#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
CSV Tabular Data Input / Output
===============================
Defines various input / output objects for CSV tabular data files:
- :func:`read_spectral_data_from_csv_file`
- :func:`read_spds_from_csv_file`
- :func:`write_spds_to_csv_file`
"""
from __future__ import division, unicode_literals
try:
from collections import OrderedDict
except ImportError:
from ordereddict import OrderedDict
import csv
from colour.colorimetry import SpectralPowerDistribution
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013 - 2015 - Colour Developers'
__license__ = 'New BSD License - http://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = ['read_spectral_data_from_csv_file',
'read_spds_from_csv_file',
'write_spds_to_csv_file']
[docs]def read_spectral_data_from_csv_file(path,
delimiter=',',
fields=None,
default=0):
"""
Reads the spectral data from given CSV file in the following form:
390, 4.15003E-04, 3.68349E-04, 9.54729E-03
395, 1.05192E-03, 9.58658E-04, 2.38250E-02
400, 2.40836E-03, 2.26991E-03, 5.66498E-02
...
830, 9.74306E-07, 9.53411E-08, 0.00000
and returns it as an *OrderedDict* of *dict* as follows:
OrderedDict([
('field', {'wavelength': 'value', ..., 'wavelength': 'value'}),
...,
('field', {'wavelength': 'value', ..., 'wavelength': 'value'})])
Parameters
----------
path : unicode
Absolute CSV file path.
delimiter : unicode, optional
CSV file content delimiter.
fields : array_like, optional
CSV file spectral data fields names. If no value is provided the
first line of the file will be used as spectral data fields names.
default : numeric, optional
Default value for fields row with missing value.
Returns
-------
OrderedDict
CSV file content.
Raises
------
RuntimeError
If the CSV spectral data file doesn't define the appropriate fields.
Notes
-----
- A CSV spectral data file should define at least define two fields:
one for the wavelengths and one for the associated values of one
spectral power distribution.
- If no value is provided for the fields names, the first line of the
file will be used as spectral data fields names.
Examples
--------
>>> import os
>>> from pprint import pprint
>>> csv_file = os.path.join(
... os.path.dirname(__file__),
... 'tests',
... 'resources',
... 'colorchecker_n_ohta.csv')
>>> spds_data = read_spectral_data_from_csv_file(csv_file)
>>> pprint(list(spds_data.keys()))
['1',
'2',
'3',
'4',
'5',
'6',
'7',
'8',
'9',
'10',
'11',
'12',
'13',
'14',
'15',
'16',
'17',
'18',
'19',
'20',
'21',
'22',
'23',
'24']
"""
with open(path, 'rU') as csv_file:
reader = csv.DictReader(csv_file,
delimiter=str(delimiter),
fieldnames=fields)
if len(reader.fieldnames) == 1:
raise RuntimeError(('A CSV spectral data file should define '
'the following fields: '
'("wavelength", "field 1", ..., "field n")!'))
wavelength = reader.fieldnames[0]
fields = reader.fieldnames[1:]
data = OrderedDict(zip(fields, ({} for _ in range(len(fields)))))
for line in reader:
for field in fields:
try:
value = float(line[field])
except ValueError:
value = default
data[field][float(line[wavelength])] = value
return data
[docs]def read_spds_from_csv_file(path,
delimiter=',',
fields=None,
default=0):
"""
Reads the spectral data from given CSV file and return its content as an
*OrderedDict* of
:class:`colour.colorimetry.spectrum.SpectralPowerDistribution` classes.
Parameters
----------
path : unicode
Absolute CSV file path.
delimiter : unicode, optional
CSV file content delimiter.
fields : array_like, optional
CSV file spectral data fields names. If no value is provided the
first line of the file will be used for as spectral data fields names.
default : numeric
Default value for fields row with missing value.
Returns
-------
OrderedDict
:class:`colour.colorimetry.spectrum.SpectralPowerDistribution`
classes of given CSV file.
Examples
--------
>>> import os
>>> from pprint import pprint
>>> csv_file = os.path.join(
... os.path.dirname(__file__),
... 'tests',
... 'resources',
... 'colorchecker_n_ohta.csv')
>>> spds = read_spds_from_csv_file(csv_file)
>>> pprint(tuple(spds.items())) # doctest: +ELLIPSIS
(('1',
<...SpectralPowerDistribution object at 0x...>),
('2',
<...SpectralPowerDistribution object at 0x...>),
('3',
<...SpectralPowerDistribution object at 0x...>),
('4',
<...SpectralPowerDistribution object at 0x...>),
('5',
<...SpectralPowerDistribution object at 0x...>),
('6',
<...SpectralPowerDistribution object at 0x...>),
('7',
<...SpectralPowerDistribution object at 0x...>),
('8',
<...SpectralPowerDistribution object at 0x...>),
('9',
<...SpectralPowerDistribution object at 0x...>),
('10',
<...SpectralPowerDistribution object at 0x...>),
('11',
<...SpectralPowerDistribution object at 0x...>),
('12',
<...SpectralPowerDistribution object at 0x...>),
('13',
<...SpectralPowerDistribution object at 0x...>),
('14',
<...SpectralPowerDistribution object at 0x...>),
('15',
<...SpectralPowerDistribution object at 0x...>),
('16',
<...SpectralPowerDistribution object at 0x...>),
('17',
<...SpectralPowerDistribution object at 0x...>),
('18',
<...SpectralPowerDistribution object at 0x...>),
('19',
<...SpectralPowerDistribution object at 0x...>),
('20',
<...SpectralPowerDistribution object at 0x...>),
('21',
<...SpectralPowerDistribution object at 0x...>),
('22',
<...SpectralPowerDistribution object at 0x...>),
('23',
<...SpectralPowerDistribution object at 0x...>),
('24',
<...SpectralPowerDistribution object at 0x...>))
"""
data = read_spectral_data_from_csv_file(path,
delimiter,
fields,
default)
spds = OrderedDict(((key, SpectralPowerDistribution(key, value))
for key, value in data.items()))
return spds
[docs]def write_spds_to_csv_file(spds,
path,
delimiter=',',
fields=None):
"""
Writes the given spectral power distributions to given CSV file.
Parameters
----------
spds : dict
Spectral power distributions to write.
path : unicode
Absolute CSV file path.
delimiter : unicode, optional
CSV file content delimiter.
fields : array_like, optional
CSV file spectral data fields names. If no value is provided the
order of fields will be the one defined by the sorted spectral power
distributions *dict*.
Returns
-------
bool
Definition success.
Raises
------
RuntimeError
If the given spectral power distributions have different shapes.
"""
if len(spds) != 1:
shapes = [spd.shape for spd in spds.values()]
if not all(shape == shapes[0] for shape in shapes):
raise RuntimeError(('Cannot write spectral power distributions '
'with different shapes to CSV file!'))
wavelengths = tuple(spds.values())[0].wavelengths
with open(path, 'w') as csv_file:
fields = list(fields) if fields is not None else sorted(spds.keys())
writer = csv.DictWriter(csv_file,
delimiter=str(delimiter),
fieldnames=['wavelength'] + fields)
# Python 2.7.x / 3.4.x only.
# writer.writeheader()
writer.writerow(dict((name, name) for name in writer.fieldnames))
for wavelength in wavelengths:
row = {'wavelength': wavelength}
row.update(
dict((field, spds[field][wavelength]) for field in fields))
writer.writerow(row)
return True
Colour 0.3