From e600f40c1a991844730d8cf7352185ef02c360a0 Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Mon, 20 May 2024 01:37:35 +0200
Subject: [PATCH 1/8] corrected symmetry cosntraint
---
backend/src/optimizer.py | 153 ++++++++++++++++++++++++++++++---------
1 file changed, 120 insertions(+), 33 deletions(-)
diff --git a/backend/src/optimizer.py b/backend/src/optimizer.py
index dac0df5..82d136a 100644
--- a/backend/src/optimizer.py
+++ b/backend/src/optimizer.py
@@ -10,11 +10,44 @@ class landmark :
self.attractiveness = attractiveness
self.loc = loc
+
+
+
+def untangle2(resx: list) :
+ N = len(resx) # length of res
+ L = int(np.sqrt(N)) # number of landmarks. CAST INTO INT but should not be a problem because N = L**2 by def.
+ n_edges = resx.sum() # number of edges
+
+ order = []
+ nonzeroind = np.nonzero(resx)[0] # the return is a little funny so I use the [0]
+
+ nonzero_tup = np.unravel_index(nonzeroind, (L,L))
+
+ indx = nonzero_tup[0].tolist()
+ indy = nonzero_tup[1].tolist()
+
+ vert = (indx[0], indy[0])
+
+ order.append(vert[0])
+ order.append(vert[1])
+
+ while len(order) < n_edges + 1 :
+ ind = indx.index(vert[1])
+
+ vert = (indx[ind], indy[ind])
+
+ order.append(vert[1])
+
+ return order
+
+
+
+
# Convert the result (edges from j to k like d_25 = edge between vertex 2 and vertex 5) into the list of indices corresponding to the landmarks
-def untangle(res: list) :
- N = len(res) # length of res
+def untangle(resx: list) :
+ N = len(resx) # length of res
L = int(np.sqrt(N)) # number of landmarks. CAST INTO INT but should not be a problem because N = L**2 by def.
- n_landmarks = res.sum() # number of visited landmarks
+ n_landmarks = resx.sum() # number of edges
visit_order = []
cnt = 0
@@ -40,47 +73,67 @@ def untangle(res: list) :
return visit_order
# Just to print the result
-def print_res(res: list, P) :
+def print_res(res: list, landmarks: list, P) :
X = abs(res.x)
- order = untangle(X)
+
+ N = int(np.sqrt(len(X)))
+ for i in range(N):
+ print(X[i*N:i*N+N])
+
+ order = untangle2(X)
+
+ order_ideal = [0, 0, 0, 0, 0, 0, 1, 0]
# print("Optimal value:", -res.fun) # Minimization, so we negate to get the maximum
# print("Optimal point:", res.x)
- # N = int(np.sqrt(len(X)))
- # for i in range(N):
- # print(X[i*N:i*N+N])
- # print(order)
+
+ #for i,x in enumerate(X) : X[i] = round(x,0)
+
+ #print(order)
if (X.sum()+1)**2 == len(X) :
print('\nAll landmarks can be visited within max_steps, the following order is most likely not the fastest')
else :
print('Could not visit all the landmarks, the following order could be the fastest but not sure')
print("Order of visit :")
- for i, elem in enumerate(landmarks) :
- if i in order : print('- ' + elem.name)
+ for idx in order :
+ print('- ' + landmarks[idx].name)
steps = path_length(P, abs(res.x))
print("\nSteps walked : " + str(steps))
-# Constraint to use only the upper triangular indices for travel
-def break_sym(landmarks, A_eq, b_eq):
+# Constraint to not have d14 and d41 simultaneously
+def break_sym(landmarks, A_ub, b_ub):
L = len(landmarks)
- l = [0]*L*L
- for i in range(L) :
- for j in range(L) :
- if i >= j :
- l[j+i*L] = 1
+ upper_ind = np.triu_indices(L,0,L)
- A_eq = np.vstack((A_eq,l))
- b_eq.append(0)
+ up_ind_x = upper_ind[0]
+ up_ind_y = upper_ind[1]
- return A_eq, b_eq
+ for i, _ in enumerate(up_ind_x) :
+ l = [0]*L*L
+ if up_ind_x[i] != up_ind_y[i] :
+ l[up_ind_x[i]*L + up_ind_y[i]] = 1
+ l[up_ind_y[i]*L + up_ind_x[i]] = 1
+
+ A_ub = np.vstack((A_ub,l))
+ b_ub.append(1)
+
+ """for i in range(7):
+ print(l[i*7:i*7+7])
+ print("\n")"""
+
+ return A_ub, b_ub
# Constraint to respect max number of travels
def respect_number(landmarks, A_ub, b_ub):
h = []
for i in range(len(landmarks)) : h.append([1]*len(landmarks))
T = block_diag(*h)
+ """for l in T :
+ for i in range(7):
+ print(l[i*7:i*7+7])
+ print("\n")"""
return np.vstack((A_ub, T)), b_ub + [1]*len(landmarks)
# Constraint to tie the problem together and have a connected path
@@ -99,6 +152,10 @@ def respect_order(landmarks: list, A_eq, b_eq):
A_eq = np.vstack((A_eq,l))
b_eq.append(0)
+ for i in range(7):
+ print(l[i*7:i*7+7])
+ print("\n")
+
return A_eq, b_eq
# Compute manhattan distance between 2 locations
@@ -111,12 +168,19 @@ def manhattan_distance(loc1: tuple, loc2: tuple):
def init_eq_not_stay(landmarks):
L = len(landmarks)
l = [0]*L*L
+
+
for i in range(L) :
for j in range(L) :
if j == i :
l[j + i*L] = 1
+ l[L-1] = 1 # cannot skip from start to finish
#A_eq = np.array([np.array(xi) for xi in A_eq]) # Must convert A_eq into an np array
l = np.array(np.array(l))
+
+ """for i in range(7):
+ print(l[i*7:i*7+7])"""
+
return [l], [0]
# Initialize A and c. Compute the distances from all landmarks to each other and store attractiveness
@@ -135,24 +199,37 @@ def init_ub_dist(landmarks: list, max_steps: int):
c = c*len(landmarks)
A_ub = []
for line in A :
+ #print(line)
A_ub += line
return c, A_ub, [max_steps]
# Go through the landmarks and force the optimizer to use landmarks where attractiveness is set to -1
def respect_user_mustsee(landmarks: list, A_eq: list, b_eq: list) :
L = len(landmarks)
+ H = 0 # sort of heuristic to get an idea of the number of steps needed
+ for i in landmarks :
+ if i.name == "départ" : elem_prev = i # list of all matches
for i, elem in enumerate(landmarks) :
if elem.attractiveness == -1 :
l = [0]*L*L
if elem.name != "arrivée" :
for j in range(L) :
l[j +i*L] = 1
+
else : # This ensures we go to goal
for k in range(L-1) :
- l[k*L+L-1] = 1
+ l[k*L+L-1] = 1
+
+ H += manhattan_distance(elem.loc, elem_prev.loc)
+ elem_prev = elem
+
+ """for i in range(7):
+ print(l[i*7:i*7+7])
+ print("\n")"""
+
A_eq = np.vstack((A_eq,l))
b_eq.append(1)
- return A_eq, b_eq
+ return A_eq, b_eq, H
# Computes the path length given path matrix (dist_table) and a result
def path_length(P: list, resx: list) :
@@ -161,27 +238,30 @@ def path_length(P: list, resx: list) :
# Initialize all landmarks (+ start and goal). Order matters here
landmarks = []
landmarks.append(landmark("départ", -1, (0, 0)))
-landmarks.append(landmark("concorde", -1, (5,5)))
-landmarks.append(landmark("tour eiffel", 99, (1,1))) # PUT IN JSON
-landmarks.append(landmark("arc de triomphe", 99, (2,3)))
-landmarks.append(landmark("louvre", 70, (4,2)))
-landmarks.append(landmark("montmartre", 20, (0,2)))
+landmarks.append(landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
+landmarks.append(landmark("arc de triomphe", 99, (0,4)))
+landmarks.append(landmark("louvre", 99, (0,6)))
+landmarks.append(landmark("montmartre", 99, (0,10)))
+landmarks.append(landmark("concorde", 99, (0,8)))
landmarks.append(landmark("arrivée", -1, (0, 0)))
# CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
-max_steps = 25
+max_steps = 16
# SET CONSTRAINTS FOR INEQUALITY
c, A_ub, b_ub = init_ub_dist(landmarks, max_steps) # Add the distances from each landmark to the other
P = A_ub # store the paths for later. Needed to compute path length
A_ub, b_ub = respect_number(landmarks, A_ub, b_ub) # Respect max number of visits.
+# TODO : Problems with circular symmetry
+A_ub, b_ub = break_sym(landmarks, A_ub, b_ub) # break the symmetry. Only use the upper diagonal values
+
# SET CONSTRAINTS FOR EQUALITY
A_eq, b_eq = init_eq_not_stay(landmarks) # Force solution not to stay in same place
-A_eq, b_eq = respect_user_mustsee(landmarks, A_eq, b_eq) # Check if there are user_defined must_see. Also takes care of start/goal
-A_eq, b_eq = break_sym(landmarks, A_eq, b_eq) # break the symmetry. Only use the upper diagonal values
+A_eq, b_eq, H = respect_user_mustsee(landmarks, A_eq, b_eq) # Check if there are user_defined must_see. Also takes care of start/goal
+
A_eq, b_eq = respect_order(landmarks, A_eq, b_eq) # Respect order of visit (only works when max_steps is limiting factor)
# Bounds for variables (x can only be 0 or 1)
@@ -192,10 +272,17 @@ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds,
# Raise error if no solution is found
if not res.success :
- raise ValueError("No solution has been found, please adapt your max steps")
+ print(f"No solution has been found within given timeframe.\nMinimum steps to visit all must_see is : {H}")
+ # Override the max_steps using the heuristic
+ for i, val in enumerate(b_ub) :
+ if val == max_steps : b_ub[i] = H
+
+ # Solve problem again :
+ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+
# Print result
-print_res(res, P)
+print_res(res, landmarks, P)
From 82a864e57f5e9876103252993b76b9dc81705ed2 Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Wed, 22 May 2024 00:40:57 +0200
Subject: [PATCH 2/8] fixed circular symmetry
---
backend/src/optimizer.py | 83 +++++++++++++++++++++++++++++++++++++---
1 file changed, 77 insertions(+), 6 deletions(-)
diff --git a/backend/src/optimizer.py b/backend/src/optimizer.py
index 82d136a..aaf214b 100644
--- a/backend/src/optimizer.py
+++ b/backend/src/optimizer.py
@@ -40,9 +40,6 @@ def untangle2(resx: list) :
return order
-
-
-
# Convert the result (edges from j to k like d_25 = edge between vertex 2 and vertex 5) into the list of indices corresponding to the landmarks
def untangle(resx: list) :
N = len(resx) # length of res
@@ -102,7 +99,49 @@ def print_res(res: list, landmarks: list, P) :
steps = path_length(P, abs(res.x))
print("\nSteps walked : " + str(steps))
-# Constraint to not have d14 and d41 simultaneously
+
+# Checks for cases of circular symmetry in the result
+def has_circle(resx: list) :
+ N = len(resx) # length of res
+ L = int(np.sqrt(N)) # number of landmarks. CAST INTO INT but should not be a problem because N = L**2 by def.
+ n_edges = resx.sum() # number of edges
+
+
+ nonzeroind = np.nonzero(resx)[0] # the return is a little funny so I use the [0]
+
+ nonzero_tup = np.unravel_index(nonzeroind, (L,L))
+
+ indx = nonzero_tup[0].tolist()
+ indy = nonzero_tup[1].tolist()
+
+
+ verts = []
+
+ for i, x in enumerate(indx) :
+ verts.append((x, indy[i]))
+
+
+ for vert in verts :
+ visited = []
+ visited.append(vert)
+
+ while len(visited) < n_edges + 1 :
+
+ try :
+ ind = indx.index(vert[1])
+
+ vert = (indx[ind], indy[ind])
+
+ if vert in visited :
+ return visited
+ else :
+ visited.append(vert)
+ except :
+ break
+
+ return []
+
+# Constraint to not have d14 and d41 simultaneously. Does not prevent circular symmetry with more elements
def break_sym(landmarks, A_ub, b_ub):
L = len(landmarks)
upper_ind = np.triu_indices(L,0,L)
@@ -125,6 +164,26 @@ def break_sym(landmarks, A_ub, b_ub):
return A_ub, b_ub
+
+def prevent_circle(landmarks, A_ub, b_ub, circle) :
+ N = len(landmarks)
+ l = [0]*N*N
+
+ for index in circle :
+ x = index[0]
+ y = index[1]
+ l[x*N+y] = 1
+
+ A_ub = np.vstack((A_ub,l))
+ b_ub.append(len(circle)-1)
+
+ """print("\n\nPREVENT CIRCLE")
+ for i in range(7):
+ print(l[i*7:i*7+7])
+ print("\n")"""
+
+ return A_ub, b_ub
+
# Constraint to respect max number of travels
def respect_number(landmarks, A_ub, b_ub):
h = []
@@ -152,9 +211,9 @@ def respect_order(landmarks: list, A_eq, b_eq):
A_eq = np.vstack((A_eq,l))
b_eq.append(0)
- for i in range(7):
+ """for i in range(7):
print(l[i*7:i*7+7])
- print("\n")
+ print("\n")"""
return A_eq, b_eq
@@ -268,7 +327,19 @@ A_eq, b_eq = respect_order(landmarks, A_eq, b_eq) # Respect order o
x_bounds = [(0, 1)] * len(c)
# Solve linear programming problem
+
res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+circle = has_circle(res.x)
+
+while len(circle) != 0 :
+ print("The solution has a circular path. Not interpretable.")
+ print("Need to add constraints until no circle ")
+
+ A_ub, b_ub = prevent_circle(landmarks, A_ub, b_ub, circle)
+ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+ circle = has_circle(res.x)
+
+
# Raise error if no solution is found
if not res.success :
From 2b31ce5f6b057c985bc22caa97d5d299a5e8392c Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Wed, 22 May 2024 10:16:33 +0200
Subject: [PATCH 3/8] Cleanup and created main
---
.../src/__pycache__/optimizer.cpython-310.pyc | Bin 0 -> 6065 bytes
backend/src/main.py | 37 +++--
backend/src/main_example.py | 23 +++
backend/src/optimizer.py | 155 +++++++-----------
4 files changed, 100 insertions(+), 115 deletions(-)
create mode 100644 backend/src/__pycache__/optimizer.cpython-310.pyc
create mode 100644 backend/src/main_example.py
diff --git a/backend/src/__pycache__/optimizer.cpython-310.pyc b/backend/src/__pycache__/optimizer.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..2446c047e04e4aa4cec9c2a5628a2c89ec72a9c7
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diff --git a/backend/src/main.py b/backend/src/main.py
index e0072b0..772daca 100644
--- a/backend/src/main.py
+++ b/backend/src/main.py
@@ -1,23 +1,26 @@
-import fastapi
-from dataclasses import dataclass
+from optimizer import solve_optimization
+from optimizer import landmark
+
+def main():
+
+ # CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
+ max_steps = 16
-@dataclass
-class Destination:
- name: str
- location: tuple
- attractiveness: int
+ # Initialize all landmarks (+ start and goal). Order matters here
+ landmarks = []
+ landmarks.append(landmark("départ", -1, (0, 0)))
+ landmarks.append(landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
+ landmarks.append(landmark("arc de triomphe", 99, (0,4)))
+ landmarks.append(landmark("louvre", 99, (0,6)))
+ landmarks.append(landmark("montmartre", 99, (0,10)))
+ landmarks.append(landmark("concorde", 99, (0,8)))
+ landmarks.append(landmark("arrivée", -1, (0, 0)))
+
+
+ visiting_order = solve_optimization(landmarks, max_steps, True)
-d = Destination()
-
-
-
-def get_route() -> list[Destination]:
- return {"route": "Hello World"}
-
-endpoint = ("/get_route", get_route)
-end
if __name__ == "__main__":
- fastapi.run()
+ main()
\ No newline at end of file
diff --git a/backend/src/main_example.py b/backend/src/main_example.py
new file mode 100644
index 0000000..e0072b0
--- /dev/null
+++ b/backend/src/main_example.py
@@ -0,0 +1,23 @@
+import fastapi
+from dataclasses import dataclass
+
+
+@dataclass
+class Destination:
+ name: str
+ location: tuple
+ attractiveness: int
+
+
+
+d = Destination()
+
+
+
+def get_route() -> list[Destination]:
+ return {"route": "Hello World"}
+
+endpoint = ("/get_route", get_route)
+end
+if __name__ == "__main__":
+ fastapi.run()
diff --git a/backend/src/optimizer.py b/backend/src/optimizer.py
index aaf214b..66efaeb 100644
--- a/backend/src/optimizer.py
+++ b/backend/src/optimizer.py
@@ -11,9 +11,8 @@ class landmark :
self.loc = loc
-
-
-def untangle2(resx: list) :
+# Convert the solution of the optimization into the list of edges to follow. Order is taken into account
+def untangle(resx: list) :
N = len(resx) # length of res
L = int(np.sqrt(N)) # number of landmarks. CAST INTO INT but should not be a problem because N = L**2 by def.
n_edges = resx.sum() # number of edges
@@ -40,65 +39,31 @@ def untangle2(resx: list) :
return order
-# Convert the result (edges from j to k like d_25 = edge between vertex 2 and vertex 5) into the list of indices corresponding to the landmarks
-def untangle(resx: list) :
- N = len(resx) # length of res
- L = int(np.sqrt(N)) # number of landmarks. CAST INTO INT but should not be a problem because N = L**2 by def.
- n_landmarks = resx.sum() # number of edges
- visit_order = []
- cnt = 0
-
- if n_landmarks % 2 == 1 : # if odd number of visited checkpoints
- for i in range(L) :
- for j in range(L) :
- if res[i*L + j] == 1 : # if index is 1
- cnt += 1 # increment counter
- if cnt % 2 == 1 : # if counter odd
- visit_order.append(i)
- visit_order.append(j)
- else : # if even number of ones
- for i in range(L) :
- for j in range(L) :
- if res[i*L + j] == 1 : # if index is one
- cnt += 1 # increment counter
- if j % (L-1) == 0 : # if last node
- visit_order.append(j) # append only the last index
- return visit_order # return
- if cnt % 2 == 1 :
- visit_order.append(i)
- visit_order.append(j)
- return visit_order
-
# Just to print the result
-def print_res(res: list, landmarks: list, P) :
+def print_res(res, landmarks: list, P) :
X = abs(res.x)
+ order = untangle(X)
- N = int(np.sqrt(len(X)))
+ """N = int(np.sqrt(len(X)))
for i in range(N):
print(X[i*N:i*N+N])
-
- order = untangle2(X)
-
- order_ideal = [0, 0, 0, 0, 0, 0, 1, 0]
-
- # print("Optimal value:", -res.fun) # Minimization, so we negate to get the maximum
- # print("Optimal point:", res.x)
-
- #for i,x in enumerate(X) : X[i] = round(x,0)
-
- #print(order)
+ print("Optimal value:", -res.fun) # Minimization, so we negate to get the maximum
+ print("Optimal point:", res.x)
+ for i,x in enumerate(X) : X[i] = round(x,0)
+ print(order)"""
if (X.sum()+1)**2 == len(X) :
- print('\nAll landmarks can be visited within max_steps, the following order is most likely not the fastest')
+ print('\nAll landmarks can be visited within max_steps, the following order is suggested : ')
else :
- print('Could not visit all the landmarks, the following order could be the fastest but not sure')
- print("Order of visit :")
+ print('Could not visit all the landmarks, the following order is suggested : ')
+
for idx in order :
print('- ' + landmarks[idx].name)
steps = path_length(P, abs(res.x))
print("\nSteps walked : " + str(steps))
+ return order
# Checks for cases of circular symmetry in the result
def has_circle(resx: list) :
@@ -164,8 +129,8 @@ def break_sym(landmarks, A_ub, b_ub):
return A_ub, b_ub
-
-def prevent_circle(landmarks, A_ub, b_ub, circle) :
+# Constraint to not have circular paths. Want to go from start -> finish without unconnected loops
+def break_circle(landmarks, A_ub, b_ub, circle) :
N = len(landmarks)
l = [0]*N*N
@@ -195,7 +160,7 @@ def respect_number(landmarks, A_ub, b_ub):
print("\n")"""
return np.vstack((A_ub, T)), b_ub + [1]*len(landmarks)
-# Constraint to tie the problem together and have a connected path
+# Constraint to tie the problem together. Necessary but not sufficient to avoid circles
def respect_order(landmarks: list, A_eq, b_eq):
N = len(landmarks)
for i in range(N-1) : # Prevent stacked ones
@@ -294,68 +259,62 @@ def respect_user_mustsee(landmarks: list, A_eq: list, b_eq: list) :
def path_length(P: list, resx: list) :
return np.dot(P, resx)
-# Initialize all landmarks (+ start and goal). Order matters here
-landmarks = []
-landmarks.append(landmark("départ", -1, (0, 0)))
-landmarks.append(landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
-landmarks.append(landmark("arc de triomphe", 99, (0,4)))
-landmarks.append(landmark("louvre", 99, (0,6)))
-landmarks.append(landmark("montmartre", 99, (0,10)))
-landmarks.append(landmark("concorde", 99, (0,8)))
-landmarks.append(landmark("arrivée", -1, (0, 0)))
+# Main optimization pipeline
+def solve_optimization (landmarks, max_steps, printing) :
+ # SET CONSTRAINTS FOR INEQUALITY
+ c, A_ub, b_ub = init_ub_dist(landmarks, max_steps) # Add the distances from each landmark to the other
+ P = A_ub # store the paths for later. Needed to compute path length
+ A_ub, b_ub = respect_number(landmarks, A_ub, b_ub) # Respect max number of visits.
+ # TODO : Problems with circular symmetry
+ A_ub, b_ub = break_sym(landmarks, A_ub, b_ub) # break the symmetry. Only use the upper diagonal values
-# CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
-max_steps = 16
+ # SET CONSTRAINTS FOR EQUALITY
+ A_eq, b_eq = init_eq_not_stay(landmarks) # Force solution not to stay in same place
+ A_eq, b_eq, H = respect_user_mustsee(landmarks, A_eq, b_eq) # Check if there are user_defined must_see. Also takes care of start/goal
-# SET CONSTRAINTS FOR INEQUALITY
-c, A_ub, b_ub = init_ub_dist(landmarks, max_steps) # Add the distances from each landmark to the other
-P = A_ub # store the paths for later. Needed to compute path length
-A_ub, b_ub = respect_number(landmarks, A_ub, b_ub) # Respect max number of visits.
+ A_eq, b_eq = respect_order(landmarks, A_eq, b_eq) # Respect order of visit (only works when max_steps is limiting factor)
-# TODO : Problems with circular symmetry
-A_ub, b_ub = break_sym(landmarks, A_ub, b_ub) # break the symmetry. Only use the upper diagonal values
+ # Bounds for variables (x can only be 0 or 1)
+ x_bounds = [(0, 1)] * len(c)
-# SET CONSTRAINTS FOR EQUALITY
-A_eq, b_eq = init_eq_not_stay(landmarks) # Force solution not to stay in same place
-A_eq, b_eq, H = respect_user_mustsee(landmarks, A_eq, b_eq) # Check if there are user_defined must_see. Also takes care of start/goal
+ # Solve linear programming problem
-A_eq, b_eq = respect_order(landmarks, A_eq, b_eq) # Respect order of visit (only works when max_steps is limiting factor)
-
-# Bounds for variables (x can only be 0 or 1)
-x_bounds = [(0, 1)] * len(c)
-
-# Solve linear programming problem
-
-res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
-circle = has_circle(res.x)
-
-while len(circle) != 0 :
- print("The solution has a circular path. Not interpretable.")
- print("Need to add constraints until no circle ")
-
- A_ub, b_ub = prevent_circle(landmarks, A_ub, b_ub, circle)
res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
circle = has_circle(res.x)
+ i = 0
+
+ # Break the circular symmetry if needed
+ while len(circle) != 0 :
+ A_ub, b_ub = break_circle(landmarks, A_ub, b_ub, circle)
+ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+ circle = has_circle(res.x)
+ i += 1
+ # Raise error if no solution is found
+ if not res.success :
-# Raise error if no solution is found
-if not res.success :
- print(f"No solution has been found within given timeframe.\nMinimum steps to visit all must_see is : {H}")
- # Override the max_steps using the heuristic
- for i, val in enumerate(b_ub) :
- if val == max_steps : b_ub[i] = H
+ # Override the max_steps using the heuristic
+ for i, val in enumerate(b_ub) :
+ if val == max_steps : b_ub[i] = H
- # Solve problem again :
- res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
-
-
-# Print result
-print_res(res, landmarks, P)
+ # Solve problem again :
+ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+ if not res.success :
+ raise ValueError("No solution could be found, even when increasing max_steps using the heuristic")
+
+ if printing is True :
+ if i != 0 :
+ print(f"Neded to recompute paths {i} times because of unconnected loops...")
+ X = print_res(res, landmarks, P)
+ return X
+
+ else :
+ return untangle(res.x)
From 101af0ebc62cd89f5378b29559b336013c147e2e Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Wed, 22 May 2024 15:01:46 +0200
Subject: [PATCH 4/8] included fastapi
---
backend/app/__init__.py | 0
.../app/__pycache__/__init__.cpython-310.pyc | Bin 0 -> 199 bytes
backend/app/__pycache__/main.cpython-310.pyc | Bin 0 -> 986 bytes
backend/app/dependencies.py | 1 +
backend/{src => app}/main.py | 18 +++++++++++++-----
backend/app/src/__init__.py | 0
.../src/__pycache__/__init__.cpython-310.pyc | Bin 0 -> 203 bytes
.../src/__pycache__/optimizer.cpython-310.pyc | Bin 6065 -> 6114 bytes
backend/{ => app}/src/main_example.py | 0
backend/{ => app}/src/optimizer.py | 10 +++++-----
10 files changed, 19 insertions(+), 10 deletions(-)
create mode 100644 backend/app/__init__.py
create mode 100644 backend/app/__pycache__/__init__.cpython-310.pyc
create mode 100644 backend/app/__pycache__/main.cpython-310.pyc
create mode 100644 backend/app/dependencies.py
rename backend/{src => app}/main.py (59%)
create mode 100644 backend/app/src/__init__.py
create mode 100644 backend/app/src/__pycache__/__init__.cpython-310.pyc
rename backend/{ => app}/src/__pycache__/optimizer.cpython-310.pyc (51%)
rename backend/{ => app}/src/main_example.py (100%)
rename backend/{ => app}/src/optimizer.py (98%)
diff --git a/backend/app/__init__.py b/backend/app/__init__.py
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diff --git a/backend/app/dependencies.py b/backend/app/dependencies.py
new file mode 100644
index 0000000..2cb6801
--- /dev/null
+++ b/backend/app/dependencies.py
@@ -0,0 +1 @@
+import app.src
\ No newline at end of file
diff --git a/backend/src/main.py b/backend/app/main.py
similarity index 59%
rename from backend/src/main.py
rename to backend/app/main.py
index 772daca..84b3141 100644
--- a/backend/src/main.py
+++ b/backend/app/main.py
@@ -1,10 +1,15 @@
-from optimizer import solve_optimization
-from optimizer import landmark
+from src.optimizer import solve_optimization
+from src.optimizer import landmark
+from fastapi import FastAPI
-def main():
+app = FastAPI()
+
+
+@app.get("/optimize/{max_steps}/{print_to_console}")
+def main(max_steps: int, print_to_console: bool):
# CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
- max_steps = 16
+ #max_steps = 16
# Initialize all landmarks (+ start and goal). Order matters here
@@ -18,8 +23,11 @@ def main():
landmarks.append(landmark("arrivée", -1, (0, 0)))
- visiting_order = solve_optimization(landmarks, max_steps, True)
+ visiting_order = solve_optimization(landmarks, max_steps, print_to_console)
+ #return visiting_order
+
+ return("max steps :", max_steps, "\n", visiting_order)
if __name__ == "__main__":
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diff --git a/backend/src/main_example.py b/backend/app/src/main_example.py
similarity index 100%
rename from backend/src/main_example.py
rename to backend/app/src/main_example.py
diff --git a/backend/src/optimizer.py b/backend/app/src/optimizer.py
similarity index 98%
rename from backend/src/optimizer.py
rename to backend/app/src/optimizer.py
index 66efaeb..4c1b631 100644
--- a/backend/src/optimizer.py
+++ b/backend/app/src/optimizer.py
@@ -10,7 +10,6 @@ class landmark :
self.attractiveness = attractiveness
self.loc = loc
-
# Convert the solution of the optimization into the list of edges to follow. Order is taken into account
def untangle(resx: list) :
N = len(resx) # length of res
@@ -43,6 +42,7 @@ def untangle(resx: list) :
def print_res(res, landmarks: list, P) :
X = abs(res.x)
order = untangle(X)
+ things = []
"""N = int(np.sqrt(len(X)))
for i in range(N):
@@ -59,11 +59,12 @@ def print_res(res, landmarks: list, P) :
for idx in order :
print('- ' + landmarks[idx].name)
+ things.append(landmarks[idx].name)
steps = path_length(P, abs(res.x))
print("\nSteps walked : " + str(steps))
- return order
+ return things
# Checks for cases of circular symmetry in the result
def has_circle(resx: list) :
@@ -260,7 +261,7 @@ def path_length(P: list, resx: list) :
return np.dot(P, resx)
# Main optimization pipeline
-def solve_optimization (landmarks, max_steps, printing) :
+def solve_optimization (landmarks, max_steps, printing_console) :
# SET CONSTRAINTS FOR INEQUALITY
c, A_ub, b_ub = init_ub_dist(landmarks, max_steps) # Add the distances from each landmark to the other
@@ -307,12 +308,11 @@ def solve_optimization (landmarks, max_steps, printing) :
raise ValueError("No solution could be found, even when increasing max_steps using the heuristic")
- if printing is True :
+ if printing_console is True :
if i != 0 :
print(f"Neded to recompute paths {i} times because of unconnected loops...")
X = print_res(res, landmarks, P)
return X
-
else :
return untangle(res.x)
From 70cebc0aa19f900cac6bf0bca8cee79fd2e9934a Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Wed, 22 May 2024 15:12:54 +0200
Subject: [PATCH 5/8] fixed return order
---
backend/app/__pycache__/main.cpython-310.pyc | Bin 986 -> 980 bytes
backend/app/main.py | 6 +--
.../src/__pycache__/optimizer.cpython-310.pyc | Bin 6114 -> 6107 bytes
backend/app/src/optimizer.py | 37 ++++++++++--------
4 files changed, 24 insertions(+), 19 deletions(-)
diff --git a/backend/app/__pycache__/main.cpython-310.pyc b/backend/app/__pycache__/main.cpython-310.pyc
index 21f3cee4583cade7331b40935c4fb79e719f22cd..cd67059540ba463b9a64189908a944b49246cc02 100644
GIT binary patch
delta 66
zcmcb`eubSkpO=@50SIK@`lcyP<lV%mI`M$4Qc7w`VrEWp?JdsS#ESUhlGK9YTf7BD
PnRzAgP^rzVj8~Ze$R8I(
delta 71
zcmcb@ev6$qpO=@50SJD*_D$28$h(PAW8wi>jgtKM<ovwi{G8O<Tb#Lx74gL-sRhNi
S1PY2W^Gf0ovK#+jWdZ<!dK<|A
diff --git a/backend/app/main.py b/backend/app/main.py
index 84b3141..d7e153c 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -5,8 +5,8 @@ from fastapi import FastAPI
app = FastAPI()
-@app.get("/optimize/{max_steps}/{print_to_console}")
-def main(max_steps: int, print_to_console: bool):
+@app.get("/optimize/{max_steps}/{print_details}")
+def main(max_steps: int, print_details: bool):
# CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
#max_steps = 16
@@ -23,7 +23,7 @@ def main(max_steps: int, print_to_console: bool):
landmarks.append(landmark("arrivée", -1, (0, 0)))
- visiting_order = solve_optimization(landmarks, max_steps, print_to_console)
+ visiting_order = solve_optimization(landmarks, max_steps, print_details)
#return visiting_order
diff --git a/backend/app/src/__pycache__/optimizer.cpython-310.pyc b/backend/app/src/__pycache__/optimizer.cpython-310.pyc
index 55a6337409776ed6c3207b9db525d84153adfb21..e60b82c34deb09c2e891f1f4f1cc3ba6d701d1f9 100644
GIT binary patch
delta 488
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delta 411
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diff --git a/backend/app/src/optimizer.py b/backend/app/src/optimizer.py
index 4c1b631..2681469 100644
--- a/backend/app/src/optimizer.py
+++ b/backend/app/src/optimizer.py
@@ -261,7 +261,7 @@ def path_length(P: list, resx: list) :
return np.dot(P, resx)
# Main optimization pipeline
-def solve_optimization (landmarks, max_steps, printing_console) :
+def solve_optimization (landmarks, max_steps, printing_details) :
# SET CONSTRAINTS FOR INEQUALITY
c, A_ub, b_ub = init_ub_dist(landmarks, max_steps) # Add the distances from each landmark to the other
@@ -283,15 +283,7 @@ def solve_optimization (landmarks, max_steps, printing_console) :
# Solve linear programming problem
res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
- circle = has_circle(res.x)
- i = 0
-
- # Break the circular symmetry if needed
- while len(circle) != 0 :
- A_ub, b_ub = break_circle(landmarks, A_ub, b_ub, circle)
- res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
- circle = has_circle(res.x)
- i += 1
+
# Raise error if no solution is found
@@ -305,16 +297,29 @@ def solve_optimization (landmarks, max_steps, printing_console) :
res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
if not res.success :
- raise ValueError("No solution could be found, even when increasing max_steps using the heuristic")
+ s = "No solution could be found, even when increasing max_steps using the heuristic"
+ return s
+ #raise ValueError("No solution could be found, even when increasing max_steps using the heuristic")
+ # If there is a solution, we're good to go, just check for
+ else :
+ circle = has_circle(res.x)
+ i = 0
- if printing_console is True :
- if i != 0 :
- print(f"Neded to recompute paths {i} times because of unconnected loops...")
+ # Break the circular symmetry if needed
+ while len(circle) != 0 :
+ A_ub, b_ub = break_circle(landmarks, A_ub, b_ub, circle)
+ res = linprog(c, A_ub=A_ub, b_ub=b_ub, A_eq=A_eq, b_eq = b_eq, bounds=x_bounds, method='highs', integrality=3)
+ circle = has_circle(res.x)
+ i += 1
+
+ if printing_details is True :
+ if i != 0 :
+ print(f"Neded to recompute paths {i} times because of unconnected loops...")
X = print_res(res, landmarks, P)
return X
- else :
- return untangle(res.x)
+ else :
+ return untangle(res.x)
From d8d425a922f139a52914c0beae1755cb1aa590a0 Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Thu, 23 May 2024 10:39:14 +0200
Subject: [PATCH 6/8] added dataclass
---
backend/app/main.py | 22 +++++++++++-----------
backend/app/src/optimizer.py | 11 ++++++-----
2 files changed, 17 insertions(+), 16 deletions(-)
diff --git a/backend/app/main.py b/backend/app/main.py
index d7e153c..17ba5c6 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -1,5 +1,5 @@
from src.optimizer import solve_optimization
-from src.optimizer import landmark
+from src.optimizer import Landmark
from fastapi import FastAPI
app = FastAPI()
@@ -12,18 +12,18 @@ def main(max_steps: int, print_details: bool):
#max_steps = 16
- # Initialize all landmarks (+ start and goal). Order matters here
- landmarks = []
- landmarks.append(landmark("départ", -1, (0, 0)))
- landmarks.append(landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
- landmarks.append(landmark("arc de triomphe", 99, (0,4)))
- landmarks.append(landmark("louvre", 99, (0,6)))
- landmarks.append(landmark("montmartre", 99, (0,10)))
- landmarks.append(landmark("concorde", 99, (0,8)))
- landmarks.append(landmark("arrivée", -1, (0, 0)))
+ # Initialize all Landmarks (+ start and goal). Order matters here
+ Landmarks = []
+ Landmarks.append(Landmark("départ", -1, (0, 0)))
+ Landmarks.append(Landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
+ Landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
+ Landmarks.append(Landmark("louvre", 99, (0,6)))
+ Landmarks.append(Landmark("montmartre", 99, (0,10)))
+ Landmarks.append(Landmark("concorde", 99, (0,8)))
+ Landmarks.append(Landmark("arrivée", -1, (0, 0)))
- visiting_order = solve_optimization(landmarks, max_steps, print_details)
+ visiting_order = solve_optimization(Landmarks, max_steps, print_details)
#return visiting_order
diff --git a/backend/app/src/optimizer.py b/backend/app/src/optimizer.py
index 2681469..527b8eb 100644
--- a/backend/app/src/optimizer.py
+++ b/backend/app/src/optimizer.py
@@ -1,14 +1,15 @@
from scipy.optimize import linprog
import numpy as np
from scipy.linalg import block_diag
+from dataclasses import dataclass
# Defines the landmark class (aka some place there is to visit)
-class landmark :
- def __init__(self, name: str, attractiveness: int, loc: tuple):
- self.name = name
- self.attractiveness = attractiveness
- self.loc = loc
+@dataclass
+class Landmark :
+ name : str
+ attractiveness : int
+ loc : tuple
# Convert the solution of the optimization into the list of edges to follow. Order is taken into account
def untangle(resx: list) :
From 99dc8b5e6780766693f8cd07c37b17b68371eedd Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Thu, 23 May 2024 12:20:32 +0200
Subject: [PATCH 7/8] added OSM api
---
backend/app/main.py | 22 ++++++------
backend/app/src/landmarks_manager.py | 52 ++++++++++++++++++++++++++++
backend/app/src/optimizer.py | 8 +----
3 files changed, 64 insertions(+), 18 deletions(-)
create mode 100644 backend/app/src/landmarks_manager.py
diff --git a/backend/app/main.py b/backend/app/main.py
index 17ba5c6..38863e2 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -1,5 +1,5 @@
from src.optimizer import solve_optimization
-from src.optimizer import Landmark
+from src.landmarks_manager import Landmark
from fastapi import FastAPI
app = FastAPI()
@@ -12,18 +12,18 @@ def main(max_steps: int, print_details: bool):
#max_steps = 16
- # Initialize all Landmarks (+ start and goal). Order matters here
- Landmarks = []
- Landmarks.append(Landmark("départ", -1, (0, 0)))
- Landmarks.append(Landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
- Landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
- Landmarks.append(Landmark("louvre", 99, (0,6)))
- Landmarks.append(Landmark("montmartre", 99, (0,10)))
- Landmarks.append(Landmark("concorde", 99, (0,8)))
- Landmarks.append(Landmark("arrivée", -1, (0, 0)))
+ # Initialize all landmarks (+ start and goal). Order matters here
+ landmarks = []
+ landmarks.append(Landmark("départ", -1, (0, 0)))
+ landmarks.append(Landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
+ landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
+ landmarks.append(Landmark("louvre", 99, (0,6)))
+ landmarks.append(Landmark("montmartre", 99, (0,10)))
+ landmarks.append(Landmark("concorde", 99, (0,8)))
+ landmarks.append(Landmark("arrivée", -1, (0, 0)))
- visiting_order = solve_optimization(Landmarks, max_steps, print_details)
+ visiting_order = solve_optimization(landmarks, max_steps, print_details)
#return visiting_order
diff --git a/backend/app/src/landmarks_manager.py b/backend/app/src/landmarks_manager.py
new file mode 100644
index 0000000..df2bb9f
--- /dev/null
+++ b/backend/app/src/landmarks_manager.py
@@ -0,0 +1,52 @@
+from OSMPythonTools.api import Api
+from OSMPythonTools.overpass import Overpass
+from dataclasses import dataclass
+
+
+# Defines the landmark class (aka some place there is to visit)
+@dataclass
+class Landmark :
+ name : str
+ attractiveness : int
+ id : int
+
+
+# Converts a OSM id to a landmark
+def add_from_id(id: int, score: int) :
+
+ try :
+ s = 'way/' + str(id) # prepare string for query
+ obj = api.query(s) # object to add
+ except :
+ s = 'relation/' + str(id) # prepare string for query
+ obj = api.query(s) # object to add
+
+ return Landmark(obj.tag('name:fr'), score, id) # create Landmark out of it
+
+
+# take a lsit of tuples (id, score) to generate a list of landmarks
+def generate_landmarks(ids_and_scores: list) :
+
+ L = []
+ for tup in ids_and_scores :
+ L.append(add_from_id(tup[0], tup[1]))
+
+ return L
+
+api = Api()
+
+
+l = (7515426, 70)
+t = (5013364, 100)
+n = (201611261, 99)
+a = (226413508, 50)
+m = (23762981, 30)
+
+
+ids_and_scores = [t, l, n, a, m]
+
+landmarks = generate_landmarks(ids_and_scores)
+
+
+for obj in landmarks :
+ print(obj)
\ No newline at end of file
diff --git a/backend/app/src/optimizer.py b/backend/app/src/optimizer.py
index 527b8eb..d74d1b9 100644
--- a/backend/app/src/optimizer.py
+++ b/backend/app/src/optimizer.py
@@ -1,15 +1,9 @@
from scipy.optimize import linprog
import numpy as np
from scipy.linalg import block_diag
-from dataclasses import dataclass
-# Defines the landmark class (aka some place there is to visit)
-@dataclass
-class Landmark :
- name : str
- attractiveness : int
- loc : tuple
+# landmarks = [Landmark_1, Landmark_2, ...]
# Convert the solution of the optimization into the list of edges to follow. Order is taken into account
def untangle(resx: list) :
From ae9860cc8ec44adba9d7f55c54b59af075746bc6 Mon Sep 17 00:00:00 2001
From: Kilian Scheidecker <kilian.scheidecker@orange.fr>
Date: Wed, 29 May 2024 18:14:40 +0200
Subject: [PATCH 8/8] proper fast api suage
---
backend/.gitignore | 164 ++
backend/Pipfile | 26 +-
backend/Pipfile.lock | 2369 ++++++++++++++++----------
backend/app/main.py | 68 +-
backend/app/src/landmarks_manager.py | 107 +-
backend/app/src/main_example.py | 46 +-
6 files changed, 1774 insertions(+), 1006 deletions(-)
create mode 100644 backend/.gitignore
diff --git a/backend/.gitignore b/backend/.gitignore
new file mode 100644
index 0000000..2e722c1
--- /dev/null
+++ b/backend/.gitignore
@@ -0,0 +1,164 @@
+# osm-cache
+cache/
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+# in version control.
+# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+# and can be added to the global gitignore or merged into this file. For a more nuclear
+# option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
\ No newline at end of file
diff --git a/backend/Pipfile b/backend/Pipfile
index dfcd2a4..f02576b 100644
--- a/backend/Pipfile
+++ b/backend/Pipfile
@@ -1,14 +1,12 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[packages]
-numpy = "*"
-scipy = "*"
-fastapi = "*"
-
-[dev-packages]
-
-[requires]
-python_version = "3.12"
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+numpy = "*"
+scipy = "*"
+fastapi = "*"
+osmpythontools = "*"
+
+[dev-packages]
diff --git a/backend/Pipfile.lock b/backend/Pipfile.lock
index a4c1f54..f07cd8e 100644
--- a/backend/Pipfile.lock
+++ b/backend/Pipfile.lock
@@ -1,884 +1,1485 @@
-{
- "_meta": {
- "hash": {
- "sha256": "338629802198c23b4efab9dde90a89e178caf0840d99ff5c5936550b91d64d5e"
- },
- "pipfile-spec": 6,
- "requires": {
- "python_version": "3.12"
- },
- "sources": [
- {
- "name": "pypi",
- "url": "https://pypi.org/simple",
- "verify_ssl": true
- }
- ]
- },
- "default": {
- "annotated-types": {
- "hashes": [
- "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43",
- "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==0.6.0"
- },
- "anyio": {
- "hashes": [
- "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8",
- "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==4.3.0"
- },
- "certifi": {
- "hashes": [
- "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f",
- "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"
- ],
- "markers": "python_version >= '3.6'",
- "version": "==2024.2.2"
- },
- "click": {
- "hashes": [
- "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28",
- "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"
- ],
- "markers": "python_version >= '3.7'",
- "version": "==8.1.7"
- },
- "dnspython": {
- "hashes": [
- "sha256:5ef3b9680161f6fa89daf8ad451b5f1a33b18ae8a1c6778cdf4b43f08c0a6e50",
- "sha256:e8f0f9c23a7b7cb99ded64e6c3a6f3e701d78f50c55e002b839dea7225cff7cc"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==2.6.1"
- },
- "email-validator": {
- "hashes": [
- "sha256:200a70680ba08904be6d1eef729205cc0d687634399a5924d842533efb824b84",
- "sha256:97d882d174e2a65732fb43bfce81a3a834cbc1bde8bf419e30ef5ea976370a05"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==2.1.1"
- },
- "fastapi": {
- "hashes": [
- "sha256:97ecbf994be0bcbdadedf88c3150252bed7b2087075ac99735403b1b76cc8fc0",
- "sha256:b9db9dd147c91cb8b769f7183535773d8741dd46f9dc6676cd82eab510228cd7"
- ],
- "index": "pypi",
- "markers": "python_version >= '3.8'",
- "version": "==0.111.0"
- },
- "fastapi-cli": {
- "hashes": [
- "sha256:3b6e4d2c4daee940fb8db59ebbfd60a72c4b962bcf593e263e4cc69da4ea3d7f",
- "sha256:ae233115f729945479044917d949095e829d2d84f56f55ce1ca17627872825a5"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==0.0.3"
- },
- "h11": {
- "hashes": [
- "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d",
- "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"
- ],
- "markers": "python_version >= '3.7'",
- "version": "==0.14.0"
- },
- "httpcore": {
- "hashes": [
- "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61",
- "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==1.0.5"
- },
- "httptools": {
- "hashes": [
- "sha256:00d5d4b68a717765b1fabfd9ca755bd12bf44105eeb806c03d1962acd9b8e563",
- "sha256:0ac5a0ae3d9f4fe004318d64b8a854edd85ab76cffbf7ef5e32920faef62f142",
- "sha256:0cf2372e98406efb42e93bfe10f2948e467edfd792b015f1b4ecd897903d3e8d",
- "sha256:1ed99a373e327f0107cb513b61820102ee4f3675656a37a50083eda05dc9541b",
- "sha256:3c3b214ce057c54675b00108ac42bacf2ab8f85c58e3f324a4e963bbc46424f4",
- "sha256:3e802e0b2378ade99cd666b5bffb8b2a7cc8f3d28988685dc300469ea8dd86cb",
- "sha256:3f30d3ce413088a98b9db71c60a6ada2001a08945cb42dd65a9a9fe228627658",
- "sha256:405784577ba6540fa7d6ff49e37daf104e04f4b4ff2d1ac0469eaa6a20fde084",
- "sha256:48ed8129cd9a0d62cf4d1575fcf90fb37e3ff7d5654d3a5814eb3d55f36478c2",
- "sha256:4bd3e488b447046e386a30f07af05f9b38d3d368d1f7b4d8f7e10af85393db97",
- "sha256:4f0f8271c0a4db459f9dc807acd0eadd4839934a4b9b892f6f160e94da309837",
- "sha256:5cceac09f164bcba55c0500a18fe3c47df29b62353198e4f37bbcc5d591172c3",
- "sha256:639dc4f381a870c9ec860ce5c45921db50205a37cc3334e756269736ff0aac58",
- "sha256:678fcbae74477a17d103b7cae78b74800d795d702083867ce160fc202104d0da",
- "sha256:6a4f5ccead6d18ec072ac0b84420e95d27c1cdf5c9f1bc8fbd8daf86bd94f43d",
- "sha256:6f58e335a1402fb5a650e271e8c2d03cfa7cea46ae124649346d17bd30d59c90",
- "sha256:75c8022dca7935cba14741a42744eee13ba05db00b27a4b940f0d646bd4d56d0",
- "sha256:7a7ea483c1a4485c71cb5f38be9db078f8b0e8b4c4dc0210f531cdd2ddac1ef1",
- "sha256:7d9ceb2c957320def533671fc9c715a80c47025139c8d1f3797477decbc6edd2",
- "sha256:7ebaec1bf683e4bf5e9fbb49b8cc36da482033596a415b3e4ebab5a4c0d7ec5e",
- "sha256:85ed077c995e942b6f1b07583e4eb0a8d324d418954fc6af913d36db7c05a5a0",
- "sha256:8ae5b97f690badd2ca27cbf668494ee1b6d34cf1c464271ef7bfa9ca6b83ffaf",
- "sha256:8b0bb634338334385351a1600a73e558ce619af390c2b38386206ac6a27fecfc",
- "sha256:8e216a038d2d52ea13fdd9b9c9c7459fb80d78302b257828285eca1c773b99b3",
- "sha256:93ad80d7176aa5788902f207a4e79885f0576134695dfb0fefc15b7a4648d503",
- "sha256:95658c342529bba4e1d3d2b1a874db16c7cca435e8827422154c9da76ac4e13a",
- "sha256:95fb92dd3649f9cb139e9c56604cc2d7c7bf0fc2e7c8d7fbd58f96e35eddd2a3",
- "sha256:97662ce7fb196c785344d00d638fc9ad69e18ee4bfb4000b35a52efe5adcc949",
- "sha256:9bb68d3a085c2174c2477eb3ffe84ae9fb4fde8792edb7bcd09a1d8467e30a84",
- "sha256:b512aa728bc02354e5ac086ce76c3ce635b62f5fbc32ab7082b5e582d27867bb",
- "sha256:c6e26c30455600b95d94b1b836085138e82f177351454ee841c148f93a9bad5a",
- "sha256:d2f6c3c4cb1948d912538217838f6e9960bc4a521d7f9b323b3da579cd14532f",
- "sha256:dcbab042cc3ef272adc11220517278519adf8f53fd3056d0e68f0a6f891ba94e",
- "sha256:e0b281cf5a125c35f7f6722b65d8542d2e57331be573e9e88bc8b0115c4a7a81",
- "sha256:e57997ac7fb7ee43140cc03664de5f268813a481dff6245e0075925adc6aa185",
- "sha256:fe467eb086d80217b7584e61313ebadc8d187a4d95bb62031b7bab4b205c3ba3"
- ],
- "version": "==0.6.1"
- },
- "httpx": {
- "hashes": [
- "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5",
- "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==0.27.0"
- },
- "idna": {
- "hashes": [
- "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc",
- "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"
- ],
- "markers": "python_version >= '3.5'",
- "version": "==3.7"
- },
- "jinja2": {
- "hashes": [
- "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369",
- "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"
- ],
- "markers": "python_version >= '3.7'",
- "version": "==3.1.4"
- },
- "markdown-it-py": {
- "hashes": [
- "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1",
- "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"
- ],
- "markers": "python_version >= '3.8'",
- "version": "==3.0.0"
- },
- "markupsafe": {
- "hashes": [
- "sha256:00e046b6dd71aa03a41079792f8473dc494d564611a8f89bbbd7cb93295ebdcf",
- "sha256:075202fa5b72c86ad32dc7d0b56024ebdbcf2048c0ba09f1cde31bfdd57bcfff",
- "sha256:0e397ac966fdf721b2c528cf028494e86172b4feba51d65f81ffd65c63798f3f",
- "sha256:17b950fccb810b3293638215058e432159d2b71005c74371d784862b7e4683f3",
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- "sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc",
- "sha256:a549b9c31bec33820e885335b451286e2969a2d9e24879f83fe904a5ce59d70a",
- "sha256:ac07bad82163452a6884fe8fa0963fb98c2346ba78d779ec06bd7a6262132aee",
- "sha256:ae2ad8ae6ebee9d2d94b17fb62763125f3f374c25618198f40cbb8b525411900",
- "sha256:b91c037585eba9095565a3556f611e3cbfaa42ca1e865f7b8015fe5c7336d5a5",
- "sha256:bc1667f8b83f48511b94671e0e441401371dfd0f0a795c7daa4a3cd1dde55bea",
- "sha256:bec0a414d016ac1a18862a519e54b2fd0fc8bbfd6890376898a6c0891dd82e9f",
- "sha256:bf50cd79a75d181c9181df03572cdce0fbb75cc353bc350712073108cba98de5",
- "sha256:bff1b4290a66b490a2f4719358c0cdcd9bafb6b8f061e45c7a2460866bf50c2e",
- "sha256:c061bb86a71b42465156a3ee7bd58c8c2ceacdbeb95d05a99893e08b8467359a",
- "sha256:c8b29db45f8fe46ad280a7294f5c3ec36dbac9491f2d1c17345be8e69cc5928f",
- "sha256:ce409136744f6521e39fd8e2a24c53fa18ad67aa5bc7c2cf83645cce5b5c4e50",
- "sha256:d050b3361367a06d752db6ead6e7edeb0009be66bc3bae0ee9d97fb326badc2a",
- "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b",
- "sha256:d9fad5155d72433c921b782e58892377c44bd6252b5af2f67f16b194987338a4",
- "sha256:daa4ee5a243f0f20d528d939d06670a298dd39b1ad5f8a72a4275124a7819eff",
- "sha256:db0b55e0f3cc0be60c1f19efdde9a637c32740486004f20d1cff53c3c0ece4d2",
- "sha256:e61659ba32cf2cf1481e575d0462554625196a1f2fc06a1c777d3f48e8865d46",
- "sha256:ea3d8a3d18833cf4304cd2fc9cbb1efe188ca9b5efef2bdac7adc20594a0e46b",
- "sha256:ec6a563cff360b50eed26f13adc43e61bc0c04d94b8be985e6fb24b81f6dcfdf",
- "sha256:f5dfb42c4604dddc8e4305050aa6deb084540643ed5804d7455b5df8fe16f5e5",
- "sha256:fa173ec60341d6bb97a89f5ea19c85c5643c1e7dedebc22f5181eb73573142c5",
- "sha256:fa9db3f79de01457b03d4f01b34cf91bc0048eb2c3846ff26f66687c2f6d16ab",
- "sha256:fce659a462a1be54d2ffcacea5e3ba2d74daa74f30f5f143fe0c58636e355fdd",
- "sha256:ffee1f21e5ef0d712f9033568f8344d5da8cc2869dbd08d87c84656e6a2d2f68"
- ],
- "markers": "python_version >= '3.7'",
- "version": "==2.1.5"
- },
- "mdurl": {
- "hashes": [
- "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8",
- "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"
- ],
- "markers": "python_version >= '3.7'",
- "version": "==0.1.2"
- },
- "numpy": {
- "hashes": [
- "sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b",
- "sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818",
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+}
diff --git a/backend/app/main.py b/backend/app/main.py
index 38863e2..257d572 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -1,34 +1,34 @@
-from src.optimizer import solve_optimization
-from src.landmarks_manager import Landmark
-from fastapi import FastAPI
-
-app = FastAPI()
-
-
-@app.get("/optimize/{max_steps}/{print_details}")
-def main(max_steps: int, print_details: bool):
-
- # CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
- #max_steps = 16
-
-
- # Initialize all landmarks (+ start and goal). Order matters here
- landmarks = []
- landmarks.append(Landmark("départ", -1, (0, 0)))
- landmarks.append(Landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
- landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
- landmarks.append(Landmark("louvre", 99, (0,6)))
- landmarks.append(Landmark("montmartre", 99, (0,10)))
- landmarks.append(Landmark("concorde", 99, (0,8)))
- landmarks.append(Landmark("arrivée", -1, (0, 0)))
-
-
- visiting_order = solve_optimization(landmarks, max_steps, print_details)
-
- #return visiting_order
-
- return("max steps :", max_steps, "\n", visiting_order)
-
-
-if __name__ == "__main__":
- main()
\ No newline at end of file
+from .src.optimizer import solve_optimization
+from .src.landmarks_manager import Landmark
+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+@app.get("/optimize/{max_steps}/{print_details}")
+def main(max_steps: int, print_details: bool):
+
+ # CONSTRAINT TO RESPECT MAX NUMBER OF STEPS
+ #max_steps = 16
+
+
+ # Initialize all landmarks (+ start and goal). Order matters here
+ landmarks = []
+ landmarks.append(Landmark("départ", -1, (0, 0)))
+ landmarks.append(Landmark("tour eiffel", 99, (0,2))) # PUT IN JSON
+ landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
+ landmarks.append(Landmark("louvre", 99, (0,6)))
+ landmarks.append(Landmark("montmartre", 99, (0,10)))
+ landmarks.append(Landmark("concorde", 99, (0,8)))
+ landmarks.append(Landmark("arrivée", -1, (0, 0)))
+
+
+ visiting_order = solve_optimization(landmarks, max_steps, print_details)
+
+ #return visiting_order
+
+ return("max steps :", max_steps, "\n", visiting_order)
+
+
+"""if __name__ == "__main__":
+ main()"""
\ No newline at end of file
diff --git a/backend/app/src/landmarks_manager.py b/backend/app/src/landmarks_manager.py
index df2bb9f..0c3a0e2 100644
--- a/backend/app/src/landmarks_manager.py
+++ b/backend/app/src/landmarks_manager.py
@@ -1,52 +1,57 @@
-from OSMPythonTools.api import Api
-from OSMPythonTools.overpass import Overpass
-from dataclasses import dataclass
-
-
-# Defines the landmark class (aka some place there is to visit)
-@dataclass
-class Landmark :
- name : str
- attractiveness : int
- id : int
-
-
-# Converts a OSM id to a landmark
-def add_from_id(id: int, score: int) :
-
- try :
- s = 'way/' + str(id) # prepare string for query
- obj = api.query(s) # object to add
- except :
- s = 'relation/' + str(id) # prepare string for query
- obj = api.query(s) # object to add
-
- return Landmark(obj.tag('name:fr'), score, id) # create Landmark out of it
-
-
-# take a lsit of tuples (id, score) to generate a list of landmarks
-def generate_landmarks(ids_and_scores: list) :
-
- L = []
- for tup in ids_and_scores :
- L.append(add_from_id(tup[0], tup[1]))
-
- return L
-
-api = Api()
-
-
-l = (7515426, 70)
-t = (5013364, 100)
-n = (201611261, 99)
-a = (226413508, 50)
-m = (23762981, 30)
-
-
-ids_and_scores = [t, l, n, a, m]
-
-landmarks = generate_landmarks(ids_and_scores)
-
-
-for obj in landmarks :
+from OSMPythonTools.api import Api
+from OSMPythonTools.overpass import Overpass
+from dataclasses import dataclass
+
+
+# Defines the landmark class (aka some place there is to visit)
+@dataclass
+class Landmarkkkk :
+ name : str
+ attractiveness : int
+ id : int
+
+@dataclass
+class Landmark :
+ name : str
+ attractiveness : int
+ loc : tuple
+
+# Converts a OSM id to a landmark
+def add_from_id(id: int, score: int) :
+
+ try :
+ s = 'way/' + str(id) # prepare string for query
+ obj = api.query(s) # object to add
+ except :
+ s = 'relation/' + str(id) # prepare string for query
+ obj = api.query(s) # object to add
+
+ return Landmarkkkk(obj.tag('name:fr'), score, id) # create Landmark out of it
+
+
+# take a lsit of tuples (id, score) to generate a list of landmarks
+def generate_landmarks(ids_and_scores: list) :
+
+ L = []
+ for tup in ids_and_scores :
+ L.append(add_from_id(tup[0], tup[1]))
+
+ return L
+
+api = Api()
+
+
+l = (7515426, 70)
+t = (5013364, 100)
+n = (201611261, 99)
+a = (226413508, 50)
+m = (23762981, 30)
+
+
+ids_and_scores = [t, l, n, a, m]
+
+landmarks = generate_landmarks(ids_and_scores)
+
+
+for obj in landmarks :
print(obj)
\ No newline at end of file
diff --git a/backend/app/src/main_example.py b/backend/app/src/main_example.py
index e0072b0..1a49305 100644
--- a/backend/app/src/main_example.py
+++ b/backend/app/src/main_example.py
@@ -1,23 +1,23 @@
-import fastapi
-from dataclasses import dataclass
-
-
-@dataclass
-class Destination:
- name: str
- location: tuple
- attractiveness: int
-
-
-
-d = Destination()
-
-
-
-def get_route() -> list[Destination]:
- return {"route": "Hello World"}
-
-endpoint = ("/get_route", get_route)
-end
-if __name__ == "__main__":
- fastapi.run()
+import fastapi
+from dataclasses import dataclass
+
+
+@dataclass
+class Destination:
+ name: str
+ location: tuple
+ attractiveness: int
+
+
+
+d = Destination()
+
+
+
+def get_route() -> list[Destination]:
+ return {"route": "Hello World"}
+
+endpoint = ("/get_route", get_route)
+end
+if __name__ == "__main__":
+ fastapi.run()