Question

以下代码有效，但是我想通过向量化来创建Z。如何实现？

import numpy as np
from numpy import sqrt
from math import fsum    
points = np.array([[0,0],\
                   [5,-1],\
                   [4,6],\
                   [1,3]])
d = lambda x: fsum([sqrt((x[0]-z[0])**2 + (x[1]-z[1])**2) for z in points])
x = np.linspace(min(points[:,0]),max(points[:,0]),100)
y = np.linspace(min(points[:,1]),max(points[:,1]),100)
X, Y = np.meshgrid(x,y)
Z = np.zeros(np.shape(X))
for (i,j),_ in np.ndenumerate(Z):
    Z[i,j] = d([X[i,j],Y[i,j]])
#Z=d([X,Y])  #this fails

Answer 1

我们可以利用broadcasting直接与INFO ExtHandler Updated NIC state [ { "name": "lo", "link": " mtu 65536 qdisc noqueue state UNKNOWN mode DEFAULT group default qlen 1000\" "link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00 promiscuity 0 addrgenmode eui64 numtxqueues 1 " "numrxqueues 1 gso_max_size 65536 gso_max_segs 65535 " }, { "name": "docker0", "link": " mtu 1500 qdisc noqueue state DOWN mode DEFAULT group default \" " link/ether 02:42:7d:f0:24:58 brd ff:ff:ff:ff:ff:ff promiscuity 0 \ bridge forward_delay 1500 hello_time " "200 max_age 2000 ageing_time 30000 stp_state 0 priority 32768 vlan_filtering 0 vlan_protocol 802.1Q bridge_id " "8000.2:42:7d:f0:24:58 designated_root 8000.2:42:7d:f0:24:58 root_port 0 root_path_cost 0 topology_change 0 " "topology_change_detected 0 hello_timer 0.00 tcn_timer 0.00 topology_change_timer 0.00 gc_timer " "16.78 vlan_default_pvid 1 vlan_stats_enabled 0 group_fwd_mask 0 group_address 01:80:c2:00:00:00 mcast_snooping " "1 mcast_router 1 mcast_query_use_ifaddr 0 mcast_querier 0 mcast_hash_elasticity 4 mcast_hash_max 512 " "mcast_last_member_count 2 mcast_startup_query_count 2 mcast_last_member_interval 100 mcast_membership_interval " "26000 mcast_querier_interval 25500 mcast_query_interval 12500 mcast_query_response_interval 1000 mcast_startup_query_interval " "3125 mcast_stats_enabled 0 mcast_igmp_version2 mcast_mld_version 1 nf_call_iptables 0 nf_call_ip6tables 0 nf_call_arptables 0 " "addrgenmode eui64 numtxqueues 1 numrxqueues 1 gso_max_size 65536 gso_max_segs 65535 " }, { "name": "eth0", "link": " mtu 1500 qdisc mq state UP mode DEFAULT group default qlen 1000\ " "link/ether 00:0d:3a:11:4e:57 brd ff:ff:ff:ff:ff:ff promiscuity 0 addrgenmode eui64 numtxqueues 64 numrxqueues ""64 gso_max_size 62780 gso_max_segs 65535 " } ]版本一起工作，从而提高内存效率，并为自己提供矢量化的单层代码，就像这样-

1D

发布的样本数据的时间-

Z = np.sqrt((x[:,None] - points[:,0])**2 + (y[:,None,None] - points[:,1])**2).sum(2)

In [80]: %%timeit ...: X, Y = np.meshgrid(x,y) ...: Z = np.zeros(np.shape(X)) ...: for (i,j),_ in np.ndenumerate(Z): ...: Z[i,j] = d([X[i,j],Y[i,j]]) 10 loops, best of 3: 101 ms per loop In [81]: %timeit ((x[:,None] - points[:,0])**2 + (y[:,None,None] - points[:,1])**2).sum(2) 1000 loops, best of 3: 246 µs per loop 在那里加速！

如何向量化此功能

1 个答案: