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CMSIS-DSP: Added f16 versions of linear and bilinear interpolations

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pull/19/head
Christophe Favergeon 6 years ago
parent d2d691cc23
commit 71218873eb
30 changed files with 2393 additions and 7 deletions
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66
Include/dsp/interpolation_functions_f16.h
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@ -26,12 +26,78 @@
#ifndef _INTERPOLATION_FUNCTIONS_F16_H_
#define _INTERPOLATION_FUNCTIONS_F16_H_
#include "arm_math_types_f16.h"
#include "arm_math_memory.h"
#include "dsp/none.h"
#include "dsp/utils.h"
#ifdef __cplusplus
extern "C"
{
#endif
#if defined(ARM_FLOAT16_SUPPORTED)
typedef struct
{
uint32_t nValues; /**< nValues */
float16_t x1; /**< x1 */
float16_t xSpacing; /**< xSpacing */
float16_t *pYData; /**< pointer to the table of Y values */
} arm_linear_interp_instance_f16;
/**
* @brief Instance structure for the floating-point bilinear interpolation function.
*/
typedef struct
{
uint16_t numRows;/**< number of rows in the data table. */
uint16_t numCols;/**< number of columns in the data table. */
float16_t *pData; /**< points to the data table. */
} arm_bilinear_interp_instance_f16;
/**
* @addtogroup LinearInterpolate
* @{
*/
/**
* @brief Process function for the floating-point Linear Interpolation Function.
* @param[in,out] S is an instance of the floating-point Linear Interpolation structure
* @param[in] x input sample to process
* @return y processed output sample.
*
*/
float16_t arm_linear_interp_f16(
arm_linear_interp_instance_f16 * S,
float16_t x);
/**
* @} end of LinearInterpolate group
*/
/**
* @addtogroup BilinearInterpolate
* @{
*/
/**
* @brief Floating-point bilinear interpolation.
* @param[in,out] S points to an instance of the interpolation structure.
* @param[in] X interpolation coordinate.
* @param[in] Y interpolation coordinate.
* @return out interpolated value.
*/
float16_t arm_bilinear_interp_f16(
const arm_bilinear_interp_instance_f16 * S,
float16_t X,
float16_t Y);
/**
* @} end of BilinearInterpolate group
*/
#endif /*defined(ARM_FLOAT16_SUPPORTED)*/
#ifdef __cplusplus
}

2
PythonWrapper/setup.py
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@ -55,7 +55,7 @@ common.remove(os.path.join(ROOT,"Source","CommonTables","CommonTables.c"))
interpolation = glob.glob(os.path.join(ROOT,"Source","InterpolationFunctions","*.c"))
interpolation.remove(os.path.join(ROOT,"Source","InterpolationFunctions","InterpolationFunctions.c"))
interpolation.remove(os.path.join(ROOT,"Source","InterpolationFunctions","InterpolationFunctionsF16.c"))
#modulesrc = glob.glob(os.path.join("cmsisdsp_pkg","src","*.c"))
modulesrc = []

19
Source/InterpolationFunctions/CMakeLists.txt
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@ -5,9 +5,20 @@ project(CMSISDSPInterpolation)
include(configLib)
include(configDsp)
file(GLOB SRC "./*_*.c")
add_library(CMSISDSPInterpolation STATIC ${SRC})
add_library(CMSISDSPInterpolation STATIC)
target_sources(CMSISDSPInterpolation PRIVATE arm_bilinear_interp_f32.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_bilinear_interp_q15.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_bilinear_interp_q31.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_bilinear_interp_q7.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_linear_interp_f32.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_linear_interp_q15.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_linear_interp_q31.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_linear_interp_q7.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_spline_interp_f32.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_spline_interp_init_f32.c)
configLib(CMSISDSPInterpolation ${ROOT})
configDsp(CMSISDSPInterpolation ${ROOT})
@ -17,3 +28,7 @@ target_include_directories(CMSISDSPInterpolation PUBLIC "${DSP}/Include")
if ((NOT ARMAC5) AND (NOT DISABLEFLOAT16))
target_sources(CMSISDSPInterpolation PRIVATE arm_bilinear_interp_f16.c)
target_sources(CMSISDSPInterpolation PRIVATE arm_linear_interp_f16.c)
endif()

33
Source/InterpolationFunctions/InterpolationFunctionsF16.c
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@ -0,0 +1,33 @@
/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: InterpolationFunctions.c
* Description: Combination of all interpolation function source files.
*
* $Date: 22. July 2020
* $Revision: V1.0.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2020 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "arm_bilinear_interp_f16.c"
#include "arm_linear_interp_f16.c"

167
Source/InterpolationFunctions/arm_bilinear_interp_f16.c
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@ -0,0 +1,167 @@
/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_bilinear_interp_f16.c
* Description: Floating-point bilinear interpolation
*
* $Date: 22 July 2020
* $Revision: V1.9.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2020 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "dsp/interpolation_functions_f16.h"
#if defined(ARM_FLOAT16_SUPPORTED)
/**
@ingroup groupInterpolation
*/
/**
* @defgroup BilinearInterpolate Bilinear Interpolation
*
* Bilinear interpolation is an extension of linear interpolation applied to a two dimensional grid.
* The underlying function <code>f(x, y)</code> is sampled on a regular grid and the interpolation process
* determines values between the grid points.
* Bilinear interpolation is equivalent to two step linear interpolation, first in the x-dimension and then in the y-dimension.
* Bilinear interpolation is often used in image processing to rescale images.
* The CMSIS DSP library provides bilinear interpolation functions for Q7, Q15, Q31, and floating-point data types.
*
* <b>Algorithm</b>
* \par
* The instance structure used by the bilinear interpolation functions describes a two dimensional data table.
* For floating-point, the instance structure is defined as:
* <pre>
* typedef struct
* {
* uint16_t numRows;
* uint16_t numCols;
* float16_t *pData;
* } arm_bilinear_interp_instance_f16;
* </pre>
*
* \par
* where <code>numRows</code> specifies the number of rows in the table;
* <code>numCols</code> specifies the number of columns in the table;
* and <code>pData</code> points to an array of size <code>numRows*numCols</code> values.
* The data table <code>pTable</code> is organized in row order and the supplied data values fall on integer indexes.
* That is, table element (x,y) is located at <code>pTable[x + y*numCols]</code> where x and y are integers.
*
* \par
* Let <code>(x, y)</code> specify the desired interpolation point. Then define:
* <pre>
* XF = floor(x)
* YF = floor(y)
* </pre>
* \par
* The interpolated output point is computed as:
* <pre>
* f(x, y) = f(XF, YF) * (1-(x-XF)) * (1-(y-YF))
* + f(XF+1, YF) * (x-XF)*(1-(y-YF))
* + f(XF, YF+1) * (1-(x-XF))*(y-YF)
* + f(XF+1, YF+1) * (x-XF)*(y-YF)
* </pre>
* Note that the coordinates (x, y) contain integer and fractional components.
* The integer components specify which portion of the table to use while the
* fractional components control the interpolation processor.
*
* \par
* if (x,y) are outside of the table boundary, Bilinear interpolation returns zero output.
*/
/**
* @addtogroup BilinearInterpolate
* @{
*/
/**
* @brief Floating-point bilinear interpolation.
* @param[in,out] S points to an instance of the interpolation structure.
* @param[in] X interpolation coordinate.
* @param[in] Y interpolation coordinate.
* @return out interpolated value.
*/
float16_t arm_bilinear_interp_f16(
const arm_bilinear_interp_instance_f16 * S,
float16_t X,
float16_t Y)
{
float16_t out;
float16_t f00, f01, f10, f11;
float16_t *pData = S->pData;
int32_t xIndex, yIndex, index;
float16_t xdiff, ydiff;
float16_t b1, b2, b3, b4;
xIndex = (int32_t) X;
yIndex = (int32_t) Y;
/* Care taken for table outside boundary */
/* Returns zero output when values are outside table boundary */
if (xIndex < 0 || xIndex > (S->numCols - 2) || yIndex < 0 || yIndex > (S->numRows - 2))
{
return (0);
}
/* Calculation of index for two nearest points in X-direction */
index = (xIndex ) + (yIndex ) * S->numCols;
/* Read two nearest points in X-direction */
f00 = pData[index];
f01 = pData[index + 1];
/* Calculation of index for two nearest points in Y-direction */
index = (xIndex ) + (yIndex+1) * S->numCols;
/* Read two nearest points in Y-direction */
f10 = pData[index];
f11 = pData[index + 1];
/* Calculation of intermediate values */
b1 = f00;
b2 = f01 - f00;
b3 = f10 - f00;
b4 = f00 - f01 - f10 + f11;
/* Calculation of fractional part in X */
xdiff = X - xIndex;
/* Calculation of fractional part in Y */
ydiff = Y - yIndex;
/* Calculation of bi-linear interpolated output */
out = b1 + b2 * xdiff + b3 * ydiff + b4 * xdiff * ydiff;
/* return to application */
return (out);
}
/**
* @} end of BilinearInterpolate group
*/
#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */

131
Source/InterpolationFunctions/arm_linear_interp_f16.c
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@ -0,0 +1,131 @@
/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_linear_interp_f16.c
* Description: Floating-point linear interpolation
*
* $Date: 22 July 2020
* $Revision: V1.9.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2020 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "dsp/interpolation_functions_f16.h"
#if defined(ARM_FLOAT16_SUPPORTED)
/**
@ingroup groupInterpolation
*/
/**
* @defgroup LinearInterpolate Linear Interpolation
*
* Linear interpolation is a method of curve fitting using linear polynomials.
* Linear interpolation works by effectively drawing a straight line between two neighboring samples and returning the appropriate point along that line
*
* \par
* \image html LinearInterp.gif "Linear interpolation"
*
* \par
* A Linear Interpolate function calculates an output value(y), for the input(x)
* using linear interpolation of the input values x0, x1( nearest input values) and the output values y0 and y1(nearest output values)
*
* \par Algorithm:
* <pre>
* y = y0 + (x - x0) * ((y1 - y0)/(x1-x0))
* where x0, x1 are nearest values of input x
* y0, y1 are nearest values to output y
* </pre>
*
* \par
* This set of functions implements Linear interpolation process
* for Q7, Q15, Q31, and floating-point data types. The functions operate on a single
* sample of data and each call to the function returns a single processed value.
* <code>S</code> points to an instance of the Linear Interpolate function data structure.
* <code>x</code> is the input sample value. The functions returns the output value.
*
* \par
* if x is outside of the table boundary, Linear interpolation returns first value of the table
* if x is below input range and returns last value of table if x is above range.
*/
/**
* @addtogroup LinearInterpolate
* @{
*/
/**
* @brief Process function for the floating-point Linear Interpolation Function.
* @param[in,out] S is an instance of the floating-point Linear Interpolation structure
* @param[in] x input sample to process
* @return y processed output sample.
*
*/
float16_t arm_linear_interp_f16(
arm_linear_interp_instance_f16 * S,
float16_t x)
{
float16_t y;
float16_t x0, x1; /* Nearest input values */
float16_t y0, y1; /* Nearest output values */
float16_t xSpacing = S->xSpacing; /* spacing between input values */
int32_t i; /* Index variable */
float16_t *pYData = S->pYData; /* pointer to output table */
/* Calculation of index */
i = (int32_t) ((x - S->x1) / xSpacing);
if (i < 0)
{
/* Iniatilize output for below specified range as least output value of table */
y = pYData[0];
}
else if ((uint32_t)i >= (S->nValues - 1))
{
/* Iniatilize output for above specified range as last output value of table */
y = pYData[S->nValues - 1];
}
else
{
/* Calculation of nearest input values */
x0 = S->x1 + i * xSpacing;
x1 = S->x1 + (i + 1) * xSpacing;
/* Read of nearest output values */
y0 = pYData[i];
y1 = pYData[i + 1];
/* Calculation of output */
y = y0 + (x - x0) * ((y1 - y0) / (x1 - x0));
}
/* returns output value */
return (y);
}
/**
* @} end of LinearInterpolate group
*/
#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */

1
Testing/CMakeLists.txt
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@ -328,6 +328,7 @@ if ((NOT ARMAC5) AND (FLOAT16TESTS) AND ((FLOAT16) OR (MVEF) OR (HELIUM) OR (NEO
set(TESTSRC16
Source/Tests/BasicTestsF16.cpp
Source/Tests/ComplexTestsF16.cpp
Source/Tests/InterpolationTestsF16.cpp
Source/Tests/FIRF16.cpp
Source/Tests/BIQUADF16.cpp
Source/Tests/MISCF16.cpp

33
Testing/Include/Tests/InterpolationTestsF16.h
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@ -0,0 +1,33 @@
#include "Test.h"
#include "Pattern.h"
#include "dsp/interpolation_functions_f16.h"
class InterpolationTestsF16:public Client::Suite
{
public:
InterpolationTestsF16(Testing::testID_t id);
virtual void setUp(Testing::testID_t,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr);
virtual void tearDown(Testing::testID_t,Client::PatternMgr *mgr);
private:
#include "InterpolationTestsF16_decl.h"
Client::Pattern<float16_t> input;
Client::Pattern<float16_t> y;
Client::Pattern<int16_t> config;
Client::LocalPattern<float16_t> output;
// Reference patterns are not loaded when we are in dump mode
Client::RefPattern<float16_t> ref;
arm_linear_interp_instance_f16 S;
arm_bilinear_interp_instance_f16 SBI;
Client::Pattern<float16_t> inputX;
Client::Pattern<float16_t> inputY;
Client::Pattern<float16_t> outputX;
Client::LocalPattern<float16_t> buffer;
Client::LocalPattern<float16_t> splineCoefs;
};

10
Testing/PatternGeneration/Interpolate.py
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@ -22,9 +22,9 @@ def writeTests(config,format):
data=data[:-1]
z = f(data)
if format != 0:
if format != 0 and format != 16:
data = data / 2.0**11
if format != 0:
if format != 0 and format != 16:
config.writeInputQ31(1, data,"Input")
else:
config.writeInput(1, data)
@ -81,10 +81,10 @@ def writeTests(config,format):
ref=np.array([f(i[0],i[1]) for i in inputVals])
if format != 0:
if format != 0 and format != 16:
inputSamples = inputSamples / 2.0**11
data = inputSamples.reshape(np.size(inputSamples))
if format != 0:
if format != 0 and format != 16:
config.writeInputQ31(2, data,"Input")
else:
config.writeInput(2, data)
@ -130,11 +130,13 @@ def generatePatterns():
PARAMDIR = os.path.join("Parameters","DSP","Interpolation","Interpolation")
configf32=Tools.Config(PATTERNDIR,PARAMDIR,"f32")
configf16=Tools.Config(PATTERNDIR,PARAMDIR,"f16")
configq31=Tools.Config(PATTERNDIR,PARAMDIR,"q31")
configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")
configq7=Tools.Config(PATTERNDIR,PARAMDIR,"q7")
writeTests(configf32,0)
writeTests(configf16,16)
writeTests(configq31,31)
writeTests(configq15,15)
writeTests(configq7,7)

6
Testing/Patterns/DSP/Interpolation/InterpolationF16/Config2_s16.txt
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@ -0,0 +1,6 @@
H
2
// 7
0x0007
// 8
0x0008

82
Testing/Patterns/DSP/Interpolation/InterpolationF16/Input1_f16.txt
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@ -0,0 +1,82 @@
H
40
// 0.500000
0x3800
// 1.500000
0x3e00
// 2.500000
0x4100
// 3.500000
0x4300
// 4.500000
0x4480
// 5.500000
0x4580
// 6.500000
0x4680
// 7.500000
0x4780
// 8.500000
0x4840
// 9.500000
0x48c0
// 10.500000
0x4940
// 11.500000
0x49c0
// 12.500000
0x4a40
// 13.500000
0x4ac0
// 14.500000
0x4b40
// 15.500000
0x4bc0
// 16.500000
0x4c20
// 17.500000
0x4c60
// 18.500000
0x4ca0
// 19.500000
0x4ce0
// 20.500000
0x4d20
// 21.500000
0x4d60
// 22.500000
0x4da0
// 23.500000
0x4de0
// 24.500000
0x4e20
// 25.500000
0x4e60
// 26.500000
0x4ea0
// 27.500000
0x4ee0
// 28.500000
0x4f20
// 29.500000
0x4f60
// 30.500000
0x4fa0
// 31.500000
0x4fe0
// 32.500000
0x5010
// 33.500000
0x5030
// 34.500000
0x5050
// 35.500000
0x5070
// 36.500000
0x5090
// 37.500000
0x50b0
// 38.500000
0x50d0
// 39.500000
0x50f0

602
Testing/Patterns/DSP/Interpolation/InterpolationF16/Input2_f16.txt
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@ -0,0 +1,602 @@
H
300
// 0.500000
0x3800
// 0.500000
0x3800
// 0.944444
0x3b8e
// 0.500000
0x3800
// 1.388889
0x3d8e
// 0.500000
0x3800
// 1.833333
0x3f55
// 0.500000
0x3800
// 2.277778
0x408e
// 0.500000
0x3800
// 2.722222
0x4172
// 0.500000
0x3800
// 3.166667
0x4255
// 0.500000
0x3800
// 3.611111
0x4339
// 0.500000
0x3800
// 4.055556
0x440e
// 0.500000
0x3800
// 4.500000
0x4480
// 0.500000
0x3800
// 0.500000
0x3800
// 0.857143
0x3adb
// 0.944444
0x3b8e
// 0.857143
0x3adb
// 1.388889
0x3d8e
// 0.857143
0x3adb
// 1.833333
0x3f55
// 0.857143
0x3adb
// 2.277778
0x408e
// 0.857143
0x3adb
// 2.722222
0x4172
// 0.857143
0x3adb
// 3.166667
0x4255
// 0.857143
0x3adb
// 3.611111
0x4339
// 0.857143
0x3adb
// 4.055556
0x440e
// 0.857143
0x3adb
// 4.500000
0x4480
// 0.857143
0x3adb
// 0.500000
0x3800
// 1.214286
0x3cdb
// 0.944444
0x3b8e
// 1.214286
0x3cdb
// 1.388889
0x3d8e
// 1.214286
0x3cdb
// 1.833333
0x3f55
// 1.214286
0x3cdb
// 2.277778
0x408e
// 1.214286
0x3cdb
// 2.722222
0x4172
// 1.214286
0x3cdb
// 3.166667
0x4255
// 1.214286
0x3cdb
// 3.611111
0x4339
// 1.214286
0x3cdb
// 4.055556
0x440e
// 1.214286
0x3cdb
// 4.500000
0x4480
// 1.214286
0x3cdb
// 0.500000
0x3800
// 1.571429
0x3e49
// 0.944444
0x3b8e
// 1.571429
0x3e49
// 1.388889
0x3d8e
// 1.571429
0x3e49
// 1.833333
0x3f55
// 1.571429
0x3e49
// 2.277778
0x408e
// 1.571429
0x3e49
// 2.722222
0x4172
// 1.571429
0x3e49
// 3.166667
0x4255
// 1.571429
0x3e49
// 3.611111
0x4339
// 1.571429
0x3e49
// 4.055556
0x440e
// 1.571429
0x3e49
// 4.500000
0x4480
// 1.571429
0x3e49
// 0.500000
0x3800
// 1.928571
0x3fb7
// 0.944444
0x3b8e
// 1.928571
0x3fb7
// 1.388889
0x3d8e
// 1.928571
0x3fb7
// 1.833333
0x3f55
// 1.928571
0x3fb7
// 2.277778
0x408e
// 1.928571
0x3fb7
// 2.722222
0x4172
// 1.928571
0x3fb7
// 3.166667
0x4255
// 1.928571
0x3fb7
// 3.611111
0x4339
// 1.928571
0x3fb7
// 4.055556
0x440e
// 1.928571
0x3fb7
// 4.500000
0x4480
// 1.928571
0x3fb7
// 0.500000
0x3800
// 2.285714
0x4092
// 0.944444
0x3b8e
// 2.285714
0x4092
// 1.388889
0x3d8e
// 2.285714
0x4092
// 1.833333
0x3f55
// 2.285714
0x4092
// 2.277778
0x408e
// 2.285714
0x4092
// 2.722222
0x4172
// 2.285714
0x4092
// 3.166667
0x4255
// 2.285714
0x4092
// 3.611111
0x4339
// 2.285714
0x4092
// 4.055556
0x440e
// 2.285714
0x4092
// 4.500000
0x4480
// 2.285714
0x4092
// 0.500000
0x3800
// 2.642857
0x4149
// 0.944444
0x3b8e
// 2.642857
0x4149
// 1.388889
0x3d8e
// 2.642857
0x4149
// 1.833333
0x3f55
// 2.642857
0x4149
// 2.277778
0x408e
// 2.642857
0x4149
// 2.722222
0x4172
// 2.642857
0x4149
// 3.166667
0x4255
// 2.642857
0x4149
// 3.611111
0x4339
// 2.642857
0x4149
// 4.055556
0x440e
// 2.642857
0x4149
// 4.500000
0x4480
// 2.642857
0x4149
// 0.500000
0x3800
// 3.000000
0x4200
// 0.944444
0x3b8e
// 3.000000
0x4200
// 1.388889
0x3d8e
// 3.000000
0x4200
// 1.833333
0x3f55
// 3.000000
0x4200
// 2.277778
0x408e
// 3.000000
0x4200
// 2.722222
0x4172
// 3.000000
0x4200
// 3.166667
0x4255
// 3.000000
0x4200
// 3.611111
0x4339
// 3.000000
0x4200
// 4.055556
0x440e
// 3.000000
0x4200
// 4.500000
0x4480
// 3.000000
0x4200
// 0.500000
0x3800
// 3.357143
0x42b7
// 0.944444
0x3b8e
// 3.357143
0x42b7
// 1.388889
0x3d8e
// 3.357143
0x42b7
// 1.833333
0x3f55
// 3.357143
0x42b7
// 2.277778
0x408e
// 3.357143
0x42b7
// 2.722222
0x4172
// 3.357143
0x42b7
// 3.166667
0x4255
// 3.357143
0x42b7
// 3.611111
0x4339
// 3.357143
0x42b7
// 4.055556
0x440e
// 3.357143
0x42b7
// 4.500000
0x4480
// 3.357143
0x42b7
// 0.500000
0x3800
// 3.714286
0x436e
// 0.944444
0x3b8e
// 3.714286
0x436e
// 1.388889
0x3d8e
// 3.714286
0x436e
// 1.833333
0x3f55
// 3.714286
0x436e
// 2.277778
0x408e
// 3.714286
0x436e
// 2.722222
0x4172
// 3.714286
0x436e
// 3.166667
0x4255
// 3.714286
0x436e
// 3.611111
0x4339
// 3.714286
0x436e
// 4.055556
0x440e
// 3.714286
0x436e
// 4.500000
0x4480
// 3.714286
0x436e
// 0.500000
0x3800
// 4.071429
0x4412
// 0.944444
0x3b8e
// 4.071429
0x4412
// 1.388889
0x3d8e
// 4.071429
0x4412
// 1.833333
0x3f55
// 4.071429
0x4412
// 2.277778
0x408e
// 4.071429
0x4412
// 2.722222
0x4172
// 4.071429
0x4412
// 3.166667
0x4255
// 4.071429
0x4412
// 3.611111
0x4339
// 4.071429
0x4412
// 4.055556
0x440e
// 4.071429
0x4412
// 4.500000
0x4480
// 4.071429
0x4412
// 0.500000
0x3800
// 4.428571
0x446e
// 0.944444
0x3b8e
// 4.428571
0x446e
// 1.388889
0x3d8e
// 4.428571
0x446e
// 1.833333
0x3f55
// 4.428571
0x446e
// 2.277778
0x408e
// 4.428571
0x446e
// 2.722222
0x4172
// 4.428571
0x446e
// 3.166667
0x4255
// 4.428571
0x446e
// 3.611111
0x4339
// 4.428571
0x446e
// 4.055556
0x440e
// 4.428571
0x446e
// 4.500000
0x4480
// 4.428571
0x446e
// 0.500000
0x3800
// 4.785714
0x44c9
// 0.944444
0x3b8e
// 4.785714
0x44c9
// 1.388889
0x3d8e
// 4.785714
0x44c9
// 1.833333
0x3f55
// 4.785714
0x44c9
// 2.277778
0x408e
// 4.785714
0x44c9
// 2.722222
0x4172
// 4.785714
0x44c9
// 3.166667
0x4255
// 4.785714
0x44c9
// 3.611111
0x4339
// 4.785714
0x44c9
// 4.055556
0x440e
// 4.785714
0x44c9
// 4.500000
0x4480
// 4.785714
0x44c9
// 0.500000
0x3800
// 5.142857
0x4525
// 0.944444
0x3b8e
// 5.142857
0x4525
// 1.388889
0x3d8e
// 5.142857
0x4525
// 1.833333
0x3f55
// 5.142857
0x4525
// 2.277778
0x408e
// 5.142857
0x4525
// 2.722222
0x4172
// 5.142857
0x4525
// 3.166667
0x4255
// 5.142857
0x4525
// 3.611111
0x4339
// 5.142857
0x4525
// 4.055556
0x440e
// 5.142857
0x4525
// 4.500000
0x4480
// 5.142857
0x4525
// 0.500000
0x3800
// 5.500000
0x4580
// 0.944444
0x3b8e
// 5.500000
0x4580
// 1.388889
0x3d8e
// 5.500000
0x4580
// 1.833333
0x3f55
// 5.500000
0x4580
// 2.277778
0x408e
// 5.500000
0x4580
// 2.722222
0x4172
// 5.500000
0x4580
// 3.166667
0x4255
// 5.500000
0x4580
// 3.611111
0x4339
// 5.500000
0x4580
// 4.055556
0x440e
// 5.500000
0x4580
// 4.500000
0x4480
// 5.500000
0x4580

10
Testing/Patterns/DSP/Interpolation/InterpolationF16/InputX3_f16.txt
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4
// 0.000000
0x0
// 3.000000
0x4200
// 10.000000
0x4900
// 20.000000
0x4d00

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Testing/Patterns/DSP/Interpolation/InterpolationF16/InputX4_f16.txt
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9
// 0.000000
0x0
// 0.785398
0x3a48
// 1.570796
0x3e48
// 2.356194
0x40b6
// 3.141593
0x4248
// 3.926991
0x43db
// 4.712389
0x44b6
// 5.497787
0x457f
// 6.283185
0x4648

8
Testing/Patterns/DSP/Interpolation/InterpolationF16/InputX5_f16.txt
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3
// 0.000000
0x0
// 3.000000
0x4200
// 10.000000
0x4900

10
Testing/Patterns/DSP/Interpolation/InterpolationF16/InputY3_f16.txt
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4
// 0.000000
0x0
// 9.000000
0x4880
// 100.000000
0x5640
// 400.000000
0x5e40

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Testing/Patterns/DSP/Interpolation/InterpolationF16/InputY4_f16.txt
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9
// 0.000000
0x0
// 0.707107
0x39a8
// 1.000000
0x3c00
// 0.707107
0x39a8
// 0.000000
0x0
// -0.707107
0xb9a8
// -1.000000
0xbc00
// -0.707107
0xb9a8
// -0.000000
0x8000

8
Testing/Patterns/DSP/Interpolation/InterpolationF16/InputY5_f16.txt
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// 0.000000
0x0
// 3.000000
0x4200
// 10.000000
0x4900

42
Testing/Patterns/DSP/Interpolation/InterpolationF16/OutputX3_f16.txt
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// 0.000000
0x0
// 1.000000
0x3c00
// 2.000000
0x4000
// 3.000000
0x4200
// 4.000000
0x4400
// 5.000000
0x4500
// 6.000000
0x4600
// 7.000000
0x4700
// 8.000000
0x4800
// 9.000000
0x4880
// 10.000000
0x4900
// 11.000000
0x4980
// 12.000000
0x4a00
// 13.000000
0x4a80
// 14.000000
0x4b00
// 15.000000
0x4b80
// 16.000000
0x4c00
// 17.000000
0x4c40
// 18.000000
0x4c80
// 19.000000
0x4cc0

68
Testing/Patterns/DSP/Interpolation/InterpolationF16/OutputX4_f16.txt
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33
// 0.000000
0x0
// 0.196350
0x3248
// 0.392699
0x3648
// 0.589049
0x38b6
// 0.785398
0x3a48
// 0.981748
0x3bdb
// 1.178097
0x3cb6
// 1.374447
0x3d7f
// 1.570796
0x3e48
// 1.767146
0x3f12
// 1.963495
0x3fdb
// 2.159845
0x4052
// 2.356194
0x40b6
// 2.552544
0x411b
// 2.748894
0x417f
// 2.945243
0x41e4
// 3.141593
0x4248
// 3.337942
0x42ad
// 3.534292
0x4312
// 3.730641
0x4376
// 3.926991
0x43db
// 4.123340
0x4420
// 4.319690
0x4452
// 4.516039
0x4484
// 4.712389
0x44b6
// 4.908739
0x44e9
// 5.105088
0x451b
// 5.301438
0x454d
// 5.497787
0x457f
// 5.694137
0x45b2
// 5.890486
0x45e4
// 6.086836
0x4616
// 6.283185
0x4648

62
Testing/Patterns/DSP/Interpolation/InterpolationF16/OutputX5_f16.txt
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30
// -10.000000
0xc900
// -9.000000
0xc880
// -8.000000
0xc800
// -7.000000
0xc700
// -6.000000
0xc600
// -5.000000
0xc500
// -4.000000
0xc400
// -3.000000
0xc200
// -2.000000
0xc000
// -1.000000
0xbc00
// 0.000000
0x0
// 1.000000
0x3c00
// 2.000000
0x4000
// 3.000000
0x4200
// 4.000000
0x4400
// 5.000000
0x4500
// 6.000000
0x4600
// 7.000000
0x4700
// 8.000000
0x4800
// 9.000000
0x4880
// 10.000000
0x4900
// 11.000000
0x4980
// 12.000000
0x4a00
// 13.000000
0x4a80
// 14.000000
0x4b00
// 15.000000
0x4b80
// 16.000000
0x4c00
// 17.000000
0x4c40
// 18.000000
0x4c80
// 19.000000
0x4cc0

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Testing/Patterns/DSP/Interpolation/InterpolationF16/Reference1_f16.txt
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40
// 0.999836
0x3c00
// 0.997208
0x3bfa
// 0.984118
0x3bdf
// 0.945255
0x3b90
// 0.859251
0x3ae0
// 0.702426
0x399f
// 0.456301
0x374d
// 0.119531
0x2fa6
// -0.277482
0xb471
// -0.661314
0xb94a
// -0.918537
0xbb59
// -0.925695
0xbb68
// -0.611097
0xb8e4
// -0.030945
0xa7ec
// 0.589481
0x38b7
// 0.915804
0x3b54
// 0.695054
0x398f
// -0.004498
0x9c9b
// -0.712082
0xb9b2
// -0.829765
0xbaa3
// -0.183298
0xb1de
// 0.647457
0x392e
// 0.765024
0x3a1f
// -0.024301
0xa639
// -0.770387
0xba2a
// -0.447708
0xb72a
// 0.521104
0x382b
// 0.650064
0x3933
// -0.298863
0xb4c8
// -0.688210
0xb981
// 0.207648
0x32a5
// 0.656951
0x3941
// -0.253282
0xb40d
// -0.570816
0xb891
// 0.398647
0x3661
// 0.379176
0x3611
// -0.548368
0xb863
// -0.036721
0xa8b3
// 0.524152
0x3831
// -0.358152
0xb5bb

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Testing/Patterns/DSP/Interpolation/InterpolationF16/Reference2_f16.txt
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150
// 0.373384
0x35f9
// 0.203820
0x3286
// 0.011612
0x21f2
// -0.183830
0xb1e2
// -0.345125
0xb586
// -0.485933
0xb7c6
// -0.560815
0xb87d
// -0.525820
0xb835
// -0.435634
0xb6f8
// 0.040890
0x293c
// 0.026219
0x26b6
// -0.324983
0xb533
// -0.122774
0xafdc
// 0.158492
0x3112
// 0.004431
0x1c8a
// -0.410827
0xb693
// -0.590305
0xb8b9
// -0.376814
0xb607
// -0.151634
0xb0da
// 0.155369
0x30f9
// -0.057384
0xab58
// -0.300094
0xb4cd
// -0.099685
0xae61
// 0.164026
0x3140
// 0.075748
0x2cd9
// -0.223723
0xb329
// -0.350221
0xb59b
// -0.188431
0xb208
// -0.028933
0xa768
// 0.114515
0x2f54
// 0.034722
0x2872
// 0.093922
0x2e03
// 0.028388
0x2744
// -0.054967
0xab09
// -0.038428
0xa8eb
// 0.038047
0x28df
// 0.069578
0x2c74
// 0.026203
0x26b5
// -0.013765
0xa30c
// -0.029893
0xa7a7
// 0.126828
0x300f
// 0.487939
0x37cf
// 0.156461
0x3102
// -0.273959
0xb462
// -0.152604
0xb0e2
// 0.299816
0x34cc
// 0.489377
0x37d4
// 0.240837
0x33b5
// 0.001402
0x15be
// -0.174301
0xb194
// -0.145827
0xb0ab
// 0.144655
0x30a1
// 0.077152
0x2cf0
// -0.041492
0xa950
// 0.115844
0x2f6a
// 0.438769
0x3705
// 0.583165
0x38aa
// 0.430014
0x36e1
// 0.250144
0x3401
// -0.116764
0xaf79
// -0.509673
0xb814
// -0.382953
0xb621
// -0.054002
0xaaea
// 0.303839
0x34dd
// 0.479948
0x37ae
// 0.547017
0x3860
// 0.595451
0x38c3
// 0.612827
0x38e7
// 0.557279
0x3875
// -0.008740
0xa07a
// -0.873518
0xbafd
// -0.910562
0xbb49
// -0.185156
0xb1ed
// 0.649170
0x3932
// 0.844051
0x3ac1
// 0.655264
0x393e
// 0.607736
0x38dd
// 0.795640
0x3a5d
// 0.864414
0x3aea
// 0.099283
0x2e5b
// -0.814436
0xba84
// -0.928275
0xbb6d
// -0.201519
0xb273
// 0.645323
0x392a
// 0.793662
0x3a59
// 0.522901
0x382f
// 0.437868
0x3702
// 0.662386
0x394d
// 0.777657
0x3a39
// 0.128210
0x301a
// -0.755355
0xba0b
// -0.945988
0xbb91
// -0.217881
0xb2f9
// 0.641475
0x3922
// 0.743273
0x39f2
// 0.390537
0x3640
// 0.268001
0x344a
// 0.529132
0x383c
// 0.690901
0x3987
// 0.157136
0x3107
// -0.719795
0xb9c2
// -0.950653
0xbb9b
// -0.225545
0xb338
// 0.636130
0x3917
// 0.712439
0x39b3
// 0.317528
0x3515
// 0.175498
0x319e
// 0.454936
0x3747
// 0.640823
0x3920
// 0.171852
0x3180
// -0.778323
0xba3a
// -0.903125
0xbb3a
// -0.198415
0xb259
// 0.624797
0x3900
// 0.759823
0x3a14
// 0.481938
0x37b6
// 0.392455
0x3647
// 0.616975
0x38f0
// 0.737463
0x39e6
// 0.129721
0x3027
// -0.836852
0xbab2
// -0.855598
0xbad8
// -0.171286
0xb17b
// 0.613463
0x38e8
// 0.807207
0x3a75
// 0.646348
0x392c
// 0.609412
0x38e0
// 0.779014
0x3a3b
// 0.834102
0x3aac
// 0.087591
0x2d9b
// -0.681885
0xb975
// -0.591371
0xb8bb
// -0.101033
0xae77
// 0.446422
0x3725
// 0.648792
0x3931
// 0.644111
0x3927
// 0.668335
0x3959
// 0.740732
0x39ed
// 0.717385
0x39bd
// 0.023824
0x2619
// -0.206676
0xb29d
// -0.002096
0x984b
// 0.033904
0x2857
// 0.045820
0x29dd
// 0.181680
0x31d0
// 0.391905
0x3645
// 0.490207
0x37d8
// 0.401969
0x366e
// 0.280633
0x347d
// -0.072398
0xaca2

42
Testing/Patterns/DSP/Interpolation/InterpolationF16/Reference3_f16.txt
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20
// 0.000000
0x0
// 1.000000
0x3c00
// 4.000000
0x4400
// 9.000000
0x4880
// 16.000000
0x4c00
// 25.000000
0x4e40
// 36.000000
0x5080
// 49.000000
0x5220
// 64.000000
0x5400
// 81.000000
0x5510
// 100.000000
0x5640
// 121.000000
0x5790
// 144.000000
0x5880
// 169.000000
0x5948
// 196.000000
0x5a20
// 225.000000
0x5b08
// 256.000000
0x5c00
// 289.000000
0x5c84
// 324.000000
0x5d10
// 361.000000
0x5da4

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Testing/Patterns/DSP/Interpolation/InterpolationF16/Reference4_f16.txt
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33
// 0.000000
0x0
// 0.194708
0x323b
// 0.382243
0x361e
// 0.555433
0x3872
// 0.707107
0x39a8
// 0.830791
0x3aa5
// 0.922816
0x3b62
// 0.980209
0x3bd7
// 1.000000
0x3c00
// 0.980209
0x3bd7
// 0.922816
0x3b62
// 0.830791
0x3aa5
// 0.707107
0x39a8
// 0.555433
0x3872
// 0.382243
0x361e
// 0.194708
0x323b
// 0.000000
0x0
// -0.194708
0xb23b
// -0.382243
0xb61e
// -0.555433
0xb872
// -0.707107
0xb9a8
// -0.830791
0xbaa5
// -0.922816
0xbb62
// -0.980209
0xbbd7
// -1.000000
0xbc00
// -0.980209
0xbbd7
// -0.922816
0xbb62
// -0.830791
0xbaa5
// -0.707107
0xb9a8
// -0.555433
0xb872
// -0.382243
0xb61e
// -0.194708
0xb23b
// -0.000000
0x8000

62
Testing/Patterns/DSP/Interpolation/InterpolationF16/Reference5_f16.txt
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H
30
// -10.000000
0xc900
// -9.000000
0xc880
// -8.000000
0xc800
// -7.000000
0xc700
// -6.000000
0xc600
// -5.000000
0xc500
// -4.000000
0xc400
// -3.000000
0xc200
// -2.000000
0xc000
// -1.000000
0xbc00
// 0.000000
0x0
// 1.000000
0x3c00
// 2.000000
0x4000
// 3.000000
0x4200
// 4.000000
0x4400
// 5.000000
0x4500
// 6.000000
0x4600
// 7.000000
0x4700
// 8.000000
0x4800
// 9.000000
0x4880
// 10.000000
0x4900
// 11.000000
0x4980
// 12.000000
0x4a00
// 13.000000
0x4a80
// 14.000000
0x4b00
// 15.000000
0x4b80
// 16.000000
0x4c00
// 17.000000
0x4c40
// 18.000000
0x4c80
// 19.000000
0x4cc0

84
Testing/Patterns/DSP/Interpolation/InterpolationF16/YVals1_f16.txt
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H
41
// 1.000000
0x3c00
// 0.999671
0x3bff
// 0.994745
0x3bf5
// 0.973491
0x3bca
// 0.917019
0x3b56
// 0.801483
0x3a69
// 0.603369
0x38d4
// 0.309233
0x34f3
// -0.070172
0xac7e
// -0.484793
0xb7c2
// -0.837836
0xbab4
// -0.999238
0xbbfe
// -0.852151
0xbad1
// -0.370043
0xb5ec
// 0.308154
0x34ee
// 0.870807
0x3af7
// 0.960802
0x3bb0
// 0.429307
0x36de
// -0.438304
0xb703
// -0.985860
0xbbe3
// -0.673670
0xb964
// 0.307075
0x34ea
// 0.987839
0x3be7
// 0.542209
0x3856
// -0.590811
0xb8ba
// -0.949963
0xbb9a
// 0.054547
0x2afb
// 0.987662
0x3be7
// 0.312466
0x3500
// -0.910193
0xbb48
// -0.466228
0xb776
// 0.881524
0x3b0d
// 0.432377
0x36eb
// -0.938941
0xbb83
// -0.202690
0xb27c
// 0.999984
0x3c00
// -0.241631
0xb3bb
// -0.855104
0xbad7
// 0.781662
0x3a41
// 0.266643
0x3444
// -0.982948
0xbbdd

114
Testing/Patterns/DSP/Interpolation/InterpolationF16/YVals2_f16.txt
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H
56
// 0.764099
0x3a1d
// 0.954734
0x3ba3
// -0.986643
0xbbe5
// -0.438943
0xb706
// -0.922467
0xbb61
// 0.683706
0x3978
// -0.724533
0xb9cc
// 0.364190
0x35d4
// -0.589486
0xb8b7
// 0.472403
0x378f
// -0.708934
0xb9ac
// -0.067933
0xac59
// 0.470253
0x3786
// 0.886085
0x3b17
// -0.328930
0xb543
// 0.619429
0x38f5
// -0.505195
0xb80b
// 0.681926
0x3975
// 0.030388
0x27c8
// -0.436752
0xb6fd
// -0.902880
0xbb39
// -0.831844
0xbaa8
// -0.915192
0xbb52
// 0.962043
0x3bb2
// 0.537273
0x384c
// 0.960055
0x3bae
// -0.761489
0xba18
// 0.642363
0x3924
// -0.424511
0xb6cb
// -0.991667
0xbbef
// 0.964409
0x3bb7
// 0.023198
0x25f0
// 0.676648
0x396a
// -0.316092
0xb50f
// 0.946295
0x3b92
// -0.922467
0xbb61
// -0.821471
0xba92
// 0.892290
0x3b23
// 0.688341
0x3982
// 0.995808
0x3bf7
// -0.871183
0xbaf8
// 0.484313
0x37c0
// 0.048810
0x2a3f
// 0.868424
0x3af3
// -0.791713
0xba55
// 0.358250
0x35bb
// -0.346284
0xb58a
// -0.067933
0xac59
// -0.998178
0xbbfc
// -0.201840
0xb275
// -0.934347
0xbb7a
// 0.876246
0x3b03
// -0.210401
0xb2bc
// 0.486444
0x37c8
// -0.086315
0xad86
// 0.995582
0x3bf7

202
Testing/Source/Tests/InterpolationTestsF16.cpp
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#include "InterpolationTestsF16.h"
#include <stdio.h>
#include "Error.h"
#define SNR_THRESHOLD 55
/*
Reference patterns are generated with
a double precision computation.
*/
#define REL_ERROR (5.0e-3)
#define ABS_ERROR (5.0e-3)
void InterpolationTestsF16::test_linear_interp_f16()
{
const float16_t *inp = input.ptr();
float16_t *outp = output.ptr();
unsigned long nb;
for(nb = 0; nb < input.nbSamples(); nb++)
{
outp[nb] = arm_linear_interp_f16(&S,inp[nb]);
}
ASSERT_EMPTY_TAIL(output);
ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
}
void InterpolationTestsF16::test_bilinear_interp_f16()
{
const float16_t *inp = input.ptr();
float16_t *outp = output.ptr();
float16_t x,y;
unsigned long nb;
for(nb = 0; nb < input.nbSamples(); nb += 2)
{
x = inp[nb];
y = inp[nb+1];
*outp++=arm_bilinear_interp_f16(&SBI,x,y);
}
ASSERT_EMPTY_TAIL(output);
ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
}
#if 0
void InterpolationTestsF16::test_spline_square_f16()
{
const float16_t *inpX = inputX.ptr();
const float16_t *inpY = inputY.ptr();
const float16_t *outX = outputX.ptr();
float16_t *outp = output.ptr();
float16_t *buf = buffer.ptr(); // ((2*4-1)*sizeof(float16_t))
float16_t *coef = splineCoefs.ptr(); // ((3*(4-1))*sizeof(float16_t))
arm_spline_instance_f16 S;
arm_spline_init_f16(&S, ARM_SPLINE_PARABOLIC_RUNOUT, inpX, inpY, 4, coef, buf);
arm_spline_f16(&S, outX, outp, 20);
ASSERT_EMPTY_TAIL(buffer);
ASSERT_EMPTY_TAIL(splineCoefs);
ASSERT_EMPTY_TAIL(output);
ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
}
void InterpolationTestsF16::test_spline_sine_f16()
{
const float16_t *inpX = inputX.ptr();
const float16_t *inpY = inputY.ptr();
const float16_t *outX = outputX.ptr();
float16_t *outp = output.ptr();
float16_t *buf = buffer.ptr(); // ((2*9-1)*sizeof(float16_t))
float16_t *coef = splineCoefs.ptr(); // ((3*(9-1))*sizeof(float16_t))
arm_spline_instance_f16 S;
arm_spline_init_f16(&S, ARM_SPLINE_NATURAL, inpX, inpY, 9, coef, buf);
arm_spline_f16(&S, outX, outp, 33);
ASSERT_EMPTY_TAIL(buffer);
ASSERT_EMPTY_TAIL(splineCoefs);
ASSERT_EMPTY_TAIL(output);
ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
}
void InterpolationTestsF16::test_spline_ramp_f16()
{
const float16_t *inpX = inputX.ptr();
const float16_t *inpY = inputY.ptr();
const float16_t *outX = outputX.ptr();
float16_t *outp = output.ptr();
float16_t *buf = buffer.ptr(); // ((2*3-1)*sizeof(float16_t))
float16_t *coef = splineCoefs.ptr(); // ((3*(3-1))*sizeof(float16_t))
arm_spline_instance_f16 S;
arm_spline_init_f16(&S, ARM_SPLINE_PARABOLIC_RUNOUT, inpX, inpY, 3, coef, buf);
arm_spline_f16(&S, outX, outp, 30);
ASSERT_EMPTY_TAIL(buffer);
ASSERT_EMPTY_TAIL(splineCoefs);
ASSERT_EMPTY_TAIL(output);
ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
}
#endif
void InterpolationTestsF16::setUp(Testing::testID_t id,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr)
{
const int16_t *pConfig;
Testing::nbSamples_t nb=MAX_NB_SAMPLES;
(void)params;
switch(id)
{
case InterpolationTestsF16::TEST_LINEAR_INTERP_F16_1:
input.reload(InterpolationTestsF16::INPUT_F16_ID,mgr,nb);
y.reload(InterpolationTestsF16::YVAL_F16_ID,mgr,nb);
ref.reload(InterpolationTestsF16::REF_LINEAR_F16_ID,mgr,nb);
S.nValues=y.nbSamples(); /**< nValues */
/* Those values must be coherent with the ones in the
Python script generating the patterns */
S.x1=0.0; /**< x1 */
S.xSpacing=1.0; /**< xSpacing */
S.pYData=y.ptr(); /**< pointer to the table of Y values */
break;
case InterpolationTestsF16::TEST_BILINEAR_INTERP_F16_2:
input.reload(InterpolationTestsF16::INPUTBI_F16_ID,mgr,nb);
config.reload(InterpolationTestsF16::CONFIGBI_S16_ID,mgr,nb);
y.reload(InterpolationTestsF16::YVALBI_F16_ID,mgr,nb);
ref.reload(InterpolationTestsF16::REF_BILINEAR_F16_ID,mgr,nb);
pConfig = config.ptr();
SBI.numRows = pConfig[1];
SBI.numCols = pConfig[0];
SBI.pData = y.ptr();
break;
#if 0
case TEST_SPLINE_SQUARE_F16_3:
inputX.reload(InterpolationTestsF16::INPUT_SPLINE_SQU_X_F16_ID,mgr,4);
inputY.reload(InterpolationTestsF16::INPUT_SPLINE_SQU_Y_F16_ID,mgr,4);
outputX.reload(InterpolationTestsF16::OUTPUT_SPLINE_SQU_X_F16_ID,mgr,20);
ref.reload(InterpolationTestsF16::REF_SPLINE_SQU_F16_ID,mgr,20);
splineCoefs.create(3*(4-1),InterpolationTestsF16::COEFS_SPLINE_F16_ID,mgr);
buffer.create(2*4-1,InterpolationTestsF16::TEMP_SPLINE_F16_ID,mgr);
output.create(20,InterpolationTestsF16::OUT_SAMPLES_F16_ID,mgr);
break;
case TEST_SPLINE_SINE_F16_4:
inputX.reload(InterpolationTestsF16::INPUT_SPLINE_SIN_X_F16_ID,mgr,9);
inputY.reload(InterpolationTestsF16::INPUT_SPLINE_SIN_Y_F16_ID,mgr,9);
outputX.reload(InterpolationTestsF16::OUTPUT_SPLINE_SIN_X_F16_ID,mgr,33);
ref.reload(InterpolationTestsF16::REF_SPLINE_SIN_F16_ID,mgr,33);
splineCoefs.create(3*(9-1),InterpolationTestsF16::COEFS_SPLINE_F16_ID,mgr);
buffer.create(2*9-1,InterpolationTestsF16::TEMP_SPLINE_F16_ID,mgr);
output.create(33,InterpolationTestsF16::OUT_SAMPLES_F16_ID,mgr);
break;
case TEST_SPLINE_RAMP_F16_5:
inputX.reload(InterpolationTestsF16::INPUT_SPLINE_RAM_X_F16_ID,mgr,3);
inputY.reload(InterpolationTestsF16::INPUT_SPLINE_RAM_Y_F16_ID,mgr,3);
outputX.reload(InterpolationTestsF16::OUTPUT_SPLINE_RAM_X_F16_ID,mgr,30);
ref.reload(InterpolationTestsF16::REF_SPLINE_RAM_F16_ID,mgr,30);
splineCoefs.create(3*(3-1),InterpolationTestsF16::COEFS_SPLINE_F16_ID,mgr);
buffer.create(2*3-1,InterpolationTestsF16::TEMP_SPLINE_F16_ID,mgr);
output.create(30,InterpolationTestsF16::OUT_SAMPLES_F16_ID,mgr);
break;
#endif
}
output.create(ref.nbSamples(),InterpolationTestsF16::OUT_SAMPLES_F16_ID,mgr);
}
void InterpolationTestsF16::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
{
(void)id;
output.dump(mgr);
}

44
Testing/desc_f16.txt
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@ -5,6 +5,50 @@ group Root {
class = DSPTests
folder = DSP
group Interpolation Tests{
class = InterpolationTests
folder = Interpolation
suite Interpolation Tests F16{
class = InterpolationTestsF16
folder = InterpolationF16
Pattern INPUT_F16_ID : Input1_f16.txt
Pattern INPUTBI_F16_ID : Input2_f16.txt
Pattern CONFIGBI_S16_ID : Config2_s16.txt
Pattern YVAL_F16_ID : YVals1_f16.txt
Pattern YVALBI_F16_ID : YVals2_f16.txt
Pattern REF_LINEAR_F16_ID : Reference1_f16.txt
Pattern REF_BILINEAR_F16_ID : Reference2_f16.txt
Pattern REF_SPLINE_SQU_F16_ID : Reference3_f16.txt
Pattern REF_SPLINE_SIN_F16_ID : Reference4_f16.txt
Pattern REF_SPLINE_RAM_F16_ID : Reference5_f16.txt
Pattern INPUT_SPLINE_SQU_X_F16_ID : InputX3_f16.txt
Pattern INPUT_SPLINE_SQU_Y_F16_ID : InputY3_f16.txt
Pattern OUTPUT_SPLINE_SQU_X_F16_ID : OutputX3_f16.txt
Pattern INPUT_SPLINE_SIN_X_F16_ID : InputX4_f16.txt
Pattern INPUT_SPLINE_SIN_Y_F16_ID : InputY4_f16.txt
Pattern OUTPUT_SPLINE_SIN_X_F16_ID : OutputX4_f16.txt
Pattern INPUT_SPLINE_RAM_X_F16_ID : InputX5_f16.txt
Pattern INPUT_SPLINE_RAM_Y_F16_ID : InputY5_f16.txt
Pattern OUTPUT_SPLINE_RAM_X_F16_ID : OutputX5_f16.txt
Output OUT_SAMPLES_F16_ID : Output
Output COEFS_SPLINE_F16_ID : SplineCoefs
Output TEMP_SPLINE_F16_ID : SplineTemp
Functions {
Test arm_linear_interp_f16:test_linear_interp_f16
Test arm_bilinear_interp_f16:test_bilinear_interp_f16
}
}
}
group Basic Tests {
class = BasicTests
folder = BasicMaths

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