NumCpp  2.1.0
A C++ implementation of the Python Numpy library
trapz.hpp
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1 #pragma once
30 
33 #include "NumCpp/Core/Shape.hpp"
34 #include "NumCpp/Core/Types.hpp"
35 #include "NumCpp/NdArray.hpp"
36 
37 #include <string>
38 
39 namespace nc
40 {
41  //============================================================================
42  // Method Description:
54  template<typename dtype>
55  NdArray<double> trapz(const NdArray<dtype>& inArray, double dx = 1.0, Axis inAxis = Axis::NONE)
56  {
58 
59  const Shape inShape = inArray.shape();
60  switch (inAxis)
61  {
62  case Axis::COL:
63  {
64  NdArray<double> returnArray(inShape.rows, 1);
65  for (uint32 row = 0; row < inShape.rows; ++row)
66  {
67  double sum = 0;
68  for (uint32 col = 0; col < inShape.cols - 1; ++col)
69  {
70  sum += static_cast<double>(inArray(row, col + 1) - inArray(row, col)) / 2.0 +
71  static_cast<double>(inArray(row, col));
72  }
73 
74  returnArray[row] = sum * dx;
75  }
76 
77  return returnArray;
78  }
79  case Axis::ROW:
80  {
81  NdArray<dtype> arrayTranspose = inArray.transpose();
82  const Shape transShape = arrayTranspose.shape();
83  NdArray<double> returnArray(transShape.rows, 1);
84  for (uint32 row = 0; row < transShape.rows; ++row)
85  {
86  double sum = 0;
87  for (uint32 col = 0; col < transShape.cols - 1; ++col)
88  {
89  sum += static_cast<double>(arrayTranspose(row, col + 1) - arrayTranspose(row, col)) / 2.0 +
90  static_cast<double>(arrayTranspose(row, col));
91  }
92 
93  returnArray[row] = sum * dx;
94  }
95 
96  return returnArray;
97  }
98  case Axis::NONE:
99  {
100  double sum = 0.0;
101  for (uint32 i = 0; i < inArray.size() - 1; ++i)
102  {
103  sum += static_cast<double>(inArray[i + 1] - inArray[i]) / 2.0 + static_cast<double>(inArray[i]);
104  }
105 
106  NdArray<double> returnArray = { sum * dx };
107  return returnArray;
108  }
109  default:
110  {
111  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
112  return {}; // get rid of compiler warning
113  }
114  }
115  }
116 
117  //============================================================================
118  // Method Description:
130  template<typename dtype>
131  NdArray<double> trapz(const NdArray<dtype>& inArrayY, const NdArray<dtype>& inArrayX, Axis inAxis = Axis::NONE)
132  {
133  const Shape inShapeY = inArrayY.shape();
134  const Shape inShapeX = inArrayX.shape();
135 
136  if (inShapeY != inShapeX)
137  {
138  THROW_INVALID_ARGUMENT_ERROR("input x and y arrays should be the same shape.");
139  }
140 
141  switch (inAxis)
142  {
143  case Axis::COL:
144  {
145  NdArray<double> returnArray(inShapeY.rows, 1);
146  for (uint32 row = 0; row < inShapeY.rows; ++row)
147  {
148  double sum = 0;
149  for (uint32 col = 0; col < inShapeY.cols - 1; ++col)
150  {
151  const auto dx = static_cast<double>(inArrayX(row, col + 1) - inArrayX(row, col));
152  sum += dx * (static_cast<double>(inArrayY(row, col + 1) - inArrayY(row, col)) / 2.0 +
153  static_cast<double>(inArrayY(row, col)));
154  }
155 
156  returnArray[row] = sum;
157  }
158 
159  return returnArray;
160  }
161  case Axis::ROW:
162  {
163  NdArray<dtype> arrayYTranspose = inArrayY.transpose();
164  NdArray<dtype> arrayXTranspose = inArrayX.transpose();
165  const Shape transShape = arrayYTranspose.shape();
166  NdArray<double> returnArray(transShape.rows, 1);
167  for (uint32 row = 0; row < transShape.rows; ++row)
168  {
169  double sum = 0;
170  for (uint32 col = 0; col < transShape.cols - 1; ++col)
171  {
172  const auto dx = static_cast<double>(arrayXTranspose(row, col + 1) - arrayXTranspose(row, col));
173  sum += dx * (static_cast<double>(arrayYTranspose(row, col + 1) - arrayYTranspose(row, col)) / 2.0 +
174  static_cast<double>(arrayYTranspose(row, col)));
175  }
176 
177  returnArray[row] = sum;
178  }
179 
180  return returnArray;
181  }
182  case Axis::NONE:
183  {
184  double sum = 0.0;
185  for (uint32 i = 0; i < inArrayY.size() - 1; ++i)
186  {
187  const auto dx = static_cast<double>(inArrayX[i + 1] - inArrayX[i]);
188  sum += dx * (static_cast<double>(inArrayY[i + 1] - inArrayY[i]) / 2.0 + static_cast<double>(inArrayY[i]));
189  }
190 
191  NdArray<double> returnArray = { sum };
192  return returnArray;
193  }
194  default:
195  {
196  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
197  return {}; // get rid of compiler warning
198  }
199  }
200  }
201 } // namespace nc
StaticAsserts.hpp
nc::NdArray::shape
Shape shape() const noexcept
Definition: NdArrayCore.hpp:4312
nc::Axis::NONE
@ NONE
Error.hpp
STATIC_ASSERT_ARITHMETIC
#define STATIC_ASSERT_ARITHMETIC(dtype)
Definition: StaticAsserts.hpp:38
nc::Axis::ROW
@ ROW
nc::trapz
NdArray< double > trapz(const NdArray< dtype > &inArray, double dx=1.0, Axis inAxis=Axis::NONE)
Definition: trapz.hpp:55
nc::NdArray::transpose
NdArray< dtype > transpose() const
Definition: NdArrayCore.hpp:4608
nc::NdArray< double >
nc::uint32
std::uint32_t uint32
Definition: Types.hpp:41
NdArray.hpp
nc::Shape
A Shape Class for NdArrays.
Definition: Core/Shape.hpp:41
nc::NdArray::size
size_type size() const noexcept
Definition: NdArrayCore.hpp:4326
nc::Shape::cols
uint32 cols
Definition: Core/Shape.hpp:46
nc::sum
NdArray< dtype > sum(const NdArray< dtype > &inArray, Axis inAxis=Axis::NONE)
Definition: sum.hpp:48
nc::Axis
Axis
Enum To describe an axis.
Definition: Types.hpp:47
Shape.hpp
nc
Definition: Coordinate.hpp:45
nc::Shape::rows
uint32 rows
Definition: Core/Shape.hpp:45
THROW_INVALID_ARGUMENT_ERROR
#define THROW_INVALID_ARGUMENT_ERROR(msg)
Definition: Error.hpp:37
Types.hpp
nc::Axis::COL
@ COL