Spec-Zone.ru › Matplotlib 3.3

matplotlib.axes.Axes.semilogx

Axes.semilogx(self, *args, **kwargs) [source]

Создать график с логарифмической шкалой по оси X.

Подписи:

semilogx([x], y, [fmt], data=None, **kwargs)
semilogx([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)

Это всего лишь тонкий обертка вокруг plot, которая дополнительно меняет шкалу оси X на логарифмическую. Все понятия и параметры plot также можно использовать здесь.

Дополнительные параметры base, subs и nonpositive контролируют свойства оси X. Они просто передаются в Axes.set_xscale.

Параметры:
basefloat, default: 10

Основание логарифма оси X.

subsarray-like, optional

Позиции дополнительных делений на оси X. Если None, то разумные позиции автоматически выбираются в зависимости от количества десятичных разрядов на графике. Подробнее см. Axes.set_xscale.

nonpositive{'mask', 'clip'}, default: 'mask'

Значения на оси X, меньшие или равные нулю, могут быть замаскированы как недопустимые или ограничены очень маленьким положительным числом.

Возвращает:
lines

Список объектов Line2D, представляющих нарисованные данные.

Другие параметры:
**kwargs

Все параметры, поддерживаемые plot.

Примеры использования matplotlib.axes.Axes.semilogx

<img alt="Демонстрация логарифмов" src="data:image/png;base64,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

Демонстрация логарифмического масштаба

Ось логарифмического масштаба

Ось логарифмического масштаба

Учебник по преобразованиям

Учебник по преобразованиям

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