class MarketMap(DOMWidget):
"""Waffle wrapped map.
Attributes
----------
names: numpy.ndarray of strings (default: [])
The elements can also be objects convertible to string
primary key for the map data. A rectangle is created for each
unique entry in this array
groups: numpy.ndarray (default: [])
attribute on which the groupby is run. If this is an empty arrray, then
there is no group by for the map.
display_text: numpy.ndarray or None(default: None)
data to be displayed on each rectangle of the map.If this is empty it
defaults to the names attribute.
ref_data: pandas.DataDrame or None (default: None)
Additional data associated with each element of the map. The data in
this data frame can be displayed as a tooltip.
color: numpy.ndarray (default: [])
Data to represent the color for each of the cells. If the value of the
data is NaN for a cell, then the color of the cell is the color of the
group it belongs to in absence of data for color
scales: Dictionary of scales holding a scale for each data attribute
If the map has data being passed as color, then a corresponding color
scale is required
axes: List of axes
Ability to add an axis for the scales which are used to scale data
represented in the map
on_hover: custom event
This event is received when the mouse is hovering over a cell. Returns
the data of the cell and the ref_data associated with the cell.
tooltip_widget: Instance of a widget
Widget to be displayed as the tooltip. This can be combined with the
on_hover event to display the chart corresponding to the cell being
hovered on.
tooltip_fields: list
names of the fields from the ref_data dataframe which should be
displayed in the tooltip.
tooltip_formats: list
formats for each of the fields for the tooltip data. Order should match
the order of the tooltip_fields
show_groups: bool
attribute to determine if the groups should be displayed. If set to
True, the finer elements are blurred
Map Drawing Attributes
cols: int
Suggestion for no of columns in the map.If not specified, value is
inferred from the no of rows and no of cells
rows: int
No of rows in the map.If not specified, value is inferred from the no
of cells and no of columns.
If both rows and columns are not specified, then a square is
constructed basing on the no of cells.
The above two attributes are suggestions which are respected unless
they are not feasible. One required condition is that, the number of
columns is odd when row_groups is greater than 1.
row_groups: int
No of groups the rows should be divided into. This can be used to draw
more square cells for each of the groups
Layout Attributes
map_margin: dict (default: {top=50, bottom=50, left=50, right=50})
Dictionary containing the top, bottom, left and right margins. The user
is responsible for making sure that the width and height are greater
than the sum of the margins.
min_aspect_ratio: float
minimum width / height ratio of the figure
max_aspect_ratio: float
maximum width / height ratio of the figure
Display Attributes
colors: list of colors
Colors for each of the groups which are cycled over to cover all the
groups
title: string
Title of the Market Map
title_style: dict
CSS style for the title of the Market Map
stroke: color
Stroke of each of the cells of the market map
group_stroke: color
Stroke of the border for the group of cells corresponding to a group
selected_stroke: color
stroke for the selected cells
hovered_stroke: color
stroke for the cell being hovered on
font_style: dict
CSS style for the text of each cell
Other Attributes
enable_select: bool
boolean to control the ability to select the cells of the map by
clicking
enable_hover: bool
boolean to control if the map should be aware of which cell is being
hovered on. If it is set to False, tooltip will not be displayed
Note
----
The aspect ratios stand for width / height ratios.
- If the available space is within bounds in terms of min and max aspect
ratio, we use the entire available space.
- If the available space is too oblong horizontally, we use the client
height and the width that corresponds max_aspect_ratio (maximize width
under the constraints).
- If the available space is too oblong vertically, we use the client width
and the height that corresponds to min_aspect_ratio (maximize height
under the constraint).
This corresponds to maximizing the area under the constraints.
Default min and max aspect ratio are both equal to 16 / 9.
"""
names = Array([]).tag(sync=True, **array_serialization)
groups = Array([]).tag(sync=True, **array_serialization)
display_text = Array(None, allow_none=True).tag(sync=True, **array_serialization)
ref_data = DataFrame(None, allow_none=True).tag(sync=True, **dataframe_serialization).valid(dataframe_warn_indexname)
title = Unicode().tag(sync=True)
tooltip_fields = List().tag(sync=True)
tooltip_formats = List().tag(sync=True)
show_groups = Bool().tag(sync=True)
cols = Int(allow_none=True).tag(sync=True)
rows = Int(allow_none=True).tag(sync=True)
row_groups = Int(1).tag(sync=True)
colors = List(CATEGORY10).tag(sync=True)
scales = Dict().tag(sync=True, **widget_serialization)
axes = List().tag(sync=True, **widget_serialization)
color = Array([]).tag(sync=True, **array_serialization)
map_margin = Dict(dict(top=50, right=50, left=50, bottom=50)).tag(sync=True)
layout = Instance(Layout, kw={
'min_width': '125px'
}, allow_none=True).tag(sync=True, **widget_serialization)
min_aspect_ratio = Float(1.0).tag(sync=True)
# Max aspect ratio is such that we can have 3 charts stacked vertically
# on a 16:9 monitor: 16/9*3 ~ 5.333
max_aspect_ratio = Float(6.0).tag(sync=True)
stroke = Color('white').tag(sync=True)
group_stroke = Color('black').tag(sync=True)
selected_stroke = Color('dodgerblue', allow_none=True).tag(sync=True)
hovered_stroke = Color('orangered', allow_none=True).tag(sync=True)
font_style = Dict().tag(sync=True)
title_style = Dict().tag(sync=True)
selected = List().tag(sync=True)
enable_hover = Bool(True).tag(sync=True)
enable_select = Bool(True).tag(sync=True)
tooltip_widget = Instance(DOMWidget, allow_none=True, default_value=None).tag(sync=True, **widget_serialization)
def __init__(self, **kwargs):
super(MarketMap, self).__init__(**kwargs)
self._hover_handlers = CallbackDispatcher()
self.on_msg(self._handle_custom_msgs)
def on_hover(self, callback, remove=False):
self._hover_handlers.register_callback(callback, remove=remove)
def _handle_custom_msgs(self, _, content, buffers=None):
if content.get('event', '') == 'hover':
self._hover_handlers(self, content)
def _compare(self, a, b):
# Compare dataframes properly
import pandas as pd
if isinstance(a, pd.DataFrame) or isinstance(b, pd.DataFrame):
return pd.DataFrame.equals(a,b)
return super(MarketMap, self)._compare(a, b)
_view_name = Unicode('MarketMap').tag(sync=True)
_model_name = Unicode('MarketMapModel').tag(sync=True)
_view_module = Unicode('bqplot').tag(sync=True)
_model_module = Unicode('bqplot').tag(sync=True)
_view_module_version = Unicode(__frontend_version__).tag(sync=True)
_model_module_version = Unicode(__frontend_version__).tag(sync=True)
class Foo(HasTraits):
bar = DataFrame()
baz = DataFrame(allow_none=True)
class Foo(HasTraits):
bar = DataFrame([1, 2])
@observe('bar')
def _(self, change):
notifications.append(change)
class Foo(HasTraits):
a = DataFrame()
b = DataFrame(None, allow_none=True)
c = DataFrame([])
d = DataFrame(Undefined)
class MarketMap(DOMWidget):
"""Waffle wrapped map.
Attributes
----------
names: numpy.ndarray of strings (default: [])
The elements can also be objects convertible to string
primary key for the map data. A rectangle is created for each
unique entry in this array
groups: numpy.ndarray (default: [])
attribute on which the groupby is run. If this is an empty arrray, then
there is no group by for the map.
display_text: numpy.ndarray or None(default: None)
data to be displayed on each rectangle of the map.If this is empty it
defaults to the names attribute.
ref_data: pandas.DataDrame or None (default: None)
Additional data associated with each element of the map. The data in
this data frame can be displayed as a tooltip.
color: numpy.ndarray (default: [])
Data to represent the color for each of the cells. If the value of the
data is NaN for a cell, then the color of the cell is the color of the
group it belongs to in absence of data for color
scales: Dictionary of scales holding a scale for each data attribute
If the map has data being passed as color, then a corresponding color
scale is required
axes: List of axes
Ability to add an axis for the scales which are used to scale data
represented in the map
on_hover: custom event
This event is received when the mouse is hovering over a cell. Returns
the data of the cell and the ref_data associated with the cell.
tooltip_widget: Instance of a widget
Widget to be displayed as the tooltip. This can be combined with the
on_hover event to display the chart corresponding to the cell being
hovered on.
tooltip_fields: list
names of the fields from the ref_data dataframe which should be
displayed in the tooltip.
tooltip_formats: list
formats for each of the fields for the tooltip data. Order should match
the order of the tooltip_fields
show_groups: bool
attribute to determine if the groups should be displayed. If set to
True, the finer elements are blurred
Map Drawing Attributes
map_width: int
minimum width of the entire map
map_height: int
minimum height of the entire map
map_margin: dict
margin for the market map plot area with respect to the entire display
area
preserve_aspect: bool
boolean to control if the aspect ratio should be preserved or not
during a resize
cols: int
Suggestion for no of columns in the map.If not specified, value is
inferred from the no of rows and no of cells
rows: int
No of rows in the map.If not specified, value is inferred from the no
of cells and no of columns.
If both rows and columns are not specified, then a square is
constructed basing on the no of cells.
The above two attributes are suggestions which are respected unless
they are not feasible. One required condition is that, the number of
columns is odd when row_groups is greater than 1.
row_groups: int
No of groups the rows should be divided into. This can be used to draw
more square cells for each of the groups
Display Attributes
colors: list of colors
Colors for each of the groups which are cycled over to cover all the
groups
title: string
Title of the Market Map
title_style: dict
CSS style for the title of the Market Map
stroke: color
Stroke of each of the cells of the market map
group_stroke: color
Stroke of the border for the group of cells corresponding to a group
selected_stroke: color
stroke for the selected cells
hovered_stroke: color
stroke for the cell being hovered on
font_style: dict
CSS style for the text of each cell
Other Attributes
enable_select: bool
boolean to control the ability to select the cells of the map by
clicking
enable_hover: bool
boolean to control if the map should be aware of which cell is being
hovered on. If it is set to False, tooltip will not be displayed
"""
map_width = Int(1080).tag(sync=True)
map_height = Int(800).tag(sync=True)
names = Array([]).tag(sync=True, **array_serialization)
groups = Array([]).tag(sync=True, **array_serialization)
display_text = Array(None, allow_none=True).tag(sync=True,
**array_serialization)
ref_data = DataFrame(None, allow_none=True).tag(
sync=True, **dataframe_serialization).valid(dataframe_warn_indexname)
title = Unicode().tag(sync=True)
tooltip_fields = List().tag(sync=True)
tooltip_formats = List().tag(sync=True)
show_groups = Bool().tag(sync=True)
cols = Int(allow_none=True).tag(sync=True)
rows = Int(allow_none=True).tag(sync=True)
row_groups = Int(1).tag(sync=True)
colors = List(CATEGORY10).tag(sync=True)
scales = Dict().tag(sync=True, **widget_serialization)
axes = List().tag(sync=True, **widget_serialization)
color = Array([]).tag(sync=True, **array_serialization)
map_margin = Dict(dict(top=50, right=50, left=50,
bottom=50)).tag(sync=True)
preserve_aspect = Bool().tag(sync=True,
display_name='Preserve aspect ratio')
stroke = Color('white').tag(sync=True)
group_stroke = Color('black').tag(sync=True)
selected_stroke = Color('dodgerblue').tag(sync=True)
hovered_stroke = Color('orangered').tag(sync=True)
font_style = Dict().tag(sync=True)
title_style = Dict().tag(sync=True)
selected = List().tag(sync=True)
enable_hover = Bool(True).tag(sync=True)
enable_select = Bool(True).tag(sync=True)
tooltip_widget = Instance(DOMWidget, allow_none=True,
default_value=None).tag(sync=True,
**widget_serialization)
def __init__(self, **kwargs):
super(MarketMap, self).__init__(**kwargs)
self._hover_handlers = CallbackDispatcher()
self.on_msg(self._handle_custom_msgs)
def on_hover(self, callback, remove=False):
self._hover_handlers.register_callback(callback, remove=remove)
def _handle_custom_msgs(self, _, content, buffers=None):
if content.get('event', '') == 'hover':
self._hover_handlers(self, content)
_view_name = Unicode('MarketMap').tag(sync=True)
_model_name = Unicode('MarketMapModel').tag(sync=True)
_view_module = Unicode('bqplot').tag(sync=True)
_model_module = Unicode('bqplot').tag(sync=True)
