Jun-24-2024, 03:41 PM
(This post was last modified: Jun-24-2024, 09:14 PM by Larz60+.
Edit Reason: fixed bbcode tags
)
Hi.
I try to make and run first time AI Neural Network on my computer.
Knowledge Python is basic.
I'm using Linux Ubuntu.
I install whole in system using apt.
When show communicate about pip, then I'm doing that.
[Is a lot of problems with right file names and compatibility.]
I try to configure to direction in home catalogue [advice from Gemini].
Port 65432 is unblocked in firewall.
Helpful is Gemini, but can't solve problems what I have now.
Please help me with that.
Python engine:
I have too second code in C++:
Error:
I try to make and run first time AI Neural Network on my computer.
Knowledge Python is basic.
I'm using Linux Ubuntu.
I install whole in system using apt.
When show communicate about pip, then I'm doing that.
[Is a lot of problems with right file names and compatibility.]
I try to configure to direction in home catalogue [advice from Gemini].
Port 65432 is unblocked in firewall.
Helpful is Gemini, but can't solve problems what I have now.
Please help me with that.
Python engine:
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import brian2 import socket import numpy as np from brian2 import Neuron, Eq # Define neuron equations eqs = ''' dv/dt = (I - gl*(v-Vl) - gNa*(m**3)*h*(v-VNa) - gK*(n**4)*(v-VK)) / Cm dm/dt = alpha_m(v)*(1-m) - beta_m(v)*m dh/dt = alpha_h(v)*(1-h) - beta_h(v)*h dn/dt = alpha_n(v)*(1-n) - beta_n(v)*n ''' # Define parameters and functions for the equations (replace with actual definitions) Vl = - 65 * mV # Leak reversal potential VNa = 50 * mV # Sodium reversal potential VK = - 70 * mV # Potassium reversal potential Cm = 1 * uF / cm2 # Membrane capacitance gl = 0.3e - 3 * siemens / cm2 # Leak conductance gNa = 120e - 3 * siemens / cm2 # Sodium conductance gK = 36e - 3 * siemens / cm2 # Potassium conductance # Define neuron object using custom equations neurons = Neuron(eqs = eqs, methods = { 'alpha_m' : alpha_m, 'beta_m' : beta_m, 'alpha_h' : alpha_h, 'beta_h' : beta_h, 'alpha_n' : alpha_n, 'beta_n' : beta_n}) # Include all required methods # Standard variables num_neurons = 1000 duration = 1000 # Simulation duration in milliseconds # **(Replace with your implementation)** # Hodgkin-Huxley neuron model with STDP learning (replace with your specific neuron and synapse definitions) # ... (Include your specific code for defining synapses and learning rules) # Data variables average_firing_rates = [] average_synaptic_weights = [] # Recording functions def record_firing_rates(): global average_firing_rates average_firing_rates.append(np.mean(spike_monitor.count / (duration * 1000 ))) # Convert to Hz def record_synaptic_weights(): global average_synaptic_weights weights = synapses.weight # Assuming you have a 'synapses' object with weight attribute average_synaptic_weights.append(np.mean(weights)) # Network monitors spike_monitor = brian2.SpikeMonitor(source = neurons) brian2.NetworkOperation(record_firing_rates, dt = 10 * brian2.ms) # Record every 10 ms brian2.NetworkOperation(record_synaptic_weights, dt = 100 * brian2.ms) # Record every 100 ms # Network socket setup (replace with your IP address and port) HOST = '127.0.0.1' # Standard loopback interface address (localhost) PORT = 65432 # Port to listen on (non-privileged ports are > 1023) s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind((HOST, PORT)) # Run the simulation brian2.run(duration * brian2.ms) # Send data to C++ program (replace with IPC if on the same machine) data = { 'firing_rates' : average_firing_rates, 'synaptic_weights' : average_synaptic_weights} data_str = str (data) # Convert data to string for sending s.sendall(data_str.encode()) # Close the socket s.close() |
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#include <iostream> #include <stdio.h> #include <stdlib.h> #include <unistd.h> #include <string.h> #include <sys/types.h> #include <sys/socket.h> #include <netinet/in.h> #include <arpa/inet.h> #include <sstream> #include <jsoncpp/json.h> // Include JSON library for parsing int main() { / / Standard variables int port = 65432 ; / / Port used by Brian 2 simulation std::string host = "localhost" ; / / Replace with IP address of Brian 2 ( if not localhost) / / Socket setup int sockfd; struct sockaddr_in servaddr; sockfd = socket(AF_INET, SOCK_STREAM, 0 ); if (sockfd = = - 1 ) { perror( "socket creation failed" ); exit(EXIT_FAILURE); } memset(&servaddr, 0 , sizeof(servaddr)); servaddr.sin_family = AF_INET; servaddr.sin_port = htons(port); servaddr.sin_addr.s_addr = inet_addr(host.c_str()); if (connect(sockfd, (struct sockaddr * )&servaddr, sizeof(servaddr)) ! = 0 ) { perror( "connection failed" ); exit(EXIT_FAILURE); } / / Data receiving and processing loop while ( 1 ) { char buffer [ 1024 ]; / / Adjust buffer size based on data volume int n = recv(sockfd, buffer , sizeof( buffer ), 0 ); if (n = = 0 ) { printf( "Connection closed by server\n" ); break ; } else if (n = = - 1 ) { perror( "recv failed" ); exit(EXIT_FAILURE); } / / Parse received data (assuming JSON format ) std::string data_str( buffer , n); Json::Reader reader; Json::Value data; if (!reader.parse(data_str, data)) { |
Error:Python 3.12.3 (main, Apr 10 2024, 05:33:47) [GCC 13.2.0] on linux
Type "help", "copyright", "credits" or "license()" for more information.
= RESTART: /home/peter/python/ai_neural_brain_2/engine_brain_2.py =
ERROR Brian 2 encountered an unexpected error. If you think this is a bug in Brian 2, please report this issue either to the discourse forum at <http://brian.discourse.group/>, or to the issue tracker at <https://github.com/brian-team/brian2/issues>. Please include this file with debug information in your report: /tmp/brian_debug_vkzoele7.log Additionally, you can also include a copy of the script that was run, available at: /tmp/brian_script_fgiuug_k.py Thanks! [brian2]
Traceback (most recent call last):
File "/usr/lib/python3.12/idlelib/run.py", line 580, in runcode
exec(code, self.locals)
File "/home/peter/python/ai_neural_brain_2/engine_brain_2.py", line 5, in <module>
from brian2 import Neuron, Eq
ImportError: cannot import name 'Neuron' from 'brian2' (/usr/lib/python3/dist-packages/brian2/__init__.py)