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160 lines
3.5 KiB
Markdown
160 lines
3.5 KiB
Markdown
---
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title: "pseudo_moving_average"
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---
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A moving average algorithm that continuously calculates an average value from a stream of samples.
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The sample size does not affect the size of the instantiated object. There is no overhead based on the number of samples as it simulates a window of N values from the current average.
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There are four variants of the algorithm; two for integral values and two for floating point. Each sub-variant allows the selection of compile time or run time sample size.
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The integral variant allows a compile time scaling factor to emulate fixed point arithmetic.
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## Integral
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```cpp
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template <typename T, const size_t SAMPLE_SIZE, const size_t SCALING>
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pseudo_moving_average;
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```
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```cpp
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static const size_t SAMPLE_SIZE
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```
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The number of samples averaged over.
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If this value is zero, then the run time sample size specialisation is used.
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```cpp
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static const size_t SCALING
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```
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The sample scaling factor.
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```cpp
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pseudo_moving_average(const T initial_value)
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```
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**Description**
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Constructs the object with the initial value for the average.
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---
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```cpp
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pseudo_moving_average(const T initial_value, const size_t sample_size)
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```
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**Description**
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*For runtime sample size specialisation only.*
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Constructs the object with the initial value for the average and the sample size.
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---
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```cpp
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void clear(const T initial_value)
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```
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**Description**
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Clears the object to the initial value for the average.
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---
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```cpp
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void add(T new_value)
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```
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**Description**
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Adds a new sample value.
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---
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```cpp
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T value() const
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```
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**Description**
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Returns the scaled value of the average.
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To unscale the returned value, use one of the rounding found in scaled_rounding.
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---
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```cpp
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iterator input()
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```
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**Description**
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Returns an iterator that allows the input of new values.
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## Example
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```cpp
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std::array data{ 9, 1, 8, 2, 7, 3, 6, 4, 5 };
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etl::pseudo_moving_average<int, SAMPLE_SIZE, SCALING> cma(0);
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std::copy(data.begin(), data.end(), cma.input());
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int average = cma.value();
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```
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---
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```cpp
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void set_sample_size(const size_t sample_size)
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```
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**Description**
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For runtime sample size specialisation only.
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Sets the sample size.
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## Floating point
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```cpp
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template <typename T, const size_t SAMPLE_SIZE>
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pseudo_moving_average;
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```
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```cpp
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static const size_t SAMPLE_SIZE
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```
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The number of samples averaged over.
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---
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```cpp
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pseudo_moving_average(const T initial_value)
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```
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**Description**
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Constructs the object with the initial value for the average.
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---
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```cpp
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pseudo_moving_average(const T initial_value, const size_t sample_size)
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```
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**Description**
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For runtime sample size specialisation only.
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Constructs the object with the initial value for the average and the sample size.
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---
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```cpp
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void clear(const T initial_value)
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```
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**Description**
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Clears the object to the initial value for the average.
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---
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```cpp
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void add(T new_value)
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```
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**Description**
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Adds a new sample value.
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---
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```cpp
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T value() const
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```
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**Description**
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Returns the average value.
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---
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```cpp
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void set_sample_size(const size_t sample_size)
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```
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**Description**
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For runtime sample size specialisation only.
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Sets the sample size.
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## How It Works
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If the current moving average is 5, then an equivalent sequence of samples (for a sample size of 9), that gives the same average, would be 5, 5, 5, 5, 5, 5, 5, 5, 5
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This means, to find the average when adding a new sample to a moving average that has a current value of 5, all we need to do is multiply the current average by the sample size (9), add the new sample, and divide by the sample size + 1 (10).
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