The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert_(sl1.base is arr)
assert_(sl1.base.base is arr.base)
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert_(sl2.base is arr)
assert_(sl2.base.base is arr.base)
assert_(arr[0, 0] == asbytes('abc')) Example 2
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert_(sl1.base is arr)
assert_(sl1.base.base is arr.base)
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert_(sl2.base is arr)
assert_(sl2.base.base is arr.base)
assert_(arr[0, 0] == asbytes('abc')) Example 3
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert sl1.base is arr
assert sl1.base.base is arr.base
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert sl2.base is arr
assert sl2.base.base is arr.base
assert arr[0, 0] == asbytes('abc') Example 4
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert sl1.base is arr
assert sl1.base.base is arr.base
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert sl2.base is arr
assert sl2.base.base is arr.base
assert arr[0, 0] == asbytes('abc') Example 5
def getHaploidIndividualSequence(self,msa,ind):
"""
Extract individuals "ind" sequence(s) from MSA dictionary
------------------------------------------------------------------------
Parameters:
- msa: dictionary
- ind: dict(indexREP,seqDEscription)
Returns:
- sequence of the individual
"""
# ind: [indID,indexREP,seqDescription]
self.appLogger.debug("getHaploidIndividualSequence(self,msa,ind)")
seqSize=len(msa["{0}_{1}".format(str(1),str(0))][str(0)]['sequence'])
fullInd=None; speciesID=None; tipID=None; tmp=None
fullInd=np.chararray(shape=(1,seqSize), itemsize=1)
speciesID=ind["spID"].strip()
locusID=ind["locID"].strip()
tipID=ind["geneID"].strip()
tmp=list(msa["{0}_{1}".format(str(speciesID), str(locusID))][str(tipID)]['sequence'])
fullInd=[item for item in tmp]
return fullInd Example 6
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert_(sl1.base is arr)
assert_(sl1.base.base is arr.base)
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert_(sl2.base is arr)
assert_(sl2.base.base is arr.base)
assert_(arr[0, 0] == asbytes('abc')) Example 7
def lisa_sig_vals(pvals, quads, threshold):
"""
Produce Moran's I classification based of n
"""
sig = (pvals <= threshold)
lisa_sig = np.empty(len(sig), np.chararray)
for idx, val in enumerate(sig):
if val:
lisa_sig[idx] = map_quads(quads[idx])
else:
lisa_sig[idx] = 'Not significant'
return lisa_sig Example 8
def lisa_sig_vals(pvals, quads, threshold):
"""
Produce Moran's I classification based of n
"""
sig = (pvals <= threshold)
lisa_sig = np.empty(len(sig), np.chararray)
for idx, val in enumerate(sig):
if val:
lisa_sig[idx] = map_quads(quads[idx])
else:
lisa_sig[idx] = 'Not significant'
return lisa_sig Example 9
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert_(sl1.base is arr)
assert_(sl1.base.base is arr.base)
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert_(sl2.base is arr)
assert_(sl2.base.base is arr.base)
assert_(arr[0, 0] == asbytes('abc')) Example 10
def converttochars(pixarray):
#array of chars in increasing darnkess
chars = [' ', '.','-','~','=','!',']','}','#','$','%','&','@',]
procarray = numpy.chararray(pixarray.shape)
k = 0
for row in pixarray:
j = 0
for val in row:
val = 255.0-val
i = ((len(chars)-1)*(val/255.0))
i = int(round(i))
procarray[k][j] = chars[i]
j+=1
k+=1
return procarray
#get array of pixel values Example 11
def teams_to_seat_arr(teams, seats_arr, allocated_seats):
if isinstance(teams.values()[0], int):
# plot the team dist
teams_seats_arr = np.zeros(seats_arr.shape)
else:
teams_seats_arr = np.chararray(seats_arr.shape)
for person, seat in allocated_seats.iteritems():
# get location for the seat
y, x = np.where(seats_arr == seat)
# now get the team for the
team = teams[person]
teams_seats_arr[y, x] = team
return teams_seats_arr Example 12
def test_slice(self):
"""Regression test for https://github.com/numpy/numpy/issues/5982"""
arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']],
dtype='S4').view(np.chararray)
sl1 = arr[:]
assert_array_equal(sl1, arr)
assert_(sl1.base is arr)
assert_(sl1.base.base is arr.base)
sl2 = arr[:, :]
assert_array_equal(sl2, arr)
assert_(sl2.base is arr)
assert_(sl2.base.base is arr.base)
assert_(arr[0, 0] == asbytes('abc')) Example 13
def test_chararray_rstrip(self,level=rlevel):
# Ticket #222
x = np.chararray((1,), 5)
x[0] = asbytes('a ')
x = x.rstrip()
assert_equal(x[0], asbytes('a')) Example 14
def setUp(self):
self.A = np.array([['abc ', '123 '],
['789 ', 'xyz ']]).view(np.chararray)
self.B = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray) Example 15
def setUp(self):
self.A = np.array('abc1', dtype='c').view(np.chararray) Example 16
def setUp(self):
self.A = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray)
self.B = np.array([['efg', '123 '],
['051', 'tuv']]).view(np.chararray) Example 17
def setUp(self):
TestComparisons.setUp(self)
self.B = np.array([['efg', '123 '],
['051', 'tuv']], np.unicode_).view(np.chararray) Example 18
def setUp(self):
self.A = np.array([[' abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']]).view(np.chararray)
self.B = np.array([[sixu(' \u03a3 '), sixu('')],
[sixu('12345'), sixu('MixedCase')],
[sixu('123 \t 345 \0 '), sixu('UPPER')]]).view(np.chararray) Example 19
def setUp(self):
self.A = np.array([[' abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']],
dtype='S').view(np.chararray)
self.B = np.array([[sixu(' \u03a3 '), sixu('')],
[sixu('12345'), sixu('MixedCase')],
[sixu('123 \t 345 \0 '), sixu('UPPER')]]).view(np.chararray) Example 20
def setUp(self):
self.A = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray)
self.B = np.array([['efg', '456'],
['051', 'tuv']]).view(np.chararray) Example 21
def test_add(self):
AB = np.array([['abcefg', '123456'],
['789051', 'xyztuv']]).view(np.chararray)
assert_array_equal(AB, (self.A + self.B))
assert_(len((self.A + self.B)[0][0]) == 6) Example 22
def test_radd(self):
QA = np.array([['qabc', 'q123'],
['q789', 'qxyz']]).view(np.chararray)
assert_array_equal(QA, ('q' + self.A)) Example 23
def test_rmul(self):
A = self.A
for r in (2, 3, 5, 7, 197):
Ar = np.array([[A[0, 0]*r, A[0, 1]*r],
[A[1, 0]*r, A[1, 1]*r]]).view(np.chararray)
assert_array_equal(Ar, (r * self.A))
for ob in [object(), 'qrs']:
try:
ob * A
except ValueError:
pass
else:
self.fail("chararray can only be multiplied by integers") Example 24
def test_mod(self):
"""Ticket #856"""
F = np.array([['%d', '%f'], ['%s', '%r']]).view(np.chararray)
C = np.array([[3, 7], [19, 1]])
FC = np.array([['3', '7.000000'],
['19', '1']]).view(np.chararray)
assert_array_equal(FC, F % C)
A = np.array([['%.3f', '%d'], ['%s', '%r']]).view(np.chararray)
A1 = np.array([['1.000', '1'], ['1', '1']]).view(np.chararray)
assert_array_equal(A1, (A % 1))
A2 = np.array([['1.000', '2'], ['3', '4']]).view(np.chararray)
assert_array_equal(A2, (A % [[1, 2], [3, 4]])) Example 25
def test_rmod(self):
assert_(("%s" % self.A) == str(self.A))
assert_(("%r" % self.A) == repr(self.A))
for ob in [42, object()]:
try:
ob % self.A
except TypeError:
pass
else:
self.fail("chararray __rmod__ should fail with "
"non-string objects") Example 26
def test_empty_indexing():
"""Regression test for ticket 1948."""
# Check that indexing a chararray with an empty list/array returns an
# empty chararray instead of a chararray with a single empty string in it.
s = np.chararray((4,))
assert_(s[[]].size == 0) Example 27
def test_chararray_rstrip(self,level=rlevel):
# Ticket #222
x = np.chararray((1,), 5)
x[0] = asbytes('a ')
x = x.rstrip()
assert_equal(x[0], asbytes('a')) Example 28
def setUp(self):
self.A = np.array([['abc ', '123 '],
['789 ', 'xyz ']]).view(np.chararray)
self.B = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray) Example 29
def setUp(self):
self.A = np.array('abc1', dtype='c').view(np.chararray) Example 30
def setUp(self):
self.A = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray)
self.B = np.array([['efg', '123 '],
['051', 'tuv']]).view(np.chararray) Example 31
def setUp(self):
TestComparisons.setUp(self)
self.B = np.array([['efg', '123 '],
['051', 'tuv']], np.unicode_).view(np.chararray) Example 32
def setUp(self):
self.A = np.array([[' abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']]).view(np.chararray)
self.B = np.array([[sixu(' \u03a3 '), sixu('')],
[sixu('12345'), sixu('MixedCase')],
[sixu('123 \t 345 \0 '), sixu('UPPER')]]).view(np.chararray) Example 33
def setUp(self):
self.A = np.array([[' abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']],
dtype='S').view(np.chararray)
self.B = np.array([[sixu(' \u03a3 '), sixu('')],
[sixu('12345'), sixu('MixedCase')],
[sixu('123 \t 345 \0 '), sixu('UPPER')]]).view(np.chararray) Example 34
def setUp(self):
self.A = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray)
self.B = np.array([['efg', '456'],
['051', 'tuv']]).view(np.chararray) Example 35
def test_add(self):
AB = np.array([['abcefg', '123456'],
['789051', 'xyztuv']]).view(np.chararray)
assert_array_equal(AB, (self.A + self.B))
assert_(len((self.A + self.B)[0][0]) == 6) Example 36
def test_radd(self):
QA = np.array([['qabc', 'q123'],
['q789', 'qxyz']]).view(np.chararray)
assert_array_equal(QA, ('q' + self.A)) Example 37
def test_rmul(self):
A = self.A
for r in (2, 3, 5, 7, 197):
Ar = np.array([[A[0, 0]*r, A[0, 1]*r],
[A[1, 0]*r, A[1, 1]*r]]).view(np.chararray)
assert_array_equal(Ar, (r * self.A))
for ob in [object(), 'qrs']:
try:
ob * A
except ValueError:
pass
else:
self.fail("chararray can only be multiplied by integers") Example 38
def test_mod(self):
"""Ticket #856"""
F = np.array([['%d', '%f'], ['%s', '%r']]).view(np.chararray)
C = np.array([[3, 7], [19, 1]])
FC = np.array([['3', '7.000000'],
['19', '1']]).view(np.chararray)
assert_array_equal(FC, F % C)
A = np.array([['%.3f', '%d'], ['%s', '%r']]).view(np.chararray)
A1 = np.array([['1.000', '1'], ['1', '1']]).view(np.chararray)
assert_array_equal(A1, (A % 1))
A2 = np.array([['1.000', '2'], ['3', '4']]).view(np.chararray)
assert_array_equal(A2, (A % [[1, 2], [3, 4]])) Example 39
def test_rmod(self):
assert_(("%s" % self.A) == str(self.A))
assert_(("%r" % self.A) == repr(self.A))
for ob in [42, object()]:
try:
ob % self.A
except TypeError:
pass
else:
self.fail("chararray __rmod__ should fail with "
"non-string objects") Example 40
def test_empty_indexing():
"""Regression test for ticket 1948."""
# Check that indexing a chararray with an empty list/array returns an
# empty chararray instead of a chararray with a single empty string in it.
s = np.chararray((4,))
assert_(s[[]].size == 0) Example 41
def __init__(self, filename):
self.filename = filename
self.xyzfile = open(self.filename, 'r')
self.offsets = []
self.n_atoms = self._n_atoms()
self.n_frames = self._n_frames()
self.box_size = np.empty([self.n_frames, 3], dtype=np.float)
self.atom_names = np.chararray([self.n_frames, self.n_atoms, 1], itemsize=3)
self.coords = np.empty([self.n_frames, self.n_atoms, 3], dtype=np.float)
self.read_all_frames() Example 42
def echantillonnage (fichier):
data = np.genfromtxt(fichier,delimiter=',')
clen, rlen = data.shape
new_tab=np.chararray([clen,rlen],itemsize=25)
for c in range(0,rlen):
petit=str(c)+'_1'
moyen=str(c)+'_2'
grand=str(c)+'_3'
#----------------- sur le rang --------------------------
data_sort=np.sort(data[:,c])
x=len(data_sort)/3.
tiers=data_sort[int(x)]
deux_tiers=data_sort[2*int(x)]
#-----------------------------------------------------------
for l in range(0,clen):
if data[l,c]<tiers:
new_tab[l,c]=petit
elif data[l,c]<deux_tiers:
new_tab[l,c]=moyen
else :
new_tab[l,c]=grand
return new_tab Example 43
def echantillonnage_glucose (fichier):
data = np.genfromtxt(fichier,delimiter=',')
clen, rlen = data.shape
rlen=rlen+1
diab= np.genfromtxt('glucose_a_traiter.csv',delimiter=',')
new_tab=np.chararray([clen,rlen],itemsize=25)
for c in range(0,rlen-1):
petit=str(c)+'_1'
moyen=str(c)+'_2'
grand=str(c)+'_3'
#----------------- sur le rang --------------------------
data_sort=np.sort(data[:,c])
x=len(data_sort)/3.
tiers=data_sort[int(x)]
deux_tiers=data_sort[2*int(x)]
#-----------------------------------------------------------
for l in range(0,clen):
if data[l,c]<tiers:
new_tab[l,c]=petit
elif data[l,c]<deux_tiers:
new_tab[l,c]=moyen
else :
new_tab[l,c]=grand
for l in range (0,clen):
if diab[0,l]<6.5:
if diab[1,l]==0 and diab[2,l]==0 :
new_tab[l,-1]=petit
else :
new_tab[l,-1]=moyen
else : new_tab[l,-1]=grand
return new_tab Example 44
def fill_matrix(matrix, width, value='n/a'):
if matrix.shape[0] < width:
nraters = matrix.shape[1]
nas = np.chararray((1, nraters), itemsize=len(value))
nas[:] = value
matrix = np.vstack(tuple([matrix] + [nas] * (width - matrix.shape[0])))
return matrix Example 45
def one_hot_encoding_sequences(seqs): CHARS = 'acgt' CHARS_COUNT = len(CHARS) maxlen = max(map(len, seqs)) res = numpy.zeros((len(seqs), CHARS_COUNT * maxlen), dtype=numpy.uint8) for si, seq in enumerate(seqs): seqlen = len(seq) arr = numpy.chararray((seqlen,), buffer=seq) for ii, char in enumerate(CHARS): res[si][ii*seqlen:(ii+1)*seqlen][arr == char] = 1 return res
Example 46
def one_hot_encoding_sequences(seqs, sequenceLength): """ input: genome sequences output: one_hot encoded sequence array """ le = preprocessing.LabelEncoder() one_hot_sequences = [] le.fit_transform(['a','t','g','c']) for si, seq in enumerate(seqs): seqlen = len(seq) arr = np.chararray((seqlen,), buffer=seq) a = le.transform(arr) a = np.array(a) b = np.zeros((len(a), 4)) b[np.arange(len(a)), a] = 1 #b = np.array(b) b = b.transpose() if b.shape[1] == sequenceLength: one_hot_sequences.append(b) return one_hot_sequences #print one_hot_encoding_sequences(['atgctgc','gctatgc']) #print numpy.arange(8).reshape((4,8/4), order = 'F')
Example 47
def write_kmers(kmers, filename):
char_kmers = np.chararray(kmers.shape)
for _char, _int in six.iteritems(ALPHABET):
char_kmers[kmers == _int] = _char
with open(filename, 'w') as fh:
for i, kmer in enumerate(char_kmers):
print('>%d' % i, file=fh)
print(kmer.tostring().decode(), file=fh) Example 48
def test_chararray_rstrip(self,level=rlevel):
# Ticket #222
x = np.chararray((1,), 5)
x[0] = asbytes('a ')
x = x.rstrip()
assert_equal(x[0], asbytes('a')) Example 49
def setUp(self):
self.A = np.array([['abc ', '123 '],
['789 ', 'xyz ']]).view(np.chararray)
self.B = np.array([['abc', '123'],
['789', 'xyz']]).view(np.chararray) Example 50
def setUp(self):
self.A = np.array('abc1', dtype='c').view(np.chararray) 