numpy.clip — NumPy v2.6.dev0 Manual

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Learn | NEPs | User Guide | API reference | Building from source | Development | Release notes | NumPy’s module structure | Array objects | Universal functions (ufunc) | Routines and objects by topic | Constants | Bit-wise operations | String functionality | Data type routines | Floating point error handling | Discrete Fourier Transform | Input and output | Linear algebra | Logic functions | Masked array operations | Mathematical functions | Miscellaneous routines | Random sampling | Set routines | Sorting, searching, and counting | Test support | Window functions

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NumPy v2.6.dev0 Manual - Home

Building from source

NumPy’s module structure

Universal functions (ufunc)

Routines and objects by topic

Array creation routines

Array manipulation routines

Bit-wise operations

String functionality

Datetime support functions

Data type routines

Mathematical functions with automatic domain

Floating point error handling

Exceptions and Warnings

Discrete Fourier Transform

Functional programming

Masked array operations

Mathematical functions

numpy.cumulative_sum

numpy.cumulative_prod

numpy.floor_divide

numpy.real_if_close

Miscellaneous routines

Sorting, searching, and counting

Typing (numpy.typing)

Array API standard compatibility

CPU/SIMD optimizations

Global Configuration Options

Testing guidelines

Status of numpy.distutils and migration advice

Output type determination

Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1.

previous numpy.convolve

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