Get Started COVID-19

import pandas as pd
import matplotlib.pyplot as plt
import math
import glob
import random
from PIL import Image


def point(xlimit,ylimit):
    x = random.uniform(0,xlimit)
    y = random.uniform(0,ylimit)
    return x,y


def Generate(GrupSize,xlimit,ylimit):
    df = pd.DataFrame(columns='X,Y,Covid-19,Day'.split(','))
   
    for i in range(GrupSize):
        df.loc[i,'X'], df.loc[i,'Y'] = point(xlimit,ylimit)
        df.loc[i,'Covid-19'] = False
   
    samplesize = math.floor(GrupSize/100)
    MoversList = df.sample(n = samplesize).index.values.tolist()
   
    StatofDay = pd.DataFrame(columns='Healthy,Covid-19(+),Hospitalized,Cured,Dead'.split(','))
    return df, StatofDay, MoversList

   
def plt1color(df):
    cols=[]
    for l in df.index:
        if df.loc[l,'Covid-19']==True: #Infected
            cols.append('red')
        elif df.loc[l,'Covid-19']==666: #Dead
            cols.append('black')
        elif df.loc[l,'Covid-19']==115: #Hospitalized
            cols.append('yellow')
        elif df.loc[l,'Covid-19']==7: #Cured
            cols.append('green')
        else:
            cols.append('blue') #Healthy
    return cols


def plt2color(Stat):
    cols=[]
    for i in Stat.columns:
        if i=='Covid-19(+)': #Infected
            cols.append('red')
        elif i=='Dead': #Dead
            cols.append('black')
        elif i=='Hospitalized': #Hospitalized
            cols.append('yellow')
        elif i=='Cured': #Cured
            cols.append('green')
        else:
            cols.append('blue') #Healthy
    return cols


def Plot():
    global df, fig, Stat, Day, Moverslist
    cols=plt1color(df)
    ld = ['Healthy','Covid-19(+)','Hospitalized','Cured','Death Toll']
    axs[0].cla()
    axs[0].scatter(df['X'],df['Y'],s=1,c=cols)
    for i in MoversList:
        axs[0].scatter(df.loc[i,'X'],df.loc[i,'Y'],s=6,facecolors='none', edgecolors='black')
        axs[0].text(df.loc[i,'X']+0.02, df.loc[i,'Y']+0.02, str(i), fontsize=5)
    cols=plt2color(Stat)
    sDay = str(Day)
    title = 'Day' + sDay
    axs[0].set_title(title,loc='left')
    axs[0].set_yticklabels([])
    axs[0].set_xticklabels([])
    axs[0].tick_params(
#    axis='both',       # changes apply to the x-axis
    which='both',      # both major and minor ticks are affected
    bottom=False,      # ticks along the bottom edge are off
    top=False,         # ticks along the top edge are off
    right=False,      # ticks along the right edge are off
    left=False,         # ticks along the left edge are off
    labelbottom=False) # labels along the bottom edge are off
    axs[1].cla()
    axs[1].plot(Stat.Healthy,label=ld[0],color=cols[0])
    axs[1].plot(Stat['Covid-19(+)'],label=ld[1],color=cols[1])
    axs[1].plot(Stat.Hospitalized,label=ld[2],color=cols[2])
    axs[1].plot(Stat.Cured,label=ld[3],color=cols[3])
    axs[1].plot(Stat.Dead,label=ld[4],color=cols[4])
#    axs[1].set_prop_cycle(color=cols)
    axs[1].legend(bbox_to_anchor=(0, 1), loc='upper left', borderaxespad=0.)
    plt.xlabel('Days')
#    plt.show()
    if Day<10 : sDay = '0' + sDay
    title = 'Day' + sDay + '.png'
    plt.savefig(title)

    return


def Png_to_gif():  
    # Create frames
    frames = []
    imgs = sorted(glob.glob("*.png"))
    for i in imgs:
        new_frame = Image.open(i)
        frames.append(new_frame)
       
    # Save into GIF
    frames[0].save('png_to_gif.gif', format='GIF',
          append_images=frames[1:],
          save_all=True,
          duration=500, loop=0)


def infect(Person):
    global df,Day
    if random.random()>0.25 and Day>3 : return
    if df.loc[Person,'Covid-19']==False:
        df.loc[Person,'Covid-19'], df.loc[Person,'Day'] = True, Day
   
   
def Move(xlimit,ylimit):
    """
    Move Movers Randomly
    """
    global df, MoversList
    for i in MoversList:
        if (df.loc[i,'Covid-19']==115) or (df.loc[i,'Covid-19']==666) :
           MoversList.remove(i)
        df.loc[i,'X'], df.loc[i,'Y'] = (df.loc[i,'X']+random.uniform(1,xlimit/3))%xlimit, (df.loc[i,'Y']+random.uniform(1,ylimit/3))%ylimit


def check(i,j):
    global df, YesterdayPatients, Distlimit
    Dist = math.sqrt((df.loc[i,'X']-df.loc[j,'X'])**2+(df.loc[i,'Y']-df.loc[j,'Y'])**2)
    flag = ((YesterdayPatients[i]==True) ^ (YesterdayPatients[j]==True)) and Dist<Distlimit
    return flag
   

def interact():
    global Day, df
    for i in range(len(df)):
        for j in range(i):
            if check(i,j):
                if (df.loc[i,'Covid-19']==False) :
                    infect(i)
                else:
                    infect(j)


def kill():
    global df
    samplesize = math.floor(len(df[df['Covid-19']==True])*.005+len(df[df['Covid-19']==115])*.005)
    if samplesize>len(df[df['Covid-19']==True]):
        return
    df.loc[df[df['Covid-19']==True].sample(n = samplesize).index.values.tolist(),'Covid-19']=666
    return


def hospitilize():
    global df
    samplesize = math.floor(len(df[df['Covid-19']==True])*0.03)
    if samplesize>len(df[df['Covid-19']==True]):
        return
    df.loc[df[df['Covid-19']==True].sample(n = samplesize).index.values.tolist(),'Covid-19']=115
    return


def cure():
    global df, Day
    df.loc[(df['Day']<Day-10) & (df['Covid-19']==True) ,'Covid-19'] = 7
    df.loc[(df['Day']<Day-21) & (df['Covid-19']==115) ,'Covid-19'] = 7
    return
   
   
def Tomorrow(): # To Be checked and Resolved!!!
    global df, Day
    Day +=1
    kill()
    hospitilize()
    cure()
    Move(xlimit,ylimit)
    interact()


def Count(Day):
    global df, Stat
    List = list(df['Covid-19'])
    Stat.loc[Day,'Healthy'] = List.count(False)
    Stat.loc[Day,'Covid-19(+)'] = List.count(True)    
    Stat.loc[Day,'Hospitalized'] = List.count(115)    
    Stat.loc[Day,'Cured'] = List.count(7)
    Stat.loc[Day,'Dead'] = List.count(666)
     
    return
   

def write_log(*args):
    global log_file
    line = ' '.join([str(a) for a in args])
    log_file.write(line+'\n')
    print(line)
   

# Main ---
log_file = open("Log.txt","w+")

n = 1000
xlimit,ylimit=30,30
Distlimit = 1.5

write_log(31*'-')
write_log("Here's the Input Data:")
write_log(8*'- - ')
write_log('Numper of Sample:',n)
write_log('X & Y limites: ',xlimit,', ',ylimit)
write_log('Distance required for Contamination:', Distlimit)

# Day = 0,  Generating Model...
Day = 0

df, Stat, MoversList = Generate(n,xlimit,ylimit)
infect(random.randrange(n))
fig, axs = plt.subplots(2)
fig.suptitle('Covid-19 Epidemic Sample Model', fontsize=16)
Plot()
Count(Day)
write_log(31*'-')
write_log('Day:',Day)
write_log(8*'- - ')    
write_log(Stat.loc[Day])

# Day=1
YesterdayPatients = list(df['Covid-19'])
Tomorrow()
Plot()
Count(Day)
write_log(31*'-')
write_log('Day:',Day)
write_log(8*'- - ')    
write_log(Stat.loc[Day])
   
#Main Loop ---

countsames = 0
while Stat.loc[Day, 'Healthy']>0 and Day<100:
    log_file = open("Log.txt","a+")
    if (list(Stat.loc[Day])==list(Stat.loc[Day-1])):
        countsames +=1
        if countsames>2 : break
    else :
        countsames = 0
   
    YesterdayPatients = list(df['Covid-19'])
    Tomorrow()
    Plot()
    Count(Day)
    write_log(31*'-')
    write_log('Day:',Day)
    write_log(8*'- - ')    
    write_log(Stat.loc[Day])
    log_file.close()

Png_to_gif()
Stat.to_excel('Stat.xlsx')
Stat.plot(title='Statistical Data Vs. Days Passed')
plt.savefig('Stat')

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


DAYS = 180
POPULATION = 100000
SPREAD_FACTOR = 0.05
DAYS_TO_RECOVER = 10
INITIALLY_AFFECTED = 4

city = pd.DataFrame(data={'id': np.arange(POPULATION), 'infected': False, 'recovery_day': None, 'recovered': False})
city = city.set_index('id')

firstCases = city.sample(INITIALLY_AFFECTED, replace=False)
city.loc[firstCases.index, 'infected'] = True
city.loc[firstCases.index, 'recovery_day'] = DAYS_TO_RECOVER

stat_active_cases = [INITIALLY_AFFECTED]
stat_recovered = [0]

for today in range(1, DAYS):
    city.loc[city['recovery_day'] == today, 'recovered'] = True
    city.loc[city['recovery_day'] == today, 'infected'] = False

    spreadingPeople = city[ (city['infected'] == True)]
    totalCasesToday = round(len(spreadingPeople) * SPREAD_FACTOR)
    casesToday = city.sample(totalCasesToday, replace=True)
    # Ignore already infected or recovered people
    casesToday = casesToday[ (casesToday['infected'] == False) & (casesToday['recovered'] == False) ]
    # Mark the new cases as infected
    city.loc[casesToday.index, 'infected'] = True
    city.loc[casesToday.index, 'recovery_day'] = today + DAYS_TO_RECOVER

    stat_active_cases.append(len(city[city['infected'] == True]))
    stat_recovered.append(len(city[city['recovered'] == True]))


title = "Spread Factor " + str(SPREAD_FACTOR).replace('.', '')
fig = plt.figure(figsize=(16, 8))
plt.bar(np.arange(DAYS), stat_active_cases, color="red")
plt.text(145, 90000, title, fontsize=14)
#plt.show()
plt.savefig(title)

import glob
from PIL import Image


def Png_to_gif():  
    # Create frames
    frames = []
    imgs = sorted(glob.glob("*.png"))
    for i in imgs:
        new_frame = Image.open(i)
        frames.append(new_frame)
       
    # Save into GIF
    frames[0].save('result.gif', format='GIF',
          append_images=frames[1:],
          save_all=True,
          duration=500, loop=0)

# Main ---
Png_to_gif()

import requests
import time
import signal
from gfxhat import touch, lcd, backlight, fonts
from PIL import Image, ImageFont, ImageDraw

resp = requests.get('https://thevirustracker.com/free-api?global=stats')
if resp.status_code != 200:
    # This means something went wrong.
    raise ApiError('GET /tasks/ {}'.format(resp.status_code))

dic = resp.json()
total_cases = 'total cases {}'.format(dic['results'][0]['total_cases'])
total_recovered = 'total recovered {}'.format(dic['results'][0]['total_recovered'])
total_deaths = 'total deaths {}'.format(dic['results'][0]['total_deaths'])
new_cases = 'total new cases today {}'.format(dic['results'][0]['total_new_cases_today'])

led_states = [False for _ in range(6)]

width, height = lcd.dimensions()

image = Image.new('P', (width, height))

draw = ImageDraw.Draw(image)

font = ImageFont.truetype(fonts.AmaticSCBold, 12)

text1 = total_cases
text2 = total_recovered
text3 = total_deaths
text4 = new_cases
#text = "Hello World"

w, h = font.getsize(text1)

x = (width - w) // 2
y = (height - h) // 2

draw.text((x, y-25), text1, 1, font)
draw.text((x, y-13), text2, 1, font)
draw.text((x, y), text3, 1, font)
draw.text((x, y+13), text4, 1, font)

def handler(ch, event):
    if event == 'press':
        led_states[ch] = not led_states[ch]
        touch.set_led(ch, led_states[ch])
        if led_states[ch]:
            backlight.set_pixel(ch, 0, 255, 255)
        else:
            backlight.set_pixel(ch, 0, 255, 0)
        backlight.show()

for x in range(6):
    touch.set_led(x, 1)
    time.sleep(0.1)
    touch.set_led(x, 0)

for x in range(6):
    backlight.set_pixel(x, 0, 255, 0)
    touch.on(x, handler)

backlight.show()

for x in range(128):
    for y in range(64):
        pixel = image.getpixel((x, y))
        lcd.set_pixel(x, y, pixel)


lcd.show()

try:
    signal.pause()
except KeyboardInterrupt:
    for x in range(6):
        backlight.set_pixel(x, 0, 0, 0)
        touch.set_led(x, 0)
    backlight.show()
    lcd.clear()
    lcd.show()