dev

itstools/connectv2x/__init__.py

@@ -1,5 +1,4 @@
-"""Top-level package for connectv2x."""
-
-__author__ = """Andres Ladino"""
-__email__ = 'aladinoster@gmail.com'
-__version__ = '0.3.0'
+from .carfollow import Tampere
+from .support import sigmoid, speed_pulse
+from .plottools import plot_xva
+from .messages import Msg2, Msg1

itstools/connectv2x/traffic.py

@@ -6,6 +6,7 @@
 # Imports
 # ==============================================================================
 
+from dataclasses import dataclass
 import numpy as np
 from bokeh.plotting import figure, show
 from .vehicles import K_X, W_I, U_I
@@ -15,11 +16,12 @@
 # ==============================================================================
 
 
+@dataclass
 class FundamentalDiagram:
-    def __init__(self, w=W_I, u=U_I, k_x=K_X):
-        self.w = w
-        self.k_x = k_x
-        self.u = u
+
+    w: float = W_I
+    k_x: float = K_X
+    u: float = U_I
 
     @property
     def C(self):
@@ -57,9 +59,3 @@ def plot_diagram(self):
         p.xaxis.axis_label = xlabel
         p.yaxis.axis_label = ylabel
         return p
-
-    def __repr__(self):
-        return f"{self.__class__.__name__}({self.w},{self.u},{self.k_x})"
-
-    def __str__(self):
-        return f"Fundamental diagram w: {self.w}, u:{self.u}, k_x:{self.k_x}"

itstools/macrotrasim/__init__.py

@@ -1,5 +1,3 @@
-"""Top-level package for macrotrasim."""
-
-__author__ = """Andres Ladino"""
-__email__ = 'aladinoster@gmail.com'
-__version__ = '0.1.0'
+from .traffic import FundamentalDiagram, RoadLink, Demand
+from .network import Network
+from .lights import Light

itstools/macrotrasim/constants.py

@@ -0,0 +1,7 @@
+RANDOM_SEED = 100
+TRAFFIC_LIGHT_PERIOD = 90
+
+U_I = 25
+W_I = 6.25  # 5  # 6.25
+K_X = 0.16  # 0.2  # 0.16
+DT = 1 / (W_I * K_X)

itstools/macrotrasim/lights.py

@@ -0,0 +1,46 @@
+# ==============================================================================
+# STANDARD IMPORTS
+# ==============================================================================
+
+from dataclasses import dataclass, field
+import numpy as np
+
+# ==============================================================================
+# INTERNAL IMPORTS
+# ==============================================================================
+
+from .constants import TRAFFIC_LIGHT_PERIOD as T
+from .constants import RANDOM_SEED
+
+# ==============================================================================
+# CLASS AND DEFINITIONS
+# ==============================================================================
+
+RANDOM_SEED = 100
+np.random.state = RANDOM_SEED
+np.random.seed = RANDOM_SEED
+
+
+def random_initializer(period: int = T):
+    green_time = np.random.randint(period)
+    return np.concatenate([np.ones(green_time), np.zeros(T - green_time)])
+
+
+@dataclass
+class Light:
+    state: np.array = field(default_factory=random_initializer)
+    period: int = T
+
+    @property
+    def duty(self):
+        """Duty cycle"""
+        return np.sum(self.state) / len(self.state)
+
+    def __index__(self, value):
+        return self.state[value]
+
+    def setlight(self, duty: float = 0):
+        green_time = 10
+        self.state = np.concatenate(
+            [np.ones(green_time), np.zeros(self.period - green_time)]
+        )

itstools/macrotrasim/manhattan.py

@@ -0,0 +1,80 @@
+"""
+Manhattan Network
+=================
+"""
+
+import networkx as nx
+from networkx.readwrite.edgelist import write_weighted_edgelist
+
+
+def create_manhattan_intersections(m: int = 10, n: int = 10):
+    """ Build a manhattan grid road graph of n by m roads
+
+        Args:
+            m (int): number of rows
+            n (int): number of columns
+
+        N,W,E,S: North,Weast,East,South
+    """
+    nodes = tuple((i, j) for i in range(m) for j in range(n))
+    vert_edgesSN = tuple(
+        (o, d) for o, d in zip(nodes, nodes[1:]) if o[1] != n - 1 and o[0] % 2
+    )
+    vert_edgesNS = tuple(
+        (d, o) for o, d in zip(nodes, nodes[1:]) if o[1] != n - 1 and ~o[0] % 2
+    )
+    vert_edges = vert_edgesSN + vert_edgesNS
+
+    # Suplementary external nodes/edges South
+    nodes_S = tuple((-1, i) for i in range(n))
+    edges_S = tuple(((-1, i), (0, i)) for i in range(n) if i % 2) + tuple(
+        ((0, i), (-1, i)) for i in range(n) if ~i % 2
+    )
+
+    # Suplementary external nodes/edges North
+    nodes_N = tuple((m, i) for i in range(n))
+    edges_N = tuple(((m, i), (m - 1, i)) for i in range(n) if ~i % 2) + tuple(
+        ((m - 1, i), (m, i)) for i in range(n) if i % 2
+    )
+
+    nodes = nodes + nodes_S + nodes_N
+
+    nodes_transposed = tuple((i, j) for j in range(n) for i in range(m))
+    horz_edgesEW = tuple(
+        (o, d)
+        for o, d in zip(nodes_transposed, nodes_transposed[1:])
+        if o[0] != m - 1 and o[1] % 2
+    )
+    horz_edgesWE = tuple(
+        (d, o)
+        for o, d in zip(nodes_transposed, nodes_transposed[1:])
+        if o[0] != m - 1 and ~o[1] % 2
+    )
+    horz_edges = horz_edgesEW + horz_edgesWE
+
+    # Suplementary external nodes/edges West
+    nodes_W = tuple((i, -1) for i in range(m))
+    edges_W = tuple(((i, -1), (i, 0)) for i in range(n) if i % 2) + tuple(
+        ((i, 0), (i, -1)) for i in range(n) if ~i % 2
+    )
+
+    # Suplementary external nodes/edges East
+    nodes_E = tuple((i, n) for i in range(m))
+    edges_E = tuple(((i, n), (i, n - 1)) for i in range(n) if ~i % 2) + tuple(
+        ((i, n - 1), (i, n)) for i in range(n) if i % 2
+    )
+
+    nodes = nodes + nodes_W + nodes_E
+    K = 10  # Scale factor
+    # Positions
+    nodesnpos = tuple((n,) + ({"pos": (K * n[0], K * n[1])},) for n in nodes)
+
+    edges = horz_edges + vert_edges + edges_S + edges_N + edges_E + edges_W
+    weightededges = tuple(e + (0,) for e in edges)
+
+    G = nx.DiGraph()
+    G.add_nodes_from(nodesnpos)
+    G.add_weighted_edges_from(weightededges, weight="density")
+
+    pos = {n: G.nodes[n]["pos"] for n in G.nodes}
+    return G, pos

itstools/macrotrasim/metaclass.py

@@ -0,0 +1,13 @@
+import abc
+import networkx as nx
+from dataclasses import dataclass
+
+
+@dataclass
+class NetworkAbs(metaclass=abc.ABCMeta):
+    @abc.abstractproperty
+    def supply(self):
+        pass
+
+    def demand(self):
+        return 2