rahulbhadani

Installing Rust and Cargo

curl https://sh.rustup.rs -sSf | sh

Installing UV

curl -LsSf https://astral.sh/uv/install.sh | sh

rahulbhadani

# start a new project
uv init --lib --package dev --build-backend maturin --author-from "Rahul Bhadani"
cd dev
# install python
uv python install 3.12
# create a virtual environment
uv venv --python 3.12
# activate virtual environment
source .venv/bin/activate

rahulbhadani

import os
from colorama import Fore, Style

WANTED_WIDTH = 100
DISPLAY_WIDTH = min(WANTED_WIDTH, os.get_terminal_size().columns - 2)
print("┏" + "".center(DISPLAY_WIDTH, "━") + "┓")
print(f"┃{Fore.RED}" + "CMakeLists to C++17 Utils".center(DISPLAY_WIDTH, " ") + f"{Style.RESET_ALL}┃")
print(f"┃{Style.BRIGHT+ Fore.BLACK}" + "Meltwin - 2023".center(DISPLAY_WIDTH, " ") + f"{Style.RESET_ALL}┃")
print("┗" + "".center(DISPLAY_WIDTH, "━") + "┛")
print()

rahulbhadani

---

I made a repository where you can create issues if you have any problem during manual installation of ROS1. It will hopefully help people to find their problem more quickly. If you have any problem with the steps below, please:

1. Check if someone else had the same problem below this gist,
2. Create an issue on this repository otherwise.

---

rahulbhadani

"""
RNN character generator

RNN implementation with Dense layers

There is an RNN layer in pytorch, but in this case we will be using
normal Dense layers to demonstrate the difference between
RNN and Normal feedforward networks.

This is a character level generator, which means it will create character by character

rahulbhadani

"""
Three ways of computing the Hellinger distance between two discrete
probability distributions using NumPy and SciPy.
"""

import numpy as np
from scipy.linalg import norm
from scipy.spatial.distance import euclidean

rahulbhadani

import pygame
from pygame import gfxdraw
import numpy as np

class Window:
    def __init__(self, sim=None, config={}):
        # Simulation to draw
        #self.sim = sim

        # Set default configurations

rahulbhadani

Electron apps

• Marp: Markdown presentation ecosystem.

• muryoimpl/slippr: markdown presentation app by Electron

• joe-re/cafe-pitch Markdown-driven presentation tool built on Electron.

Slide deck frameworks supporting Markdown source

rahulbhadani

def minimize_fuel_consumption(num_timesteps, velocity, acceleration, fuel_consumption_function):
    # Initialize the cost function with a large value for all states
    cost = [[float('inf') for _ in range(len(velocity))] for _ in range(num_timesteps)]

    # Define the set of actions
    actions = ['accelerate', 'decelerate', 'maintain constant speed']

    # Initialize the cost for the initial state to zero
    cost[0][0] = 0

rahulbhadani

import numpy as np
class MDP:
    # Author: Rahul Bhadani 
    # Initial Date: Dec 10, 2022
    
    def __init__(self, velocity_min, velocity_max, acceleration_min, acceleration_max, velocity_step, acceleration_step, acceleration_min_accelerate, acceleration_max_accelerate):
        # Define minimum and maximum values for velocity and acceleration
        self.VELOCITY_MIN = velocity_min
        self.VELOCITY_MAX = velocity_max
        self.ACCELERATION_MIN = acceleration_min