Metadata-Version: 2.1
Name: libcalculus
Version: 0.3.5.3
Summary: Real/Complex analysis library for Python 3.
Home-page: https://pypi.org/project/libcalculus
Author: Ariel Terkeltoub
Author-email: ariter777@gmail.com
License: UNKNOWN
Project-URL: Documentation, https://libcalculus.readthedocs.io/en/latest/
Project-URL: Source Code, https://gitlab.com/ariter777/libcalculus
Description: # libcalculus: A comprehensive real and complex analysis library for Python
        
        [![pipeline status](https://gitlab.com/ariter777/libcalculus/badges/master/pipeline.svg)](https://gitlab.com/ariter777/libcalculus/commits/master)
        
        libcalculus is fully written in C++ and Cython for bindings to Python; all numeric calculations take place in C++ and take full advantage of SIMD vectorization and OpenMP threading wherever available.
        
        ## Features
        
        - Functional programming approach to analysis in Python
        - Numeric integration and differentiation of real and complex functions
        - Full integration with NumPy: functions support array inputs
        - LaTeX support: every function object has a `.latex()` that produces its LaTeX markup
        
        ## Technology
        libcalculus is written in C\+\+20 and bound to Python via Cython; operations between functions are performed using C++ lambdas, and all calculations happen at the C++ level, with Python only interfacing methods and results.
        
        ## Installation
        libcalculus can be installed from pip:
        ```
        pip install libcalculus
        ```
        
        ## Examples
        Here is a snippet demonstrating some of the library's features:
        ```python
        >>> import libcalculus, numpy as np
        >>> f = libcalculus.csc @ (1 / libcalculus.identity)
        >>> f(1 + 2j)
        (1.0316491868272164+1.9336686363989997j)
        >>> libcalculus.residue(f, 0, tol=1e-4)
        (0.16666666639893526-8.181230860681676e-06j)
        
        >>> print(f.latex("z"))
        \csc\left( \frac{1}{z}\right)
        
        >>> contour = libcalculus.line(2, 1 + 1j) # 2(1 - t) + (1 + 1i)t
        >>> libcalculus.integrate(f, contour, 0, 1) # integrate along the contour between t=0 and t=1
        (-2.0551412843830605+1.1351565349386723j)
        
        >>> libcalculus.threads(4) # Enable threading
        >>> arr = np.array([[1, 2j, 3], [4 + 1j, 5 + 2j, 7 + 3j]])
        >>> print(f(arr))
        [[ 1.18839511+0.j         -0.        +1.91903475j  3.05628425+0.j        ]
         [ 4.03942207+0.99000843j  5.02878731+1.98839211j  7.02013025+2.99133798j]]
        ```
        
        ## License
        Copyright (c) 2022, Ariel Terkeltoub
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are
        met:
        
            * Redistributions of source code must retain the above copyright
               notice, this list of conditions and the following disclaimer.
        
            * Redistributions in binary form must reproduce the above
               copyright notice, this list of conditions and the following
               disclaimer in the documentation and/or other materials provided
               with the distribution.
        
            * Neither the name of the libcalculus developers nor the names of any
               contributors may be used to endorse or promote products derived
               from this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
        "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
        LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
        A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
        OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
        SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
        LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
        DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
        THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
        (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
        OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE
        
Keywords: analysis,real,complex,integral,derivative
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
