diff --git a/uxsim/uxsim.py b/uxsim/uxsim.py index 30980aa..8cf01df 100644 --- a/uxsim/uxsim.py +++ b/uxsim/uxsim.py @@ -153,9 +153,9 @@ def transfer(s): if (len(outlink.vehicles) == 0 or outlink.vehicles[-1].x > outlink.delta*s.W.DELTAN) and outlink.capacity_in_remain >= s.W.DELTAN: #受け入れ可能かつ流出可能の場合，リンク優先度に応じて選択 vehs = [ - veh for veh in s.incoming_vehicles + veh for veh in s.incoming_vehicles if veh.route_next_link == outlink and - (s.signal_phase in veh.link.signal_group or len(s.signal)<=1) and + (s.signal_phase in veh.link.signal_group or len(s.signal)<=1) and veh.link.capacity_out_remain >= s.W.DELTAN ] if len(vehs) == 0: @@ -1492,6 +1492,13 @@ def cumulative_curves(s, links=None, figsize=(6,4)): else: plt.close("all") + def import_contextily(s): + try: + import contextily as ctx + return ctx + except ImportError: + raise ImportError("contextily must be installed to use the basemap feature.") + @catch_exceptions_and_warn() def network(s, t=None, detailed=1, minwidth=0.5, maxwidth=12, left_handed=1, tmp_anim=0, figsize=(6,6), network_font_size=4, node_size=2): """ @@ -1598,7 +1605,7 @@ def network(s, t=None, detailed=1, minwidth=0.5, maxwidth=12, left_handed=1, tmp plt.close("all") @catch_exceptions_and_warn() - def network_pillow(s, t=None, detailed=1, minwidth=0.5, maxwidth=12, left_handed=1, tmp_anim=0, figsize=6, network_font_size=20, node_size=2, image_return=0): + def network_pillow(s, t=None, detailed=1, minwidth=0.5, maxwidth=12, left_handed=1, tmp_anim=0, figsize=6, network_font_size=20, node_size=2, basemap=None, image_return=0): """ Visualizes the entire transportation network and its current traffic conditions. Faster implementation using Pillow. @@ -1624,6 +1631,9 @@ def network_pillow(s, t=None, detailed=1, minwidth=0.5, maxwidth=12, left_handed The font size for the network labels. Default is 4. node_size : int, optional The size of the nodes in the visualization. Default is 2. + basemap : Contextily provider object, optional + The basemap provider to be used for the visualization. Default is None. + See https://contextily.readthedocs.io/en/latest/providers_deepdive.html Notes ----- @@ -1689,6 +1699,16 @@ def flip(y): font = ImageFont.truetype(font_fname, int(30)) draw.text((img.size[0]/2,20), f"t = {t :>8} (s)", font=font, fill="black", anchor="mm") + # Add a basemap with contextily + if basemap is not None: + ctx = s.import_contextily() + # Adjust bounds to the format expected by contextily (west, south, east, north) + bounds_ctx = [minx, miny, maxx, maxy] + # Fetch the basemap + basemap_img, basemap_extent = ctx.bounds2img(*bounds_ctx, zoom='auto', source=basemap) + # Overlay the network visualization on the basemap + img = Image.alpha_composite(Image.fromarray(basemap_img), img) + img = img.resize((int((maxx-minx)/scale), int((maxy-miny)/scale)), resample=Resampling.LANCZOS) if image_return: return img @@ -1716,7 +1736,7 @@ def show_simulation_progress(s): print(f"{s.W.TIME:>8.0f} s| {sum_vehs:>8.0f} vehs| {avev:>4.1f} m/s| {time.time()-s.W.sim_start_time:8.2f} s", flush=True) @catch_exceptions_and_warn() - def network_anim(s, animation_speed_inverse=10, detailed=0, minwidth=0.5, maxwidth=12, left_handed=1, figsize=(6,6), node_size=2, network_font_size=20, timestep_skip=24): + def network_anim(s, animation_speed_inverse=10, detailed=0, minwidth=0.5, maxwidth=12, left_handed=1, figsize=(6,6), node_size=2, network_font_size=20, timestep_skip=24, basemap=None): """ Generates an animation of the entire transportation network and its traffic states over time. @@ -1743,6 +1763,9 @@ def network_anim(s, animation_speed_inverse=10, detailed=0, minwidth=0.5, maxwid The font size for the network labels in the animation. Default is 20. timestep_skip : int, optional How many timesteps are skipped per frame. Large value means coarse and lightweight animation. Default is 8. + basemap : Contextily provider object, optional + The basemap provider to be used for the visualization. Default is None. + See https://contextily.readthedocs.io/en/latest/providers_deepdive.html Notes ----- @@ -1760,7 +1783,7 @@ def network_anim(s, animation_speed_inverse=10, detailed=0, minwidth=0.5, maxwid #todo_later: 今後はこちらもpillowにする s.network(int(t), detailed=detailed, minwidth=minwidth, maxwidth=maxwidth, left_handed=left_handed, tmp_anim=1, figsize=figsize, node_size=node_size, network_font_size=network_font_size) else: - s.network_pillow(int(t), detailed=detailed, minwidth=minwidth, maxwidth=maxwidth, left_handed=left_handed, tmp_anim=1, figsize=figsize, node_size=node_size, network_font_size=network_font_size) + s.network_pillow(int(t), detailed=detailed, minwidth=minwidth, maxwidth=maxwidth, left_handed=left_handed, tmp_anim=1, figsize=figsize, node_size=node_size, network_font_size=network_font_size, basemap=basemap) pics.append(Image.open(f"out{s.W.name}/tmp_anim_{t}.png")) pics[0].save(f"out{s.W.name}/anim_network{detailed}.gif", save_all=True, append_images=pics[1:], optimize=False, duration=animation_speed_inverse*timestep_skip, loop=0) for f in glob.glob(f"out{s.W.name}/tmp_anim_*.png"): @@ -2828,7 +2851,7 @@ def on_time(W, time): else: return False - + #@catch_exceptions_and_warn() def show_network(W, width=1, left_handed=1, figsize=(6,6), network_font_size=10, node_size=6): """ @@ -2864,4 +2887,4 @@ def show_network(W, width=1, left_handed=1, figsize=(6,6), network_font_size=10, plt.xlim([minx-buffx, maxx+buffx]) plt.ylim([miny-buffy, maxy+buffy]) plt.tight_layout() - plt.show() \ No newline at end of file + plt.show()