| import matplotlib.pyplot as plt | |
| # Additional lists to store properties at each step | |
| magnetizations = [] | |
| energies = [] | |
| heat_capacities = [] | |
| # Run the simulation | |
| for i in range(num_steps): | |
| lattice = metropolis_step(lattice) |
| import numpy as np | |
| # Set parameters | |
| J = 1.0 # Interaction energy | |
| h = 0.0 # External magnetic field | |
| kT = 1.0 # Temperature times Boltzmann's constant | |
| num_steps = 10000 # Number of steps in the simulation | |
| N = 10 # Size of the lattice, N x N | |
| # Initialize lattice with random spins |
| import os | |
| from crewai import Agent, Task, Crew, Process | |
| from crewai_tools import SerperDevTool | |
| # Define tools | |
| search_tool = SerperDevTool() | |
| # Define agents | |
| theory_agent = Agent( | |
| role='Theory Agent', |
People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
The git command-line utility has plenty of inconsistencies http://steveko.wordpress.com/2012/02/24/10-things-i-hate-about-git/
A GUI like http://sourcetreeapp.com is often helpful, but staying on the command line usually quicker. This is a list of the commands I use most frequently, listed by funcional category:
git status list which (unstaged) files have changed
| <script src="https://www.amcharts.com/lib/4/core.js"></script> | |
| <script src="https://www.amcharts.com/lib/4/charts.js"></script> | |
| <script src="https://www.amcharts.com/lib/4/themes/animated.js"></script> | |
| <div id="chartdiv"></div> |
| #BART (Bayesian Additive Regression Tree) Models | |
| library(BayesTree) | |
| trainingdata <- read.csv("Kaggle_training.csv") | |
| testdata <- read.csv("sorted_test.csv") | |
| soil_properties <- c("Ca", "P", "pH", "SOC", "Sand") | |
| # CO2_bands <- 2656:2670 | |
| names(trainingdata)[2656:2670] |
