Spec-Zone.ru › Matplotlib 3.5

matplotlib.axes.Axes.contour

Axes.contour(*args, data=None, **kwargs)[source]

Построение контурных линий.

Вызов:

contour([X, Y,] Z, [levels], **kwargs)

contour и contourf рисуют контурные линии и заполненные контуры соответственно. За исключением указанных случаев, сигнатуры функций и возвращаемые значения одинаковы для обеих версий.

Параметры
X, Yмассив-подобный объект, необязательно

Координаты значений в Z.

X и Y должны быть оба 2D с такой же формой, что и Z (например, созданные с помощью numpy.meshgrid), или они оба должны быть 1D, так что len(X) == N является количеством столбцов в Z, а len(Y) == M является количеством строк в Z.

X и Y должны быть упорядочены монотонно.

Если не заданы, предполагается, что они являются целочисленными индексами, т.е. X = range(N), Y = range(M).

Z(M, N) массив-подобный объект

Значения высот, по которым строится контур.

levelsцелое число или массив-подобный объект, необязательно

Определяет количество и позиции контурных линий / областей.

Если целое число n, используйте MaxNLocator, который пытается автоматически выбрать не более n+1 «приличных» уровней контуров между vmin и vmax.

Если массив-подобный объект, строит контурные линии на заданных уровнях. Значения должны быть в порядке возрастания.

Возвращает
QuadContourSet
Другие параметры
END_OF_DOCUMENT_MARKER
corner_maskbool, default: rcParams["contour.corner_mask"] (default: True)

Включить/отключить маскировку углов, что оказывает влияние только если Z является массивной маской. Если False, любой квадрат, соприкасающийся с замаскированной точкой, будет замаскирован. Если True, только треугольные углы квадратов, ближайших к этим точкам, всегда будут замаскированы, другие треугольные углы, состоящие из трёх незамаскированных точек, будут контурированы как обычно.

colorsстрока цвета или последовательность цветов, необязательно

Цвета уровней, то есть линии для contour и области для contourf.

Последовательность циклически применяется к уровням в порядке возрастания. Если последовательность короче, чем количество уровней, она повторяется.

В качестве сокращения можно использовать строковые цвета вместо списков с одним элементом, например, 'red' вместо ['red'], чтобы окрасить все уровни одним цветом. Это сокращение работает только для строковых цветов, а не для других способов задания цветов.

По умолчанию (значение None) будет использована цветовая карта, указанная параметром cmap.

alphafloat, default: 1

Значение альфа-смешивания, от 0 (прозрачный) до 1 (непрозрачный).

cmapстрока или Colormap, default: rcParams["image.cmap"] (default: 'viridis')

Экземпляр Colormap или зарегистрированное имя цветовой карты. Цветовая карта сопоставляет значения уровня с цветами.

Если заданы и colors и cmap, произойдёт ошибка.

normNormalize, optional

Если используется цветовая карта, экземпляр Normalize масштабирует значения уровня до стандартного диапазона цветовой карты [0, 1] для сопоставления с цветами. Если не задано, используется стандартное линейное масштабирование.

vmin, vmaxfloat, optional

Если не None, эти значения будут переданы экземпляру Normalize, переопределяя стандартное масштабирование цветов на основе levels.

origin{None, 'upper', 'lower', 'image'}, default: None

Определяет ориентацию и точное положение Z, указывая положение Z[0, 0]. Это актуально только если X, Y не заданы.

  • None: Z[0, 0] находится в левом нижнем углу при X=0, Y=0.
  • 'lower': Z[0, 0] находится в левом нижнем углу при X=0.5, Y=0.5.
  • 'upper': Z[0, 0] находится в левом верхнем углу при X=N+0.5, Y=0.5.
  • 'image': Использовать значение из rcParams["image.origin"] (default: 'upper').
extent(x0, x1, y0, y1), optional

Если origin не None, то extent интерпретируется как в imshow: он задаёт внешние границы пикселя. В этом случае положение Z[0, 0] - центр пикселя, а не угол. Если origin равен None, то (x0, y0) - положение Z[0, 0], а (x1, y1) - положение Z[-1, -1].

Этот аргумент игнорируется, если X и Y указаны при вызове contour.

locatorподкласс ticker.Locator, optional

Локатор используется для определения уровней контура, если они не заданы явно через levels. По умолчанию MaxNLocator.

extend{'neither', 'both', 'min', 'max'}, default: 'neither'

Определяет contourf-окрашивание значений, которые лежат вне диапазона levels.

Если 'neither', значения вне диапазона levels не окрашиваются. Если 'min', 'max' или 'both', окрашиваются значения ниже, выше или ниже и выше диапазона levels.

Значения ниже min(levels) и выше max(levels) сопоставляются со значениями ниже/выше цветовой карты Colormap. Обратите внимание, что большинство цветовых карт по умолчанию не имеют выделенных цветов для них, поэтому значения выше/ниже - это крайние значения цветовой карты. Вы можете явно установить эти значения с помощью Colormap.set_under и Colormap.set_over.

Примечание

Существующий QuadContourSet не получает уведомлений о изменениях свойств его цветовой карты. Поэтому требуется явный вызов QuadContourSet.changed() после изменения цветовой карты. Явный вызов можно пропустить, если цветовая шкала присвоена QuadContourSet, так как она в этом случае внутри вызывает QuadContourSet.changed().

Пример:

x = np.arange(1, 10)
y = x.reshape(-1, 1)
h = x * y

cs = plt.contourf(h, levels=[10, 30, 50],
    colors=['#808080', '#A0A0A0', '#C0C0C0'], extend='both')
cs.cmap.set_over('red')
cs.cmap.set_under('blue')
cs.changed()
xunits, yunitsзарегистрированные единицы, необязательно

Переопределить единицы оси, указав экземпляр matplotlib.units.ConversionInterface.

antialiasedbool, optional

Включить сглаживание, переопределив значения по умолчанию. Для заполненных контуров значение по умолчанию True. Для контуров линий оно взято из rcParams["lines.antialiased"] (default: True).

nchunkint >= 0, optional

Если 0, подсечения области не происходит. Укажите положительное целое число, чтобы разделить область на поддомены размером nchunk на nchunk квадратов. Разбиение уменьшает максимальную длину полигонов, генерируемых алгоритмом контурирования, что снижает нагрузку на отрисовку, передаваемую бэкэнду, и также требует немного меньше ОЗУ. Однако в зависимости от бэкэнда, флага antialiased и значения alpha, оно может вводить артефакты отрисовки на границах поддоменов.

linewidthsfloat или массив, default: rcParams["contour.linewidth"] (default: None)

Только применимо к contour.

Ширина линий контуров.

Если число, все уровни будут нарисованы с этой шириной.

Если последовательность, уровни в порядке возрастания будут нарисованы с ширинами линий в указанном порядке.

Если None, это обращается к значению rcParams["lines.linewidth"] (default: 1.5).

linestyles{None, 'solid', 'dashed', 'dashdot', 'dotted'}, optional

Только применимо к contour.

Если linestyles равно None, значение по умолчанию - 'solid', за исключением случаев монохромных линий. В этом случае отрицательные контуры будут использовать стиль линии из rcParams["contour.negative_linestyle"] (default: 'dashed').

linestyles также может быть итерируемым списком вышеуказанных строк, определяющих набор стилей линий, которые будут использоваться. Если этот список короче, чем количество уровней контура, он будет повторяться по необходимости.

hatchesсписок[строка], optional

Только применимо к contourf.

Список шаблонов штриховки для заполненных областей. Если None, штриховка не будет добавлена к контуру. Штриховка поддерживается только в бэкендах PostScript, PDF, SVG и Agg.

dataиндексируемый объект, необязательно

Если задан, все параметры также принимают строку s, которая интерпретируется как data[s] (если это не вызовет исключение).

Примечания

  1. contourf отличается от версии MATLAB тем, что не рисует края полигонов. Чтобы нарисовать края, добавьте контуры линий с помощью вызовов contour.
  2. contourf заполняет интервалы, которые закрыты сверху; то есть для границ z1 и z2 заполненная область:

    z1 < Z <= z2
    

    за исключением самого нижнего интервала, который закрыт с обеих сторон (т.е. включает самое низкое значение).

  3. contour и contourf используют алгоритм marching squares для вычисления положений контура. Дополнительную информацию можно найти в исходном коде src/_contour.h.

Примеры использования matplotlib.axes.Axes.contour

<img alt="Маска угла контура" 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

Маска углов контура

Демонстрация контуров

Демонстрация контуров

Демонстрация меток контура

Демонстрация меток контура

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<img alt="Демонстрация Contourf" 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

Демонстрация Contourf

<img alt="Контурное заполнение" src="data:image/png;base64,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

Штриховка контуров

<img alt="Построение контуров области решений задач оптимизации" 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

Контурирование области решений оптимизаций

<img alt="Смешивание прозрачности с цветом в 2D изображениях" 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

Смешивание прозрачности с цветом на 2D изображениях

<img alt="График контуров неравномерно расположенных данных" 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

График контуров неравномерно распределённых данных

Демонстрация эффекта траекторииДемонстрация эффекта траектории
Эффект штриховки с делениями

Эффект штриховки с делениями

<img alt="Демонстрирует построение линий контура (уровня) в 3D" 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LjxlQc9XU6lTTGbKwcoybAQbzT2wnlTGXEgjgrjKzFzePmfq+GgXa80BYywO4jtWneMirvXnd6X61TedtK2JjvRQoJnGN/bZ7buoo8rr+a4tXfjCdA3hYx4hsIxp2dZ2+XpAZmuoio8QlMhzoj6SYwVlGI8DQT16UmuVmqczpZTpuhYkHsjXWm1OredTqt70221+medi4MvnTZXdM6tKn8/6h5chWNKPIP/taT9OVoQPM+cQ/tmfn7+7cTzlTE9wohkfXDNxSNCxEP5sbNLIm3dQjwP80ykYYDIEw57sPoCP285aeAfc720uke9MMlg7gBaw1azEDaLlvav8+vLyw5GeXFw0GsNK2AGLU6TOKvQ71V2YRgaSc6qzJ+H7q6fHID+l/98/fr9X16OJ8CnGEYSFxsLhtmWDNblX/baPYluklLEAo3wI1mECEDWlKcFhFWYE6qNUk01wcbhzla4q8CjVp8JB4i27kLmHDq/Hva7vYODi25/WD9J/yY0T4YHA4ssdyTKMSI73Ei0wMxzdy9yQfetfGTHF2A2SGNAtyfCAB1NNp0hnDG75KUORzcyxFPrIoJDzftVRGyMJlVXSzWGi4KNiy+p9rASE+wcZu4W2lQzVVZS+UqbQDzA7cnFRa/XcQxQLBckwxGym0miBU6dNx6FjQGAwSyWEpI84/YC5umakaBDOE9imS5WIlFPKiDQSPeyuA9xs2EV8QAwqnBeQCjMYBsYx6UUwHYFf1jCWfesea8bQiwa1KVI0nc06He73duzQf2k6GhPzB6OyJDru/x5DDAz//TRAMzoEVt9sTt2+XUXy6Z8UIqiFAxTi8N6l1PELOIjTFoSFNYcgPgTIKxiRW0ebh9eH27ttOv1ylHz+LY1ECxHNmIkPJgM4ZbPhwuxMzyyHLyqzDkmMK7EwrNZbBjzryceBcAnsDRZztnqq3NeKYjIEA4ChFjOoGeZVZcW7DGTf0qKQiWGNUPQcBsMAPEPL1ZLqxu1rWNMrl6vbx0eXh1vHW93uq3BUVOEisQA7fAgkJCU0MKg3+q0BYpQk7iRVa3A5qLsN3VnppRfeRaZeDO3PK4AkSe+mDJs9+KfJHRAmGEFhmFZcpaxZmToOBOhhWkSqLJ+b256OjSV1uxWjhNqG6v7ehTe3cXtilhWpjfP6/WzVre/vbNTr6RlZ5UD+ubUByV03m+1BqI12g7aI8+MlvU/++UlVRE1uTinz8XfCmMKEKtvNGF3Iu5FmW6zsUnTRefBcR8Cg8PDNhZ+wqV/sLfNE7qi4UtPWvoQtN0wrrJqo1FaVwWO7FppS9P4zjOHrdZZe2dr+3inXTmB6xEYZXTONxWZvrxptfGT6QcAuZCPYTyh+TWnE/nxZu3HxPyYdiJGJG1ofntYHnqu2u4lGKYrMPgsG0xkEiFYJsI3oRxIaIiyVjwuEeaVizDP9NH8QJQzU/uNUrUGEHk9I5hxRfp21WoNj3K/1THFrZ36EZzogM6Qt9OlrrqdupiOMA8A4sbufij35NO7ieWVibfmmFagByFvmK5xyNFUjh5UVt8U7HmwT5UBpUuiTxgJuBRZRsesQUQEVeGwNMD2gQaDdVGob59/La2WNqqqbs7MzDBa3h+7vOl2DoUC16y0t7a3d+rNfJinp9mq9G+ulxbtXwAFCI2da9Np3WL/XnnFv577PK6DdeQmw3LYR+Dspg65/ItZw54HKwr11ApCyQhcipgxG435UjkKUMPM7DRQIYN1ptne3vGtb5RWG6sbuBZFjscm8fD2pkXjVC+BeA6FSHBZw87UYiSmZ3OOk5Y13Mktf3ZeYCaYnmADYxuoIpj1ullOmcKFR5o6fFDzZpLaP/fSNImx0F8b67/u/VwsuP1Rlg1I3qeptA2QhtDEyE1J5QiswQDCE243/HsVY1wt4Wqs/WwubWFN7g8qTavINf843t5qVyhDrmmGeTXvl+QEDRdiuJ1xv//xOGzMBMbDhyD6A3RJ7PCwe4ka5qS9mrBghy+F09ONjRL+wDfc19Oa9T2RNlzwFyZUSXwwWPdDRyFghO2mDp2It1arbgDHRqn09dvV7W0HLHQ2MVPZ2d6qnwBCsiYM2+jQzODrVMbfdL9683gAehTYHycHNmiA5LKIjJfYdCxn7/iymXKaRW5X0fr16+lXINlYra5Xa16YpT8crAvpJOxrmTtbdivHEeXN7NXWq1CR+/t7e/t74Ww+k/nj+Hi73uRmgn4eHqLrIcpSORvljJej4cGTsQbIMssJGkmzwSAfIm8LSSdYhLKSYDhvbw3JNMYyEpsmfsD1/dffN04bp43V0n61JgocN/qWf4aY5W+HQOdui/d/1FxtT9tYFpav7Rs7duw4sR077y91nEzTQFuUZmlZUmgLYcKQBijtilmJ0hdpWhZBhTogDZqZLfNhtNKq00rT+bYf2v+5597rJE4/j0YpEuIl+WAezj3nOc95znU5CpKsmOvrF6et0+NO5wOA+T3Um873vZX19XWTtSOllp7R7Lnl8TMu/3roTS2AHu8bLRQoqnVLY2UkrXvI1kXm8QX2V4g6mJbq2FLSYztfhUQlVSmcnp5ukJJLQJxc+fer83/8/uAbNagVdXfsbcNS3qm6hgsl/mA9Vv3V/kBiurPKXk0nJDmt//TT6AzL99KLrekFMK8pTOMj7GWesZeoqcusp6uXeSgqSZ7KWFE+79hMffWA6AjAA+XKltYgYUR4ixz2BxJLZezjgwcfK0RjwXUHT1gHEWdCmGq5usr9e/vnNYhMRQks+0Crsfev+yMrR/Jq5Mny1AJYs0XeUVmbYd8oDr0dLcNnM+KsBy0xTzdtoqKtU/EQznS5XfeQQm86UUy6sX4BQdRLqKHhhgsdhbK2/fsfVr6EKxMAUskv8PhaVbtwJeS9rNCp5sOZ0SMq97g781MLILVRku6CN424XwiMlYXHwTy4VKhagYzl4UQ16pFCDWe6DEAiRqTJHIms2Rjuh87G6oo64dSFg722/fMPmYSRUUN2rKGbiNWN+S19rKeyWBV2tPEzPr31dXR6jzCAQ7oLvmakvLROM6DkuE6QFf12lslYtpImmiufT/K8YtQIkCwCh8Z8DIGYaUNZ6ZlB2nNj7KsMjOXZf+Y1qxwLzJdkZBzafS2U445BLP/Ujc4AXMiF/8vT7EwAlIAUiwVHipLJOlOkOYfhp7SM4FDndI2MSQjTAXbDE8ooqcpnxnx1JpuYebNxc51UFBaBDMIfnz14sEYWsW0qPXB62I4FP6GA/eR9LMXJ8pjwZyx6/WUAZksctRDRPXQIRdPDjshcMvlCIGO9NLb4kEzWNKg0fLUWxWYqpZqaGeaBMk7VcscAIRQYazztxdz7H7aBN6dqNrkRAOdqE1tgNTxkP0DDbV3isHCn8oUASKdKthZjbjaLF2gocgAgcWNxKhtnUvGAXRizpRPSA5EoSsQZWJ9Jq5NzYUhr/mqnc1E3/PHIGNd0zHoP6PgsbT5nhjKiHVpi8qszj91yiVtEo0csvLh/KbL8VJhWAKO81mIlQ+BcTIm0ILmIR04OKovNxkyVLBVqeHQ9wdNv4jP5tCQKfqMuk0BUJgfrWOl13nzKUNMby3pJcj3Ko2+ekR74USqTSZCJcLDpNbHEhPK5UtZ58aotDR+x9e2d+/fnHj6fUgB5yd4KDNCCOJNhNA+5oqJBF0c9vnwc6gvd9eLNRIL1dhKXzltaMX8jFUVIktWUaX6WEJXexoZtjRzn7HIKzBSt7Z8/rtWLluZUiS0Qu/VJiiNxUvmXh6QMy47jJCORhfaCkbo1nQBGoGQMtRe+GtxuIohOzUgzjy8dYrJdL76SUSvkvSL8ieLsrGp8Oj3u9buXUROdQSCaZth0hd2Lm6ulmpNJQPVFo9s9IOgerf26DShuP4sDgSzUFXfCsk/uBuDqbCSi7+zs/D1y90lkruFfnU4ARSvlsYsQoqLuWIE1IbqlcYHHF/o4qu1XiN0IewRskeMQ6u5t7u4PBvvwOdjdPNzrXz47qzZS5lhbSKTV1U7vQCajtpybC3mpOaeCH/24tkY3dFyjXUiHOSJUaK46N55q/uPVcnzp2tzdKT3C0PBWinSPX6sKxNZGe5Ilph1EuYyRDLT9qE6aYwAbcVea/c3B7ttOv3twcNDt9zbevn25v7t581Q9ezTOiAkf4/WbnR6WcCo504bSMNzBwRYxBOJgmKnMOJqRGxqtOTuJZak4N1ZgrNvL1cj19qXpBPCSMNzjzwAbpJIBmQe7mIkv9WDkyZeTbmCWFrCE9gaHPeN9E6GzszOEms0rsWLm6O3Lwe5hHw6zmqKBSDa2ZLzeubmOMaoWSlmN+j8IWR5RRKbhm5gZrYnDhi4WS/pC5AuhMUSS9nNelBkPiGRA3GwetL7kJFcNg7UkXvYx2zqETlVsHg76pUYFeMzoAwnIaDin7yAQ9y43z7BiplTDx6yadFZNKU8u7CY7ONAYy5LlhwE0UuyyngJBWCU6rGR9/SUBmNJFh0mCjkwzHc87JnFj6brEsiJfbzMZS1BcTV8d9N8bZhg/CcmJsiDK9RzE4f5ht4kkVL2RpqVZxiakwmKRG91pZOjXY6HVTarhMxZI7B9tvaQIiZ3wI3KRSJyfYgBxRgsWkRyZQcnbqSiPE1AwNJGKL06RvkOE6ivXz9+15mNIRGP8RDNDiDVCopTOv3m5v9lvJjUF6A2UZkUhqXDjfxwew9S+YeVHGVHJKKFFL6XhJAz9bigCv7p27dLzq4vS1ALoJZdSwTzYrjMo+ZzvpSknTCDiC8zxNSJNI44DlLoDw827WraCxQBEEfj0MCABWLm3OTg/TYvkZUx5towvNlbNsYFD8yv0vFI7lpqRw2NhLcWlkndePRm1Iss7C+l7kbmtKQXQE4qGFhBpL9EKakbBjxtknhlNSDzWqkyaljBBqLnyMg/QqHDanKRKAlGsN9ITB7rZPD7ff2uUYxzBkIOqothZOMfysGXLmHicERVtAkAy1Yx++1vFg9j7bXHxzvK9F780FiPPb08pgJJVRIlgmaG6FAvuiSk3HKrzRy3EZKx4ngf2TKIt/W6Xxp0o4kpOs/JpEU7rZELk3OxZf3N/w9HsGoM4dr1CXXA4nPWAwdANnZb6eUYUltmiF06Zau3uwiv7XvmWM6UAluM8tZIT9peltjaiCG65PPvOybP7O+plkeFXb6wORkhByqu6j5fqV8RQRkSylhchH+4NNtdjBc0q+6iU8UUOm6QeT2Y9EojF9sgjTF5rwGvC0/BQrvQ00r769KspBZAAZUmM/Xll5ogxtUadH7YkNBIJt+FEKBJ5Q/nboD9CC/2zaR9fvDk9rinN2Sb9NWIFBQ7yweZgZRaqinN9qYwhENHZAZxjqCpKOOtxaQsC0dB0tuVEM6Jw9/YXQ2M85kzlY0Ck2cSDr2fMZI0iiZzHzG0uylVLy1XkggNd3OZmM4APOpLvTo6Ovjs6OTl5fb560JxFon9jWFBIEB4iFK014jnNJeqNiIBXl1R/Rpm4+Inc9OvTLSUfqyQjCn/KptxfBiCwF56s1RC5lCxlWhy7LxqCsqZTiyrCEpSNuLXUrilotjtYabIQGxydnO/1u91uf+9w8Pro6PV/uxUjVFCa/cFhM2/Iosj55USiUMGC1Ous6LoKyU0JT5EYR8xpmjMDgcg/mf+iALRN0udSu7RHxQN23XEpU/J0MnBi5VdQtaRfSFj51N6gC6cVHbw++VSCg0s+mrOz6GDv/P/UXVtP29gWlne8HcdOHF/i2Ekc50YupmkaWgSUaaANFIpKRZogzXRUkGhajZQTSpgjxEwfkI40p1KOkGhLGZ2H8tQ/OntvO4ntPp45FfEj3rGcj7XW963L3kG2uMPXJgERaZ6dcwrY8dIh7tjOzjOWQrmKXXlwdTzxfIexhEQS/5M8ecGVhlR8O2/eYAAD+oJijyaIJYoIQUy6AUUIBQK44UTZ9BFB2Rumjbz65WN7qwZr7ZPqC08+V9s3/3h5fPIxi+Klc6O90z0EY86BTMQQlhb+vU1Ih+Exhr6WcTnBW9nn/3w6BuzRg5Xw88bS3MyNBTCQazoV1UBEEJz9wfliBgsZJAhH+CkpDTpKOVy56O5Yz47/uA1Yj37JJN7VD1FY/CpEka8j2mD1tIty8GNYNV3RpTi5zWJDDCuqOzFGDs1Q9PonrJsja2try6vvn/7jl73gxk3NRGZRzEsknS5metnpB0fiehbX9gOZCCD4gawcmgABwUH349cTM8a65QurxxFkoE51er2HBqINjdLzW8Tdx2sYJHEgTpqRgixjVgF8VcERcQSg3dW0N3oVVlZWXj19Q899WqE3AjdVxsSjXNbuKdGZO86mzGKhaeuYgKES+ULpcdZjbfVW/7T333PZiODbNjayYfstssL2cQckTaG5sN0+8khESYEjBWmqQtRieEGELK7e2Kxin6dHrWrjF4w+WF0RH8w9vqkxkFe4Ytayjwk0k86mzMiubiMJ+FJCSEdiqunJNVjIfyltnraPtpX4l7iI3RHy0mQNqB8cd+Ft+bez7qVuJyPkz3yqMlmDeT2aasphFv8LKLuMaA8L8quu4xbLKBxq+RvLwrOkyWufzUaOyMcpnWqRdiZE4Q8C+krtLVi8u/wCk1UR1s96nfbLo81K+lxXXmiSNcEGgP2tXvuy3+5sMRFE3HlsxiyMTWoOThUxtGgiQxzVJZAhhvNxJsQk16laCz48AAAOtUlEQVSpkTFks5cSwP30gDMunY7T9uC5TR90QcrlsBLWRhjCQjWHkrXD3tn9gw7uiDz87U5T1d7VyAVubbU2jzrtXvuAFAYhqyGRnLaomFTw2XG4atEQxBRd0pUYfjqILYoxLRxZB1MD4Az+jYZ

Демонстрирует построение линий уровня (контуров) в 3D

<img alt="Демонстрирует построение контурных (уровневых) кривых в 3D с использованием опции extend3d" 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

Демонстрация построения контурных (уровневых) кривых в 3D с использованием опции extend3d

<img alt="Проектирование контурных профилей на график" 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

Проекция контурных профилей на график

contour(X, Y, Z)

contour(X, Y, Z)

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Spec-Zone.ru

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Spec-Zone .ru
спецификации, руководства, описания, API