RMUL2025/lib/cmsis_5/CMSIS/DSP/Testing/PatternGeneration/Interpolate.py

147 lines
4.4 KiB
Python
Executable File

import os.path
import numpy as np
import itertools
import Tools
from scipy.interpolate import interp1d,interp2d,CubicSpline
# Those patterns are used for tests and benchmarks.
# For tests, there is the need to add tests for saturation
# Get lists of points in row order for use in CMSIS function
def getLinearPoints(x,y):
return(np.array([[p[1],p[0]] for p in np.array(np.meshgrid(y,x)).T.reshape(-1,2)]))
def writeTests(config,format):
# Linear interpolation test
NBSAMPLES=40
x = np.linspace(0, NBSAMPLES, num=NBSAMPLES+1, endpoint=True)
y = np.cos(-x**2/(NBSAMPLES - 1))
f = interp1d(x, y)
data=x+0.5
data=data[:-1]
z = f(data)
if format != 0 and format != 16:
data = data / 2.0**11
if format != 0 and format != 16:
config.writeInputQ31(1, data,"Input")
else:
config.writeInput(1, data)
config.writeInput(1, y,"YVals")
ref = z
config.writeReference(1, ref)
# Bilinear interpolation test
x = np.arange(-3.14, 3.14, 1.0)
y = np.arange(-3.14, 3.14, 0.8)
xx, yy = np.meshgrid(x, y)
z = np.sin(xx**2+yy**2)
f = interp2d(x, y, z, kind='linear')
# Configuration for the test (to initialize the bilinear structure)
matrixSize=[np.size(x),np.size(y)]
# Generate reference value for bilinear instance
# getLinearPoints ensure they are in row order
samples = getLinearPoints(x,y)
# We recompute the value of the function on the samples in row
# order
yvals = np.array([np.sin(i[0]**2+i[1]**2) for i in samples])
# Now we generate other points. The points where we want to evaluate
# the function.
# In Python they must be rescale between -3.14 and tghe max x or max y defined above.
# In CMSIS they will be between 1 and numRow-1 or numCols-1.
# Since we add 0.5 to be sure we are between grid point, we use
# numCols-2 as bound to be sured we are <= numCols-1
numCols = np.size(x)
numRows = np.size(y)
NBX = 10
NBY = 15
# The CMSIS indexes
ix = np.linspace(0, numCols-3, num=NBX, endpoint=True)+0.5
iy = np.linspace(0, numRows-3, num=NBY, endpoint=True)+0.5
# The corresponding Python values
ixVal = ((ix ) / (numCols-1)) * (x[-1] + 3.14) - 3.14
iyVal = ((iy ) / (numRows-1)) * (y[-1] + 3.14) - 3.14
# Input samples for CMSIS.
inputSamples = getLinearPoints(ix,iy)
# We compute the Python interpolated function on the values
inputVals = getLinearPoints(ixVal,iyVal)
ref=np.array([f(i[0],i[1]) for i in inputVals])
if format != 0 and format != 16:
inputSamples = inputSamples / 2.0**11
data = inputSamples.reshape(np.size(inputSamples))
if format != 0 and format != 16:
config.writeInputQ31(2, data,"Input")
else:
config.writeInput(2, data)
config.writeInput(2, yvals.reshape(np.size(yvals)),"YVals")
config.writeReference(2, ref.reshape(np.size(ref)))
config.writeInputS16(2, matrixSize,"Config")
x = [0,3,10,20]
config.writeInput(3,x,"InputX")
y = [0,9,100,400]
config.writeInput(3,y,"InputY")
xnew = np.arange(0,20,1)
config.writeInput(3,xnew,"OutputX")
ynew = CubicSpline(x,y)
config.writeReference(3, ynew(xnew))
x = np.arange(0, 2*np.pi+np.pi/4, np.pi/4)
config.writeInput(4,x,"InputX")
y = np.sin(x)
config.writeInput(4,y,"InputY")
xnew = np.arange(0, 2*np.pi+np.pi/16, np.pi/16)
config.writeInput(4,xnew,"OutputX")
ynew = CubicSpline(x,y,bc_type="natural")
config.writeReference(4, ynew(xnew))
x = [0,3,10]
config.writeInput(5,x,"InputX")
y = x
config.writeInput(5,y,"InputY")
xnew = np.arange(-10,20,1)
config.writeInput(5,xnew,"OutputX")
ynew = CubicSpline(x,y)
config.writeReference(5, ynew(xnew))
def generatePatterns():
PATTERNDIR = os.path.join("Patterns","DSP","Interpolation","Interpolation")
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)
if __name__ == '__main__':
generatePatterns()