def draw_hist(self):
list_checked = []
for i in range(1, self.verticalLayout_hotels.count()):
if self.verticalLayout_hotels.itemAt(
i).widget().isChecked() == True:
list_checked.append(
self.verticalLayout_hotels.itemAt(i).widget().text())
print(list_checked)
filter = self.filter_hist.currentText()
filer_pos_neg = ""
b = False
if self.pos_hist.isChecked() and self.neg_hist.isChecked():
filer_pos_neg = "posneg"
b = True
else:
if self.pos_hist.isChecked():
filer_pos_neg = "positive"
b = True
if self.neg_hist.isChecked():
filer_pos_neg = "negative"
b = True
if b and len(list_checked) > 0:
histogram(self.file, filter, filer_pos_neg, list_checked)
def test__idiv__2(self):
"histogram: h/=h1"
h = self._histogram.copy()
h2 = self._histogram2
h /= h2
self.assertVectorAlmostEqual( h[1.5,1], (1,2.0/3) )
h = self._histogram.copy()
h2 = createHistogram( noerror = True )
h /= h2
self.assertVectorAlmostEqual( h[1.5,1], (1,1./3) )
from histogram import histogram, axis, arange, datasetFromFunction
x = axis('x', arange(1, 2, .2 ) )
y = axis('y', arange(0, 3, .5 ) )
def fa(x,y): return x*y + x
ha = histogram('a', [x,y], datasetFromFunction( fa, (x,y) ) )
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( fa(xi,yi), ha[xi,yi][0] )
def fb(x,y): return x
hb = histogram('b', [x,y], datasetFromFunction( fb, (x,y) ) )
hc = ha/hb
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( yi+1, hc[xi,yi][0] )
def fberr(x,y): return 0*x
hb = histogram('b', [x,y], datasetFromFunction( fb, (x,y) ),
datasetFromFunction( fberr, (x,y) ) )
hc = ha/hb
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( yi+1, hc[xi,yi][0] )
#involve units
h1 = histogram(
'h1',
[ ('x', [1,2,3]),
],
unit = 'meter',
data = [1,2,3],
errors = [1,2,3],
)
h2 = histogram(
'h2',
[ ('x', [1,2,3]),
],
data = [1,1,1],
errors = [1,1,1],
unit = 'second',
)
h3 = h1/h2
self.assertVectorAlmostEqual( h3.I, (1,2,3) )
self.assertVectorAlmostEqual( h3.E2, (2,6,12) )
return
def test__idiv__2(self):
"histogram: h/=h1"
h = self._histogram.copy()
h2 = self._histogram2
h /= h2
self.assertVectorAlmostEqual( h[1.5,1], (1,2.0/3) )
h = self._histogram.copy()
h2 = createHistogram( noerror = True )
h /= h2
self.assertVectorAlmostEqual( h[1.5,1], (1,1./3) )
from histogram import histogram, axis, arange, datasetFromFunction
x = axis('x', arange(1, 2, .2 ) )
y = axis('y', arange(0, 3, .5 ) )
def fa(x,y): return x*y + x
ha = histogram('a', [x,y], datasetFromFunction( fa, (x,y) ) )
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( fa(xi,yi), ha[xi,yi][0] )
def fb(x,y): return x
hb = histogram('b', [x,y], datasetFromFunction( fb, (x,y) ) )
hc = ha/hb
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( yi+1, hc[xi,yi][0] )
def fberr(x,y): return 0*x
hb = histogram('b', [x,y], datasetFromFunction( fb, (x,y) ),
datasetFromFunction( fberr, (x,y) ) )
hc = ha/hb
for xi in x.binCenters():
for yi in y.binCenters():
self.assertAlmostEqual( yi+1, hc[xi,yi][0] )
#involve units
h1 = histogram(
'h1',
[ ('x', [1,2,3]),
],
unit = 'meter',
data = [1,2,3],
errors = [1,2,3],
)
h2 = histogram(
'h2',
[ ('x', [1,2,3]),
],
data = [1,1,1],
errors = [1,1,1],
unit = 'second',
)
h3 = h1/h2
self.assertVectorAlmostEqual( h3.I, (1,2,3) )
self.assertVectorAlmostEqual( h3.E2, (2,6,12) )
return
def test_histogram1a(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'
"""
def f(x): return x*x
h = histogram('h', [ ('x',range(10)) ],
fromfunction = f )
def g(x): return x
h = histogram('h', [ ('x',range(10)) ],
fromfunction = (f,g) )
return
def test_histogram1a(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'
"""
def f(x):
return x * x
h = histogram('h', [('x', list(range(10)))], fromfunction=f)
def g(x):
return x
h = histogram('h', [('x', list(range(10)))], fromfunction=(f, g))
return
def test_histogram1c(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'. math.sin
"""
import math
h = histogram('h', [
('x', arange(0, 3.0, 0.1)),
],
fromfunction=math.sin)
h = histogram('h', [
('x', arange(0, 3.0, 0.1)),
('y', arange(0, 3.0, 0.1)),
],
fromfunction=lambda x, y: math.sin(x + y))
return
def test_as_floattype(self):
from histogram import histogram, arange
h = histogram( 'h', [ ('x',arange(10)) ], data_type = 'int')
h1 = h.as_floattype()
self.assertEqual( h1.typeCode(), 6 )
self.assertTrue( h1.axisFromName( 'x' ) is not h.axisFromName( 'x' ) )
return
def normalize(self, IQE):
'normalize IQE'
# only the master node need to do normalization
if self.mpiRank != 0: return
#for debug
from histogram.hdf import dump
filename = 'IQE-nosolidanglenormalization.h5'
import os
if os.path.exists( filename ): os.remove( filename )
dump( IQE, filename, '/', 'c' )
info.log( 'node %s: convert I(Q,E) datatype from integer to double'
% self.mpiRank)
from histogram import histogram
newIQE = histogram( IQE.name(), IQE.axes() )
newIQE[(), ()] = IQE[(), ()]
Ei = self.Ei
pixelPositions = self.pixelPositions
pixelSolidAngles = self.pixelSolidAngles
from arcseventdata.normalize_iqe import normalize_iqe
info.log( 'node %s: normalize I(Q,E) by solid angle: Ei=%s, positions.shape=%s, solidangles.shape=%s'
% (self.mpiRank, Ei, pixelPositions.shape, pixelSolidAngles.shape))
import time
t0 = time.time()
normalize_iqe( newIQE, Ei, pixelPositions, pixelSolidAngles )
t1 = time.time()
info.log( 'node %s: normalization done: %s seconds' % (
self.mpiRank, t1-t0))
return newIQE
def test_as_floattype(self):
from histogram import histogram, arange
h = histogram( 'h', [ ('x',arange(10)) ], data_type = 'int')
h1 = h.as_floattype()
self.assertEqual( h1.typeCode(), 6 )
self.assert_( h1.axisFromName( 'x' ) is not h.axisFromName( 'x' ) )
return
def test_load(self):
"Histogram: pickle.load"
import pickle
h = self._histogram
pickle.dump( h, open( "tmp.pkl", 'w' ) )
h1 = pickle.load( open("tmp.pkl") )
self.assertEqual( h.name(), h1.name() )
print ("data=%s" % h1.data().storage().asNumarray() )
self.assert_( h.data().storage().compare( h1.data().storage() ) )
print ("errors=%s" % h1.errors().storage().asNumarray() )
self.assert_( h.errors().storage().compare( h1.errors().storage() ) )
for axisName in h.axisNameList():
print ("axis %s" % axisName)
axis = h.axisFromName( axisName )
axis1 = h1.axisFromName( axisName )
self.assert_( axis.storage().compare( axis1.storage() ) )
continue
from histogram import histogram
h2 = histogram(
'h2',
[ ('x', [1,2,3]),
],
unit = 'meter' )
pickle.dump( h2, open( "tmp.pkl", 'w' ) )
h2a = pickle.load( open("tmp.pkl") )
return
def testIadd_and_SetItem(self):
"Histogram: h[ x,y,z ] += sth"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
import numpy as N
h[ 1,5 ] = N.array( [1,1] )
return
def testIadd_and_SetItem(self):
"Histogram: h[ x,y,z ] += sth"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
import numpy as N
h[ 1,5 ] = N.array( [1,1] )
return
def test_load(self):
"Histogram: pickle.load"
import pickle
h = self._histogram
pickle.dump( h, open( "tmp.pkl", 'wb' ) )
h1 = pickle.load( open("tmp.pkl", 'rb') )
self.assertEqual( h.name(), h1.name() )
print(("data=%s" % h1.data().storage().asNumarray() ))
self.assertTrue( h.data().storage().compare( h1.data().storage() ) )
print(("errors=%s" % h1.errors().storage().asNumarray() ))
self.assertTrue( h.errors().storage().compare( h1.errors().storage() ) )
for axisName in h.axisNameList():
print(("axis %s" % axisName))
axis = h.axisFromName( axisName )
axis1 = h1.axisFromName( axisName )
self.assertTrue( axis.storage().compare( axis1.storage() ) )
continue
from histogram import histogram
h2 = histogram(
'h2',
[ ('x', [1,2,3]),
],
unit = 'meter' )
pickle.dump( h2, open( "tmp.pkl", 'wb' ) )
h2a = pickle.load( open("tmp.pkl", 'rb') )
return
def frequency_weight():
weight_dictionary = {}
sum_values = sum(histogram(word_list).values())
for word in word_list:
word_occurances = word_list.count(word)
weighted_occurances = word_occurances / sum_values
return
def test_values2indexes(self):
"Histogram: values2indexes"
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertVectorEqual( h.values2indexes( (2, 0.2) ), (1,12) )
return
def test_histogram6(self):
"""Histogram.__init__: errors = None"""
h = histogram('h', [
('x', [1, 2, 3]),
], unit='meter', data=[1, 2, 3])
self.assertVectorAlmostEqual(h.errors().storage().asNumarray(),
[0, 0, 0])
return
def t2():
from histogram import histogram, arange
from numpy import exp
h = histogram("h", [("tof", arange(1000.0, 3000.0, 1.0), "microsecond")], fromfunction=lambda x: exp(-x / 1000.0))
print h
plot(h)
return
def test_values2indexes(self):
"Histogram: values2indexes"
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertVectorEqual( h.values2indexes( (2, 0.2) ), (1,12) )
return
def t2():
from histogram import histogram, arange
from numpy import exp
h = histogram("h", [('tof', arange(1000., 3000., 1.0), "microsecond")],
fromfunction=lambda x: exp(-x / 1000.))
print(h)
plot(h)
return
def test_axisFromId(self):
"Histogram: axisFromId"
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertEqual( h.axisFromId(1), x )
self.assertEqual( h.axisFromId(2), y )
return
def test_axisFromId(self):
"Histogram: axisFromId"
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertEqual( h.axisFromId(1), x )
self.assertEqual( h.axisFromId(2), y )
return
def test_histogram5(self):
"""Histogram.__init__: unit"""
h = histogram(
'h',
[
('x', [1,2,3] ),
],
unit = 'meter',
)
return
def test_histogram1c(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'. math.sin
"""
import math
h = histogram(
'h',
[
('x',arange(0, 3.0, 0.1)),
],
fromfunction = math.sin )
h = histogram(
'h',
[
('x',arange(0, 3.0, 0.1)),
('y',arange(0, 3.0, 0.1)),
],
fromfunction = lambda x,y: math.sin(x+y) )
return
def testSetItem(self):
"Histogram: h[ x,y,z ] = value"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
h[ 1,5 ] = 1,1
self.assertVectorAlmostEqual(
h.data().storage().asList(), [0,1,0,0,0,0] )
self.assertVectorAlmostEqual(
h.errors().storage().asList(), [0,1,0,0,0,0] )
self.assertVectorAlmostEqual( h[1,5], (1,1) )
h = histogram( 'h', [('a', [1,2,3])] )
h[1] = 10,10
h = histogram( 'h', [('a', [1,2,3])], unit = 'meter')
from pyre.units.length import meter
h[1] = 10*meter,10*meter*meter
return
def t7():
from histogram import histogram
axes = [('x', [1, 2, 3]), ('yID', [1])]
data = [[1], [2], [3]]
errs = [[1], [2], [3]]
h = histogram('h', axes, data, errs)
assert h.shape() == (3, 1)
h.reduce()
assert h.shape() == (3, )
return
def testReplaceAxis(self):
'Hisogram: replaceAxis'
from histogram import histogram, axis, arange
a = axis('a', arange(1,10,1.0))
b = axis('b', arange(1,100,10.))
h = histogram( 'h', [a] )
self.assert_(a is h.axisFromName('a'))
h.replaceAxis(name='a', axis=b)
self.assert_(b is h.axisFromName('a'))
return
def testReplaceAxis(self):
'Hisogram: replaceAxis'
from histogram import histogram, axis, arange
a = axis('a', arange(1,10,1.0))
b = axis('b', arange(1,100,10.))
h = histogram( 'h', [a] )
self.assertTrue(a is h.axisFromName('a'))
h.replaceAxis(name='a', axis=b)
self.assertTrue(b is h.axisFromName('a'))
return
def test_histogram5(self):
"""Histogram.__init__: unit"""
h = histogram(
'h',
[
('x', [1, 2, 3]),
],
unit='meter',
)
return
def testSetItem(self):
"Histogram: h[ x,y,z ] = value"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
h[ 1,5 ] = 1,1
self.assertVectorAlmostEqual(
h.data().storage().asList(), [0,1,0,0,0,0] )
self.assertVectorAlmostEqual(
h.errors().storage().asList(), [0,1,0,0,0,0] )
self.assertVectorAlmostEqual( h[1,5], (1,1) )
h = histogram( 'h', [('a', [1,2,3])] )
h[1] = 10,10
h = histogram( 'h', [('a', [1,2,3])], unit = 'meter')
from pyre.units.length import meter
h[1] = 10*meter,10*meter*meter
return
def t7():
from histogram import histogram
axes = [("x", [1, 2, 3]), ("yID", [1])]
data = [[1], [2], [3]]
errs = [[1], [2], [3]]
h = histogram("h", axes, data, errs)
assert h.shape() == (3, 1)
h.reduce()
assert h.shape() == (3,)
return
def test_histogram1b(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'. 3D
"""
h = histogram('h', [
('x', list(range(2))),
('y', list(range(2, 4))),
('z', list(range(4, 6))),
],
fromfunction=lambda x, y, z: x + y + z)
return
def testSlicingIsRefering(self):
#slice is just a reference, not a copy
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
from numpy import ones
h[(),()] = ones( (3,2) ), ones((3,2) )
self.assertVectorAlmostEqual( h[1,4], (1,1) )
sh = h[1,()]
sh.clear()
self.assertVectorAlmostEqual( h[1,4], (0,0) )
return
def testSlicingIsRefering(self):
#slice is just a reference, not a copy
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
from numpy import ones
h[(),()] = ones( (3,2) ), ones((3,2) )
self.assertVectorAlmostEqual( h[1,4], (1,1) )
sh = h[1,()]
sh.clear()
self.assertVectorAlmostEqual( h[1,4], (0,0) )
return
def _test_histogram3a(self):
"""Histogram.__init__: histogram of non-float datatype"""
detaxis = axis('detectorID', list(range(10)))
pixaxis = axis('pixelID', list(range(10)))
mask = histogram('mask', (detaxis, pixaxis), data_type='char')
from numpy import ones
data = createDataset('data',
shape=(10, 10),
data=ones((10, 10), int),
data_type='int')
counts = histogram('counts', (detaxis, pixaxis),
data=data,
errors=None)
counts1 = histogram('counts', (detaxis, pixaxis),
data=ones((10, 10), int),
errors=ones((10, 10), int),
data_type='double')
self.assertEqual(counts1.errors().name(), 'errors')
return
def test_histogram6(self):
"""Histogram.__init__: errors = None"""
h = histogram(
'h',
[
('x', [1,2,3] ),
],
unit = 'meter',
data = [1,2,3]
)
self.assertVectorAlmostEqual( h.errors().storage().asNumarray(), [0,0,0] )
return
def _test_histogram3a(self):
"""Histogram.__init__: histogram of non-float datatype"""
detaxis = axis('detectorID', range(10) )
pixaxis = axis('pixelID', range(10) )
mask = histogram( 'mask', (detaxis, pixaxis), data_type = 'char' )
from numpy import ones
data = createDataset(
'data', shape = (10,10), data = ones( (10,10), int ),
data_type = 'int' )
counts = histogram(
'counts', (detaxis, pixaxis),
data = data,
errors = None)
counts1 = histogram(
'counts', (detaxis, pixaxis),
data = ones( (10, 10), int ),
errors = ones( (10,10), int ),
data_type = 'double')
self.assertEqual( counts1.errors().name(), 'errors' )
return
def test_histogram2(self):
"""Histogram.__init__: datasetFromFunction"""
qaxis = axis( 'q', arange( 0, 13, 0.1), 'angstrom**(-1)' )
eaxis = axis( 'e', arange( -50, 50, 1.), 'meV' )
axes = (qaxis,eaxis)
def f1(q,e): return q**2 + e**2
data = datasetFromFunction( f1, (qaxis,eaxis) )
errs = data**2
h = histogram('h', axes, data, errs)
q = 6.; e = 10.
self.assertVectorAlmostEqual( h[ q,e ] , (f1(q,e), f1(q,e)**2 ) )
return
def testClear(self):
"Histogram: h.clear()"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
from numpy import ones
h[(),()] = ones( (3,2) ), ones( (3,2) )
self.assertVectorAlmostEqual( h[1,4] , (1,1) )
h.clear()
self.assertVectorAlmostEqual(
h.data().storage().asList(), [0,0,0,0,0,0] )
self.assertVectorAlmostEqual(
h.errors().storage().asList(), [0,0,0,0,0,0] )
return
def test_histogram1b(self):
"""Histogram.__init__: histogram factory method, keyword 'fromfunction'. 3D
"""
h = histogram(
'h',
[
('x',range(2)),
('y',range(2,4)),
('z',range(4,6)),
],
fromfunction = lambda x,y,z: x+y+z )
return
def testClear(self):
"Histogram: h.clear()"
from histogram import histogram
h = histogram( 'h', [('a', [1,2,3]),('b', [4,5])] )
from numpy import ones
h[(),()] = ones( (3,2) ), ones( (3,2) )
self.assertVectorAlmostEqual( h[1,4] , (1,1) )
h.clear()
self.assertVectorAlmostEqual(
h.data().storage().asList(), [0,0,0,0,0,0] )
self.assertVectorAlmostEqual(
h.errors().storage().asList(), [0,0,0,0,0,0] )
return
def test_histogram4(self):
"""Histogram.__init__: histogram factory method, axes are specified
using a list of (name, values). data and errors are unspecified"""
detIDaxis = "detID", list(range(100))
tofAxis = "tof", arange(1000, 5000, 1.0), "microsecond"
shape = len(detIDaxis[1]), len(tofAxis[1])
from numpy import zeros
h = histogram('h', (detIDaxis, tofAxis))
self.assertVectorAlmostEqual(h[30, 3000.], (0, 0))
return
def test_histogram4(self):
"""Histogram.__init__: histogram factory method, axes are specified
using a list of (name, values). data and errors are unspecified"""
detIDaxis = "detID", range(100)
tofAxis = "tof", arange( 1000, 5000, 1.0), "microsecond"
shape = len(detIDaxis[1]), len(tofAxis[1])
from numpy import zeros
h = histogram('h', (detIDaxis, tofAxis) )
self.assertVectorAlmostEqual( h[ 30, 3000. ], (0,0) )
return
def test_getSliceCopyFromHistogram(self):
'''Histogram.__init__: getSliceCopyFromHistogram'''
h = histogram(
'h',
[
('x', [1, 2, 3]),
('y', [0.1, 0.2, 0.3]),
('z', list(range(0, 1000, 100))),
],
unit='meter',
)
xaxis = axis('x', [1, 2])
yaxis = axis('y', [0.2, 0.3])
s = getSliceCopyFromHistogram('s', [xaxis, yaxis], h)
self.assertVectorEqual(s.shape(), (2, 2, 10))
return
def test_getSliceCopyFromHistogram(self):
'''Histogram.__init__: getSliceCopyFromHistogram'''
h = histogram(
'h',
[
('x', [1,2,3] ),
('y', [0.1,0.2,0.3] ),
('z', range(0,1000,100) ),
],
unit = 'meter',
)
xaxis = axis('x', [1, 2])
yaxis = axis('y', [0.2, 0.3])
s = getSliceCopyFromHistogram( 's', [xaxis, yaxis], h )
self.assertVectorEqual( s.shape(), (2,2,10) )
return
def test_histogram2(self):
"""Histogram.__init__: datasetFromFunction"""
qaxis = axis('q', arange(0, 13, 0.1), 'angstrom**(-1)')
eaxis = axis('e', arange(-50, 50, 1.), 'meV')
axes = (qaxis, eaxis)
def f1(q, e):
return q**2 + e**2
data = datasetFromFunction(f1, (qaxis, eaxis))
errs = data**2
h = histogram('h', axes, data, errs)
q = 6.
e = 10.
self.assertVectorAlmostEqual(h[q, e], (f1(q, e), f1(q, e)**2))
return
def test_histogram1(self):
"""Histogram.__init__: histogram factory method, axes are specified using
instances of Axis"""
detIDaxis = axis( "detID", range(10) )
pixIDaxis = axis( "pixID", range(8) )
axes = [detIDaxis, pixIDaxis]
from numpy import fromfunction
def f(i,j): return i+j
data = fromfunction( f, (detIDaxis.size(), pixIDaxis.size()) )
errs = data**2
h = histogram('h', axes, data, errs)
detID, pixID = 3, 5
self.assertVectorAlmostEqual(
h[detID, pixID], ( f(detID, pixID), f(detID, pixID) ** 2 ) )
return
def test_getattribute(self):
'Histogram: __getattribute__'
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertVectorEqual( h.x, x.binCenters() )
self.assertVectorEqual( h.y, y.binCenters() )
t1 = h.I; t2 = h.data().storage().asNumarray()
t1.shape = t2.shape = -1,
self.assertVectorEqual( t1, t2 )
t1 = h.E2; t2 = h.errors().storage().asNumarray()
t1.shape = t2.shape = -1,
self.assertVectorEqual( t1, t2 )
return
def test_getattribute(self):
'Histogram: __getattribute__'
from histogram import histogram, axis, arange
x = axis( 'x', arange(1., 10., 1.) )
y = axis( 'y', arange(-1., 1., 0.1) )
h = histogram('h', (x,y) )
self.assertVectorEqual( h.x, x.binCenters() )
self.assertVectorEqual( h.y, y.binCenters() )
t1 = h.I; t2 = h.data().storage().asNumarray()
t1.shape = t2.shape = -1,
self.assertVectorEqual( t1, t2 )
t1 = h.E2; t2 = h.errors().storage().asNumarray()
t1.shape = t2.shape = -1,
self.assertVectorEqual( t1, t2 )
return
def test_histogram1(self):
"""Histogram.__init__: histogram factory method, axes are specified using
instances of Axis"""
detIDaxis = axis("detID", list(range(10)))
pixIDaxis = axis("pixID", list(range(8)))
axes = [detIDaxis, pixIDaxis]
from numpy import fromfunction
def f(i, j):
return i + j
data = fromfunction(f, (detIDaxis.size(), pixIDaxis.size()))
errs = data**2
h = histogram('h', axes, data, errs)
detID, pixID = 3, 5
self.assertVectorAlmostEqual(h[detID, pixID],
(f(detID, pixID), f(detID, pixID)**2))
return
def make_anagram_dict(words):
anagramdict = {}
for i in words:
key = get_key(i)
if key not in anagramdict:
anagramdict[key] = [i]
else:
current = anagramdict[key]
current.append(i)
anagramdict[key] = current
longest = sorted(anagramdict.values(), key=len)[-1][0]
print('the longest is', longest)
count = 0
for i, k in anagramdict.items():
if len(i) > count:
count = len(i)
biggest = k
print(histogram(range(6), list(anagramdict.keys()), 30))
return anagramdict, biggest
def setUp(self):
self.sample1 = histogram("This is the text that i will put in the histogram".split())
path_list = []
for dirpath, dirnames, filenames in os.walk(BASE_DIR):
if dirpath not in ignore_dirs:
for files in filenames:
path_list.append(os.path.join(dirpath,files))
dbook_epub = []
zip_epub = []
largest = 0
hmin = 0.0
hmax = 8000000.0
nbins = 100
bin_size = (hmax-hmin)/nbins
bin_center = bin_size/2
h = histogram("h", [('freq', arange(hmin+bin_center,hmax+bin_center,bin_size))])
for files in path_list:
raw_base,raw_ext = os.path.splitext(files)
base = raw_base.lower()
ext = raw_ext.lower()
if '.jpg' == ext:
fsize = os.path.getsize(files)
if fsize > largest:
largest = fsize
bin_value = h[fsize,fsize+0.01].I
bin_value += 1
h[fsize,fsize+0.01] = bin_value ,None
print "Largest File Size = " + str(largest)
#!/home/tgni/ml/env/bin/python3
from histogram import *
def reverse_lookup(d, v):
r = []
for k in d:
if d[k] == v:
r.append(k)
return r
h = histogram('parrot')
for i in range(4):
k = reverse_lookup(h, i)
print k
ax.set_ylabel('count (# of times a water was found at that coordinate')
minorLocator = MultipleLocator(2)
majorLocator = MultipleLocator(10)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_minor_locator(minorLocator)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
for line in ax.get_xticklines() + ax.get_yticklines():
line.set_markeredgewidth(3)
line.set_markersize(10)
for line in ax.xaxis.get_minorticklines():
line.set_markeredgewidth(2)
line.set_markersize(5)
##the next part uses the histogram class (need histogram.py) to color the histogram. Not necessary
from histogram import *
from numpy import random
h1 = histogram(xcoords, bins=500, range=[-20,80])
colors = ['red', 'blue', 'red']
ranges = [[-20,0], [0,43.3], [43.3,80]]
for c, r in zip(colors, ranges):
plt = ax.overlay(h1, range=r, facecolor=c)
pyplot.savefig("ChannelCross-Section.png")
#~ plt.savefig("ChannelCross-Section.png")
#~ plt.show()
if dirpath not in ignore_dirs:
for files in filenames:
file_list.append(os.path.join(dirpath,files))
jpg_counter = 0
png_counter = 0
gif_counter = 0
bad_counter = 0
over_counter = 0
hmin = 0.0
hmax = 2000000.0
nbins = 9
bin_list = ['Thumbnail','XXXS','XXS','XS','S','M','L','XL','XXL']
bin_size = (hmax-hmin)/nbins
bin_center = bin_size/2
h = histogram("h", [('Image Size', arange(hmin+bin_center,hmax+bin_center,bin_size))])
tmb_list = []
bin_number = 1
counter = 0
for files in file_list:
counter += 1
raw_path,raw_name = os.path.split(files)
raw_base,raw_ext = os.path.splitext(raw_name)
base = raw_base.lower()
ext = raw_ext.lower()
pixels, image_type = get_img_size(files)
if pixels > 1000000:
print files
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 18 19:21:38 2019
@author: craigdeng
"""
from histogram import *
import matplotlib.pyplot as plt
from skimage.util import img_as_ubyte
from skimage import data
if __name__ =='__main__':
noisy_image = img_as_ubyte(data.camera())#import image as ubyte
hist, hist_centers = histogram(noisy_image)#apply the function
fig, ax = plt.subplots(ncols=2, figsize=(10, 5))#plot the image and histogram
ax[0].imshow(noisy_image, cmap=plt.cm.gray)
ax[0].axis('off')#adjust original image plot
ax[1].plot(hist_centers, hist, lw=2)
ax[1].set_title('Histogram of grey values')#adjust histogram plot
plt.tight_layout()
import text_tokenizer
import histogram
import hashtable
import Heap
from text_tokenizer import *
from hashtable import *
from histogram import *
from Heap import MaxHeap
# If we subtract the Unix dictionary's keys from our word count dict's keys,
# we can find specialized/jargon words in our corpus or words
# we didn't normalize. We can even use this to refine our regular expressions
# and normalization techniques!
if __name__ == '__main__':
user_input = "humannature.txt"
tokenized_text = text_Parser(user_input)
# TODO are we supposed to rewrite the histogram function to incorporate our hash table?
histogram = histogram(tokenized_text)
max_heap = MaxHeap()
for i in histogram:
max_heap.insert((i, histogram[i]))
print(max_heap.peek(10))
def testSlicing(self):
"Histogram: slicing"
histogram = self._histogram
#get element
self.assertVectorEqual( histogram[1.5,1], (3,3) )
#get slice
from histogram.SlicingInfo import SlicingInfo, all, front, back
slice1 = histogram[SlicingInfo((0.5, 1.5)), SlicingInfo((1,3))]
self.assertVectorEqual( slice1.shape(), (2,2 ) )
print slice1.name()
slice1 = histogram[(0.5, 1.5), (1,3)]
self.assertVectorEqual( slice1.shape(), (2,2 ) )
print slice1.name()
slice2 = histogram[0.5, SlicingInfo((1,3))]
self.assertVectorEqual(slice2.shape(), (2,) )
slice2 = histogram[0.5, (1,3)]
self.assertVectorEqual(slice2.shape(), (2,) )
slice3 = histogram[all, 99]
self.assertVectorEqual(slice3.shape(), (3,) )
slice3 = histogram[(), 99]
self.assertVectorEqual(slice3.shape(), (3,) )
slice3a = slice3[ SlicingInfo( (1.5, back) ) ]
self.assertVectorEqual(slice3a.shape(), (2,) )
slice3a = slice3[ (1.5, None) ]
self.assertVectorEqual(slice3a.shape(), (2,) )
slice4 = histogram[all, all]
self.assertVectorEqual(slice4.shape(), (3,3) )
slice4 = histogram[(), ()]
self.assertVectorEqual(slice4.shape(), (3,3) )
slice5 = histogram[SlicingInfo( (1.5,back) ), all]
self.assertVectorEqual(slice5.shape(), (2,3) )
slice5 = histogram[(1.5, None), ()]
self.assertVectorEqual(slice5.shape(), (2,3) )
slice6 = histogram[SlicingInfo( (front,1.5) ), all]
self.assertVectorEqual(slice6.shape(), (2,3) )
slice6 = histogram[(None,1.5), ()]
self.assertVectorEqual(slice6.shape(), (2,3) )
#getitem with units
from histogram._units import length
meter = length.meter
slice8 = histogram[ {'E':(0.5*meter, 1.5*meter), 'tubeId':(1,3)} ]
self.assertVectorEqual(slice8.shape(), (2,2))
#getitem for 1D histogram
number7 = histogram[ 1.5, () ][3]
#getitem using dictionary
number7 = histogram[ {'E':1.5, 'tubeId':3} ]
number7 = histogram[ 1.5, () ][ {'tubeId':3} ]
# special test case: coordinate = 0
from histogram import histogram, axis
detIDaxis = axis('detID', range(5))
h = histogram( 'h', [detIDaxis])
h[ {'detID':0 } ]
#get slice. units envolved
h = histogram( 'distance',
[ ('x', [1,2,3] ),
],
unit = 'meter', data = [1,2,3] )
h1 = h[(2,3)]
self.assertEqual( h1.unit(), h.unit() )
return
from histogram import *
import sys
# The number of arguments must be at least 2: the name of the file
# with the raw data, and the size of the bin.
f = sys.argv[1]
of = "_hist_" + f
print(f)
s = float(sys.argv[2])
print(s)
histogram(s, f, of)
print("File " + of + " has been generated.")
gp = open('_hist.gp', 'w')
print('set style data histogram ', file=gp)
print('set style histogram cluster gap 0', file=gp)
print('set style fill solid 1.0', file=gp)
print('plot \'' + of + '\' using 1:2 ti col smooth frequency with boxes',
file=gp)
gp.close()
print("File _hist.gp has been generated.")
from histogram import *
import sys
# The number of arguments must be at least 2: the name of the file
# with the raw data, and the size of the bin.
f = sys.argv[1]
of = "_hist_" + f
print(f)
s = float(sys.argv[2])
print(s)
histogram(s,f,of)
print("File "+of+" has been generated.")
gp = open('_hist.gp','w')
print('set style data histogram ',file=gp)
print('set style histogram cluster gap 0',file=gp)
print('set style fill solid 1.0',file=gp)
print('plot \'' + of + '\' using 1:2 ti col smooth frequency with boxes',file=gp)
gp.close()
print("File _hist.gp has been generated.")
