python类chararray()的实例源码

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'))

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'))

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')

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')

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

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'))

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

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

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'))

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

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

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'))

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'))

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)

def setUp(self):
        self.A = np.array('abc1', dtype='c').view(np.chararray)

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)

def setUp(self):
        TestComparisons.setUp(self)
        self.B = np.array([['efg', '123  '],
                           ['051', 'tuv']], np.unicode_).view(np.chararray)

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)

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)

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)

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)

def test_radd(self):
        QA = np.array([['qabc', 'q123'],
                       ['q789', 'qxyz']]).view(np.chararray)
        assert_array_equal(QA, ('q' + self.A))

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")

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]]))

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")

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)

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'))

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)

def setUp(self):
        self.A = np.array('abc1', dtype='c').view(np.chararray)

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)