epsilon, epsilonE, Qu, coefF, coefP, rootE, port1, port2 = CP.S2FP(
freq,
S21,
S11,
filterOrder,
w1,
w2,
fc=fc,
method=extractMethod,
startFreq=captureStartFreq,
stopFreq=captureStopFreq,
isSymmetric=isSymmetric)
polyF = Polynomial(coefF)
polyP = Polynomial(coefP)
polyE = Polynomial.fromroots(rootE)
rootF = polyF.roots()
rootP = polyP.roots()
matrixMethod = 5
transversalMatrix = CP.FPE2M(epsilon,
epsilonE,
coefF,
coefP,
rootE,
method=matrixMethod)
# print(np.round(transversalMatrix, 3))
# extractedMatrix, msg = CP.FPE2MComprehensive(epsilon, epsilonE, rootF, rootP, rootE, topology, method = matrixMethod)
# arrowM = CP.RotateM2Arrow(transversalMatrix, isComplex = True)
def get_task(method):
if method == "try":
sFile = WriteString2TempFile("hello sam")
fileContent = sFile.read()
sFile.close()
print(flask.request.is_json)
print(method, fileContent)
bodyJson = flask.request.get_json()
bodyJson['pythonVal'] = 'back from python'
print(json.dumps(bodyJson, separators = (',', ':')))
return json.dumps(bodyJson, separators = (',', ':'))
# ntwk = rf.Network(sFile);
# originalFreq = ntwk.frequency.f;
# originalS21 = ntwk.s[::, 1, 0];
# originalS11 = ntwk.s[::, 0, 0];
elif method == "SynthesizeFromTranZeros":
reqJson = flask.request.get_json()
# print(json.dumps(reqJson, separators = (',', ':')))
N = reqJson['N']
returnLoss= reqJson['returnLoss']
rootP = np.array([x[0] + 1j * x[1] for x in reqJson['rootP']])
epsilon, coefP, coefF, rootE = CP.ChebyshevP2EF(rootP, N, returnLoss)
coefE = Polynomial.fromroots(rootE).coef
epsilonE = epsilon
topology = np.array(reqJson['topology'])
matrixMethod = 5
targetMatrix, msg = CP.FPE2MComprehensive(epsilon, epsilonE, coefF, coefP, rootE, topology, refRootP = rootP, method = matrixMethod)
resJson = {'epsilon': [epsilon.real, epsilon.imag], 'coefP': [[x.real, x.imag] for x in coefP], 'coefF': [[x.real, x.imag] for x in coefF], 'coefE': [[x.real, x.imag] for x in coefE], 'targetMatrix': targetMatrix.tolist(), 'message': msg}
return json.dumps(resJson, separators = (',', ':'))
elif method == "ExtractMatrix":
reqJson = flask.request.get_json()
np.save("tempData3", np.array([reqJson]))
#print(json.dumps(reqJson, separators = (',', ':')))
freq = np.array(reqJson['freq']) * 1e6
S21_amp = 10 ** (np.array(reqJson['S21_db']) / 20)
S21 = S21_amp * (np.cos(np.array(reqJson['S21_angRad'])) + 1j * np.sin(np.array(reqJson['S21_angRad'])))
S11_amp = 10 ** (np.array(reqJson['S11_db']) / 20)
S11 = S11_amp * (np.cos(np.array(reqJson['S11_angRad'])) + 1j * np.sin(np.array(reqJson['S11_angRad'])))
N = reqJson['filterOrder']
tranZeros = [x[0] + 1j * x[1] for x in reqJson['tranZeros']]
numZeros = len(tranZeros)
filterOrder = np.hstack((np.zeros((N, )), 2 * np.ones((numZeros, ))))
w1 = (reqJson['centerFreq'] - reqJson['bandwidth'] / 2) * 1e9
w2 = (reqJson['centerFreq'] + reqJson['bandwidth'] / 2) * 1e9
# print(N, numZeros, filterOrder, w1, w2)
startFreq = reqJson['captureStartFreqGHz'] * 1e9
stopFreq = reqJson['captureStopFreqGHz'] * 1e9
isSymmetric = reqJson['isSymmetric']
extractMethod = 6
fc = (w1 + w2) / 4
epsilon, epsilonE, Qu, coefF, coefP, rootE, port1, port2 = CP.S2FP(freq, S21, S11, filterOrder, w1, w2, fc=fc, method=extractMethod, startFreq=startFreq, stopFreq=stopFreq, isSymmetric=isSymmetric)
if Qu == np.inf:
Qu = 1e9
# print(Qu)
topology = np.array(reqJson['topology'])
matrixMethod = 5
extractedMatrix, msg = CP.FPE2MComprehensive(epsilon, epsilonE, coefF, coefP, rootE, topology, refRootP = tranZeros, method = matrixMethod)
targetMatrix = np.array(reqJson['targetMatrix'])
deviateMatrix = targetMatrix - extractedMatrix
resJson = {'q': Qu, 'extractedMatrix': extractedMatrix.tolist(), 'deviateMatrix': deviateMatrix.tolist(), 'message': msg}
return json.dumps(resJson, separators = (',', ':'))
elif method == "SpaceMappingCalculate":
reqJson = flask.request.get_json()
np.save("tempData2", np.array([reqJson]))
B = np.array(reqJson['B'], dtype = float)
# print(np.around(B, 2))
h = np.array(reqJson['h'], dtype = float)
xc = np.array(reqJson['xc'], dtype = float)
xc_star = np.array(reqJson['xc_star'], dtype = float)
xf = np.array(reqJson['xf'], dtype = float)
lowerLimit = np.array(reqJson['lowerLimit'], dtype = float)
upperLimit = np.array(reqJson['upperLimit'], dtype = float)
f = xc - xc_star
B += np.array(np.mat(f).T * np.mat(h)) / h.dot(h)
h = np.linalg.solve(B, -f)
xf_old = xf.copy()
xf += h
xf = np.where(xf > lowerLimit, xf, lowerLimit)
xf = np.where(xf < upperLimit, xf, upperLimit)
h = xf - xf_old
if f.dot(f) < 4e-10 * len(xc):
toStop = 1
else:
toStop = 0
resJson = {'B': B.tolist(), 'h': h.tolist(), 'xf': xf.tolist(), 'f': f.tolist(), 'toStop': toStop}
return json.dumps(resJson, separators = (',', ':'))
elif method == "CoarseModelUpdate":
reqJson = flask.request.get_json()
np.save("tempData", np.array([reqJson]))
# reqJson = np.load('tempData.npy')[0]
dimension = np.array(reqJson['dimension'])
extractedMatrix = np.array(reqJson['extractedMatrix'])
topology = np.array(reqJson['topology'])
isSymmetric = reqJson['isSymmetric']
slopeM, invSlopeM, intepM = CP.CoarseModelUpdate(dimension, extractedMatrix, topology, isSymmetric)
resJson = {'slopeM': slopeM.tolist(), 'invSlopeM': invSlopeM.tolist(), 'intepM': intepM.tolist()}
return json.dumps(resJson, separators = (',', ':'))
else:
flask.abort(404)
