1. 模块列表
  2. 函数列表
  3. numpy.recfromcsv()

Python numpy 模块，recfromcsv() 实例源码

我们从Python开源项目中，提取了以下19个代码示例，用于说明如何使用numpy.recfromcsv()。

项目：radar    作者：amoose136    | 项目源码 | 文件源码 
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)
项目：radar    作者：amoose136    | 项目源码 | 文件源码 
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)
项目：krpcScripts    作者：jwvanderbeck    | 项目源码 | 文件源码 
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)
项目：krpcScripts    作者：jwvanderbeck    | 项目源码 | 文件源码 
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)
项目：vizgen    作者：uva-graphics    | 项目源码 | 文件源码 
def load_csv_cached(filename='../apps/naive_c_stats.csv', cache={}):
    """
    Get C statistics numpy record list, or return None if the file does not exist.
    """
    if filename in cache:
        return cache[filename]
    if not os.path.exists(filename):
        ans = None
    else:
        ans = numpy.recfromcsv(filename)
    cache[filename] = ans
    return ans
项目：aws-lambda-numpy    作者：vitolimandibhrata    | 项目源码 | 文件源码 
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)
项目：aws-lambda-numpy    作者：vitolimandibhrata    | 项目源码 | 文件源码 
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)
项目：pythonwhat    作者：datacamp    | 项目源码 | 文件源码 
def setUp(self):
        self.data = {
            "DC_PEC": '''
import numpy as np
from urllib.request import urlretrieve; urlretrieve('https://s3.amazonaws.com/assets.datacamp.com/production/course_998/datasets/titanic_sub.csv', 'titanic.csv')
            ''',
            "DC_CODE": '''
file = 'titanic.csv'

# Import file using np.genfromtxt: data
data = np.genfromtxt(file , delimiter = ",", names = True , dtype = None)

# Print out datatype of data
print(type(data))

# Import file using np.recfromcsv: d
d = np.recfromcsv(file)

# Print out first three entries of d
print(d[:3])
            ''',
            "DC_SOLUTION": '''
file = 'titanic.csv'

# Import file using np.genfromtxt: data
data = np.genfromtxt(file , delimiter = ",", names = True , dtype = None)

# Print out datatype of data
print(type(data))

# Import file using np.recfromcsv: d
d = np.recfromcsv(file)

# Print out first three entries of d
print(d[:3])
'''
        }
项目：pythonwhat    作者：datacamp    | 项目源码 | 文件源码 
def test_Pass(self):
        self.data["DC_SCT"] = '''
# Test: Predefined code
predef_msg = "You don't have to change any of the predefined code."
test_object("file", undefined_msg = predef_msg, incorrect_msg = predef_msg)

# [6-21-2016: UPDATED WITH FIX]
# Test: call to np.genfromtxt() and 'data' variable
test_object("data", do_eval = False)
test_function(
        "numpy.genfromtxt",
        not_called_msg = "Make sure you call `np.genfromtxt()`.",
        incorrect_msg = "Did you pass the correct arguments to `np.genfromtxt()`?")

# [6-21-2016: NEEDS FIX]
# Test: Predefined code
test_function("type", do_eval = False, not_called_msg = "error in type", incorrect_msg = "error in type")
test_function("print", not_called_msg = predef_msg, incorrect_msg = predef_msg)

# [6-21-2016: UPDATED WITH FIX]
# Test: call to np.recfromcsv() and 'd' variable
test_object("d", do_eval = False)
test_function(
        "numpy.recfromcsv",
        not_called_msg = "Make sure you call `np.recfromcsv()`.",
        incorrect_msg = "Did you pass the correct arguments to `np.recfromcsv()`?")

# Test: Predefined code
test_function("print", index = 2, incorrect_msg = "error is in print2")

success_msg("Good job!")
        '''
        sct_payload = helper.run(self.data)
        self.assertTrue(sct_payload['correct'])
项目：lambda-numba    作者：rlhotovy    | 项目源码 | 文件源码 
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)
项目：lambda-numba    作者：rlhotovy    | 项目源码 | 文件源码 
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)
项目：ugali    作者：DarkEnergySurvey    | 项目源码 | 文件源码 
def _load(self,filename):
        kwargs = dict(delimiter=',')
        if filename is None: 
            filename = os.path.join(self.DATADIR,"extras/extra_dwarfs.csv")
        self.filename = filename
        raw = np.recfromcsv(filename,**kwargs)

        self.data.resize(len(raw))
        self.data['name'] = raw['name']

        self.data['ra'] = raw['ra']
        self.data['dec'] = raw['dec']

        self.data['glon'],self.data['glat'] = cel2gal(raw['ra'],raw['dec'])
项目：ugali    作者：DarkEnergySurvey    | 项目源码 | 文件源码 
def _load(self,filename):
        kwargs = dict(delimiter=',')
        if filename is None: 
            filename = os.path.join(self.DATADIR,"extras/extra_clusters.csv")
        self.filename = filename
        raw = np.recfromcsv(filename,**kwargs)

        self.data.resize(len(raw))
        self.data['name'] = raw['name']

        self.data['ra'] = raw['ra']
        self.data['dec'] = raw['dec']

        self.data['glon'],self.data['glat'] = cel2gal(raw['ra'],raw['dec'])
项目：deliver    作者：orchestor    | 项目源码 | 文件源码 
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)
项目：deliver    作者：orchestor    | 项目源码 | 文件源码 
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)
项目：deliver    作者：orchestor    | 项目源码 | 文件源码 
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)
项目：pygmm    作者：arkottke    | 项目源码 | 文件源码 
def load_data_file(name, skip_header=None) -> np.recarray:
    """Load a data file.

    Returns
    -------
    data : :class:`numpy.recarray`
       data values

    """
    fname = os.path.join(os.path.dirname(__file__), 'data', name)
    return np.recfromcsv(
        fname, skip_header=skip_header, case_sensitive=True).view(np.recarray)
项目：Alfred    作者：jkachhadia    | 项目源码 | 文件源码 
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)
项目：Alfred    作者：jkachhadia    | 项目源码 | 文件源码 
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)