#----------------------------------------------------------------------------- # Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors. # All rights reserved. # # The full license is in the file LICENSE.txt, distributed with this software. #----------------------------------------------------------------------------- ''' Provide properties for various visual attrributes. ''' #----------------------------------------------------------------------------- # Boilerplate #----------------------------------------------------------------------------- import logging # isort:skip log = logging.getLogger(__name__) #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- # Standard library imports import base64 import datetime # lgtm [py/import-and-import-from] import re from io import BytesIO # External imports import PIL.Image # Bokeh imports from ...util.serialization import convert_datetime_type from .. import enums from .auto import Auto from .bases import Property from .container import Seq, Tuple from .datetime import Datetime, TimeDelta from .either import Either from .enum import Enum from .numeric import Float, Int from .primitive import String from .regex import Regex #----------------------------------------------------------------------------- # Globals and constants #----------------------------------------------------------------------------- __all__ = ( 'DashPattern', 'FontSize', 'HatchPatternType', 'Image', 'MinMaxBounds', 'MarkerType', ) #----------------------------------------------------------------------------- # General API #----------------------------------------------------------------------------- [docs]class DashPattern(Either): ''' Accept line dash specifications. Express patterns that describe line dashes. ``DashPattern`` values can be specified in a variety of ways: * An enum: "solid", "dashed", "dotted", "dotdash", "dashdot" * a tuple or list of integers in the `HTML5 Canvas dash specification style`_. Note that if the list of integers has an odd number of elements, then it is duplicated, and that duplicated list becomes the new dash list. To indicate that dashing is turned off (solid lines), specify the empty list []. .. _HTML5 Canvas dash specification style: http://www.w3.org/html/wg/drafts/2dcontext/html5_canvas/#dash-list ''' _dash_patterns = { "solid": [], "dashed": [6], "dotted": [2,4], "dotdash": [2,4,6,4], "dashdot": [6,4,2,4], } def __init__(self, default=[], help=None): types = Enum(enums.DashPattern), Regex(r"^(\d+(\s+\d+)*)?$"), Seq(Int) super().__init__(*types, default=default, help=help) def __str__(self): return self.__class__.__name__ def transform(self, value): value = super().transform(value) if isinstance(value, str): try: return self._dash_patterns[value] except KeyError: return [int(x) for x in value.split()] else: return value def _sphinx_type(self): return self._sphinx_prop_link() [docs]class FontSize(String): _font_size_re = re.compile(r"^[0-9]+(.[0-9]+)?(%|em|ex|ch|ic|rem|vw|vh|vi|vb|vmin|vmax|cm|mm|q|in|pc|pt|px)$", re.I) def validate(self, value, detail=True): super().validate(value, detail) if isinstance(value, str): if len(value) == 0: msg = "" if not detail else "empty string is not a valid font size value" raise ValueError(msg) elif self._font_size_re.match(value) is None: msg = "" if not detail else "%r is not a valid font size value" % value raise ValueError(msg) class HatchPatternType(Either): ''' Accept built-in fill hatching specifications. Accepts either "long" names, e.g. "horizontal-wave" or the single letter abbreviations, e.g. "v" ''' def __init__(self, default=[], help=None): types = Enum(enums.HatchPattern), Enum(enums.HatchPatternAbbreviation) super().__init__(*types, default=default, help=help) def __str__(self): return self.__class__.__name__ def _sphinx_type(self): return self._sphinx_prop_link() [docs]class Image(Property): ''' Accept image file types, e.g PNG, JPEG, TIFF, etc. This property can be configured with: * A string filename to be loaded with ``PIL.Image.open`` * An RGB(A) NumPy array, will be converted to PNG * A ``PIL.Image.Image`` object In all cases, the image data is serialized as a Base64 encoded string. ''' def validate(self, value, detail=True): import numpy as np valid = False if value is None or isinstance(value, (str, PIL.Image.Image)): valid = True if isinstance(value, np.ndarray): valid = value.dtype == "uint8" and len(value.shape) == 3 and value.shape[2] in (3, 4) if not valid: msg = "" if not detail else "invalid value: %r; allowed values are string filenames, PIL.Image.Image instances, or RGB(A) NumPy arrays" % value raise ValueError(msg) def transform(self, value): if value is None: return None import numpy as np if isinstance(value, np.ndarray): value = PIL.Image.fromarray(value) if isinstance(value, str): value = PIL.Image.open(value) if isinstance(value, PIL.Image.Image): out = BytesIO() fmt = value.format or "PNG" value.save(out, fmt) return "data:image/%s;base64," % fmt.lower() + base64.b64encode(out.getvalue()).decode('ascii') raise ValueError("Could not transform %r" % value) [docs]class MinMaxBounds(Either): ''' Accept (min, max) bounds tuples for use with Ranges. Bounds are provided as a tuple of ``(min, max)`` so regardless of whether your range is increasing or decreasing, the first item should be the minimum value of the range and the second item should be the maximum. Setting min > max will result in a ``ValueError``. Setting bounds to None will allow your plot to pan/zoom as far as you want. If you only want to constrain one end of the plot, you can set min or max to ``None`` e.g. ``DataRange1d(bounds=(None, 12))`` ''' def __init__(self, accept_datetime=False, default='auto', help=None): if accept_datetime: types = ( Auto, Tuple(Float, Float), Tuple(TimeDelta, TimeDelta), Tuple(Datetime, Datetime), ) else: types = ( Auto, Tuple(Float, Float), Tuple(TimeDelta, TimeDelta), ) super().__init__(*types, default=default, help=help) def validate(self, value, detail=True): super().validate(value, detail) if value is None: return True if value[0] is None or value[1] is None: return True value = list(value) # make sure the values are timestamps for comparison if isinstance(value[0], datetime.datetime): value[0] = convert_datetime_type(value[0]) if isinstance(value[1], datetime.datetime): value[1] = convert_datetime_type(value[1]) if value[0] >= value[1]: msg = "" if not detail else "Invalid bounds: maximum smaller than minimum. Correct usage: bounds=(min, max)" raise ValueError(msg) return True def _sphinx_type(self): return self._sphinx_prop_link() [docs]class MarkerType(Enum): ''' ''' def __init__(self, **kw): super().__init__(enums.MarkerType, **kw) #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Code #-----------------------------------------------------------------------------