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132 lines
2.5 KiB
Markdown
132 lines
2.5 KiB
Markdown
---
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title: "Correlation"
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---
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{{< callout type="info">}}
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Header: `correlation.h`
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Since: `20.9.0`
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{{< /callout >}}
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Calculates the correlation of two sets of data.
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```cpp
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template <bool Correlation_Type, typename TInput, typename TCalc = TInput>
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class correlation : public etl::binary_function<TInput, TInput, void>
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```
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`Correlation_Type` `Population` or `Sample`.
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`TInput` The input data type.
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`TCalc` The type to use for internal calculations. By default, equal to `TInput`.
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**correlation_type**
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`etl::correlation_type::Sample`
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`etl::correlation_type::Population`
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## Construction
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```cpp
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correlation()
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```
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**Description**
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Default constructor.
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---
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```cpp
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template <typename TIterator>
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correlation(TIterator first1, TIterator last1, TIterator first2)
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```
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**Decsription**
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Construct from two iterator ranges.
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```cpp
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void add(TInput value1, TInput value2)
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```
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**Description**
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Add a pair of values.
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## Member functions
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```cpp
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template <typename TIterator>
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void add(TIterator first1, TIterator last1, TIterator first2)
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```
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**Description**
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Add a range of values.
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```cpp
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void operator()(TInput value1, TInput value2)
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```
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Add a pair of values.
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---
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```cpp
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template <typename TIterator>
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void operator()(TIterator first1, TIterator last1, TIterator first2)
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```
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**Description**
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Add a range of values.
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---
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```cpp
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double get_covariance() const
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```
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**Decsription**
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Returns the calculated covariance for the data.
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---
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```cpp
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double get_correlation() const
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```
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**Description**
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Returns the calculated correlation for the data.
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---
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```cpp
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operator double() const
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```
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**Description**
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Returns the calculated correlation for the data.
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---
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```cpp
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size_t count() const
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```
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**Description**
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Get the total number added entries.
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---
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```cpp
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void clear()
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```
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**Description**
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Clear the correlation.
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## Example
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```cpp
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std::array<char, 10> input_c
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{
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0, 1, 2, 3, 4, 5, 6, 7, 8, 9
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};
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std::array<char, 10> input_c_inv
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{
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0, -1, -2, -3, -4, -5, -6, -7, -8, -9
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};
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etl::correlation<etl::correlation_type::Population, char, int32_t> correlation(input_c.begin(),
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input_c.end(),
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input_c_inv.begin());
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double correlation_result;
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double covariance_result;
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correlation_result = correlation; // correlation_result == -1.0
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covariance_result = correlation.get_covariance(); // covariance_result == -8.25
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```
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