sumanthratna

Keybase proof

I hereby claim:

• I am sumanthratna on github.
• I am sumanthratna (https://keybase.io/sumanthratna) on keybase.
• I have a public key whose fingerprint is A930 4ABC E8CB DC50 9185 CB95 FC40 F670 A4F6 54CA

To claim this, I am signing this object:

sumanthratna

import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email import encoders
Type = input("Enter 1 for eMail, 2 for SMS: ")
toaddr = 0
if Type == '1':
    toaddr = input("Enter to address: ")
else:

sumanthratna

# ourdata is data we collected (from the 2018-2019 school year)
ourdata <-
  data.frame(
    chloride = c(
      1.233333333,
      0.866666667,
      2.8,
      1,
      1.2,
      0.6,

sumanthratna

library("ggplot2")
library("ggalt")

odo <- data.frame(time = seq(0, 600, 15), speed = c(0, 5.866666667, 5.866666667, 11.73333333, 33.73333333, 30.8, 33.73333333, 7.333333333, 45.46666667, 48.4, 45.46666667, 30.8, 32.26666667, 55.73333333, 55.73333333, 0, 0, 48.4, 58.66666667, 45.46666667, 45.46666667, 16.13333333, 33.73333333, 74.8, 73.33333333, 70.4, 60.13333333, 45.46666667, 48.4, 57.2, 55.73333333, 49.86666667, 46.93333333, 30.8, 35.2, 33.73333333, 30.8, 35.2, 30.8, 30.8, 27.86666667))

ggplot(odo, aes(odo$time, odo$speed)) + geom_point(aes(x = time, y = speed), stat = "identity") + ggtitle("Speed of a Car Over a 10 Minute Interval") + xlab("Time (s)") + ylab("Speed (ft/s)") + geom_smooth() + geom_xspline() + scale_x_continuous(breaks = round(seq(min(odo$time), max(odo$time), by = 30), 1)) + scale_y_continuous(breaks = round(seq(min(odo$speed), max(odo$speed), by = 5), 1))

lhs = 30*sum(odo$speed[seq(1, 40, 2)])

rhs = 30*sum(odo$speed[seq(3, 41, 2)])

sumanthratna

import numpy as np
from PIL import Image

sub = np.abs(np.array(Image.open('LESGO.png').convert('RGB')) - np.array(Image.open('day.png').convert('RGB')))
mask = np.zeros((sub.shape[0], sub.shape[1]))
sub_gs = np.array(Image.fromarray(sub).convert('L'))
mask[sub_gs > 0] = 1
final = np.array(Image.open('day.png').convert('RGB'))
final[mask == 0] = [0, 0, 0]
Image.fromarray(final).save('final.png')

sumanthratna

import tensorflow as tf


my_list = ['item1', 'item2', 'item3']

index = tf.random.uniform(
    [],
    maxval=len(my_list),
    dtype=tf.int32
)

sumanthratna

# adapted from https://web.archive.org/web/20200514221628/https://randomwalk.in/python/2019/10/27/Install-Python-copy.html
wget https://www.python.org/ftp/python/3.6.10/Python-3.6.10.tgz
tar zxfv Python-3.6.10.tgz
rm Python-3.6.10.tgz
find ./Python-3.6.10/Python -type d | xargs chmod 0755
cd Python-3.6.10
./configure --prefix=$PWD/Python-3.6.10/Python
make
make install
export PATH=$CWD:$PATH  # adds python3.6 to PATH