colour.read_sds_from_csv_file#

colour.read_sds_from_csv_file(path: str | PathLike, **kwargs: Any) → Dict[str, SpectralDistribution][source]#

Read spectral data from the specified CSV file and convert its content to a dict of colour.SpectralDistribution class instances.

Parameters:

path (str | PathLike) – CSV file path.
kwargs (Any) – Keywords arguments passed to numpy.genfromtxt() definition.

Returns:

dict of colour.SpectralDistribution class instances.

Return type:

dict

Raises:

IOError – If the file cannot be read.

Examples

>>> from colour.utilities import numpy_print_options
>>> import os
>>> csv_file = os.path.join(
...     os.path.dirname(__file__),
...     "tests",
...     "resources",
...     "colorchecker_n_ohta.csv",
... )
>>> sds = read_sds_from_csv_file(csv_file)
>>> print(tuple(sds.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 numpy_print_options(suppress=True):
...     sds["1"]
...
SpectralDistribution([[380.   ,   0.048],
                      [385.   ,   0.051],
                      [390.   ,   0.055],
                      [395.   ,   0.06 ],
                      [400.   ,   0.065],
                      [405.   ,   0.068],
                      [410.   ,   0.068],
                      [415.   ,   0.067],
                      [420.   ,   0.064],
                      [425.   ,   0.062],
                      [430.   ,   0.059],
                      [435.   ,   0.057],
                      [440.   ,   0.055],
                      [445.   ,   0.054],
                      [450.   ,   0.053],
                      [455.   ,   0.053],
                      [460.   ,   0.052],
                      [465.   ,   0.052],
                      [470.   ,   0.052],
                      [475.   ,   0.053],
                      [480.   ,   0.054],
                      [485.   ,   0.055],
                      [490.   ,   0.057],
                      [495.   ,   0.059],
                      [500.   ,   0.061],
                      [505.   ,   0.062],
                      [510.   ,   0.065],
                      [515.   ,   0.067],
                      [520.   ,   0.07 ],
                      [525.   ,   0.072],
                      [530.   ,   0.074],
                      [535.   ,   0.075],
                      [540.   ,   0.076],
                      [545.   ,   0.078],
                      [550.   ,   0.079],
                      [555.   ,   0.082],
                      [560.   ,   0.087],
                      [565.   ,   0.092],
                      [570.   ,   0.1  ],
                      [575.   ,   0.107],
                      [580.   ,   0.115],
                      [585.   ,   0.122],
                      [590.   ,   0.129],
                      [595.   ,   0.134],
                      [600.   ,   0.138],
                      [605.   ,   0.142],
                      [610.   ,   0.146],
                      [615.   ,   0.15 ],
                      [620.   ,   0.154],
                      [625.   ,   0.158],
                      [630.   ,   0.163],
                      [635.   ,   0.167],
                      [640.   ,   0.173],
                      [645.   ,   0.18 ],
                      [650.   ,   0.188],
                      [655.   ,   0.196],
                      [660.   ,   0.204],
                      [665.   ,   0.213],
                      [670.   ,   0.222],
                      [675.   ,   0.231],
                      [680.   ,   0.242],
                      [685.   ,   0.251],
                      [690.   ,   0.261],
                      [695.   ,   0.271],
                      [700.   ,   0.282],
                      [705.   ,   0.294],
                      [710.   ,   0.305],
                      [715.   ,   0.318],
                      [720.   ,   0.334],
                      [725.   ,   0.354],
                      [730.   ,   0.372],
                      [735.   ,   0.392],
                      [740.   ,   0.409],
                      [745.   ,   0.42 ],
                      [750.   ,   0.436],
                      [755.   ,   0.45 ],
                      [760.   ,   0.462],
                      [765.   ,   0.465],
                      [770.   ,   0.448],
                      [775.   ,   0.432],
                      [780.   ,   0.421]],
                     SpragueInterpolator,
                     {},
                     Extrapolator,
                     {'method': 'Constant', 'left': None, 'right': None})

colour.read_sds_from_csv_file#

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