colour.read_sds_from_csv_file¶
-
colour.read_sds_from_csv_file(path, delimiter=', ', fields=None, default=0)[source]¶ Reads the spectral data from given CSV file and return its content as an OrderedDict of
colour.SpectralDistributionclasses.- 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
colour.SpectralDistributionclasses of given CSV file.- Return type
OrderedDict
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]], interpolator=SpragueInterpolator, interpolator_args={}, extrapolator=Extrapolator, extrapolator_args={...})