Ejemplo n.º 1
0
 def __init__(self, *args):
     unittest.TestCase.__init__(self, *args)
     self.x = dnp.linspace(0, 5, 20)
     dnp.random.seed(12347)
     self.n = dnp.random.randn(20) * 0.1
     self.y = 3.2 * self.x + 0.35 + self.n
     self.z = 3.2 * self.x * self.x - 12.2 * self.x + 0.35 + self.n
Ejemplo n.º 2
0
 def __init__(self, *args):
     unittest.TestCase.__init__(self, *args)
     self.x = dnp.linspace(0, 5, 20)
     dnp.random.seed(12347)
     self.n = dnp.random.randn(20)*0.1
     self.y = 3.2*self.x + 0.35 + self.n
     self.z = 3.2*self.x*self.x - 12.2*self.x + 0.35 + self.n
Ejemplo n.º 3
0
    def testSpace(self):
        print "test space"
        dds = np.linspace(0, 11, 12)
        self.checkitems(range(12), dds)
        dds = np.linspace(0, 11, 12, dtype=np.int32)
        self.checkitems(range(12), dds, toInt)
        dds = np.linspace(0, 5, 11)
        self.checkitems([0.5*i for i in range(11)], dds)
        dds = np.linspace(0, 5, 11, dtype=np.int32)
        self.checkitems([i/2 for i in range(11)], dds, toInt)

        import math
        dds = np.logspace(0,2,5)
        self.checkitems([math.pow(10.,0.5*i) for i in range(5)], dds)
        dds = np.logspace(0,2,5, dtype=np.int32)
        self.checkitems([1, 3, 10, 31, 100], dds, toInt)
Ejemplo n.º 4
0
def get_chi_steps(two_theta, starting_chi_value=100.0, final_chi_value=0.0):
    theta = dnp.radians(two_theta / 2.0) # converts to radians and halfs to theta
    radius = LENGTH * float(dnp.sin(theta))
    delta_chi = float(dnp.rad2deg((WIDTH / radius)))
    number_of_steps = dnp.abs(final_chi_value-starting_chi_value)/(delta_chi*0.5)
    number_of_steps = int(number_of_steps)+1
    return dnp.linspace(starting_chi_value, final_chi_value, number_of_steps)
Ejemplo n.º 5
0
def demoRealDataFitting():
	m6Data=dnp.io.load("/dls/i06-1/data/2012/si7816-1/68917.dat", formats=['srs'], asdict=True);
#	m6Data=dnp.io.load("/dls/i06-1/data/2012/si7816-1/68918.dat", formats=['srs'], asdict=True);
	
	x, y=m6Data['m6qg'], m6Data['ca62sr'];
	
#	[mu, sigma, peak, gf] = fineGaussianFitting(y, x, "Plot 2");
	[mu, sigma, peak, gf] = fineGaussianFitting(y, x);
	
#	One vertical line on the peak point:
#	xx, yy=dnp.array([mu-1, mu+1]), dnp.array([0, peak]);
	xx, yy=dnp.array([mu-1, mu, mu+1]), dnp.array([0, peak, 0]);
	xxx, yyy=dnp.array([mu]), dnp.array([peak]);
	
#	To find the closest data point to the peak;
	cPos=(dnp.abs(x-mu)).minpos()[0];
	cX, cY=x[cPos], y[cPos];
	
	print("To plot the fitted data." )
	x1=dnp.linspace(x[0], x[x.size-1], 500);
	y1=myGaussianFunc(mu, sigma, peak, [x1]);
	
	#Line plot does not work, 
	#dnp.plot.line(x, [y, y1] ) # plot line of evaluated function
	#dnp.plot.updateline(xx, yy)
	
	dnp.plot.points(x, y, None, 5);
	sleep(1);
	dnp.plot.addpoints(x1, y1, None, 1)
	sleep(1);
	dnp.plot.addpoints(xxx, yyy, None, 10);
	
	return [mu, sigma, peak, gf];
Ejemplo n.º 6
0
    def testSpace(self):
        print "test space"
        dds = np.linspace(0, 11, 12)
        self.checkitems(range(12), dds)
        dds = np.linspace(0, 11, 12, dtype=np.int32)
        self.checkitems(range(12), dds, toInt)
        dds = np.linspace(0, 5, 11)
        self.checkitems([0.5 * i for i in range(11)], dds)
        dds = np.linspace(0, 5, 11, dtype=np.int32)
        self.checkitems([i / 2 for i in range(11)], dds, toInt)

        import math
        dds = np.logspace(0, 2, 5)
        self.checkitems([math.pow(10., 0.5 * i) for i in range(5)], dds)
        dds = np.logspace(0, 2, 5, dtype=np.int32)
        self.checkitems([1, 3, 10, 31, 100], dds, toInt)
def readTestInputs(
    filename="height.txt",
    idealname="ideal.txt",
    visit_directory="/dls/i12/data/2014/cm4963-2",
    input_directory="tmp",
    printres=False,
):
    infilename = "%s/%s/%s" % (visit_directory, input_directory, filename)
    idealfilename = "%s/%s/%s" % (visit_directory, input_directory, idealname)
    inlist = []
    ideallist = []

    try:
        infile = open(infilename, "r")
    except:
        print ("File %s not opened properly" % infilename)
        return None
    n = 0
    for line in infile:
        if printres:
            print n, line
            n = n + 1
        inlist.append(float(line))
    infile.close()
    try:
        infile = open(idealfilename, "r")
    except:
        print ("File %s not opened properly" % idealfilename)
        return None
    for line in infile:
        if printres:
            print n, line
            n = n + 1
        ideallist.append(float(line))
    infile.close()
    if printres:
        print inlist
        print ideallist
    inarray = dnp.array(inlist)
    idealarray = dnp.array(ideallist)
    print len(inarray)
    angarray = dnp.linspace(0, dnp.pi * 2.0, len(inarray), True)
    horizarray = 2500.0 * dnp.cos(angarray)
    ofile = open("%s/%s/testpoints.txt" % (visit_directory, input_directory), "w")
    ofile.write("angle,X,idealY,noisyY\n")
    for i in range(0, len(angarray)):
        ofile.write("%g,%g,%g,%g\n" % (angarray[i], horizarray[i], idealarray[i], inarray[i]))
    ofile.close()
    return (horizarray, inarray, idealarray)
Ejemplo n.º 8
0
def m6qgmax():
    print("Move exit slit s6y to -6.5")
    s6y.moveTo(-6.5)

    q0 = m6qg.getPosition()
    print("Current m6qg position: " + str(q0))

    print("Scan m6qg ...")
    m6Data = m6qgscan(q0)
    #	m6Data=GuassianScan();

    x, y = m6Data['m6qg'], m6Data['ca62sr']
    #	x, y=m6Data['x'], m6Data['y'];

    #	[mu, sigma, peak, gf] = fineGaussianFitting(y, x, "Plot 1");
    [mu, sigma, peak, gf] = fineGaussianFitting(y, x)

    #	One vertical line on the peak point:
    #	xx, yy=dnp.array([mu-1, mu+1]), dnp.array([0, peak]);
    xx, yy = dnp.array([mu - 1, mu, mu + 1]), dnp.array([0, peak, 0])
    xxx, yyy = dnp.array([mu]), dnp.array([peak])

    #	To find the closest data point to the peak;
    cPos = (dnp.abs(x - mu)).minPos()[0]
    cX, cY = x[cPos], y[cPos]

    #	data according to the model
    x1 = dnp.linspace(x[0], x[x.size - 1], 500)
    y1 = myGaussianFunc(mu, sigma, peak, [x1])

    print("To plot the fitted data.")
    dnp.plot.points(x, y, None, 5)
    sleep(1)
    dnp.plot.addpoints(x1, y1, None, 1)
    sleep(1)
    dnp.plot.addpoints(xxx, yyy, None, 10)

    print("The peak position is: (%g, %g)" % (mu, peak))
    ans = queryYesNo(
        "Do you want to move m6qg to the estimated peak position?", "no")
    if ans is 'yes':
        m6qg.moveTo(mu)
        print "m6qg:" + str(m6qg.getPosition())

    return
def readTestInputs(filename='height.txt',idealname='ideal.txt',visit_directory='/dls/i12/data/2014/cm4963-2',input_directory='tmp',printres=False):
    infilename="%s/%s/%s"%(visit_directory,input_directory,filename)
    idealfilename="%s/%s/%s"%(visit_directory,input_directory,idealname)
    inlist=[]
    ideallist=[]
    
    
    try:
        infile=open(infilename,'r')
    except:
        print("File %s not opened properly"%infilename)
        return(None)
    n=0
    for line in infile:
        if printres:
            print n,line
            n=n+1
        inlist.append(float(line))
    infile.close()
    try:
        infile=open(idealfilename,'r')
    except:
        print("File %s not opened properly"%idealfilename)
        return(None)
    for line in infile:
        if printres:
            print n,line
            n=n+1
        ideallist.append(float(line))
    infile.close()
    if printres:
        print inlist
        print ideallist
    inarray=dnp.array(inlist)
    idealarray=dnp.array(ideallist)
    print len(inarray)
    angarray=((dnp.linspace(0,dnp.pi*2.0,len(inarray),True)))
    horizarray=2500.0*dnp.cos(angarray)
    ofile=open("%s/%s/testpoints.txt"%(visit_directory,input_directory),'w')
    ofile.write("angle,X,idealY,noisyY\n")
    for i in range(0,len(angarray)):
        ofile.write("%g,%g,%g,%g\n"%(angarray[i],horizarray[i],idealarray[i],inarray[i]))
    ofile.close()
    return(horizarray,inarray,idealarray)
def dofourier(xarray, yarray, printres=False):
    nvals = len(yarray)
    avht = yarray.mean()
    angles = dnp.linspace(0, 2 * dnp.pi, len(yarray))
    # print angles
    ycarray = yarray - avht
    cosines = dnp.cos(angles)
    sines = dnp.sin(angles)
    cosint = cosines * ycarray
    sinint = sines * ycarray
    if printres:
        print "Yarray:", yarray
        print "Ycarray:", ycarray
        print "Sinint:", sinint
        print "Cosint:", cosint
    cosum = cosint[:-1].sum()
    sinsum = sinint[:-1].sum()
    cosfactor = cosum / float(nvals - 1)
    sinfactor = sinsum / float(nvals - 1)
    if printres:
        print "sinfactor, cosfactor: %.4f %.4f" % (sinfactor, cosfactor)
    ratio = sinfactor / cosfactor
    delta = math.atan(ratio)
    deltadeg = math.degrees(delta)
    if printres:
        print "Delta degrees %06.4f" % deltadeg
    halfmag = math.sqrt(sinfactor ** 2 + cosfactor ** 2)
    mag = 2.0 * halfmag
    if printres:
        print "Magnitude: %06.4f" % mag
        print "vertical centre %7.4f" % avht

    calcresult = avht + mag * dnp.cos(angles - delta)
    if printres:
        print "Calcresult:", calcresult
        for idx in range(0, len(yarray)):
            print yarray[idx], calcresult[idx]

    return (avht, mag, delta, calcresult)
def dofourier(xarray,yarray,printres=False):
    nvals=len(yarray)
    avht=yarray.mean()
    angles=dnp.linspace(0,2*dnp.pi,len(yarray))
    #print angles
    ycarray=yarray-avht
    cosines=dnp.cos(angles)
    sines=dnp.sin(angles)
    cosint=cosines*ycarray
    sinint=sines*ycarray
    if printres:
        print "Yarray:",yarray
        print "Ycarray:",ycarray
        print "Sinint:",sinint
        print "Cosint:",cosint
    cosum=cosint[:-1].sum()
    sinsum=sinint[:-1].sum()
    cosfactor=cosum/float(nvals-1)
    sinfactor=sinsum/float(nvals-1)
    if printres:
        print "sinfactor, cosfactor: %.4f %.4f"%(sinfactor,cosfactor)
    ratio=sinfactor/cosfactor
    delta=math.atan(ratio)
    deltadeg=math.degrees(delta)
    if printres:
        print"Delta degrees %06.4f"%deltadeg
    halfmag=math.sqrt(sinfactor**2+cosfactor**2)
    mag=2.0*halfmag
    if printres:
        print"Magnitude: %06.4f"%mag
        print "vertical centre %7.4f"%avht
    
    calcresult=avht+mag*dnp.cos(angles-delta)
    if printres:
        print"Calcresult:",calcresult
        for idx in range(0,len(yarray)):
            print yarray[idx],calcresult[idx]
        
    return(avht,mag,delta,calcresult)
Ejemplo n.º 12
0
def testMyGaussianFunc():
	t = dnp.linspace(0, 99, 100)# dataset of 40 coordinate points between 0 and 5
	dnp.plot.line(t, myGaussianFunc(10, 3, 10, [t]) ) # plot line of evaluated function
Ejemplo n.º 13
0
n=x.size;
a=(x[n-1] - x[0])/(n-1); b=x[0];
mu=a*mu0+b;
sigma=a*sigma0;

#One vertical line on the peak point:
#xx, yy=dnp.array([mu-1, mu+1]), dnp.array([0, peak]);
xx, yy=dnp.array([mu-1, mu, mu+1]), dnp.array([0, peak, 0]);
xxx, yyy=dnp.array([mu]), dnp.array([peak]);

#To find the closest data point to the peak;
cPos=(dnp.abs(x-mu)).minPos()[0];
cX, cY=x[cPos], y[cPos];

print("To plot the fitted data." )
x1=dnp.linspace(x[0], x[n-1], 500);
y1=myGaussianFunc(mu, sigma, peak, [x1]);

#Line plot does not work
#dnp.plot.line(x, [y, y1] ) # plot line of evaluated function
#dnp.plot.updateline(xx, yy)

dnp.plot.points(x, y, None, 5);
sleep(1);
dnp.plot.addpoints(x1, y1, None, 1)
sleep(1);
dnp.plot.addpoints(xxx, yyy, None, 10);


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