luispedro

TARGET = 5_000_000
TARGET_RATE = TARGET / 366

data = [
        ('January', 31, 271_347),
        ('February', 29, 321_084),
        ('March', 16, 226_480 - 5723),
]

print('Month          | Steps (k) | Cumm steps (k) | Month rate | Cumm rate')

luispedro

import re
import cv2
import subprocess
pat = re.compile(r'^WIFI:S:([^;]+);T:WPA;P:([^;]+);;')

detect = cv2.QRCodeDetector()
cv2.namedWindow("preview")
vc = cv2.VideoCapture(0)
rval, frame = vc.read()

luispedro

import COVID19Py
covid19 = COVID19Py.COVID19()
locations = covid19.getLocations(timelines=True)
UK = '2020-12-03T00:00:00Z'

EU = set(['AT', 'BE', 'BG', 'HR', 'CY', 'CZ', 'DK', 'EE', 'FI', 'FR', 'DE', 'GR', 'HU', 'IE', 'IT', 'LV', 'LU', 'MT', 'NL', 'PL', 'RO', 'SK', 'SI', 'ES', 'SE'])
tot = 0
for loc in locations:
    if loc['country_code'] in EU:
        tim = loc['timelines']['deaths']['timeline']

luispedro

Keybase proof

I hereby claim:

• I am luispedro on github.

• I am luispedro (https://keybase.io/luispedro) on keybase.

• I have a public key ASBto9ey42rmyXUsEJflex23RWhAlqOiCzmCroSke7XYigo

luispedro

# %matplotlib qt
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
from matplotlib import style
style.use('default')
TOTAL_POP = 100_000
MAX_ITERS = 100_000

rho = 0.5

luispedro

import pymc3 as pm
from scipy import stats
import numpy as np


NR_TESTS = 3330
POSITIVES = 50
PRE_NEG = 401
PRE_NEG_POS = 2
PRE_PLUS = 37+75+85

luispedro

# for Emacs: -*- coding: utf-8 -*-

# Originally found on the internet. Not my work


include "%L"

# def emit(keys, codepoint, word):
#     print ('<Multi_key> %s <period>\t: "%s"\tU%04X\t\t# CIRCLED DIGIT %s' % 
#            (keys, unichr(codepoint), codepoint, word)).encode('utf8')

luispedro

import numpy as np


# FROM 
# http://worldpopulationreview.com/countries/china-population/

pyramid0china = np.array(
    [16446861., 16821572., 17097250., 17284418., 17390933., 17423080.,
       17403550., 17341743., 17247061., 17129365., 16998517., 16861620.,
       16727156., 16605907., 16498945., 16404588., 16387661., 16480191.,

luispedro

Tiny animal-like things living in and around
people do many things. Some of these animal-like
things are good for us, others are bad, and, for
many, we do not know anything about them. We want
to know more.

How these small animal-like things look and act
comes from what is written inside them, which we
can only read if it is broken up in pieces. We use
computers to try to put these pieces together and

luispedro

name: ngless-bench-env
channels:
- bioconda
- conda-forge
- defaults
dependencies:
- subread=1.6.1=0
- bottle=0.12.13=py36_0
- jug=1.6.5=py_0
- pyyaml=3.12=py36_1