Sometimes you may require to import an image, you can use misc.imread() function in the following syntax to load the image. The core SciPy namespace share common functions with NumPy module, but SciPy offers an added advantage in terms of scientific computing functions.
> from scipy import signal #Replace ‘signal’ with the name of other sub-modules Since NumPy is required for most of these sub-modules, this is how standard SciPy modules are imported: > import numpy as np A concise list of SciPy sub-modules is shown below: SciPy library is composed of sub-modules designed for specific tasks. SciPy works efficiently on NumPy arrays and is standard scientific computing library in Python. It contains submodules for applications like Integration, Interpolation, Image Processing, Optimization, Special Functions and Statistics, etc.
The objective of this tutorial is to give a brief idea about the usage of SciPy library for scientific computing problems in Python. The SciPy library has several toolboxes to solve common scientific computing problems. This tutorial is an introduction SciPy library and its various functions and utilities.
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