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Revert "Implemented series period detect method using pocketfft lib"
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parent
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commit
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3
.gitmodules
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3
.gitmodules
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@ -354,6 +354,3 @@
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[submodule "contrib/aklomp-base64"]
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path = contrib/aklomp-base64
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url = https://github.com/aklomp/base64.git
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[submodule "contrib/pocketfft"]
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path = contrib/pocketfft
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url = https://github.com/mreineck/pocketfft.git
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1
contrib/CMakeLists.txt
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1
contrib/CMakeLists.txt
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@ -44,7 +44,6 @@ else ()
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endif ()
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add_contrib (miniselect-cmake miniselect)
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add_contrib (pdqsort-cmake pdqsort)
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add_contrib (pocketfft-cmake pocketfft)
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add_contrib (crc32-vpmsum-cmake crc32-vpmsum)
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add_contrib (sparsehash-c11-cmake sparsehash-c11)
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add_contrib (abseil-cpp-cmake abseil-cpp)
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1
contrib/pocketfft
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1
contrib/pocketfft
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@ -1 +0,0 @@
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Subproject commit 9efd4da52cf8d28d14531d14e43ad9d913807546
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@ -1,10 +0,0 @@
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option (ENABLE_POCKETFFT "Enable pocketfft" ${ENABLE_LIBRARIES})
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if (NOT ENABLE_POCKETFFT)
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message(STATUS "Not using pocketfft")
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return()
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endif()
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add_library(_pocketfft INTERFACE)
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target_include_directories(_pocketfft INTERFACE ${ClickHouse_SOURCE_DIR}/contrib/pocketfft)
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add_library(ch_contrib::pocketfft ALIAS _pocketfft)
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@ -1,47 +0,0 @@
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---
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slug: /en/sql-reference/functions/time-series-functions
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sidebar_position: 172
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sidebar_label: Time Series
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---
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# Time Series Functions
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Below functions are used for time series analysis.
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## seriesPeriodDetectFFT
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Finds the period of the given time series data using FFT
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Detect Period in time series data using FFT.
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FFT - Fast Fourier transform (https://en.wikipedia.org/wiki/Fast_Fourier_transform)
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**Syntax**
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``` sql
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seriesPeriodDetectFFT(series);
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```
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**Arguments**
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- `series` - An array of numeric values
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**Returned value**
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- A real value equal to the period of time series
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Type: [Float64](../../sql-reference/data-types/float.md).
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**Examples**
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Query:
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``` sql
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SELECT seriesPeriodDetectFFT([1, 4, 6, 1, 4, 6, 1, 4, 6, 1, 4, 6, 1, 4, 6, 1, 4, 6, 1, 4, 6]) AS print_0;
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```
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Result:
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``` text
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┌───────────print_0──────┐
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│ 3 │
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└────────────────────────┘
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```
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@ -436,10 +436,6 @@ dbms_target_link_libraries(PRIVATE ch_contrib::zstd)
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target_link_libraries (clickhouse_common_io PUBLIC ch_contrib::zstd)
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target_link_libraries (clickhouse_common_io PUBLIC ch_contrib::xz)
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if (TARGET ch_contrib::pocketfft)
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target_link_libraries(clickhouse_common_io PUBLIC ch_contrib::pocketfft)
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endif ()
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if (TARGET ch_contrib::icu)
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dbms_target_link_libraries (PRIVATE ch_contrib::icu)
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endif ()
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@ -61,7 +61,6 @@
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#cmakedefine01 FIU_ENABLE
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#cmakedefine01 USE_BCRYPT
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#cmakedefine01 USE_LIBARCHIVE
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#cmakedefine01 USE_POCKETFFT
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/// This is needed for .incbin in assembly. For some reason, include paths don't work there in presence of LTO.
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/// That's why we use absolute paths.
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@ -95,10 +95,6 @@ if (TARGET ch_contrib::rapidjson)
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list (APPEND PRIVATE_LIBS ch_contrib::rapidjson)
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endif()
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if (TARGET ch_contrib::pocketfft)
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list (APPEND PRIVATE_LIBS ch_contrib::pocketfft)
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endif()
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if (TARGET ch_contrib::crc32-vpmsum)
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list (APPEND PUBLIC_LIBS ch_contrib::crc32-vpmsum)
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endif()
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@ -1,164 +0,0 @@
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#include "config.h"
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#if USE_POCKETFFT
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# ifdef __clang__
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# pragma clang diagnostic push
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# pragma clang diagnostic ignored "-Wshadow"
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# pragma clang diagnostic ignored "-Wextra-semi-stmt"
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# pragma clang diagnostic ignored "-Wzero-as-null-pointer-constant"
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# endif
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# include <pocketfft_hdronly.h>
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# ifdef __clang__
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# pragma clang diagnostic pop
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# endif
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# include <cmath>
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# include <Columns/ColumnArray.h>
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# include <Columns/ColumnsNumber.h>
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# include <DataTypes/DataTypeArray.h>
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# include <DataTypes/DataTypesNumber.h>
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# include <Functions/FunctionFactory.h>
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# include <Functions/FunctionHelpers.h>
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# include <Functions/IFunction.h>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int BAD_ARGUMENTS;
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extern const int ILLEGAL_COLUMN;
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}
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/*Detect Period in time series data using FFT.
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* FFT - Fast Fourier transform (https://en.wikipedia.org/wiki/Fast_Fourier_transform)
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* 1. Convert time series data to frequency domain using FFT.
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* 2. Remove the 0th(the Dc component) and n/2th the Nyquist frequency
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* 3. Find the peak value (highest) for dominant frequency component.
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* 4. Inverse of the dominant frequency component is the period.
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*/
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class FunctionSeriesPeriodDetectFFT : public IFunction
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{
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public:
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static constexpr auto name = "seriesPeriodDetectFFT";
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static FunctionPtr create(ContextPtr) { return std::make_shared<FunctionSeriesPeriodDetectFFT>(); }
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std::string getName() const override { return name; }
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size_t getNumberOfArguments() const override { return 1; }
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bool useDefaultImplementationForConstants() const override { return true; }
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bool isSuitableForShortCircuitArgumentsExecution(const DataTypesWithConstInfo & /*arguments*/) const override { return true; }
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DataTypePtr getReturnTypeImpl(const ColumnsWithTypeAndName & arguments) const override
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{
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FunctionArgumentDescriptors args{{"time_series", &isArray<IDataType>, nullptr, "Array"}};
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validateFunctionArgumentTypes(*this, arguments, args);
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return std::make_shared<DataTypeFloat64>();
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}
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ColumnPtr executeImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr &, size_t) const override
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{
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ColumnPtr array_ptr = arguments[0].column;
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const ColumnArray * array = checkAndGetColumn<ColumnArray>(array_ptr.get());
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const IColumn & src_data = array->getData();
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auto res = ColumnFloat64::create(1);
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auto & res_data = res->getData();
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Float64 period;
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if (executeNumber<UInt8>(src_data, period) || executeNumber<UInt16>(src_data, period) || executeNumber<UInt32>(src_data, period)
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|| executeNumber<UInt64>(src_data, period) || executeNumber<Int8>(src_data, period) || executeNumber<Int16>(src_data, period)
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|| executeNumber<Int32>(src_data, period) || executeNumber<Int64>(src_data, period) || executeNumber<Float32>(src_data, period)
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|| executeNumber<Float64>(src_data, period))
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{
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res_data[0] = period;
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return res;
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}
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else
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throw Exception(
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ErrorCodes::ILLEGAL_COLUMN,
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"Illegal column {} of first argument of function {}",
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arguments[0].column->getName(),
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getName());
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}
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template <typename T>
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bool executeNumber(const IColumn & src_data, Float64 & period) const
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{
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const ColumnVector<T> * src_data_concrete = checkAndGetColumn<ColumnVector<T>>(&src_data);
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if (!src_data_concrete)
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return false;
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const PaddedPODArray<T> & src_vec = src_data_concrete->getData();
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size_t len = src_vec.size();
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if (len < 4)
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "At least four data points are needed for function {}", getName());
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std::vector<Float64> src(src_vec.begin(), src_vec.end());
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std::vector<std::complex<double>> out((len / 2) + 1);
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pocketfft::shape_t shape{len};
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pocketfft::shape_t axes;
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axes.reserve(shape.size());
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for (size_t i = 0; i < shape.size(); ++i)
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axes.push_back(i);
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pocketfft::stride_t stride_src{sizeof(double)};
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pocketfft::stride_t stride_out{sizeof(std::complex<double>)};
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pocketfft::r2c(shape, stride_src, stride_out, axes, pocketfft::FORWARD, src.data(), out.data(), static_cast<double>(1));
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size_t spec_len = (len - 1) / 2; //removing the nyquist element when len is even
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double max_mag = 0;
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size_t idx = 1;
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for (size_t i = 1; i < spec_len; ++i)
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{
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double magnitude = sqrt(out[i].real() * out[i].real() + out[i].imag() * out[i].imag());
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if (magnitude > max_mag)
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{
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max_mag = magnitude;
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idx = i;
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}
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}
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// In case all FFT values are zero, it means the input signal is flat.
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// It implies the period of the series should be 0.
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if (max_mag == 0)
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{
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period = 0;
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return true;
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}
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std::vector<double> xfreq(spec_len);
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double step = 0.5 / (spec_len - 1);
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for (size_t i = 0; i < spec_len; ++i)
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xfreq[i] = i * step;
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auto freq = xfreq[idx];
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period = std::round(1 / freq);
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return true;
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}
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};
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REGISTER_FUNCTION(SeriesPeriodDetectFFT)
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{
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factory.registerFunction<FunctionSeriesPeriodDetectFFT>(FunctionDocumentation{
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.description = R"(
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Detects period in time series data using FFT.)",
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.categories{"Time series analysis"}});
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}
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}
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#endif
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if (TARGET ch_contrib::libarchive)
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set(USE_LIBARCHIVE 1)
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endif()
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if (TARGET ch_contrib::pocketfft)
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set(USE_POCKETFFT 1)
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endif()
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set(SOURCE_DIR ${PROJECT_SOURCE_DIR})
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@ -1,5 +0,0 @@
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14
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3
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3
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3
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0
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-- Tags: no-fasttest
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SELECT seriesPeriodDetectFFT([139, 87, 110, 68, 54, 50, 51, 53, 133, 86, 141, 97, 156, 94, 149, 95, 140, 77, 61, 50, 54, 47, 133, 72, 152, 94, 148, 105, 162, 101, 160, 87, 63, 53, 55, 54, 151, 103, 189, 108, 183, 113, 175, 113, 178, 90, 71, 62, 62, 65, 165, 109, 181, 115, 182, 121, 178, 114, 170]);
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SELECT seriesPeriodDetectFFT([10,20,30,10,20,30,10,20,30, 10,20,30,10,20,30,10,20,30,10,20,30]);
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SELECT seriesPeriodDetectFFT([10.1, 20.45, 40.34, 10.1, 20.45, 40.34,10.1, 20.45, 40.34,10.1, 20.45, 40.34,10.1, 20.45, 40.34,10.1, 20.45, 40.34,10.1, 20.45, 40.34, 10.1, 20.45, 40.34]);
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SELECT seriesPeriodDetectFFT([10.1, 10, 400, 10.1, 10, 400, 10.1, 10, 400,10.1, 10, 400,10.1, 10, 400,10.1, 10, 400,10.1, 10, 400,10.1, 10, 400]);
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SELECT seriesPeriodDetectFFT([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]);
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SELECT seriesPeriodDetectFFT([1,2,3]); -- { serverError BAD_ARGUMENTS}
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SELECT seriesPeriodDetectFFT(); --{ serverError NUMBER_OF_ARGUMENTS_DOESNT_MATCH}
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SELECT seriesPeriodDetectFFT([]); -- { serverError ILLEGAL_COLUMN}
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SELECT seriesPeriodDetectFFT([NULL, NULL, NULL]); -- { serverError ILLEGAL_COLUMN}
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SELECT seriesPeriodDetectFFT([10,20,30,10,202,30,NULL]); -- { serverError ILLEGAL_COLUMN }
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@ -2231,7 +2231,6 @@ seektable
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sequenceCount
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sequenceMatch
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sequenceNextNode
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seriesPeriodDetectFFT
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serverTimeZone
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serverTimezone
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serverUUID
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