nschloe

cmake_minimum_required(VERSION 3.0)

project(mytest)

FIND_PACKAGE(CGAL REQUIRED)
find_package(Boost COMPONENTS thread REQUIRED)

ADD_EXECUTABLE(main test.cpp)
TARGET_LINK_LIBRARIES(
  main

nschloe

cmake_minimum_required(VERSION 3.0)

project(mytest)

set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")

FIND_PACKAGE(CGAL REQUIRED)
find_package(Boost COMPONENTS thread REQUIRED)

add_executable(mytest main.cpp)

nschloe

cmake_minimum_required(VERSION 3.0)

project(mytest)

FIND_PACKAGE(SWIG REQUIRED)
INCLUDE(${SWIG_USE_FILE})

if (NOT MSVC)
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
endif()

nschloe

cmake_minimum_required(VERSION 3.0)

project(mytest)

FIND_PACKAGE(SWIG REQUIRED)
INCLUDE(${SWIG_USE_FILE})

if (NOT MSVC)
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
endif()

nschloe

cmake_minimum_required(VERSION 3.0)

project(mytest)

FIND_PACKAGE(SWIG REQUIRED)
FIND_PACKAGE(Eigen3 REQUIRED)
INCLUDE(${SWIG_USE_FILE})

if (NOT MSVC)
  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")

nschloe

#ifndef MYFOO_HPP
#define MYFOO_HPP

#include <vector>

double sum(const std::vector<double> & a) {
  double sum = 0.0;
  for (const auto & elem: a) {
    sum += elem;
  }

nschloe

CMAKE_MINIMUM_REQUIRED(VERSION 2.8.8)

INCLUDE_DIRECTORIES(${CMAKE_CURRENT_BINARY_DIR})
INCLUDE_DIRECTORIES(${CMAKE_CURRENT_SOURCE_DIR})

FIND_PACKAGE(Trilinos REQUIRED COMPONENTS Kokkos)

INCLUDE_DIRECTORIES(
  SYSTEM
  ${Trilinos_INCLUDE_DIRS}

nschloe

# This gist shows how to use numpy's FFT functions to use the discrete FFT
# of a uniformly-spaced data set to get what corresponds to the actual Fourier
# transform as you'd write it down mathematically.
# In particular, the functio uniform_dft returns the corresponding frequencies
# in terms of the coordinate units.

def uniform_dft(interval_length, data):
    """Discrete Fourier Transform of real-valued data, interpreted for a uniform series
    over an interval of a given length, including starting and end point.
    The function returns the frequencies in units of the coordinate.

nschloe

import perfplot
import numpy


def setup(n):
    a = numpy.random.rand(n, 3)
    b = numpy.ascontiguousarray(a.T)
    return a, b

nschloe

import numpy
import perfplot


def setup(n):
    pts = numpy.random.rand(3, n, 2)
    e = numpy.array([
        pts[2] - pts[1],
        pts[0] - pts[2],
        pts[1] - pts[0],