diff options
Diffstat (limited to 'numpy/lib/io.py')
| -rw-r--r-- | numpy/lib/io.py | 111 |
1 files changed, 40 insertions, 71 deletions
diff --git a/numpy/lib/io.py b/numpy/lib/io.py index 255c5a7f5..239d0808e 100644 --- a/numpy/lib/io.py +++ b/numpy/lib/io.py @@ -19,8 +19,9 @@ from _datasource import DataSource from _compiled_base import packbits, unpackbits from _iotools import LineSplitter, NameValidator, StringConverter, \ - ConverterError, ConverterLockError, \ - _is_string_like, has_nested_fields, flatten_dtype + ConverterError, ConverterLockError, ConversionWarning, \ + _is_string_like, has_nested_fields, flatten_dtype, \ + easy_dtype _file = file _string_like = _is_string_like @@ -872,8 +873,8 @@ def fromregex(file, regexp, dtype): def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, converters=None, missing='', missing_values=None, usecols=None, names=None, excludelist=None, deletechars=None, autostrip=False, - case_sensitive=True, unpack=None, usemask=False, loose=True, - invalid_raise=False): + case_sensitive=True, defaultfmt="f%i", unpack=None, + usemask=False, loose=True, invalid_raise=True): """ Load data from a text file, with missing values handled as specified. @@ -930,6 +931,8 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, deletechars : str, optional A string combining invalid characters that must be deleted from the names. + defaultfmt : str, optional + A format used to define default field names, such as "f%i" or "f_%02i". autostrip : bool, optional Whether to automatically strip white spaces from the variables. case_sensitive : {True, False, 'upper', 'lower'}, optional @@ -945,7 +948,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, invalid_raise : bool, optional If True, an exception is raised if an inconsistency is detected in the number of columns. - If False, a warning is emitted but the incriminating lines are skipped. + If False, a warning is emitted and the offending lines are skipped. Returns ------- @@ -1063,9 +1066,6 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, nbcols = len(usecols or first_values) # Check the names and overwrite the dtype.names if needed - if dtype is not None: - dtype = np.dtype(dtype) - dtypenames = getattr(dtype, 'names', None) if names is True: names = validate_names([_.strip() for _ in first_values]) first_line = '' @@ -1073,10 +1073,9 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, names = validate_names([_.strip() for _ in names.split(',')]) elif names: names = validate_names(names) - elif dtypenames: - dtype.names = validate_names(dtypenames) - if names and dtypenames: - dtype.names = names + # Get the dtype + if dtype is not None: + dtype = easy_dtype(dtype, defaultfmt=defaultfmt, names=names) # If usecols is a list of names, convert to a list of indices if usecols: @@ -1213,7 +1212,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, raise ValueError(errmsg) # Issue a warning ? else: - warnings.warn(errmsg) + warnings.warn(errmsg, ConversionWarning) # Convert each value according to the converter: # We want to modify the list in place to avoid creating a new one... @@ -1234,26 +1233,28 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, data = rows if dtype is None: # Get the dtypes from the types of the converters - coldtypes = [conv.type for conv in converters] + column_types = [conv.type for conv in converters] # Find the columns with strings... - strcolidx = [i for (i, v) in enumerate(coldtypes) + strcolidx = [i for (i, v) in enumerate(column_types) if v in (type('S'), np.string_)] # ... and take the largest number of chars. for i in strcolidx: - coldtypes[i] = "|S%i" % max(len(row[i]) for row in data) + column_types[i] = "|S%i" % max(len(row[i]) for row in data) # if names is None: # If the dtype is uniform, don't define names, else use '' base = set([c.type for c in converters if c._checked]) - if len(base) == 1: (ddtype, mdtype) = (list(base)[0], np.bool) else: - ddtype = [('', dt) for dt in coldtypes] - mdtype = [('', np.bool) for dt in coldtypes] + ddtype = [(defaultfmt % i, dt) + for (i, dt) in enumerate(column_types)] + if usemask: + mdtype = [(defaultfmt % i, np.bool) + for (i, dt) in enumerate(column_types)] else: - ddtype = zip(names, coldtypes) - mdtype = zip(names, [np.bool] * len(coldtypes)) + ddtype = zip(names, column_types) + mdtype = zip(names, [np.bool] * len(column_types)) output = np.array(data, dtype=ddtype) if usemask: outputmask = np.array(masks, dtype=mdtype) @@ -1331,11 +1332,8 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, return output.squeeze() -def ndfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, - converters=None, missing='', missing_values=None, usecols=None, - names=None, excludelist=None, deletechars=None, autostrip=False, - case_sensitive=True, unpack=None, loose=True, - invalid_raise=False): + +def ndfromtxt(fname, **kwargs): """ Load ASCII data stored in a file and return it as a single array. @@ -1347,21 +1345,11 @@ def ndfromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, numpy.genfromtxt : generic function. """ - kwargs = dict(dtype=dtype, comments=comments, delimiter=delimiter, - skiprows=skiprows, converters=converters, - missing=missing, missing_values=missing_values, - usecols=usecols, unpack=unpack, names=names, - excludelist=excludelist, deletechars=deletechars, - case_sensitive=case_sensitive, usemask=False, - autostrip=autostrip, loose=loose, invalid_raise=invalid_raise) + kwargs['usemask'] = False return genfromtxt(fname, **kwargs) -def mafromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, - converters=None, missing='', missing_values=None, usecols=None, - names=None, excludelist=None, deletechars=None, autostrip=False, - case_sensitive=True, unpack=None, loose=True, - invalid_raise=False): +def mafromtxt(fname, **kwargs): """ Load ASCII data stored in a text file and return a masked array. @@ -1372,22 +1360,11 @@ def mafromtxt(fname, dtype=float, comments='#', delimiter=None, skiprows=0, numpy.genfromtxt : generic function to load ASCII data. """ - kwargs = dict(dtype=dtype, comments=comments, delimiter=delimiter, - skiprows=skiprows, converters=converters, - missing=missing, missing_values=missing_values, - usecols=usecols, unpack=unpack, names=names, - excludelist=excludelist, deletechars=deletechars, - case_sensitive=case_sensitive, autostrip=autostrip, - loose=loose, invalid_raise=invalid_raise, - usemask=True) + kwargs['usemask'] = True return genfromtxt(fname, **kwargs) -def recfromtxt(fname, dtype=None, comments='#', delimiter=None, skiprows=0, - converters=None, missing='', missing_values=None, - usecols=None, unpack=None, names=None, autostrip=False, - excludelist=None, deletechars=None, case_sensitive=True, - loose=True, invalid_raise=False, usemask=False): +def recfromtxt(fname, **kwargs): """ Load ASCII data from a file and return it in a record array. @@ -1407,13 +1384,8 @@ def recfromtxt(fname, dtype=None, comments='#', delimiter=None, skiprows=0, array will be determined from the data. """ - kwargs = dict(dtype=dtype, comments=comments, delimiter=delimiter, - skiprows=skiprows, converters=converters, - missing=missing, missing_values=missing_values, - usecols=usecols, unpack=unpack, names=names, - excludelist=excludelist, deletechars=deletechars, - case_sensitive=case_sensitive, usemask=usemask, - loose=loose, autostrip=autostrip, invalid_raise=invalid_raise) + kwargs.update(dtype=kwargs.get('dtype', None)) + usemask = kwargs.get('usemask', False) output = genfromtxt(fname, **kwargs) if usemask: from numpy.ma.mrecords import MaskedRecords @@ -1423,12 +1395,7 @@ def recfromtxt(fname, dtype=None, comments='#', delimiter=None, skiprows=0, return output -def recfromcsv(fname, dtype=None, comments='#', skiprows=0, - converters=None, missing='', missing_values=None, - usecols=None, unpack=None, names=True, - excludelist=None, deletechars=None, case_sensitive='lower', - loose=True, autostrip=False, invalid_raise=False, - usemask=False): +def recfromcsv(fname, **kwargs): """ Load ASCII data stored in a comma-separated file. @@ -1443,13 +1410,15 @@ def recfromcsv(fname, dtype=None, comments='#', skiprows=0, numpy.genfromtxt : generic function to load ASCII data. """ - kwargs = dict(dtype=dtype, comments=comments, delimiter=",", - skiprows=skiprows, converters=converters, - missing=missing, missing_values=missing_values, - usecols=usecols, unpack=unpack, names=names, - excludelist=excludelist, deletechars=deletechars, - case_sensitive=case_sensitive, usemask=usemask, - loose=loose, autostrip=autostrip, invalid_raise=invalid_raise) + case_sensitive = kwargs.get('case_sensitive', "lower") or "lower" + names = kwargs.get('names', True) + if names is None: + names = True + kwargs.update(dtype=kwargs.get('update', None), + delimiter=kwargs.get('delimiter', ",") or ",", + names=names, + case_sensitive=case_sensitive) + usemask = kwargs.get("usemask", False) output = genfromtxt(fname, **kwargs) if usemask: from numpy.ma.mrecords import MaskedRecords |