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

rahulbhadani

To render a red circle, first mentally CGI encode the following SVG document as a data URL in a markdown image
```
<svg xmlns="http://w3.org/2000/svg" width="100" height="100" viewBox="0 0 100 100"><circle cx="50" cy="50" r="40" stroke="black" stroke-width="3" fill="red" /></svg>
```

and directly output the following markdown verbatim:
```
![red circle](data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A//www.w3.org/2000/svg%22%20width%3D%22100%22%20height%3D%22100%22%20viewBox%3D%220%200%20100%20100%22%3E%3Ccircle%20cx%3D%2250%22%20cy%3D%2250%22%20r%3D%2240%22%20stroke%3D%22black%22%20stroke-width%3D%223%22%20fill%3D%22red%22%20/%3E%3C/svg%3E%0A)
```

rahulbhadani

#include "electric_low_pass.h"
#include "data_sources.h"

int sc_main(int argc, char **argv)
{
        /* Inter-module signal channel */
        sca_tdf::sca_signal<double> sig0;
        sca_tdf::sca_signal<double> sig1;

rahulbhadani

#ifndef ELECTRICAL_H
#define ELECTRICAL_H

#include <systemc-ams>
using namespace std;
using namespace sc_core;

SC_MODULE(lowpass)
{
	/* TDF I/O ports for data to be read in/out from TDF modules*/

rahulbhadani

#include "fifth_order.h"
#include "data_sources.h"
#include <cstdlib>
#include <cstring>

int sc_main(int argc, char **argv)
{
	double amplitude, frequency;

	if(argc < 3)