Assignment means point to address in python?
I am implementing a Hierarchy clustering algorithm(with similarity) using python 3.6, the following doing is basically build new empty graph ,and keep connecting the the group(represent by list here ) with largest similarity on original recursively
the code in position 1 of code ,I want to return the best partition, however the function return is exactly the same as comminity_list,it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
def pearson_clustering(G):
H = nx.create_empty_copy(G). # build a empty copy of G(no vetices)
best = 0 #for current modularity
current =0 #for best modualarty
A = nx.adj_matrix(G). #get adjacent matrix
org_deg =deg_dict(A, G.nodes()) # degree of G
org_E = G.number_of_edges(). # number of edges of G
comminity_list = intial_commnity_list(G) # function return a list of lists here
best_partition = None
p_table =pearson_table(G) #pearson_table return a dictionary of each pair Pearson correlation
l = len(comminity_list)
while True:
if(l == 2): break
current = modualratiry(H,org_deg,org_E) #find current modularity
l = len(comminity_list)
p_build_cluster(p_table,H,G,comminity_list) #building clustering on H
if(best < current):
best_partition = comminity_list. #postion1
best = current #find the clustering with largest modularity
return best_partition #postion2
python python-3.x
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
add a comment |
I am implementing a Hierarchy clustering algorithm(with similarity) using python 3.6, the following doing is basically build new empty graph ,and keep connecting the the group(represent by list here ) with largest similarity on original recursively
the code in position 1 of code ,I want to return the best partition, however the function return is exactly the same as comminity_list,it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
def pearson_clustering(G):
H = nx.create_empty_copy(G). # build a empty copy of G(no vetices)
best = 0 #for current modularity
current =0 #for best modualarty
A = nx.adj_matrix(G). #get adjacent matrix
org_deg =deg_dict(A, G.nodes()) # degree of G
org_E = G.number_of_edges(). # number of edges of G
comminity_list = intial_commnity_list(G) # function return a list of lists here
best_partition = None
p_table =pearson_table(G) #pearson_table return a dictionary of each pair Pearson correlation
l = len(comminity_list)
while True:
if(l == 2): break
current = modualratiry(H,org_deg,org_E) #find current modularity
l = len(comminity_list)
p_build_cluster(p_table,H,G,comminity_list) #building clustering on H
if(best < current):
best_partition = comminity_list. #postion1
best = current #find the clustering with largest modularity
return best_partition #postion2
python python-3.x
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
2
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50
add a comment |
I am implementing a Hierarchy clustering algorithm(with similarity) using python 3.6, the following doing is basically build new empty graph ,and keep connecting the the group(represent by list here ) with largest similarity on original recursively
the code in position 1 of code ,I want to return the best partition, however the function return is exactly the same as comminity_list,it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
def pearson_clustering(G):
H = nx.create_empty_copy(G). # build a empty copy of G(no vetices)
best = 0 #for current modularity
current =0 #for best modualarty
A = nx.adj_matrix(G). #get adjacent matrix
org_deg =deg_dict(A, G.nodes()) # degree of G
org_E = G.number_of_edges(). # number of edges of G
comminity_list = intial_commnity_list(G) # function return a list of lists here
best_partition = None
p_table =pearson_table(G) #pearson_table return a dictionary of each pair Pearson correlation
l = len(comminity_list)
while True:
if(l == 2): break
current = modualratiry(H,org_deg,org_E) #find current modularity
l = len(comminity_list)
p_build_cluster(p_table,H,G,comminity_list) #building clustering on H
if(best < current):
best_partition = comminity_list. #postion1
best = current #find the clustering with largest modularity
return best_partition #postion2
python python-3.x
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
I am implementing a Hierarchy clustering algorithm(with similarity) using python 3.6, the following doing is basically build new empty graph ,and keep connecting the the group(represent by list here ) with largest similarity on original recursively
the code in position 1 of code ,I want to return the best partition, however the function return is exactly the same as comminity_list,it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
def pearson_clustering(G):
H = nx.create_empty_copy(G). # build a empty copy of G(no vetices)
best = 0 #for current modularity
current =0 #for best modualarty
A = nx.adj_matrix(G). #get adjacent matrix
org_deg =deg_dict(A, G.nodes()) # degree of G
org_E = G.number_of_edges(). # number of edges of G
comminity_list = intial_commnity_list(G) # function return a list of lists here
best_partition = None
p_table =pearson_table(G) #pearson_table return a dictionary of each pair Pearson correlation
l = len(comminity_list)
while True:
if(l == 2): break
current = modualratiry(H,org_deg,org_E) #find current modularity
l = len(comminity_list)
p_build_cluster(p_table,H,G,comminity_list) #building clustering on H
if(best < current):
best_partition = comminity_list. #postion1
best = current #find the clustering with largest modularity
return best_partition #postion2
python python-3.x
python python-3.x
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
asked Nov 28 '18 at 18:49
ShaoyuPeiShaoyuPei
445
445
2
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50
add a comment |
2
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50
2
2
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50
add a comment |
1 Answer
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it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
That is just python's implicit assignment behaviour. When you do "best_partition = comminity_list" you just assign comminity_list to the same address as best_partition.
If you want to explicitly copy the list you can use this (which replaces the list best_partition with the comminity_list):
best_partition[:] = comminity_list
or the copy function. If comminity_list has sublists you will need the deepcopy function instead, from the same module (otherwise you will get a copy of the original list, but the sublists will still be just address references).
best_partition = comminity_list.copy
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
add a comment |
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it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
That is just python's implicit assignment behaviour. When you do "best_partition = comminity_list" you just assign comminity_list to the same address as best_partition.
If you want to explicitly copy the list you can use this (which replaces the list best_partition with the comminity_list):
best_partition[:] = comminity_list
or the copy function. If comminity_list has sublists you will need the deepcopy function instead, from the same module (otherwise you will get a copy of the original list, but the sublists will still be just address references).
best_partition = comminity_list.copy
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
add a comment |
it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
That is just python's implicit assignment behaviour. When you do "best_partition = comminity_list" you just assign comminity_list to the same address as best_partition.
If you want to explicitly copy the list you can use this (which replaces the list best_partition with the comminity_list):
best_partition[:] = comminity_list
or the copy function. If comminity_list has sublists you will need the deepcopy function instead, from the same module (otherwise you will get a copy of the original list, but the sublists will still be just address references).
best_partition = comminity_list.copy
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
add a comment |
it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
That is just python's implicit assignment behaviour. When you do "best_partition = comminity_list" you just assign comminity_list to the same address as best_partition.
If you want to explicitly copy the list you can use this (which replaces the list best_partition with the comminity_list):
best_partition[:] = comminity_list
or the copy function. If comminity_list has sublists you will need the deepcopy function instead, from the same module (otherwise you will get a copy of the original list, but the sublists will still be just address references).
best_partition = comminity_list.copy
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
it looks like best_partition = comminity_list. make best_partition point to the address of 'comminity_list' how come it happens, what I got wrong here? how should I fix that ?
That is just python's implicit assignment behaviour. When you do "best_partition = comminity_list" you just assign comminity_list to the same address as best_partition.
If you want to explicitly copy the list you can use this (which replaces the list best_partition with the comminity_list):
best_partition[:] = comminity_list
or the copy function. If comminity_list has sublists you will need the deepcopy function instead, from the same module (otherwise you will get a copy of the original list, but the sublists will still be just address references).
best_partition = comminity_list.copy
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
answered Nov 28 '18 at 19:03
IcerOutIcerOut
10616
10616
add a comment |
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2
Assignment doesn't implicitly copy in Python. See nedbatchelder.com/text/names.html
– user2357112
Nov 28 '18 at 18:50