def aubio(source_filename):
# print("Usage: %s <source_filename> [samplerate] [win_s] [hop_s] [mode]" % sys.argv[0])
# print(" where [mode] can be 'delta' or 'ddelta' for first and second derivatives")7
n_filters = 40 # must be 40 for mfcc
n_coeffs = 26
win_s = 512
hop_s = win_s // 4
# mode = "default"
samplerate = 0
s = source(source_filename, samplerate, hop_s)
samplerate = s.samplerate
p = pvoc(win_s, hop_s)
m = mfcc(win_s, n_filters, n_coeffs, samplerate)
mfccs = zeros([
n_coeffs,
])
frames_read = 0
while True:
samples, read = s()
spec = p(samples)
mfcc_out = m(spec)
mfccs = vstack((mfccs, mfcc_out))
frames_read += read
if read < hop_s: break
return mfccs
def polyfit(x, y, degree):
results = {}
coeffs = np.polyfit(x, y, degree)
# Polynomial Coefficients
results['polynomial'] = coeffs.tolist()
# r-squared
p = np.poly1d(coeffs)
# fit values, and mean
yhat = p(x)
ybar = np.sum(y)/len(y)
ssreg = np.sum((yhat-ybar)**2)
sstot = np.sum((y - ybar)**2)
results['determination'] = ssreg / sstot
return results
def obj_one_side_MSE(beta, X, Y):
p = np.poly1d(beta)
error = sum([one_side_MSE(p(X[i]), Y[i]) for i in range(X.size)]) / X.size
return (error)
def objective_function(beta, X, Y):
p=np.poly1d(beta)
error = sum([loss_function(p(X[i]), Y[i]) for i in range(X.size)])/X.size
return(error)
def poly4(x_data,beta):
p=np.poly1d(beta)
return p(x_data)
import fileinput as fi
import pprint as p
# for line in fi.FileInput("a.md",inplace=1):
# print(line)
# for i,line in enumerate(fi.FileInput("a.md",inplace=1)):
# # for line in fi.FileInput("a.md",inplace=1):
# # print(line, end='')
# if 37<i<43:
# # print(i+1, line, end='')
# # print("type of line: ",type(line))
# # line=""
# print("deleted")
temp = {}
for line in fi.input("a.md"):
if 38 < fi.lineno() < 44:
temp[fi.lineno()] = line
print(temp[fi.lineno()], end='')
p(temp.values)
##################
####################curve fitting after removing respective x when y is nan
y_n = Y[np.logical_not(np.isnan(Y))]
x_n = X[np.logical_not(np.isnan(Y))]
# plt.plot(X,Y)
# plt.show()
from numpy.polynomial import Polynomial as P
# import numpy as np
x = np.array(x_n)
y = np.array(y_n)
p = P.fit(x, y, 5)
#CGMSeriesLunchPat1[6,:].replace(to_replace = np.nan, value = 5) ##write exception
#replacing nans with respective p(X)
Y[np.isnan(Y)] = p(X[np.isnan(Y)])
# plt.figure()
# plt.plot(X,Y)
###############################################################
CGMDatenumLunchPat2.to_csv("preprocessed_CGMDatenumLunchPat2.csv",
index=False,
header=False)
CGMSeriesLunchPat2.to_csv("preprocessed_CGMSeriesLunchPat2.csv",
index=False,
header=False)
#
#Draw graph for one sample
#plt.cla()
from p import *
variable = 39
string = f"I am {variable} years old"
p(string)
# # for line in fi.FileInput("a.md",inplace=1):
# # print(line, end='')
# if 37<i<43:
# # print(i+1, line, end='')
# # print("type of line: ",type(line))
# # line=""
# print("deleted")
new = [1, 2, 3, 4, 5]
temp = {}
# for line in fi.input("a.md"):
# if 38<fi.lineno()<44:
# temp[fi.lineno()] = line
# # print(temp[fi.lineno()],end='')
# READING
with open('a.md', 'r') as f:
for i, line in enumerate(f):
if 37 < i < 43:
temp[i] = line
# WRITING
# for line in fi.FileInput("a.md",inplace=1):
# for i in temp:
# if temp[i] == line:
# line=str(new[i-38])+"\n"
# print(line,end='')
p(temp)
# p.pprint(temp)
from p import *
a = 12
b = 3
c = 5
#ruturns float
p(a // b)
#modulo
p(a % b)
for i in range(1, 4):
p(i)
#doesn't include last integer
from p import *
for i in range(1, 12):
p(i)
from p import *
name = input("please enter your name: ")
age = int(input(
"how old are you , {0}? ".format(name))) #changes string to integer
if age >= 18 and age <= 60:
p('you are able to work')
elif age < 18:
p("{1}, please come back in {0} years".format(18 - age, name))
else:
p('you are too old to work')
from p import *
p('day' in 'today')
#types of booleans that equate to false, bool(x)
p(bool(None))
p(bool(0))
p(bool(0.0))
p(bool([])) #epmty list
p(bool(())) #empty tuple
p(bool('')) #empty string
p(bool({})) #empty mapping
import webbrowser as w
import time as t
import playsound as p
a = 30
b = 2
while True:
for i in range(60):
print(b, ":", a, ":", i)
t.sleep(1)
a += 1
if a == 60:
b += 1
a = 0
if b == 2 and a == 31:
w.open('https://mail.google.com/mail/u/0/#inbox', new=1)
w.open('https://mail.google.com/mail/u/1/#inbox')
w.open('https://classroom.google.com/u/1/c/NjgxNjM4Mzc4NTha')
w.open('https://classroom.google.com/u/0/h')
p("Twin-bell-alarm-clock.mp3")
break
print("done")
def positive_mse_loss(beta, X, Y):
p=np.poly1d(beta)
error = sum([positive_mse(p(X[i]), Y[i]) for i in range(X.size)])/X.size
return(error)
from p import *
splits = "split \n strings \n everywhere"
p(splits)
tabs = "1\t2\t3\t"
p(tabs)
single_quote_apostrophe_interpolation = 'bruce said "he\'s got this"'
double_quote_quote_interpolation = "bruce said \"he's got this\""
p(single_quote_apostrophe_interpolation)
p(double_quote_quote_interpolation)
triple_quote_split = """this is going
to be
split over
a couple of lines"""
p(triple_quote_split)
triple_quote_quote_interpolation = """bruce said "he's got this" """
#leaves a space at the end
p(triple_quote_quote_interpolation)
triple_quote_quote_interpolation2 = '''bruce said "he's got this"'''
p(triple_quote_quote_interpolation2)
#3.6 interpolation
age = 39
string = f"I am {age} years old"
p(string)
parrot = 'norwiegen blue'
p(parrot[6])
from p import *
print('hello')
p('hello')
