Python numpy.recfromcsv() Examples

The following are 30 code examples of numpy.recfromcsv(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function .
Example #1
Source File: pncglobal2cmaq.py    From pseudonetcdf with GNU Lesser General Public License v3.0 6 votes vote down vote up 
def geticbcnames(inpath):
    import io
    import re
    import numpy as np
    with open(inpath) as infile:
        intxt = infile.read()
    result = re.findall("(TYPE_\S+\s*=\s*(('[^\n]+',\s*)+))", intxt)
    names = result[0][1].strip()[1:-1].replace("'", '') + '\n'
    nflds = len(names.split(':'))
    if nflds == 16:
        fmts = 'S16 f c f c f c f S16 f c c b b b b'.split()
    else:
        fmts = 'S16 f c f c f c f S16 f c b b b b'.split()
    data = re.sub('\s+', '', result[1][1])[:-1]
    data = re.sub("'", '', data)
    data = re.sub(",", '\n', data)
    data = (names + data).encode()
    rdata = np.recfromcsv(io.BytesIO(data), delimiter=b':', dtype=fmts)
    icbc_sur = []
    for row in rdata:
        if row['icbc_sur'] != b'':
            icbc_sur.append(row['icbc_sur'].decode().strip())
    icbc_sur = set(icbc_sur)
    result = icbc_sur.union([s.decode().strip() for s in rdata['spc']])
    return list(result)
Example #2
Source File: spot_setup_cmf_lumped.py    From spotpy with MIT License 6 votes vote down vote up 
def __init__(self):
        # Load data from file using numpy magic
        data = np.recfromcsv('cmf_data/fulda_climate.csv', encoding='utf-8')

        def bstr2date(bs):
            """Helper function to convert date byte string to datetime object"""
            return datetime.datetime.strptime(bs, '%d.%m.%Y')

        # Get begin, step and end from the date column
        self.begin = bstr2date(data.date[0])
        self.step = bstr2date(data.date[1]) - self.begin
        self.end = bstr2date(data.date[-1])

        def a2ts(a):
            """Converts an array column to a timeseries"""
            return cmf.timeseries.from_array(self.begin, self.step, a)

        self.P = a2ts(data.prec)
        self.T = a2ts(data.tmean)
        self.Tmin = a2ts(data.tmin)
        self.Tmax = a2ts(data.tmax)
        self.Q = a2ts(data.q)
Example #3
Source File: test_io.py    From Computable with MIT License 6 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
Example #4
Source File: test_io.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([(1,5,-1,0), (2,8,-1,1), (3,3,-2,3)], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([(1,5,0), (2,8,1), (3,3,3)], dtype=dtyp)
        assert_equal(test, control)
Example #5
Source File: test_io.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', int), ('B', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', int), ('B', int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', int), ('b', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', int), ('b', float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)

        #gh-10394
        data = TextIO('color\n"red"\n"blue"')
        test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
        control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
        assert_equal(test.dtype, control.dtype)
        assert_equal(test, control)
Example #6
Source File: test_io.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #7
Source File: test_io.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([[1,5,-1,0], [2,8,-1,1], [3,3,-2,3]], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([[1,5,0], [2,8,1], [3,3,3]], dtype=dtyp)
        assert_equal(test, control)
Example #8
Source File: test_io.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', np.int), ('b', np.float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
Example #9
Source File: test_io.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', np.int), ('B', np.int)])
            self.assertTrue(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #10
Source File: test_io.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('E1','i4'),('E2','i4'),('E3','i2'),('N', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([[1,5,-1,0], [2,8,-1,1], [3,3,-2,3]], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('E1','i4'),('E2','i4'),('N', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([[1,5,0], [2,8,1], [3,3,3]], dtype=dtyp)
        assert_equal(test, control)
Example #11
Source File: test_io.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', np.int), ('b', np.float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
Example #12
Source File: test_io.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([[1,5,-1,0], [2,8,-1,1], [3,3,-2,3]], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([[1,5,0], [2,8,1], [3,3,3]], dtype=dtyp)
        assert_equal(test, control)
Example #13
Source File: test_io.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', np.int), ('b', np.float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
Example #14
Source File: test_io.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', np.int), ('B', np.int)])
            self.assertTrue(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #15
Source File: test_io.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #16
Source File: test_io.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', int), ('B', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', int), ('B', int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', int), ('b', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', int), ('b', float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)

        #gh-10394
        data = TextIO('color\n"red"\n"blue"')
        test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
        control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
        assert_equal(test.dtype, control.dtype)
        assert_equal(test, control)
Example #17
Source File: test_io.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #18
Source File: test_io.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([(1,5,-1,0), (2,8,-1,1), (3,3,-2,3)], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([(1,5,0), (2,8,1), (3,3,3)], dtype=dtyp)
        assert_equal(test, control)
Example #19
Source File: test_io.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', int), ('B', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', int), ('B', int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', int), ('b', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', int), ('b', float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)

        #gh-10394
        data = TextIO('color\n"red"\n"blue"')
        test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
        control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
        assert_equal(test.dtype, control.dtype)
        assert_equal(test, control)
Example #20
Source File: test_io.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #21
Source File: test_io.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([(1,5,-1,0), (2,8,-1,1), (3,3,-2,3)], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([(1,5,0), (2,8,1), (3,3,3)], dtype=dtyp)
        assert_equal(test, control)
Example #22
Source File: test_io.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', int), ('B', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', int), ('B', int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', int), ('b', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', int), ('b', float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)

        #gh-10394
        data = TextIO('color\n"red"\n"blue"')
        test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
        control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
        assert_equal(test.dtype, control.dtype)
        assert_equal(test, control)
Example #23
Source File: test_io.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #24
Source File: test_io.py    From keras-lambda with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([[1,5,-1,0], [2,8,-1,1], [3,3,-2,3]], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([[1,5,0], [2,8,1], [3,3,3]], dtype=dtyp)
        assert_equal(test, control)
Example #25
Source File: test_io.py    From keras-lambda with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', np.int), ('b', np.float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
Example #26
Source File: __init__.py    From permute with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def load(f):
    r"""Load a data file located in the data directory.

    Parameters
    ----------
    f : string
        File name.

    Returns
    -------
    x : array like
        Data loaded from permute.data_dir.
    """
    return np.recfromcsv(_os.path.join(data_dir, f), delimiter=",", encoding=None)
Example #27
Source File: test_io.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', int), ('B', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', int), ('B', int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', int), ('b', int)])
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', int), ('b', float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        assert_(isinstance(test, np.recarray))
        assert_equal(test, control)

        #gh-10394
        data = TextIO('color\n"red"\n"blue"')
        test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
        control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
        assert_equal(test.dtype, control.dtype)
        assert_equal(test, control)
Example #28
Source File: test_io.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_recfromcsv(self):
        with temppath(suffix='.txt') as path:
            path = Path(path)
            with path.open('w') as f:
                f.write(u'A,B\n0,1\n2,3')

            kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
            test = np.recfromcsv(path, dtype=None, **kwargs)
            control = np.array([(0, 1), (2, 3)],
                               dtype=[('A', int), ('B', int)])
            assert_(isinstance(test, np.recarray))
            assert_equal(test, control)
Example #29
Source File: test_io.py    From lambda-packs with MIT License 5 votes vote down vote up 
def test_dtype_with_converters_and_usecols(self):
        dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
        dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
        dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
        conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             names=None, converters=conv)
        control = np.rec.array([[1,5,-1,0], [2,8,-1,1], [3,3,-2,3]], dtype=dtyp)
        assert_equal(test, control)
        dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
        test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
                             usecols=(0,1,3), names=None, converters=conv)
        control = np.rec.array([[1,5,0], [2,8,1], [3,3,3]], dtype=dtyp)
        assert_equal(test, control)
Example #30
Source File: test_io.py    From lambda-packs with MIT License 5 votes vote down vote up 
def test_recfromcsv(self):
        #
        data = TextIO('A,B\n0,1\n2,3')
        kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
        test = np.recfromcsv(data, dtype=None, **kwargs)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('A', np.int), ('B', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,N/A')
        test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
        control = ma.array([(0, 1), (2, -1)],
                           mask=[(False, False), (False, True)],
                           dtype=[('A', np.int), ('B', np.int)])
        assert_equal(test, control)
        assert_equal(test.mask, control.mask)
        assert_equal(test.A, [0, 2])
        #
        data = TextIO('A,B\n0,1\n2,3')
        test = np.recfromcsv(data, missing_values='N/A',)
        control = np.array([(0, 1), (2, 3)],
                           dtype=[('a', np.int), ('b', np.int)])
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)
        #
        data = TextIO('A,B\n0,1\n2,3')
        dtype = [('a', np.int), ('b', np.float)]
        test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
        control = np.array([(0, 1), (2, 3)],
                           dtype=dtype)
        self.assertTrue(isinstance(test, np.recarray))
        assert_equal(test, control)