NumCpp  2.11.0
A Templatized Header Only C++ Implementation of the Python NumPy Library
trapz.hpp
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1 #pragma once
29 
30 #include <string>
31 
34 #include "NumCpp/Core/Shape.hpp"
35 #include "NumCpp/Core/Types.hpp"
36 #include "NumCpp/NdArray.hpp"
37 
38 namespace nc
39 {
40  //============================================================================
41  // Method Description:
52  template<typename dtype>
53  NdArray<double> trapz(const NdArray<dtype>& inArray, double dx = 1., Axis inAxis = Axis::NONE)
54  {
56 
57  const Shape inShape = inArray.shape();
58  switch (inAxis)
59  {
60  case Axis::NONE:
61  {
62  double sum = 0.;
63  for (uint32 i = 0; i < inArray.size() - 1; ++i)
64  {
65  sum += static_cast<double>(inArray[i + 1] - inArray[i]) / 2. + static_cast<double>(inArray[i]);
66  }
67 
68  NdArray<double> returnArray = { sum * dx };
69  return returnArray;
70  }
71  case Axis::COL:
72  {
73  NdArray<double> returnArray(inShape.rows, 1);
74  for (uint32 row = 0; row < inShape.rows; ++row)
75  {
76  double sum = 0;
77  for (uint32 col = 0; col < inShape.cols - 1; ++col)
78  {
79  sum += static_cast<double>(inArray(row, col + 1) - inArray(row, col)) / 2. +
80  static_cast<double>(inArray(row, col));
81  }
82 
83  returnArray[row] = sum * dx;
84  }
85 
86  return returnArray;
87  }
88  case Axis::ROW:
89  {
90  return trapz(inArray.transpose(), dx, Axis::COL);
91  }
92  default:
93  {
94  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
95  return {}; // get rid of compiler warning
96  }
97  }
98  }
99 
100  //============================================================================
101  // Method Description:
112  template<typename dtype>
113  NdArray<double> trapz(const NdArray<dtype>& inArrayY, const NdArray<dtype>& inArrayX, Axis inAxis = Axis::NONE)
114  {
115  const Shape inShapeY = inArrayY.shape();
116  const Shape inShapeX = inArrayX.shape();
117 
118  if (inShapeY != inShapeX)
119  {
120  THROW_INVALID_ARGUMENT_ERROR("input x and y arrays should be the same shape.");
121  }
122 
123  switch (inAxis)
124  {
125  case Axis::NONE:
126  {
127  double sum = 0.;
128  for (uint32 i = 0; i < inArrayY.size() - 1; ++i)
129  {
130  const auto dx = static_cast<double>(inArrayX[i + 1] - inArrayX[i]);
131  sum += dx *
132  (static_cast<double>(inArrayY[i + 1] - inArrayY[i]) / 2. + static_cast<double>(inArrayY[i]));
133  }
134 
135  NdArray<double> returnArray = { sum };
136  return returnArray;
137  }
138  case Axis::COL:
139  {
140  NdArray<double> returnArray(inShapeY.rows, 1);
141  for (uint32 row = 0; row < inShapeY.rows; ++row)
142  {
143  double sum = 0;
144  for (uint32 col = 0; col < inShapeY.cols - 1; ++col)
145  {
146  const auto dx = static_cast<double>(inArrayX(row, col + 1) - inArrayX(row, col));
147  sum += dx * (static_cast<double>(inArrayY(row, col + 1) - inArrayY(row, col)) / 2. +
148  static_cast<double>(inArrayY(row, col)));
149  }
150 
151  returnArray[row] = sum;
152  }
153 
154  return returnArray;
155  }
156  case Axis::ROW:
157  {
158  return trapz(inArrayY.transpose(), inArrayX.transpose(), Axis::COL);
159  }
160  default:
161  {
162  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
163  return {}; // get rid of compiler warning
164  }
165  }
166  }
167 } // namespace nc
#define THROW_INVALID_ARGUMENT_ERROR(msg)
Definition: Error.hpp:37
#define STATIC_ASSERT_ARITHMETIC(dtype)
Definition: StaticAsserts.hpp:39
size_type size() const noexcept
Definition: NdArrayCore.hpp:4477
self_type transpose() const
Definition: NdArrayCore.hpp:4837
const Shape & shape() const noexcept
Definition: NdArrayCore.hpp:4464
A Shape Class for NdArrays.
Definition: Core/Shape.hpp:41
uint32 rows
Definition: Core/Shape.hpp:44
uint32 cols
Definition: Core/Shape.hpp:45
Definition: Cartesian.hpp:40
Axis
Enum To describe an axis.
Definition: Types.hpp:47
NdArray< dtype > sum(const NdArray< dtype > &inArray, Axis inAxis=Axis::NONE)
Definition: sum.hpp:46
NdArray< double > trapz(const NdArray< dtype > &inArray, double dx=1., Axis inAxis=Axis::NONE)
Definition: trapz.hpp:53
std::uint32_t uint32
Definition: Types.hpp:40