NumCpp  2.4.0
A Templatized Header Only C++ Implementation of the Python NumPy Library
trapz.hpp
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1 #pragma once
29 
32 #include "NumCpp/Core/Shape.hpp"
33 #include "NumCpp/Core/Types.hpp"
34 #include "NumCpp/NdArray.hpp"
35 
36 #include <string>
37 
38 namespace nc
39 {
40  //============================================================================
41  // Method Description:
53  template<typename dtype>
54  NdArray<double> trapz(const NdArray<dtype>& inArray, double dx = 1.0, Axis inAxis = Axis::NONE)
55  {
57 
58  const Shape inShape = inArray.shape();
59  switch (inAxis)
60  {
61  case Axis::COL:
62  {
63  NdArray<double> returnArray(inShape.rows, 1);
64  for (uint32 row = 0; row < inShape.rows; ++row)
65  {
66  double sum = 0;
67  for (uint32 col = 0; col < inShape.cols - 1; ++col)
68  {
69  sum += static_cast<double>(inArray(row, col + 1) - inArray(row, col)) / 2.0 +
70  static_cast<double>(inArray(row, col));
71  }
72 
73  returnArray[row] = sum * dx;
74  }
75 
76  return returnArray;
77  }
78  case Axis::ROW:
79  {
80  NdArray<dtype> arrayTranspose = inArray.transpose();
81  const Shape transShape = arrayTranspose.shape();
82  NdArray<double> returnArray(transShape.rows, 1);
83  for (uint32 row = 0; row < transShape.rows; ++row)
84  {
85  double sum = 0;
86  for (uint32 col = 0; col < transShape.cols - 1; ++col)
87  {
88  sum += static_cast<double>(arrayTranspose(row, col + 1) - arrayTranspose(row, col)) / 2.0 +
89  static_cast<double>(arrayTranspose(row, col));
90  }
91 
92  returnArray[row] = sum * dx;
93  }
94 
95  return returnArray;
96  }
97  case Axis::NONE:
98  {
99  double sum = 0.0;
100  for (uint32 i = 0; i < inArray.size() - 1; ++i)
101  {
102  sum += static_cast<double>(inArray[i + 1] - inArray[i]) / 2.0 + static_cast<double>(inArray[i]);
103  }
104 
105  NdArray<double> returnArray = { sum * dx };
106  return returnArray;
107  }
108  default:
109  {
110  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
111  return {}; // get rid of compiler warning
112  }
113  }
114  }
115 
116  //============================================================================
117  // Method Description:
129  template<typename dtype>
130  NdArray<double> trapz(const NdArray<dtype>& inArrayY, const NdArray<dtype>& inArrayX, Axis inAxis = Axis::NONE)
131  {
132  const Shape inShapeY = inArrayY.shape();
133  const Shape inShapeX = inArrayX.shape();
134 
135  if (inShapeY != inShapeX)
136  {
137  THROW_INVALID_ARGUMENT_ERROR("input x and y arrays should be the same shape.");
138  }
139 
140  switch (inAxis)
141  {
142  case Axis::COL:
143  {
144  NdArray<double> returnArray(inShapeY.rows, 1);
145  for (uint32 row = 0; row < inShapeY.rows; ++row)
146  {
147  double sum = 0;
148  for (uint32 col = 0; col < inShapeY.cols - 1; ++col)
149  {
150  const auto dx = static_cast<double>(inArrayX(row, col + 1) - inArrayX(row, col));
151  sum += dx * (static_cast<double>(inArrayY(row, col + 1) - inArrayY(row, col)) / 2.0 +
152  static_cast<double>(inArrayY(row, col)));
153  }
154 
155  returnArray[row] = sum;
156  }
157 
158  return returnArray;
159  }
160  case Axis::ROW:
161  {
162  NdArray<dtype> arrayYTranspose = inArrayY.transpose();
163  NdArray<dtype> arrayXTranspose = inArrayX.transpose();
164  const Shape transShape = arrayYTranspose.shape();
165  NdArray<double> returnArray(transShape.rows, 1);
166  for (uint32 row = 0; row < transShape.rows; ++row)
167  {
168  double sum = 0;
169  for (uint32 col = 0; col < transShape.cols - 1; ++col)
170  {
171  const auto dx = static_cast<double>(arrayXTranspose(row, col + 1) - arrayXTranspose(row, col));
172  sum += dx * (static_cast<double>(arrayYTranspose(row, col + 1) - arrayYTranspose(row, col)) / 2.0 +
173  static_cast<double>(arrayYTranspose(row, col)));
174  }
175 
176  returnArray[row] = sum;
177  }
178 
179  return returnArray;
180  }
181  case Axis::NONE:
182  {
183  double sum = 0.0;
184  for (uint32 i = 0; i < inArrayY.size() - 1; ++i)
185  {
186  const auto dx = static_cast<double>(inArrayX[i + 1] - inArrayX[i]);
187  sum += dx * (static_cast<double>(inArrayY[i + 1] - inArrayY[i]) / 2.0 + static_cast<double>(inArrayY[i]));
188  }
189 
190  NdArray<double> returnArray = { sum };
191  return returnArray;
192  }
193  default:
194  {
195  THROW_INVALID_ARGUMENT_ERROR("Unimplemented axis type.");
196  return {}; // get rid of compiler warning
197  }
198  }
199  }
200 } // namespace nc
StaticAsserts.hpp
nc::NdArray::shape
Shape shape() const noexcept
Definition: NdArrayCore.hpp:4356
nc::Axis::NONE
@ NONE
Error.hpp
STATIC_ASSERT_ARITHMETIC
#define STATIC_ASSERT_ARITHMETIC(dtype)
Definition: StaticAsserts.hpp:37
nc::Axis::ROW
@ ROW
nc::trapz
NdArray< double > trapz(const NdArray< dtype > &inArray, double dx=1.0, Axis inAxis=Axis::NONE)
Definition: trapz.hpp:54
nc::NdArray::transpose
NdArray< dtype > transpose() const
Definition: NdArrayCore.hpp:4652
nc::NdArray< double >
nc::uint32
std::uint32_t uint32
Definition: Types.hpp:40
NdArray.hpp
nc::Shape
A Shape Class for NdArrays.
Definition: Core/Shape.hpp:40
nc::NdArray::size
size_type size() const noexcept
Definition: NdArrayCore.hpp:4370
nc::Shape::cols
uint32 cols
Definition: Core/Shape.hpp:45
nc::sum
NdArray< dtype > sum(const NdArray< dtype > &inArray, Axis inAxis=Axis::NONE)
Definition: sum.hpp:47
nc::Axis
Axis
Enum To describe an axis.
Definition: Types.hpp:46
Shape.hpp
nc
Definition: Coordinate.hpp:44
nc::Shape::rows
uint32 rows
Definition: Core/Shape.hpp:44
THROW_INVALID_ARGUMENT_ERROR
#define THROW_INVALID_ARGUMENT_ERROR(msg)
Definition: Error.hpp:36
Types.hpp
nc::Axis::COL
@ COL