def testSums(self):
print 'test sum'
ds = np.arange(12).reshape((3,4))
self.assertEquals(np.sum(ds), 66)
self.checkitems([12, 15, 18, 21], np.sum(ds, 0))
self.checkitems([ 6, 22, 38], np.sum(ds, 1))
print 'test cumsum'
self.checkitems([0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66], np.cumsum(ds))
self.checkitems([[0, 1, 2, 3], [4, 6, 8, 10], [12, 15, 18, 21]], np.cumsum(ds, 0))
self.checkitems([[0, 1, 3, 6], [4, 9, 15, 22], [8, 17, 27, 38]], np.cumsum(ds, 1))
def testSums(self):
print 'test sum'
ds = np.arange(12).reshape((3,4))
self.assertEquals(np.sum(ds), 66)
self.checkitems([12, 15, 18, 21], np.sum(ds, 0))
self.checkitems([ 6, 22, 38], np.sum(ds, 1))
lds = np.arange(1024*1024, dtype=np.int32)
self.assertEquals(np.sum(lds, dtype=np.int32), -524288)
self.assertEquals(np.sum(lds, dtype=np.int64), 549755289600)
print 'test cumsum'
self.checkitems([0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66], np.cumsum(ds))
self.checkitems([[0, 1, 2, 3], [4, 6, 8, 10], [12, 15, 18, 21]], np.cumsum(ds, 0))
self.checkitems([[0, 1, 3, 6], [4, 9, 15, 22], [8, 17, 27, 38]], np.cumsum(ds, 1))
def simpleFitGaussian(data, x=None, plotPanel=None):
if x is None:
x=dnp.arange(data.size)
mu=sum(x*data)/sum(data)
sigma = math.sqrt(abs(dnp.sum((x-mu)**2*data)/dnp.sum(data)))
peak=data.max();
area=sum(data);
if plotPanel is not None:
print("To plot the fitted data")
y1=myGaussianFunc(mu, sigma, peak, [x]);
dnp.plot.line(x, [data, y1] ) # plot line of evaluated function
return [mu, sigma, peak, area]
def testSums(self):
print 'test sum'
ds = np.arange(12).reshape((3, 4))
self.assertEquals(ds.sum(), 66)
self.assertEquals(np.sum(ds), 66)
self.checkitems([12, 15, 18, 21], ds.sum(0))
self.checkitems([12, 15, 18, 21], ds.sum(-2))
self.checkitems([12, 15, 18, 21], np.sum(ds, 0))
self.checkitems([12, 15, 18, 21], np.sum(ds, -2))
self.checkitems([6, 22, 38], ds.sum(1))
self.checkitems([6, 22, 38], ds.sum(-1))
self.checkitems([6, 22, 38], np.sum(ds, 1))
self.checkitems([6, 22, 38], np.sum(ds, -1))
lds = np.arange(1024 * 1024, dtype=np.int32)
self.assertEquals(np.sum(lds, dtype=np.int32), -524288)
self.assertEquals(np.sum(lds, dtype=np.int64), 549755289600)
print 'test cumsum'
self.checkitems([0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66],
np.cumsum(ds))
self.checkitems([[0, 1, 2, 3], [4, 6, 8, 10], [12, 15, 18, 21]],
np.cumsum(ds, 0))
self.checkitems([[0, 1, 3, 6], [4, 9, 15, 22], [8, 17, 27, 38]],
np.cumsum(ds, 1))
self.checkitems([[0, 1, 3, 6], [4, 9, 15, 22], [8, 17, 27, 38]],
np.cumsum(ds, -1))
def scan_temps(start,stop,step,fwhm): fg.setParameterValues(0.1,start,0,1,0,fwhm) test = fg.calculateValues([x]) temps = dnp.arange(start,stop,step) result = dnp.zeros(temps.shape) count = 0 for temp in temps: fg.setParameterValues(0.1,temp,0,1,0,0.0) comp = fg.calculateValues([x]) result[count] = dnp.sum(dnp.square(dnp.array(test)-dnp.array(comp))) count+=1 dnp.plot.line(temps,result) return temps[result.minPos().tolist()]
def scan_temps(start, stop, step, fwhm):
fg.setParameterValues(0.1, start, 0, 1, 0, fwhm)
test = fg.calculateValues([x])
temps = dnp.arange(start, stop, step)
result = dnp.zeros(temps.shape)
count = 0
for temp in temps:
fg.setParameterValues(0.1, temp, 0, 1, 0, 0.0)
comp = fg.calculateValues([x])
result[count] = dnp.sum(dnp.square(dnp.array(test) - dnp.array(comp)))
count += 1
dnp.plot.line(temps, result)
return temps[result.minPos().tolist()]
def testSum(self):
a = dnp.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
self.assertEqual(dnp.sum(a, keepdims=True).shape, (1, 1, 1))
self.checkitems(dnp.sum(a, keepdims=True), dnp.array([[[36]]]))
def testSum(self):
a = dnp.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
self.assertEquals(dnp.sum(a, keepdims=True).shape, (1, 1, 1))
self.checkitems(dnp.sum(a, keepdims=True), dnp.array([[[36]]]))