# coding=utf-8
"""Class for representing geometry colored with data according to legend parameters."""
from __future__ import division
import uuid
from ladybug_geometry.geometry2d import Vector2D, Point2D, Ray2D, LineSegment2D, \
Polyline2D, Arc2D, Polygon2D, Mesh2D
from ladybug_geometry.geometry3d import Vector3D, Point3D, Ray3D, Plane, LineSegment3D, \
Polyline3D, Arc3D, Face3D, Mesh3D, Polyface3D, Sphere, Cone, Cylinder
from ladybug_geometry.bounding import bounding_box
from ladybug_geometry.dictutil import geometry_dict_to_object
from ladybug.legend import Legend, LegendParameters, LegendParametersCategorized
from ladybug.graphic import GraphicContainer
from ladybug.datatype.base import DataTypeBase
from ._base import DISPLAY_MODES, _VisualizationBase
from .typing import int_in_range
import ladybug_display.svg as svg
GEOMETRY_UNION = (
Vector2D, Point2D, Ray2D, LineSegment2D, Polyline2D, Arc2D, Polygon2D,
Mesh2D, Vector3D, Point3D, Ray3D, Plane, LineSegment3D,
Polyline3D, Arc3D, Face3D, Mesh3D, Polyface3D, Sphere, Cone, Cylinder
)
[docs]
class AnalysisGeometry(_VisualizationBase):
"""An object where geometry is colored with data.
Multiple data sets for different metrics can correspond to the same geometry.
Args:
identifier: Text string for a unique object ID. Must be less than 100
characters and not contain spaces or special characters.
geometry: A list of ladybug-geometry objects that is aligned with the values in
the input data_sets. The length of this list should usually be equal to the
total number of values in each data_set, indicating that each geometry
gets a single color. Alternatively, if all of the geometry objects are
meshes, the number of values in the data can be equal to the total number
of faces across the meshes or the total number of vertices across the meshes.
data_sets: A list of VisualizationData objects representing the data sets
that are associated with the input geometry.
active_data: An integer to denote which of the input data_sets should be
displayed by default. (Default: 0).
display_mode: Text to indicate the display mode (surface, wireframe, etc.).
Choose from the following. (Default: Surface).
* Surface
* SurfaceWithEdges
* Wireframe
* Points
hidden: A boolean to note whether the geometry is hidden by default and
must be un-hidden to be visible in the 3D scene. (Default: False).
Properties:
* identifier
* display_name
* geometry
* data_sets
* active_data
* display_mode
* hidden
* min_point
* max_point
* matching_method
* user_data
"""
__slots__ = (
'_geometry', '_data_sets', '_active_data', '_display_mode', '_hidden',
'_min_point', '_max_point', '_possible_lengths', '_matching_method')
T_FORMABLE_2D = (Point2D, Ray2D, LineSegment2D, Polyline2D, Arc2D, Polygon2D, Mesh2D)
def __init__(self, identifier, geometry, data_sets,
active_data=0, display_mode='Surface', hidden=False):
"""Initialize AnalysisGeometry."""
_VisualizationBase.__init__(self, identifier) # process the identifier
if not isinstance(geometry, tuple):
geometry = tuple(geometry)
if not isinstance(data_sets, tuple):
data_sets = tuple(data_sets)
self._possible_lengths = self._possible_data_lengths(geometry)
self._matching_method = None
for dat in data_sets:
self._check_data_set(dat)
self._geometry = geometry
self._data_sets = data_sets
self.active_data = active_data
self.display_mode = display_mode
self.hidden = hidden
self._min_point = None
self._max_point = None
[docs]
@classmethod
def from_dict(cls, data):
"""Create an AnalysisGeometry from a dictionary.
Args:
data: A python dictionary in the following format
.. code-block:: python
{
"type": "AnalysisGeometry",
"identifier": "", # unique object identifier
"geometry": [], # list of geometry objects
"data_sets": [], # list of data sets associated with the geometry
"active_data": 0, # integer for the index of the active data set
"display_mode": "Surface", # text for the display mode of the data
"hidden": True # boolean for whether the layer is hidden by default
}
"""
# check the type key
assert data['type'] == 'AnalysisGeometry', \
'Expected AnalysisGeometry, Got {}.'.format(data['type'])
# re-serialize the geometry and data sets
geos = tuple(geometry_dict_to_object(geo) for geo in data['geometry'])
dts = tuple(VisualizationData.from_dict(dt) for dt in data['data_sets'])
# re-serialize the data type and unit
act_dt = data['active_data'] if 'active_data' in data else 0
d_mode = data['display_mode'] if 'display_mode' in data else 'Surface'
hidden = False if 'hidden' not in data else data['hidden']
new_obj = cls(data['identifier'], geos, dts, act_dt, d_mode, hidden)
if 'display_name' in data and data['display_name'] is not None:
new_obj.display_name = data['display_name']
if 'user_data' in data and data['user_data'] is not None:
new_obj.user_data = data['user_data']
return new_obj
@property
def geometry(self):
"""Get a tuple of geometry objects assigned to this AnalysisGeometry."""
return self._geometry
@property
def data_sets(self):
"""Get a tuple of VisualizationData assigned to the AnalysisGeometry."""
return self._data_sets
@property
def active_data(self):
"""Get or set an integer for the index of data set that is actively displaying.
"""
return self._active_data
@active_data.setter
def active_data(self, value):
self._active_data = int_in_range(
value, 0, len(self._data_sets) - 1, 'active_data')
@property
def display_mode(self):
"""Get or set text to indicate the display mode."""
return self._display_mode
@display_mode.setter
def display_mode(self, value):
clean_input = value.lower()
for key in DISPLAY_MODES:
if key.lower() == clean_input:
value = key
break
else:
raise ValueError(
'display_mode {} is not recognized.\nChoose from the '
'following:\n{}'.format(value, DISPLAY_MODES))
self._display_mode = value
@property
def hidden(self):
"""Get or set a boolean for whether the geometry is hidden by default."""
return self._hidden
@hidden.setter
def hidden(self, value):
self._hidden = bool(value)
@property
def min_point(self):
"""A Point3D for the minimum bounding box vertex around all of the geometry."""
if self._min_point is None:
self._calculate_min_max()
return self._min_point
@property
def max_point(self):
"""A Point3D for the maximum bounding box vertex around all of the geometry."""
if self._max_point is None:
self._calculate_min_max()
return self._max_point
@property
def matching_method(self):
"""Get text for the method by which the data is matched to the geometry.
This will be one of the following.
* geometries - One value is assigned for each geometry
* faces - One value is assigned per each face of the Mesh
* vertices - One value is assigned per each vertex of the Mesh
"""
return self._matching_method
@property
def user_data(self):
"""Get or set an optional dictionary for additional meta data for this object.
This will be None until it has been set. All keys and values of this
dictionary should be of a standard Python type to ensure correct
serialization of the object to/from JSON (eg. str, float, int, list, dict)
"""
return self._user_data
@user_data.setter
def user_data(self, value):
if value is not None:
assert isinstance(value, dict), 'Expected dictionary for ' \
'object user_data. Got {}.'.format(type(value))
self._user_data = value
[docs]
def add_data_set(self, data, insert_index=None):
"""Add a data set to this AnalysisGeometry object.
Args:
data: A VisualizationData object to be added to this AnalysisGeometry.
insert_index: An integer for the index at which the data should be
inserted. If None, the data will be appended to the end. (Default: None).
"""
self._check_data_set(data)
if insert_index is None:
self._data_sets = self._data_sets + (data,)
else:
ds_list = list(self._data_sets)
ds_list.insert(insert_index, data)
self._data_sets = tuple(ds_list)
[docs]
def remove_data_set(self, data_index):
"""Remove a data set from this AnalysisGeometry object.
Args:
data_index: An integer for the data index to be removed.
"""
assert data_index < len(self._data_sets), 'data_index ({}) must be less than ' \
'the number of items in the data_sets ({}).'.format(
data_index, len(self._data_sets))
ds_list = list(self._data_sets)
ds_list.pop(data_index)
self._data_sets = tuple(ds_list)
if self._active_data == len(self._data_sets):
self._active_data = len(self._data_sets) - 1
[docs]
def graphic_container(self, data_index=None, min_point=None, max_point=None):
"""Get a Ladybug GraphicContainer object, which can be used to draw legends.
Args:
data_index: Integer for the index of the data set for which a
GraphicContainer will be returned. If None, the active_data set
will be used. (Default: None).
min_point: An optional Point3D to denote the minimum bounding box
for the graphic container. If None, this object's own min_point
will be used, which corresponds to the bounding box around
the geometry. (Default: None).
max_point: An optional Point3D to denote the maximum bounding box
for the graphic container. If None, this object's own max_point
will be used, which corresponds to the bounding box around
the geometry. (Default: None).
"""
# ensure that min and max points always make sense
min_point = self.min_point if min_point is None else min_point
max_point = self.max_point if max_point is None else max_point
# return the Graphic Container for the correct data set
data_index = self.active_data if data_index is None else data_index
return self.data_sets[data_index].graphic_container(min_point, max_point)
[docs]
def move(self, moving_vec):
"""Move this AnalysisGeometry along a vector.
Args:
moving_vec: A ladybug_geometry Vector3D with the direction and distance
to move the AnalysisGeometry.
"""
new_geo = []
moving_vec_2d = Vector2D(moving_vec.x, moving_vec.y)
for geo in self._geometry:
try: # most likely a 3D object
new_geo.append(geo.move(moving_vec))
except Exception: # possibly a 2D object
if isinstance(geo, self.T_FORMABLE_2D):
new_geo.append(geo.move(moving_vec_2d))
else: # object like a vector for which the transform is meaningless
new_geo.append(geo)
self._geometry = tuple(new_geo)
[docs]
def rotate_xy(self, angle, origin):
"""Rotate this AnalysisGeometry counterclockwise in the world XY plane.
Args:
angle: An angle in degrees.
origin: A ladybug_geometry Point3D for the origin around which the
object will be rotated.
"""
new_geo = []
origin_2d = Point2D(origin.x, origin.y)
for geo in self._geometry:
try:
new_geo.append(geo.rotate_xy(angle, origin))
except Exception: # possibly a 2D object
if isinstance(geo, self.T_FORMABLE_2D):
new_geo.append(geo.rotate(angle, origin_2d))
else: # object like a vector for which the transform is meaningless
new_geo.append(geo)
self._geometry = tuple(new_geo)
[docs]
def scale(self, factor, origin=None):
"""Scale this AnalysisGeometry by a factor from an origin point.
Args:
factor: A number representing how much the object should be scaled.
origin: A ladybug_geometry Point3D representing the origin from which
to scale. If None, it will be scaled from the World origin (0, 0, 0).
"""
new_geo = []
origin_2d = Point2D(origin.x, origin.y) if origin is not None else None
for geo in self._geometry:
try:
new_geo.append(geo.scale(factor, origin))
except Exception: # possibly a 2D object
if isinstance(geo, self.T_FORMABLE_2D):
new_geo.append(geo.scale(factor, origin_2d))
else: # object like a vector for which the transform is meaningless
new_geo.append(geo)
self._geometry = tuple(new_geo)
[docs]
def to_dict(self):
"""Get AnalysisGeometry as a dictionary."""
base = {
'type': 'AnalysisGeometry',
'identifier': self.identifier,
'geometry': [geo.to_dict() for geo in self.geometry],
'data_sets': [ds.to_dict() for ds in self.data_sets],
'active_data': self.active_data,
'display_mode': self.display_mode,
'hidden': self.hidden
}
if self._display_name is not None:
base['display_name'] = self.display_name
if self.user_data is not None:
base['user_data'] = self.user_data
return base
def _check_data_set(self, data_set):
"""Check that a data set is compatible with the geometry."""
assert isinstance(data_set, VisualizationData), 'Expected VisualizationData ' \
'for AnalysisGeometry. Got {}.'.format(type(data_set))
if self._matching_method is None: # first data set to be matched
pl = self._possible_lengths
if pl[1] == 0 and pl[2] == 0:
assert len(data_set) == pl[0], 'Expected number of data set values ' \
'({}) to align with the number of geometries ({}).'.format(
len(data_set.values), pl[0])
else:
assert len(data_set) in pl, 'Expected number of data set values ' \
'({}) to align with the number of geometries ({}), the number of ' \
'geometry faces ({}), or the number of geometry vertices ' \
'({}).'.format(len(data_set.values), pl[0], pl[1], pl[2])
self._matching_method = self._matching_type(data_set)[0]
else:
assert self._matching_type(data_set)[0] == self._matching_method, \
'Expected number of data set values ({}) to align with the number ' \
'of {} ({}).'.format(len(data_set.values), self._matching_method,
self._matching_type(data_set)[1])
def _matching_type(self, dat_set):
"""Get text and number of values for the method by which data and geometry match.
Args:
dat_set: A data set which will have its length evaluated in relation to
this object's geometry.
"""
geo_len, face_len, vert_len = self._possible_lengths
if len(dat_set) == geo_len:
return 'geometries', geo_len
if len(dat_set) == face_len:
return 'faces', face_len
if len(dat_set) == vert_len:
return 'vertices', vert_len
def _calculate_min_max(self):
"""Calculate maximum and minimum Point3D for this object."""
self._min_point, self._max_point = bounding_box(self.geometry)
@staticmethod
def _possible_data_lengths(geometry):
"""Get the acceptable data lengths given the input geometry."""
geo_count_0, geo_count_1, geo_count_2 = len(geometry), 0, 0
for geo in geometry:
if isinstance(geo, (Mesh2D, Mesh3D)):
geo_count_1 += len(geo.faces)
geo_count_2 += len(geo.vertices)
else:
assert isinstance(geo, GEOMETRY_UNION), 'Expected ladybug geometry ' \
'object for AnalysisGeometry. Got {}.'.format(type(geo))
return (geo_count_0, geo_count_1, geo_count_2)
def __copy__(self):
new_d = tuple(data.duplicate() for data in self.data_sets)
new_obj = AnalysisGeometry(
self.identifier, self.geometry, new_d, self.active_data,
self.display_mode, self.hidden)
new_obj._display_name = self._display_name
new_obj._user_data = None if self.user_data is None else self.user_data.copy()
return new_obj
def __len__(self):
"""Return number of data sets on the object."""
return len(self.data_sets)
def __getitem__(self, key):
"""Return one of the data sets."""
return self.data_sets[key]
def __iter__(self):
"""Iterate through the data sets."""
return iter(self.data_sets)
[docs]
def ToString(self):
"""Overwrite .NET ToString."""
return self.__repr__()
def __repr__(self):
"""AnalysisGeometry representation."""
return 'Analysis Geometry: {}'.format(self.display_name)
[docs]
class VisualizationData(VisualizationMetaData):
"""Represents a data set for visualization with legend parameters and data type.
Args:
values: A list of numerical values that will be used to generate the
visualization colors.
legend_parameters: An Optional LegendParameters object to override default
parameters of the legend. None indicates that default legend parameters
will be used. (Default: None).
data_type: Optional DataType from the ladybug datatype subpackage (ie.
Temperature()) , which will be used to assign default legend properties.
If None, the legend associated with this object will contain no units
unless a unit below is specified. (Default: None).
unit: Optional text string for the units of the values. (ie. "C"). If None
or empty, the default units of the data_type will be used. If no data
type is specified in this case, this will simply be an empty
string. (Default: None).
Properties:
* values
* legend_parameters
* legend
* data_type
* unit
* value_colors
* user_data
"""
__slots__ = ('_legend',)
def __init__(self, values, legend_parameters=None, data_type=None, unit=None):
"""Initialize VisualizationData."""
# set up the legend using the values and legend parameters
VisualizationMetaData.__init__(self, legend_parameters, data_type, unit)
# assign defaults to the legend parameter using the values and the data type
self._legend = Legend(values, legend_parameters)
if data_type is not None:
assert isinstance(data_type, DataTypeBase), \
'data_type should be a ladybug DataType. Got {}'.format(type(data_type))
if self.legend_parameters.is_title_default:
self._unit = unit if unit else data_type.units[0]
data_type.is_unit_acceptable(self._unit)
self.legend_parameters.title = self._unit if \
self.legend_parameters.vertical \
else '{} ({})'.format(data_type.name, self._unit)
if data_type.unit_descr is not None and \
self.legend_parameters.ordinal_dictionary is None and not \
isinstance(self.legend_parameters, LegendParametersCategorized):
self.legend_parameters.ordinal_dictionary = data_type.unit_descr
sorted_keys = sorted(data_type.unit_descr.keys())
if self.legend.is_min_default:
self.legend_parameters._min = sorted_keys[0]
if self.legend.is_max_default:
self.legend_parameters._max = sorted_keys[-1]
assert self.legend_parameters._min <= self.legend_parameters._max, \
'Legend min is greater than legend max. {} > {}.'.format(
self.legend_parameters._min, self.legend_parameters._max)
if self.legend_parameters.is_segment_count_default:
try: # try to set the number of segments to align with ordinal text
min_i = sorted_keys.index(self.legend_parameters.min)
max_i = sorted_keys.index(self.legend_parameters.max)
self.legend_parameters.segment_count = \
len(sorted_keys[min_i:max_i + 1])
except IndexError:
pass
elif unit and self.legend_parameters.is_title_default:
assert isinstance(unit, str), \
'Expected string for unit. Got {}.'.format(type(unit))
self.legend_parameters.title = unit
[docs]
@classmethod
def from_dict(cls, data):
"""Create VisualizationData from a dictionary.
Args:
data: A python dictionary in the following format
.. code-block:: python
{
"type": "VisualizationData",
"values": [0, 10],
"legend_parameters": {}, # optional LegendParameter specification
"data_type": {}, # optional DataType object
"unit": "C" # optional text for the units
}
"""
# check the type key
assert data['type'] == 'VisualizationData', \
'Expected VisualizationData, Got {}.'.format(data['type'])
# re-serialize the legend parameters
legend_parameters = None
if 'legend_parameters' in data and data['legend_parameters'] is not None:
if data['legend_parameters']['type'] == 'LegendParametersCategorized':
legend_parameters = LegendParametersCategorized.from_dict(
data['legend_parameters'])
else:
legend_parameters = LegendParameters.from_dict(data['legend_parameters'])
# re-serialize the data type and unit
data_type = None
if 'data_type' in data and data['data_type'] is not None:
data_type = DataTypeBase.from_dict(data['data_type'])
unit = data['unit'] if 'unit' in data else None
new_obj = cls(data['values'], legend_parameters, data_type, unit)
if 'user_data' in data and data['user_data'] is not None:
new_obj.user_data = data['user_data']
return new_obj
@property
def values(self):
"""Get the values assigned to the data set."""
return self._legend.values
@property
def legend_parameters(self):
"""Get the legend parameters assigned to this data set."""
return self._legend._legend_par
@property
def legend(self):
"""Get the legend assigned to this data set."""
return self._legend
@property
def value_colors(self):
"""Get a List of colors associated with the assigned values."""
return self._legend.value_colors
[docs]
def graphic_container(self, min_point, max_point):
"""Get a Ladybug GraphicContainer object, which can be used to a draw legend.
Args:
min_point: An optional Point3D to denote the minimum bounding box
for the graphic container.
max_point: An optional Point3D to denote the maximum bounding box
for the graphic container.
"""
return GraphicContainer(
self.values, min_point, max_point, self._legend_parameters,
self._data_type, self._unit)
[docs]
def convert_to_unit(self, unit, convert_min_max=False):
"""Convert the VisualizationData to the input unit.
Note that the VisualizationData must have a data_type and unit assigned
to it in order for this method to run successfully and not raise an exception.
Args:
unit: Text indicating the units to which the value should be
converted (eg. 'kWh/m2'). See ladybug.datatype.UNITS for
a dictionary containing all acceptable units for each data type.
convert_min_max: Boolean to note whether the min and max of the
LegendParameters should also have their units converted, which
may or may not be desirable depending on when this min and max
was originally set. (Default: False).
"""
assert self._data_type is not None and self._unit is not None, \
'VisualizationData must have a data_type and unit assigned in ' \
'order to perform unit conversions.'
new_values = self._data_type.to_unit(self.values, unit, self._unit)
self._change_units(new_values, unit, convert_min_max)
[docs]
def convert_to_ip(self, convert_min_max=False):
"""Convert the VisualizationData to IP units.
Note that the VisualizationData must have a data_type and unit assigned
to it in order for this method to run successfully and not raise an exception.
Args:
convert_min_max: Boolean to note whether the min and max of the
LegendParameters should also have their units converted, which
may or may not be desirable depending on when this min and max
was originally set. (Default: False).
"""
assert self._data_type is not None and self._unit is not None, \
'VisualizationData must have a data_type and unit assigned in ' \
'order to perform unit conversions.'
new_values, new_unit = self._data_type.to_ip(self.values, self._unit)
self._change_units(new_values, new_unit, convert_min_max)
[docs]
def convert_to_si(self, convert_min_max=False):
"""Convert the VisualizationData to SI units.
Note that the VisualizationData must have a data_type and unit assigned
to it in order for this method to run successfully and not raise an exception.
Args:
convert_min_max: Boolean to note whether the min and max of the
LegendParameters should also have their units converted, which
may or may not be desirable depending on when this min and max
was originally set. (Default: False).
"""
assert self._data_type is not None and self._unit is not None, \
'VisualizationData must have a data_type and unit assigned in ' \
'order to perform unit conversions.'
new_values, new_unit = self._data_type.to_si(self.values, self._unit)
self._change_units(new_values, new_unit, convert_min_max)
def _change_units(self, new_values, new_unit, convert_min_max=False):
if self._legend.is_min_default:
self._legend_parameters.min = None
elif convert_min_max:
self._legend_parameters.min = \
self._data_type.to_unit(
[self._legend_parameters.min], new_unit, self._unit)[0]
if self._legend.is_max_default:
self._legend_parameters.max = None
elif convert_min_max:
self._legend_parameters.max = \
self._data_type.to_unit(
[self._legend_parameters.max], new_unit, self._unit)[0]
self._unit = new_unit
self._legend = Legend(new_values, self._legend_parameters)
self.legend_parameters.title = new_unit if self.legend_parameters.vertical \
else '{} ({})'.format(self._data_type.name, new_unit)
[docs]
def to_dict(self):
"""Get visualization data as a dictionary."""
base = {
'type': 'VisualizationData',
'values': self.values
}
if self._legend_parameters is not None:
base['legend_parameters'] = self._legend_parameters.to_dict()
if self.data_type is not None:
base['data_type'] = self.data_type.to_dict()
if self.unit:
base['unit'] = self.unit
if self.user_data is not None:
base['user_data'] = self.user_data
return base
[docs]
def to_svg(self, width=800, height=600):
"""Get the legend of the visualization data as an editable SVG object.
Casting this SVG object to string will give the file contents of a SVG.
The legend will be rendered using the properties2d of the LegendParameters,
which is suitable for exporting the legend as a standalone graphic.
Args:
width: The screen width in pixels, which is needed to interpret
dimensions specified in the percent of the screen. (Default: 800).
height: The screen height in pixels, which is needed to interpret
dimensions specified in the percent of the screen. (Default: 600).
"""
# get the legend properties of this object
legend = self.legend
l_par = legend.legend_parameters
or_x, or_y, sh, sw, th = legend._pixel_dims_2d(width, height)
elements = [] # list to hold all of the elements of the legend
# draw a border around the whole legend bar
lh = sh * l_par.segment_count if l_par.vertical else sh
lw = sw if l_par.vertical else sw * l_par.segment_count
if l_par.continuous_legend:
if l_par.vertical:
lh = lh - sh
else:
lw = lw - sw
bound_rect = svg.Rect(x=or_x, y=or_y, height=lh, width=lw, fill='none')
bound_rect.stroke = 'black'
bound_rect.stroke_width = 1
# translate the colors of the legend to SVG shapes
colors = list(reversed(legend.segment_colors)) \
if l_par.vertical else legend.segment_colors
if not l_par.continuous_legend: # output segments as colored rectangles
for i, col in enumerate(colors):
rect = svg.Rect(x=or_x, y=or_y, height=sh, width=sw, fill=col.to_hex())
move = svg.Translate(x=0, y=sh * i) if l_par.vertical else \
svg.Translate(x=sw * i, y=0)
rect.transform = [move]
elements.append(rect)
else:
gradient = svg.LinearGradient()
gradient.gradientUnits = 'objectBoundingBox'
gradient.id = 'legend_gradient_{}'.format(str(uuid.uuid4())[:8])
if l_par.vertical:
gradient.gradientTransform = [svg.Rotate(90)]
stop_colors = []
for i, col in enumerate(colors):
stop = svg.Stop(stop_color=col.to_hex())
stop.offset = svg.Length(int((i / len(colors)) * 100), '%')
stop_colors.append(stop)
gradient.elements = stop_colors
elements.append(gradient)
bound_rect.fill = "url('#{}')".format(gradient.id)
elements.append(bound_rect)
# translate the legend title
t_pt = legend.title_location_2d(width, height)
svg_txt = svg.Text(x=t_pt.x, y=t_pt.y)
svg_txt.text = legend.title
svg_txt.font_size = th
svg_txt.font_family = l_par.font
svg_txt.text_anchor = 'start'
svg_txt.dominant_baseline = 'middle'
elements.append(svg_txt)
# translate the legend text for the values in the legend
txt_pts = legend.segment_text_location_2d(width, height)
for txt, loc in zip(legend.segment_text, txt_pts):
svg_txt = svg.Text(x=loc.x, y=loc.y)
svg_txt.text = txt
svg_txt.font_size = th
svg_txt.font_family = l_par.font
svg_txt.dominant_baseline = 'hanging'
if not l_par.vertical:
svg_txt.text_anchor = 'middle'
elements.append(svg_txt)
# combine everything into a final SVG object
canvas = svg.SVG(width=width, height=height)
canvas.elements = elements
return canvas
[docs]
def duplicate(self):
"""Get a copy of this object."""
return self.__copy__()
def __copy__(self):
new_obj = VisualizationData(
self.values, self._legend_parameters, self._data_type, self._unit)
new_obj._user_data = None if self.user_data is None else self.user_data.copy()
return new_obj
def __len__(self):
"""Return length of values on the object."""
return len(self._legend._values)
def __getitem__(self, key):
"""Return one of the values."""
return self._legend._values[key]
def __iter__(self):
"""Iterate through the values."""
return iter(self._legend._values)
[docs]
def ToString(self):
"""Overwrite .NET ToString."""
return self.__repr__()
def __repr__(self):
"""VisualizationData representation."""
return 'Visualization Data ({} values)'.format(len(self))
