python-labs/TEMA4/report.md

Отчет по теме 4

Лыкова Елизавета, А-01-23

1. Запуск IDLE, привязка католога, создание файла отчета.

import os
os.chdir("C:\\Users\\Home\\Desktop\\python-labs\\TEMA4")

2. Стандартные функции.

2.1 Функция round.

help(round)
Help on built-in function round in module builtins:

round(number, ndigits=None)
    Round a number to a given precision in decimal digits.

    The return value is an integer if ndigits is omitted or None.  Otherwise
    the return value has the same type as the number.  ndigits may be negative.

round(123.456,1)
123.5
round(123.456,0)
123.0
a = round(123.456,1)
b = round(123.456,0)
type(a)
<class 'float'>
type(b)
<class 'float'>
c = round(123.456)
c
123
type(c)
<class 'int'>

В первых двух случаях типы получившихся данных - float, когда во втором - int.

2.2 Функция range.

gg = range(76,123,9)
gg
range(76, 123, 9)
list(gg)
[76, 85, 94, 103, 112, 121]
range(23)
range(0, 23)
d = range(23)
list(d)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]

Диапазон начинается от нуля и заканчивается предыдущим числом заданных 23-х. Шаг - единица.

2.3 Функция zip.

qq = ['Лыкова','Соловьёва','Коваленко','Голощапов']
ff = zip(gg,qq)
tuple(ff)
((76, 'Лыкова'), (85, 'Соловьёва'), (94, 'Коваленко'), (103, 'Голощапов'))
print(ff[0])
Traceback (most recent call last):
  File "<pyshell#20>", line 1, in <module>
    print(ff[0])
TypeError: 'zip' object is not subscriptable
tt = tuple(ff)
tt
((76, 'Лыкова'), (85, 'Соловьёва'), (94, 'Коваленко'), (103, 'Голощапов'))
print(tt[1])
(85, 'Соловьёва')

К объекту ff можно обратиться с указанием индекса, преобразовав его в кортеж.

2.4 Функция eval.

fff = float(input('Коэффициент усиления='));dan = eval('5*fff-156')
Коэффициент усиления=3
dan
-141.0

2.5 Функция exec.

exec(input('Введите инструкции:'))
Введите инструкции:perem=-123.456;gg=round(abs(perem)+98,3)
gg
221.456

2.6 Функции abs,pow,max,min,sum,dinmod,len,map.

abs(-5)
5
abs(10-15)
5
#Возвращает модуль числа
pow(2,3)
8
pow(5,2)
25
#Возводит в степень
chis = [4,5,2,8]
max(chis)
8
min(chis)
2
slova = ['Радуга','Яблоко','Ананас','Груша']
max(slova)
'Яблоко'
min(slova)
'Ананас'
#Находят максимальное и минимальное значения
sum(chis)
19
sum(chis,10)
29
#Находит сумму элементов
divmod(10,3)
(3, 1)
#Находит частное и остаток от деления
len(chis)
4
строка  = 'Hallo!'
len(строка)
6
slov = {'a':10,'b':20,'c':30}
len(slov)
3
#Возвращает количество элементов в объекте
list(map(str,chis))
['4', '5', '2', '8']
list(map(lambda x:x*2,chis))
[8, 10, 4, 16]
#Применение функции к каждому элементу последовательности

3. Функции модуля math.

import math
dir(math)
['__doc__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'cbrt', 'ceil', 'comb', 'copysign', 'cos', 'cosh', 'degrees', 'dist', 'e', 'erf', 'erfc', 'exp', 'exp2', 'expm1', 'fabs', 'factorial', 'floor', 'fma', 'fmod', 'frexp', 'fsum', 'gamma', 'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf', 'isnan', 'isqrt', 'lcm', 'ldexp', 'lgamma', 'log', 'log10', 'log1p', 'log2', 'modf', 'nan', 'nextafter', 'perm', 'pi', 'pow', 'prod', 'radians', 'remainder', 'sin', 'sinh', 'sqrt', 'sumprod', 'tan', 'tanh', 'tau', 'trunc', 'ulp']
help(math.factorial)
Help on built-in function factorial in module math:

factorial(n, /)
    Find n!.

math.factorial(5)
120
help(math.sin)
Help on built-in function sin in module math:

sin(x, /)
    Return the sine of x (measured in radians).

math.sin(1)
0.8414709848078965
help(math.acos)
Help on built-in function acos in module math:

acos(x, /)
    Return the arc cosine (measured in radians) of x.

    The result is between 0 and pi.

math.acos(0.5)
1.0471975511965979
help(math.degrees)
Help on built-in function degrees in module math:

degrees(x, /)
    Convert angle x from radians to degrees.

math.degrees(45)
2578.3100780887044
help(math.radians)
Help on built-in function radians in module math:

radians(x, /)
    Convert angle x from degrees to radians.

math.radians(45)
0.7853981633974483
help(math.exp)
Help on built-in function exp in module math:

exp(x, /)
    Return e raised to the power of x.

math.exp(3)
20.085536923187668
help(math.log)
Help on built-in function log in module math:

log(...)
    log(x, [base=math.e])
    Return the logarithm of x to the given base.

    If the base is not specified, returns the natural logarithm (base e) of x.

math.log(4,3)
1.2618595071429148
help(math.log10)
Help on built-in function log10 in module math:

log10(x, /)
    Return the base 10 logarithm of x.

math.log10(3)
0.47712125471966244
help(math.sqrt)
Help on built-in function sqrt in module math:

sqrt(x, /)
    Return the square root of x.

math.sqrt(5)
2.23606797749979
help(math.ceil)
Help on built-in function ceil in module math:

ceil(x, /)
    Return the ceiling of x as an Integral.

    This is the smallest integer >= x.

math.ceil(3.2)
4
help(math.floor)
Help on built-in function floor in module math:

floor(x, /)
    Return the floor of x as an Integral.

    This is the largest integer <= x.

math.floor(3.8)
3
math.pi
3.141592653589793
math.sin((2*math.pi/7)+(math.exp(0.23)))
0.8334902641414562

4. Функции из модуля cmath.

import cmath
dir(cmath)
['__doc__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atanh', 'cos', 'cosh', 'e', 'exp', 'inf', 'infj', 'isclose', 'isfinite', 'isinf', 'isnan', 'log', 'log10', 'nan', 'nanj', 'phase', 'pi', 'polar', 'rect', 'sin', 'sinh', 'sqrt', 'tan', 'tanh', 'tau']
cmath.sqrt(1.2-0.5j)
(1.118033988749895-0.22360679774997896j)
cmath.phase(1-0.5j)
-0.4636476090008061

5. Модуль random.

import random
dir(random)
['BPF', 'LOG4', 'NV_MAGICCONST', 'RECIP_BPF', 'Random', 'SG_MAGICCONST', 'SystemRandom', 'TWOPI', '_ONE', '_Sequence', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', '_accumulate', '_acos', '_bisect', '_ceil', '_cos', '_e', '_exp', '_fabs', '_floor', '_index', '_inst', '_isfinite', '_lgamma', '_log', '_log2', '_os', '_parse_args', '_pi', '_random', '_repeat', '_sha512', '_sin', '_sqrt', '_test', '_test_generator', '_urandom', 'betavariate', 'binomialvariate', 'choice', 'choices', 'expovariate', 'gammavariate', 'gauss', 'getrandbits', 'getstate', 'lognormvariate', 'main', 'normalvariate', 'paretovariate', 'randbytes', 'randint', 'random', 'randrange', 'sample', 'seed', 'setstate', 'shuffle', 'triangular', 'uniform', 'vonmisesvariate', 'weibullvariate']
help(random.seed)
Help on method seed in module random:

seed(a=None, version=2) method of random.Random instance
    Initialize internal state from a seed.

    The only supported seed types are None, int, float,
    str, bytes, and bytearray.

    None or no argument seeds from current time or from an operating
    system specific randomness source if available.

    If *a* is an int, all bits are used.

    For version 2 (the default), all of the bits are used if *a* is a str,
    bytes, or bytearray.  For version 1 (provided for reproducing random
    sequences from older versions of Python), the algorithm for str and
    bytes generates a narrower range of seeds.
random.seed()
help(random.random)
Help on built-in function random:

random() method of random.Random instance
    random() -> x in the interval [0, 1).

random.random()
0.3783037280071182
help(random.uniform)
Help on method uniform in module random:

uniform(a, b) method of random.Random instance
    Get a random number in the range [a, b) or [a, b] depending on rounding.

    The mean (expected value) and variance of the random variable are:

        E[X] = (a + b) / 2
        Var[X] = (b - a) ** 2 / 12

random.uniform(3,5)
4.139029942389151
help(random.randint)
Help on method randint in module random:

randint(a, b) method of random.Random instance
    Return random integer in range [a, b], including both end points.

random.randint(4,88)
5
help(random.gauss)
Help on method gauss in module random:

gauss(mu=0.0, sigma=1.0) method of random.Random instance
    Gaussian distribution.

    mu is the mean, and sigma is the standard deviation.  This is
    slightly faster than the normalvariate() function.

    Not thread-safe without a lock around calls.

random.gauss()
0.11579183153210448
help(random.choice)
Help on method choice in module random:

choice(seq) method of random.Random instance
    Choose a random element from a non-empty sequence.
random.choice(qq)
'Лыкова'
help(random.shuffle)
Help on method shuffle in module random:

shuffle(x) method of random.Random instance
    Shuffle list x in place, and return None.

random.shuffle(qq)
qq
['Коваленко', 'Лыкова', 'Соловьёва', 'Голощапов']
help(random.sample)
Help on method sample in module random:

sample(population, k, *, counts=None) method of random.Random instance
    Chooses k unique random elements from a population sequence.

    Returns a new list containing elements from the population while
    leaving the original population unchanged.  The resulting list is
    in selection order so that all sub-slices will also be valid random
    samples.  This allows raffle winners (the sample) to be partitioned
    into grand prize and second place winners (the subslices).

    Members of the population need not be hashable or unique.  If the
    population contains repeats, then each occurrence is a possible
    selection in the sample.

    Repeated elements can be specified one at a time or with the optional
    counts parameter.  For example:

        sample(['red', 'blue'], counts=[4, 2], k=5)

    is equivalent to:

        sample(['red', 'red', 'red', 'red', 'blue', 'blue'], k=5)

    To choose a sample from a range of integers, use range() for the
    population argument.  This is especially fast and space efficient
    for sampling from a large population:

        sample(range(10000000), 60)

random.sample(qq,3)
['Соловьёва', 'Лыкова', 'Голощапов']
help(random.betavariate)
Help on method betavariate in module random:

betavariate(alpha, beta) method of random.Random instance
    Beta distribution.

    Conditions on the parameters are alpha > 0 and beta > 0.
    Returned values range between 0 and 1.

    The mean (expected value) and variance of the random variable are:

        E[X] = alpha / (alpha + beta)
        Var[X] = alpha * beta / ((alpha + beta)**2 * (alpha + beta + 1))
random.betavariate(2,5)
0.5473034184133493
help(random.gammavariate)
Help on method gammavariate in module random:

gammavariate(alpha, beta) method of random.Random instance
    Gamma distribution.  Not the gamma function!

    Conditions on the parameters are alpha > 0 and beta > 0.

    The probability distribution function is:

                x ** (alpha - 1) * math.exp(-x / beta)
      pdf(x) =  --------------------------------------
                  math.gamma(alpha) * beta ** alpha

    The mean (expected value) and variance of the random variable are:

        E[X] = alpha * beta
        Var[X] = alpha * beta ** 2

random.gammavariate(2,5)
4.616261402628337
spis = [random.uniform(0,10),random.gauss(50,15),random.betavariate(2,5),random.gammavariate(2,5)]
spis
[0.21672125817392973, 25.399177937155795, 0.14356042747670408, 10.552855133080406]

6. Функции модуля time.

import time
dir(time)
['_STRUCT_TM_ITEMS', '__doc__', '__loader__', '__name__', '__package__', '__spec__', 'altzone', 'asctime', 'ctime', 'daylight', 'get_clock_info', 'gmtime', 'localtime', 'mktime', 'monotonic', 'monotonic_ns', 'perf_counter', 'perf_counter_ns', 'process_time', 'process_time_ns', 'sleep', 'strftime', 'strptime', 'struct_time', 'thread_time', 'thread_time_ns', 'time', 'time_ns', 'timezone', 'tzname']
c1=time.time()
c2=time.time()-c1
c1,c2
(1761295798.980248, 5.403235197067261)
dat=time.gmtime()
dat
time.struct_time(tm_year=2025, tm_mon=10, tm_mday=24, tm_hour=8, tm_min=50, tm_sec=26, tm_wday=4, tm_yday=297, tm_isdst=0)
dat.tm_mon
10
local_time = time.localtime()
local_time
time.struct_time(tm_year=2025, tm_mon=10, tm_mday=24, tm_hour=11, tm_min=50, tm_sec=50, tm_wday=4, tm_yday=297, tm_isdst=0)
print(f"Год: {local_time.tm_year}")
Год: 2025
c1 = time.time()
local_struct = time.localtime(c1)
local_struct
time.struct_time(tm_year=2025, tm_mon=10, tm_mday=24, tm_hour=11, tm_min=54, tm_sec=13, tm_wday=4, tm_yday=297, tm_isdst=0)
time_str = time.asctime(local_struct)
time_str
'Fri Oct 24 11:54:13 2025'
time_str2 = time.ctime(c1)
time.sleep(2)
seconds = time.mktime(local_struct)
seconds
1761296053.0
new_struct = time.localtime(seconds)
new_struct
time.struct_time(tm_year=2025, tm_mon=10, tm_mday=24, tm_hour=11, tm_min=54, tm_sec=13, tm_wday=4, tm_yday=297, tm_isdst=0)

7. Графические функции.

import pylab
x=list(range(-3,55,4))
t=list(range(15))
x
[-3, 1, 5, 9, 13, 17, 21, 25, 29, 33, 37, 41, 45, 49, 53]
t
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]
pylab.plot(t,x)
[<matplotlib.lines.Line2D object at 0x000002487CE9E990>]
pylab.title('Первый график')
Text(0.5, 1.0, 'Первый график')
pylab.xlabel('время')
Text(0.5, 0, 'время')
pylab.ylabel('сигнал')
Text(0, 0.5, 'сигнал')
pylab.show()

X1=[12,6,8,10,7]
X2=[5,7,9,11,13]
pylab.plot(X1)
[<matplotlib.lines.Line2D object at 0x000002487D263390>]
pylab.plot(X2)
[<matplotlib.lines.Line2D object at 0x000002487D2634D0>]
pylab.show()

region=['Центр','Урал','Сибирь','Юг']
naselen=[65,12,23,17]
pylab.pie(naselen,labels=region)
([<matplotlib.patches.Wedge object at 0x000002487CE1DFD0>, <matplotlib.patches.Wedge object at 0x000002487D305090>, <matplotlib.patches.Wedge object at 0x000002487D305450>, <matplotlib.patches.Wedge object at 0x000002487D3056D0>], [Text(-0.191013134139045, 1.0832885038559115, 'Центр'), Text(-0.861328292412156, -0.6841882582231001, 'Урал'), Text(0.04429273995539947, -1.0991078896938387, 'Сибирь'), Text(0.9873750693480946, -0.48486129194837324, 'Юг')])
pylab.show()

data = [1, 2, 2, 3, 3, 3, 4, 4, 5]
pylab.hist(data,5)
(array([1., 2., 3., 2., 1.]), array([1. , 1.8, 2.6, 3.4, 4.2, 5. ]), <BarContainer object of 5 artists>)
pylab.show()

c = ['A', 'B', 'C']
v = [10, 25, 15]
pylab.bar(c, v)
<BarContainer object of 3 artists>
pylab.show()

8. Модуль statistics.

import statistics
data = [1, 2, 2, 3, 3, 3, 4, 4, 5]
sred = statistics.mean(data)
sred
3
moda = statistics.mode(data)
moda
3
mediana = statistics.median(data)
mediana
3