форкнуто от main/python-labs
Lykova Liza
1 день назад
Родитель
6eeabd204f
Сommit
1e83bb9abd
@ -0,0 +1,542 @@
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# Отчет по теме 4
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Лыкова Елизавета, А-01-23
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## 1. Запуск IDLE, привязка католога, создание файла отчета.
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```py
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import os
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os.chdir("C:\\Users\\Home\\Desktop\\python-labs\\TEMA4")
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```
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## 2. Стандартные функции.
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## 2.1 Функция round.
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```py
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help(round)
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Help on built-in function round in module builtins:
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round(number, ndigits=None)
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Round a number to a given precision in decimal digits.
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The return value is an integer if ndigits is omitted or None. Otherwise
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the return value has the same type as the number. ndigits may be negative.
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round(123.456,1)
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123.5
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round(123.456,0)
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123.0
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a = round(123.456,1)
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b = round(123.456,0)
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type(a)
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<class 'float'>
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type(b)
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<class 'float'>
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c = round(123.456)
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c
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123
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type(c)
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<class 'int'>
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```
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В первых двух случаях типы получившихся данных - float, когда во втором - int.
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## 2.2 Функция range.
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```py
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gg = range(76,123,9)
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gg
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range(76, 123, 9)
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list(gg)
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[76, 85, 94, 103, 112, 121]
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range(23)
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range(0, 23)
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d = range(23)
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list(d)
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[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]
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```
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Диапазон начинается от нуля и заканчивается предыдущим числом заданных 23-х. Шаг - единица.
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## 2.3 Функция zip.
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```py
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qq = ['Лыкова','Соловьёва','Коваленко','Голощапов']
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ff = zip(gg,qq)
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tuple(ff)
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((76, 'Лыкова'), (85, 'Соловьёва'), (94, 'Коваленко'), (103, 'Голощапов'))
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print(ff[0])
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Traceback (most recent call last):
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File "<pyshell#20>", line 1, in <module>
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print(ff[0])
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TypeError: 'zip' object is not subscriptable
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tt = tuple(ff)
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tt
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((76, 'Лыкова'), (85, 'Соловьёва'), (94, 'Коваленко'), (103, 'Голощапов'))
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print(tt[1])
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(85, 'Соловьёва')
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```
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К объекту ff можно обратиться с указанием индекса, преобразовав его в кортеж.
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## 2.4 Функция eval.
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```py
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fff = float(input('Коэффициент усиления='));dan = eval('5*fff-156')
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Коэффициент усиления=3
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dan
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-141.0
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```
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## 2.5 Функция exec.
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```py
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exec(input('Введите инструкции:'))
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Введите инструкции:perem=-123.456;gg=round(abs(perem)+98,3)
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gg
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221.456
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```
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## 2.6 Функции abs,pow,max,min,sum,dinmod,len,map.
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```py
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abs(-5)
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5
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abs(10-15)
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5
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#Возвращает модуль числа
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pow(2,3)
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8
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pow(5,2)
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25
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#Возводит в степень
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chis = [4,5,2,8]
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max(chis)
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8
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min(chis)
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2
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slova = ['Радуга','Яблоко','Ананас','Груша']
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max(slova)
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'Яблоко'
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min(slova)
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'Ананас'
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#Находят максимальное и минимальное значения
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sum(chis)
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19
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sum(chis,10)
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29
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#Находит сумму элементов
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divmod(10,3)
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(3, 1)
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#Находит частное и остаток от деления
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len(chis)
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4
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строка = 'Hallo!'
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len(строка)
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6
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slov = {'a':10,'b':20,'c':30}
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len(slov)
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3
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#Возвращает количество элементов в объекте
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list(map(str,chis))
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['4', '5', '2', '8']
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list(map(lambda x:x*2,chis))
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[8, 10, 4, 16]
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#Применение функции к каждому элементу последовательности
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```
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## 3. Функции модуля math.
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```py
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import math
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dir(math)
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['__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']
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help(math.factorial)
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Help on built-in function factorial in module math:
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factorial(n, /)
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Find n!.
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math.factorial(5)
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120
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help(math.sin)
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Help on built-in function sin in module math:
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sin(x, /)
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Return the sine of x (measured in radians).
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math.sin(1)
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0.8414709848078965
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help(math.acos)
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Help on built-in function acos in module math:
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acos(x, /)
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Return the arc cosine (measured in radians) of x.
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The result is between 0 and pi.
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math.acos(0.5)
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1.0471975511965979
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help(math.degrees)
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Help on built-in function degrees in module math:
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degrees(x, /)
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Convert angle x from radians to degrees.
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math.degrees(45)
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2578.3100780887044
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help(math.radians)
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Help on built-in function radians in module math:
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radians(x, /)
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Convert angle x from degrees to radians.
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math.radians(45)
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0.7853981633974483
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help(math.exp)
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Help on built-in function exp in module math:
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exp(x, /)
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Return e raised to the power of x.
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math.exp(3)
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20.085536923187668
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help(math.log)
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Help on built-in function log in module math:
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log(...)
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log(x, [base=math.e])
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Return the logarithm of x to the given base.
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If the base is not specified, returns the natural logarithm (base e) of x.
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math.log(4,3)
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1.2618595071429148
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help(math.log10)
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Help on built-in function log10 in module math:
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log10(x, /)
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Return the base 10 logarithm of x.
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math.log10(3)
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0.47712125471966244
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help(math.sqrt)
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Help on built-in function sqrt in module math:
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sqrt(x, /)
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Return the square root of x.
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math.sqrt(5)
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2.23606797749979
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help(math.ceil)
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Help on built-in function ceil in module math:
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ceil(x, /)
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Return the ceiling of x as an Integral.
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This is the smallest integer >= x.
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math.ceil(3.2)
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4
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help(math.floor)
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Help on built-in function floor in module math:
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floor(x, /)
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Return the floor of x as an Integral.
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This is the largest integer <= x.
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math.floor(3.8)
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3
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math.pi
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3.141592653589793
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math.sin((2*math.pi/7)+(math.exp(0.23)))
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0.8334902641414562
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```
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## 4. Функции из модуля cmath.
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```py
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import cmath
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dir(cmath)
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['__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']
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cmath.sqrt(1.2-0.5j)
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(1.118033988749895-0.22360679774997896j)
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cmath.phase(1-0.5j)
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-0.4636476090008061
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```
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## 5. Модуль random.
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```py
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import random
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dir(random)
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['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']
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help(random.seed)
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Help on method seed in module random:
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seed(a=None, version=2) method of random.Random instance
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Initialize internal state from a seed.
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The only supported seed types are None, int, float,
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str, bytes, and bytearray.
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None or no argument seeds from current time or from an operating
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system specific randomness source if available.
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If *a* is an int, all bits are used.
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For version 2 (the default), all of the bits are used if *a* is a str,
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bytes, or bytearray. For version 1 (provided for reproducing random
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sequences from older versions of Python), the algorithm for str and
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bytes generates a narrower range of seeds.
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random.seed()
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help(random.random)
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Help on built-in function random:
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random() method of random.Random instance
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random() -> x in the interval [0, 1).
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random.random()
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0.3783037280071182
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help(random.uniform)
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Help on method uniform in module random:
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uniform(a, b) method of random.Random instance
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Get a random number in the range [a, b) or [a, b] depending on rounding.
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The mean (expected value) and variance of the random variable are:
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E[X] = (a + b) / 2
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Var[X] = (b - a) ** 2 / 12
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random.uniform(3,5)
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4.139029942389151
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help(random.randint)
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Help on method randint in module random:
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randint(a, b) method of random.Random instance
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Return random integer in range [a, b], including both end points.
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random.randint(4,88)
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5
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help(random.gauss)
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Help on method gauss in module random:
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gauss(mu=0.0, sigma=1.0) method of random.Random instance
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Gaussian distribution.
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mu is the mean, and sigma is the standard deviation. This is
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slightly faster than the normalvariate() function.
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Not thread-safe without a lock around calls.
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random.gauss()
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0.11579183153210448
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help(random.choice)
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Help on method choice in module random:
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choice(seq) method of random.Random instance
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Choose a random element from a non-empty sequence.
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random.choice(qq)
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'Лыкова'
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help(random.shuffle)
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Help on method shuffle in module random:
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shuffle(x) method of random.Random instance
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Shuffle list x in place, and return None.
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random.shuffle(qq)
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qq
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['Коваленко', 'Лыкова', 'Соловьёва', 'Голощапов']
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help(random.sample)
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Help on method sample in module random:
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sample(population, k, *, counts=None) method of random.Random instance
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Chooses k unique random elements from a population sequence.
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Returns a new list containing elements from the population while
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leaving the original population unchanged. The resulting list is
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in selection order so that all sub-slices will also be valid random
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samples. This allows raffle winners (the sample) to be partitioned
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into grand prize and second place winners (the subslices).
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Members of the population need not be hashable or unique. If the
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population contains repeats, then each occurrence is a possible
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selection in the sample.
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Repeated elements can be specified one at a time or with the optional
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counts parameter. For example:
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sample(['red', 'blue'], counts=[4, 2], k=5)
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is equivalent to:
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sample(['red', 'red', 'red', 'red', 'blue', 'blue'], k=5)
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To choose a sample from a range of integers, use range() for the
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population argument. This is especially fast and space efficient
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for sampling from a large population:
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sample(range(10000000), 60)
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random.sample(qq,3)
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['Соловьёва', 'Лыкова', 'Голощапов']
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help(random.betavariate)
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Help on method betavariate in module random:
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betavariate(alpha, beta) method of random.Random instance
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Beta distribution.
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Conditions on the parameters are alpha > 0 and beta > 0.
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Returned values range between 0 and 1.
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The mean (expected value) and variance of the random variable are:
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E[X] = alpha / (alpha + beta)
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Var[X] = alpha * beta / ((alpha + beta)**2 * (alpha + beta + 1))
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random.betavariate(2,5)
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0.5473034184133493
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help(random.gammavariate)
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Help on method gammavariate in module random:
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gammavariate(alpha, beta) method of random.Random instance
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Gamma distribution. Not the gamma function!
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Conditions on the parameters are alpha > 0 and beta > 0.
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The probability distribution function is:
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x ** (alpha - 1) * math.exp(-x / beta)
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pdf(x) = --------------------------------------
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math.gamma(alpha) * beta ** alpha
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The mean (expected value) and variance of the random variable are:
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E[X] = alpha * beta
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Var[X] = alpha * beta ** 2
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random.gammavariate(2,5)
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4.616261402628337
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spis = [random.uniform(0,10),random.gauss(50,15),random.betavariate(2,5),random.gammavariate(2,5)]
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spis
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[0.21672125817392973, 25.399177937155795, 0.14356042747670408, 10.552855133080406]
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```
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## 6. Функции модуля time.
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```
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import time
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dir(time)
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['_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']
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c1=time.time()
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c2=time.time()-c1
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c1,c2
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(1761295798.980248, 5.403235197067261)
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dat=time.gmtime()
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dat
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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)
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dat.tm_mon
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10
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local_time = time.localtime()
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local_time
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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)
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print(f"Год: {local_time.tm_year}")
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Год: 2025
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c1 = time.time()
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local_struct = time.localtime(c1)
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local_struct
|
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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.
|
||||
|
||||
```py
|
||||
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.
|
||||
|
||||
```py
|
||||
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
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
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