (meta) attributes defined by users.
         """
+        warnings.warn(
+            "`adddemand_nodes2nodes()` is not recommended as it may truncate demand. Consider to use new `adddemand_nodes2nodes2() which is more accurate, smooth, and fast.`",
+            FutureWarning
+        )
 
         origs_new = []
         dests_new = []
@@ -1871,7 +1882,116 @@ def adddemand_nodes2nodes(W, origs, dests, t_start, t_end, flow=-1, volume=-1, a
             volume = volume/(len(origs)*len(dests))
         for o in origs:
             for d in dests:
-                W.adddemand(o, d, t_start, t_end, flow, volume, attribute, direct_call=True)
+                W.adddemand(o, d, t_start, t_end, flow, volume, attribute, direct_call=False)
+
+    @demand_info_record
+    def adddemand_area2area2(W, x_orig, y_orig,  radious_orig, x_dest, y_dest, radious_dest, t_start, t_end, flow=-1, volume=-1, attribute=None, direct_call=True):
+        """
+        Generate vehicles by specifying time-dependent origin-destination demand by specifying circular areas. This is new version of `adddemand_area2area`, more efficient, more smooth, and more accurate. However, it introduces some randomness.
+
+        Parameters
+        ----------
+        x_orig : float
+            The x-coordinate of the center of the origin area.
+        y_orig : float
+            The y-coordinate of the center of the origin area.
+        radious_orig : float
+            The radious of the origin area. Note that too large radious may generate too sparse demand that is rounded to zero.
+        x_dest : float
+            The x-coordinate of the center of the destination area.
+        y_dest : float
+            The y-coordinate of the center of the destination area.
+        radious_dest : float
+            The radious of the destination area.
+        t_start : float
+            The start time for the demand in seconds.
+        t_end : float
+            The end time for the demand in seconds.
+        flow : float, optional
+            The flow rate from the origin to the destination in vehicles per second.
+        volume: float, optional
+            The demand volume from the origin to the destination. If volume is specified, the flow is ignored.
+        attribute : any, optinonal
+            Additional (meta) attributes defined by users.
+        """
+        origs = W.get_nodes_in_area(x_orig, y_orig, radious_orig)
+        dests = W.get_nodes_in_area(x_dest, y_dest, radious_dest)
+
+        if flow >= 0 and volume == -1:
+            volume = flow*(t_end-t_start)
+        size = int(volume/W.DELTAN)
+
+        origs_new = []
+        dests_new = []
+        for oo in origs:
+            o = W.get_node(oo)
+            if len(o.outlinks) != 0:
+                origs_new.append(o)
+        for dd in dests:
+            d = W.get_node(dd)
+            if len(d.inlinks) != 0:
+                dests_new.append(d)
+        origs = origs_new
+        dests = dests_new
+        if len(origs) == 0:
+            origs.append(W.get_nearest_node(x_orig, y_orig))
+        if len(dests) == 0:
+            dests.append(W.get_nearest_node(x_dest, y_dest))
+
+        ts = np.linspace(t_start, t_end, size)
+
+        os = W.rng.choice(origs, size=size)
+        ds = W.rng.choice(dests, size=size)
+
+        for t, o, d, in zip(ts, os, ds):
+            W.addVehicle(o, d, t, attribute=attribute, direct_call=False)
+
+    @demand_info_record
+    def adddemand_nodes2nodes2(W, origs, dests, t_start, t_end, flow=-1, volume=-1, attribute=None, direct_call=True):
+        """
+        Generate vehicles by specifying time-dependent origin-destination demand by specifying origin area (i.e., list of nodes) and destination one. This is new version of `adddemand_nodes2nodes`, more efficient, more smooth, and more accurate. However, it introduces some randomness.
+
+        Parameters
+        ----------
+        origs : list
+            The list of origin nodes. The items can be Node objects or names of Nodes.
+        dests : list
+            The list of destination nodes. The items can be Node objects or names of Nodes.
+        t_start : float
+            The start time for the demand in seconds.
+        t_end : float
+            The end time for the demand in seconds.
+        flow : float, optional
+            The flow rate from the origin to the destination in vehicles per second.
+        volume: float, optional
+            The demand volume from the origin to the destination. If volume is specified, the flow is ignored.
+        attribute : any, optinonal
+            Additional (meta) attributes defined by users.
+        """
+
+        if flow >= 0 and volume == -1:
+            volume = flow*(t_end-t_start)
+        size = int(volume/W.DELTAN)
+
+        origs_new = []
+        dests_new = []
+        for oo in origs:
+            o = W.get_node(oo)
+            if len(o.outlinks) != 0:
+                origs_new.append(o)
+        for dd in dests:
+            d = W.get_node(dd)
+            if len(d.inlinks) != 0:
+                dests_new.append(d)
+        origs = origs_new
+        dests = dests_new
+        ts = np.linspace(t_start, t_end, size)
+
+        os = W.rng.choice(origs, size=size)
+        ds = W.rng.choice(dests, size=size)
+
+        for t, o, d, in zip(ts, os, ds):
+            W.addVehicle(o, d, t, attribute=attribute, direct_call=False)
 
     def finalize_scenario(W, tmax=None):
         """