import os.path
import numpy as np
import itertools
import Tools
from scipy import signal
#from pylab import figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show,semilogx, semilogy

# Those patterns are used for tests and benchmarks.
# For tests, there is the need to add tests for saturation

def cartesian(*somelists):
   r=[]
   for element in itertools.product(*somelists):
       r.append(element)
   return(r)

def writeTests(config,format):
    NBSAMPLES=256
    NUMTAPS = 64

    samples=np.random.randn(NBSAMPLES)
    refs=np.random.randn(NBSAMPLES)
    taps=np.random.randn(NUMTAPS)

    samples = Tools.normalize(samples)
    refs = Tools.normalize(refs)
    taps = Tools.normalize(taps)
    

    ### For benchmarks

    config.writeInput(1, samples,"Samples")
    config.writeInput(1, taps,"Coefs")
    config.writeInput(1, refs,"Refs")

    ### For tests

    # blocksize 1 2 3 8 11 
    # taps 1 2 3 4 5 6 7 8 11 25
    # state numTaps + blockSize - 1
    # ref blockSize

    # Maximum number of samples for all tested FIR configurations is 2*23
    t = np.linspace(0, 1, 2*23)

    x = np.sin(2*np.pi*50*t)+np.random.randn(len(t)) * 0.08
    x = Tools.normalize(x)
    # To avoid saturation
    x = x / 30.0
    

    config.writeInput(1, x,"FirInput")
    tapConfigs=[] 
    output=[] 
    defs=[] 

    if format == Tools.F64 or format == 0 or format == 31:
       blk = [1, 2, 3, 8, 9,10,11, 16, 23]
       taps = [1, 2, 3, 4, 5, 6, 7, 8, 11, 16, 23, 25]
    elif format == 15 or format == 16:
       blk = [1, 2, 3, 12,13,14,15]
       taps = [2, 3, 4, 5, 6, 7, 8, 11, 25]
    elif format == 7:
       blk = [1, 2, 3 ,20,21,22,23]
       taps = [1, 2, 3, 4, 5, 6, 7, 8, 11, 25]

    configs = cartesian(blk,taps)

    nb=1

    for (b,t) in configs:
        nbTaps=t
        # nbTaps + 2 to be sure all coefficients are not saturated
        pythonCoefs = np.array(list(range(1,nbTaps+1)))/(1.0*(nbTaps+2))
        coefs=pythonCoefs

        if format == 15:
          if t % 2 == 1:
            nbTaps = nbTaps + 1 
            coefs = np.append(coefs,[0.0])
        
        out=signal.lfilter(pythonCoefs,[1.0],x[0:2*b])

        output += list(out)
        coefs = list(coefs)
        coefs.reverse()
        tapConfigs += coefs
        defs += [b,nbTaps]

        nb = nb + 1

    config.writeInput(1, output,"FirRefs")
    config.writeInput(1, tapConfigs,"FirCoefs")
    config.writeReferenceS16(1,defs,"FirConfigs")

    
def generatePatterns():
    PATTERNDIR = os.path.join("Patterns","DSP","Filtering","FIR","FIR")
    PARAMDIR = os.path.join("Parameters","DSP","Filtering","FIR","FIR")
    
    configf64=Tools.Config(PATTERNDIR,PARAMDIR,"f64")
    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")
    
    configf32.setOverwrite(False)
    configf16.setOverwrite(False)
    configq31.setOverwrite(False)
    configq15.setOverwrite(False)
    configq7.setOverwrite(False)
    
    writeTests(configf64,Tools.F64)
    writeTests(configf32,0)
    writeTests(configf16,16)
    writeTests(configq31,31)
    writeTests(configq15,15)
    writeTests(configq7,7)


if __name__ == '__main__':
  generatePatterns()