Karlheinzniebuhr

[V1]

You are a powerful agentic AI coding assistant, powered by [Claude 3.7 Sonnet]. You operate exclusively in Cursor, the world's best IDE.

Your main goal is to follow the USER's instructions at each message.

# Additional context
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
Some information may be summarized or truncated.
This information may or may not be relevant to the coding task, it is up for you to decide.

Karlheinzniebuhr

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Karlheinzniebuhr

import random
import matplotlib.pyplot as plt

# Adjusted simulation settings
trading_days = 30  # Half a year
individual_portfolios = [1000, 1000, 1000, 1000]
shared_portfolio = 1000
win_rate = 0.75  # 50% win rate

# New risk-reward settings

Karlheinzniebuhr

#NoEnv  ; Recommended for performance and compatibility with future AutoHotkey releases.
; #Warn  ; Enable warnings to assist with detecting common errors.
SendMode Input  ; Recommended for new scripts due to its superior speed and reliability.
SetWorkingDir %A_ScriptDir%  ; Ensures a consistent starting directory.

^+F1:: ; Ctrl+Shift+F1 (/)

;Empty the Clipboard.
    Clipboard =
;Copy the select text to the Clipboard.

Karlheinzniebuhr

library(data.table)

?`[.data.table`

DT <- data.table(x=rep(c("b","a","c"),each=3), y=c(1,3,6), v=1:9)
X  <- data.table(x=c("c","b"), v=8:7, foo=c(4,2))

colnames(DT)
# [1] "x" "y" "v"

Karlheinzniebuhr

cat nmap_scan.txt | grep -B4 open | egrep -o "([0-9]{1,3}\.){3}[0-9]{1,3}"

Karlheinzniebuhr

"""
Given the starting point of any `x` gradient descent
should be able to find the minimum value of x for the
cost function `f` defined below.
"""
import random

def f(x):
    """
    Quadratic function.

Karlheinzniebuhr

# How to Do Linear Regression using Gradient Descent

# import Numpy, THE matrix multiplication library for python
from numpy import *

# minimize the "sum of squared errors". This is how we calculate and correct our error
def compute_error_for_line_given_points(b, m, points):
    totalError = 0
    for i in range(0, len(points)):
        x = points[i, 0]

Karlheinzniebuhr

/**
 * This Google Sheets script keeps data in the specified column sorted any time
 * the data changes.
 *
 * After much research, there wasn't an easy way to automatically keep a column
 * sorted in Google Sheets, and creating a second sheet to act as a "view" to
 * my primary one in order to achieve that was not an option. Instead, I
 * created a script that watches for when a cell is edited and triggers
 * an auto sort.
 *

Karlheinzniebuhr

import random
text_file = open("randomwordlist.txt", "w")

for i in range(100000000):
	text_file.write(str(random.randint(1, 1000000))+"\n")

text_file.close()