NumPy Input and Output: fromregex() function
numpy.fromregex() function
The fromregex() function is used to construct an array from a text file, using regular expression parsing.
The returned array is always a structured array, and is constructed from all matches of the regular expression in the file.
Groups in the regular expression are converted to fields of the structured array.
Syntax:
numpy.fromregex(file, regexp, dtype, encoding=None)
Version: 1.15.0
Parameter:
Name | Description | Required / Optional |
---|---|---|
file | File name or file object to read. str or file |
Required |
regexp | Regular expression used to parse the file. Groups in the regular expression correspond to fields in the dtype. str or regexp |
Required |
dtype | Dtype for the structured array. dtype or list of dtypes |
Required |
encoding | Encoding used to decode the inputfile. Does not apply to input streams. str |
Optional |
Returns: output : ndarray
The output array, containing the part of the content of file that was matched by regexp. output is always a structured array.
Raises:
TypeError : When dtype is not a valid dtype for a structured array.
Notes:
Dtypes for structured arrays can be specified in several forms, but all forms specify at least the data type and field name.
For details see doc.structured_arrays.
NumPy.fromregex() method Example-1:
Store data to disk, and load it again:
>>> import numpy as np
>>> x = open('test.dat', 'w')
>>> x.write("1413 foo\n1354 bar\n222 qux")
>>> x.close()
>>> regexp = r"(\d+)\s+(...)" # match [digits, whitespace, anything]
>>> output = np.fromregex('test.dat', regexp,
... [('num', np.int64), ('key', 'S3')])
>>> output
Output:
array([(1413, b'foo'), (1354, b'bar'), ( 222, b'qux')], dtype=[('num', '<i8'), ('key', 'S3')])
NumPy.fromregex() method Example-2:
>>> import numpy as np
>>> x = open('test.dat', 'w')
>>> x.write("1413 foo\n1354 bar\n222 qux")
>>> x.close()
>>> regexp = r"(\d+)\s+(...)" # match [digits, whitespace, anything]
>>> output['num']
Output:
array([1413, 1354, 222], dtype=int64)
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