class RadarChart(Chart):
def __init__(self,
blank_labels=options.get_option('chart.blank_labels'),
layout='slide_50%'):
"""Create a Radar Chart instance.
Note:
Radar charts plot each vertex in counter-clockwise order starting
from the top.
Args:
blank_labels (bool): When true removes the title,
subtitle, axes, and source labels from the chart.
Default False.
layout (str): Change size & aspect ratio of the chart for
fitting into slides.
- 'slide_100%'
- 'slide_75%'
- 'slide_50%' (Suggested for Radar Charts)
- 'slide_25%'
"""
# Validate axis type input
valid_axis_types = ['linear', 'log']
self._axis_type = 'linear'
self._x_axis_type, self._y_axis_type = self._axis_type, self._axis_type
if self._axis_type not in valid_axis_types:
raise ValueError('axis_type must be one of {options}'.format(
options=valid_axis_types))
self._blank_labels = options._get_value(blank_labels)
self.style = Style(self, layout)
self.figure = self._initialize_figure(self._axis_type, self._axis_type)
self.style._apply_settings('chart')
self.callout = Callout(self)
self.axes = BaseAxes._get_axis_class(self._axis_type,
self._axis_type)(self)
self.plot = PlotRadar(self)
self._source = self._add_source_to_figure()
self._subtitle_glyph = self._add_subtitle_to_figure()
self.figure.toolbar.logo = None # Remove bokeh logo from toolbar.
# Reverse the order of vertical legends. Used with stacked plot types
# to ensure that the stack order is consistent with the legend order.
self._reverse_vertical_legend = False
# Logos disabled for now.
# self.logo = Logo(self)
# Set default for title
title = """ch.set_title('Takeaway')"""
if self._blank_labels:
title = ""
self.set_title(title)
def __init__(self,
blank_labels=options.get_option('chart.blank_labels'),
layout='slide_100%',
x_axis_type='linear',
y_axis_type='linear',
second_y_axis=False):
"""Create a chart instance.
Args:
blank_labels (bool): When true removes the title,
subtitle, axes, and source labels from the chart.
Default False.
layout (str): Change size & aspect ratio of the chart for
fitting into slides.
- 'slide_100%'
- 'slide_75%'
- 'slide_50%'
- 'slide_25%'
x_axis_type (enum, str): Type of data plotted on the X-axis.
- 'linear':
- 'log':
- 'datetime': Use for datetime formatted data.
- 'categorical':
- 'density'
y_axis_type (enum, str): Type of data plotted on the Y-axis.
- 'linear':
- 'log':
- 'categorical':
- 'density'
Note:
Combination of x_axis_type and y_axis_type will determine the
plotting methods available.
"""
# Validate axis type input
valid_x_axis_types = [
'linear', 'log', 'datetime', 'categorical', 'density'
]
valid_y_axis_types = ['linear', 'log', 'categorical', 'density']
valid_second_y_axis_types = ['linear', 'log']
if x_axis_type not in valid_x_axis_types:
raise ValueError('x_axis_type must be one of {options}'.format(
options=valid_x_axis_types))
if y_axis_type not in valid_y_axis_types:
raise ValueError('y_axis_type must be one of {options}'.format(
options=valid_y_axis_types))
self._second_y_axis_type = None
if second_y_axis:
self._second_y_axis_type = y_axis_type
if self._second_y_axis_type not in valid_second_y_axis_types:
raise ValueError('second_y_axis can only be used when \
y_axis_type is one of {options}'.format(
options=valid_second_y_axis_types))
self._x_axis_type, self._y_axis_type = x_axis_type, y_axis_type
self._blank_labels = options._get_value(blank_labels)
self.style = Style(self, layout)
self.figure = self._initialize_figure(self._x_axis_type,
self._y_axis_type)
self.style._apply_settings('chart')
self.plot = BasePlot._get_plot_class(self._x_axis_type,
self._y_axis_type)(self)
self.callout = Callout(self)
self.axes = BaseAxes._get_axis_class(self._x_axis_type,
self._y_axis_type)(self)
if self._second_y_axis_type in valid_second_y_axis_types:
self.second_axis = SecondAxis()
self.second_axis.axes = SecondYNumericalAxis(self)
self.second_axis.plot = BasePlot._get_plot_class(
self._x_axis_type,
self._second_y_axis_type)(self,
self.second_axis.axes._y_range_name)
self._source = self._add_source_to_figure()
self._subtitle_glyph = self._add_subtitle_to_figure()
self.figure.toolbar.logo = None # Remove bokeh logo from toolbar.
# Reverse the order of vertical legends. Used with stacked plot types
# to ensure that the stack order is consistent with the legend order.
self._reverse_vertical_legend = False
# Logos disabled for now.
# self.logo = Logo(self)
# Set default for title
title = """ch.set_title('Takeaway')"""
if self._blank_labels:
title = ""
self.set_title(title)
class Chart:
"""Class Docstring
- Styling (.style)
- Plotting (.plot)
- Callouts (.callout)
- Axes (.axes)
- Bokeh figure (.figure)
"""
def __init__(self,
blank_labels=options.get_option('chart.blank_labels'),
layout='slide_100%',
x_axis_type='linear',
y_axis_type='linear',
second_y_axis=False):
"""Create a chart instance.
Args:
blank_labels (bool): When true removes the title,
subtitle, axes, and source labels from the chart.
Default False.
layout (str): Change size & aspect ratio of the chart for
fitting into slides.
- 'slide_100%'
- 'slide_75%'
- 'slide_50%'
- 'slide_25%'
x_axis_type (enum, str): Type of data plotted on the X-axis.
- 'linear':
- 'log':
- 'datetime': Use for datetime formatted data.
- 'categorical':
- 'density'
y_axis_type (enum, str): Type of data plotted on the Y-axis.
- 'linear':
- 'log':
- 'categorical':
- 'density'
Note:
Combination of x_axis_type and y_axis_type will determine the
plotting methods available.
"""
# Validate axis type input
valid_x_axis_types = [
'linear', 'log', 'datetime', 'categorical', 'density'
]
valid_y_axis_types = ['linear', 'log', 'categorical', 'density']
valid_second_y_axis_types = ['linear', 'log']
if x_axis_type not in valid_x_axis_types:
raise ValueError('x_axis_type must be one of {options}'.format(
options=valid_x_axis_types))
if y_axis_type not in valid_y_axis_types:
raise ValueError('y_axis_type must be one of {options}'.format(
options=valid_y_axis_types))
self._second_y_axis_type = None
if second_y_axis:
self._second_y_axis_type = y_axis_type
if self._second_y_axis_type not in valid_second_y_axis_types:
raise ValueError('second_y_axis can only be used when \
y_axis_type is one of {options}'.format(
options=valid_second_y_axis_types))
self._x_axis_type, self._y_axis_type = x_axis_type, y_axis_type
self._blank_labels = options._get_value(blank_labels)
self.style = Style(self, layout)
self.figure = self._initialize_figure(self._x_axis_type,
self._y_axis_type)
self.style._apply_settings('chart')
self.plot = BasePlot._get_plot_class(self._x_axis_type,
self._y_axis_type)(self)
self.callout = Callout(self)
self.axes = BaseAxes._get_axis_class(self._x_axis_type,
self._y_axis_type)(self)
if self._second_y_axis_type in valid_second_y_axis_types:
self.second_axis = SecondAxis()
self.second_axis.axes = SecondYNumericalAxis(self)
self.second_axis.plot = BasePlot._get_plot_class(
self._x_axis_type,
self._second_y_axis_type)(self,
self.second_axis.axes._y_range_name)
self._source = self._add_source_to_figure()
self._subtitle_glyph = self._add_subtitle_to_figure()
self.figure.toolbar.logo = None # Remove bokeh logo from toolbar.
# Reverse the order of vertical legends. Used with stacked plot types
# to ensure that the stack order is consistent with the legend order.
self._reverse_vertical_legend = False
# Logos disabled for now.
# self.logo = Logo(self)
# Set default for title
title = """ch.set_title('Takeaway')"""
if self._blank_labels:
title = ""
self.set_title(title)
def __repr__(self):
return """
chartify.Chart(blank_labels={blank_labels},
layout='{layout}',
x_axis_type='{x_axis_type}',
y_axis_type='{y_axis_type}')
""".format(blank_labels=self._blank_labels,
layout=self.style._layout,
x_axis_type=self._x_axis_type,
y_axis_type=self._y_axis_type)
def _initialize_figure(self, x_axis_type, y_axis_type):
x_range, y_range = None, None
if x_axis_type == 'categorical':
x_range = []
x_axis_type = 'auto'
if y_axis_type == 'categorical':
y_range = []
y_axis_type = 'auto'
if x_axis_type == 'density':
x_axis_type = 'linear'
if y_axis_type == 'density':
y_axis_type = 'linear'
figure = bokeh.plotting.figure(
x_range=x_range,
y_range=y_range,
y_axis_type=y_axis_type,
x_axis_type=x_axis_type,
plot_width=self.style.plot_width,
plot_height=self.style.plot_height,
tools='save',
# toolbar_location='right',
active_drag=None)
return figure
def _add_subtitle_to_figure(self, subtitle_text=None):
"""Create the subtitle glyph and add it to the bokeh figure."""
if subtitle_text is None:
if self._blank_labels:
subtitle_text = ""
else:
subtitle_text = """ch.set_subtitle('Data Description')"""
subtitle_settings = self.style._get_settings('subtitle')
_subtitle_glyph = bokeh.models.Title(
text=subtitle_text,
align=subtitle_settings['subtitle_align'],
text_color=subtitle_settings['subtitle_text_color'],
text_font_size=subtitle_settings['subtitle_text_size'],
text_font=subtitle_settings['subtitle_text_font'],
)
self.figure.add_layout(_subtitle_glyph,
subtitle_settings['subtitle_location'])
return _subtitle_glyph
def _add_source_to_figure(self):
"""Create the source glyph and add it to the bokeh figure."""
source_text = """ch.set_source_label('Source')"""
if self._blank_labels:
source_text = ""
source_text_color = '#898989'
source_font_size = '10px'
_source = bokeh.models.Label(x=self.style.plot_width * .9,
y=0,
x_units='screen',
y_units='screen',
level='overlay',
text=source_text,
text_color=source_text_color,
text_font_size=source_font_size,
text_align='right',
name='subtitle')
self.figure.add_layout(_source, 'below')
return _source
@property
def data(self):
"""Return a list of dictionaries of the data that have be plotted on the chart.
Note:
The format will depend on the types of plots that have been added.
"""
datasources = self.figure.select(
{'type': bokeh.models.ColumnDataSource})
# Extract the data attribute from the ColumnDataSource object
# and place in a list.
datasources_list = list(map(lambda x: x.data, datasources))
return datasources_list
@property
def source_text(self):
"""str: Data source of the chart."""
return self._source.text
def set_source_label(self, source):
"""Set the chart data source.
Args:
source (str): Data source.
Returns:
Current chart object
"""
self._source.text = source
return self
@property
def title(self):
"""str: Title text of the chart."""
return self.figure.title.text
def set_title(self, title):
"""Set the chart title.
Args:
title (str): Title text.
Returns:
Current chart object
"""
self.figure.title.text = title
return self
@property
def subtitle(self):
"""str: Subtitle text of the chart."""
return self._subtitle_glyph.text
def set_subtitle(self, subtitle):
"""Set the chart subtitle.
Args:
subtitle (str): Subtitle text.
Note:
Set value to "" to remove subtitle.
Returns:
Current chart object
"""
self._subtitle_glyph.text = subtitle
return self
@property
def legend_location(self):
"""str: Legend location."""
return self.figure.legend[0].location
def set_legend_location(self, location, orientation='horizontal'):
"""Set the legend location.
Args:
location (str or tuple): Legend location. One of:
- Outside of the chart: 'outside_top', 'outside_bottom',
'outside_right'
- Within the chart area: 'top_left', 'top_center',
'top_right', 'center_left', 'center', 'center_right',
'bottom_left', 'bottom_center', 'bottom_right'
- Coordinates: Tuple(Float, Float)
- None: Removes the legend.
orientation (str): 'horizontal' or 'vertical'
Returns:
Current chart object
"""
def add_outside_legend(legend_location, layout_location):
self.figure.legend.location = legend_location
if not self.figure.legend:
warnings.warn(
"""
Legend location will not apply.
Set the legend after plotting data.
""", UserWarning)
return self
new_legend = self.figure.legend[0]
new_legend.plot = None
new_legend.orientation = orientation
self.figure.add_layout(new_legend, layout_location)
if location == 'outside_top':
add_outside_legend('top_left', 'above')
# Re-render the subtitle so that it appears over the legend.
subtitle_index = self.figure.renderers.index(self._subtitle_glyph)
self.figure.renderers.pop(subtitle_index)
self._subtitle_glyph = self._add_subtitle_to_figure(
self._subtitle_glyph.text)
elif location == 'outside_bottom':
add_outside_legend('bottom_center', 'below')
elif location == 'outside_right':
add_outside_legend('top_left', 'right')
elif location is None:
self.figure.legend.visible = False
else:
self.figure.legend.location = location
self.figure.legend.orientation = orientation
vertical = self.axes._vertical
# Reverse the legend order
if self._reverse_vertical_legend:
if orientation == 'vertical' and vertical:
self.figure.legend[0].items = list(
reversed(self.figure.legend[0].items))
return self
def show(self, format='html'):
"""Show the chart.
Args:
format (str):
- 'html': Output chart as HTML.
Renders faster and allows for interactivity.
Charts saved as HTML in a Jupyter notebooks
WILL NOT display on Github.
Logos will not display on HTML charts.
Recommended when drafting plots.
- 'png': Output chart as PNG.
Easy to copy+paste into slides.
Will render logos.
Recommended when the plot is in a finished state.
- 'svg': Output as SVG.
"""
self._set_toolbar_for_format(format)
if format == 'html':
return bokeh.io.show(self.figure)
elif format == 'png':
image = self._figure_to_png()
# Need to re-enable this when logos are added back.
# image = self.logo._add_logo_to_image(image)
return display(image)
elif format == 'svg':
return self._show_svg()
def save(self, filename, format='html'):
"""Save the chart.
Args:
filename (str): Name of output file.
format (str):
- 'html': Output chart as HTML.
Renders faster and allows for interactivity.
Charts saved as HTML in a Jupyter notebook WILL NOT display
on Github.
Logos will not display on HTML charts.
Recommended when drafting plots.
- 'png': Output chart as PNG.
Easy to paste into google slides.
Recommended when the plot is in a finished state.
Will render logos.
- 'svg': Output as SVG.
"""
self._set_toolbar_for_format(format)
if format == 'html':
bokeh.io.saving.save(self.figure,
filename=filename,
resources=INLINE,
title='Chartify chart.')
elif format == 'png':
image = self._figure_to_png()
# Need to re-enable this when logos are added back.
# image = self.logo._add_logo_to_image(image)
image.save(filename)
elif format == 'svg':
image = self._figure_to_svg()
self._save_svg(image, filename)
print('Saved to {filename}'.format(filename=filename))
return self
def _set_toolbar_for_format(self, format):
if format == 'html':
self.figure.toolbar_location = 'right'
elif format in ('png', 'svg'):
self.figure.toolbar_location = None
elif format is None: # If format is None the chart won't be shown.
pass
else:
raise ValueError(
"""Invalid format. Valid options are 'html' or 'png'.""")
def _initialize_webdriver(self):
"""Initialize headless chrome browser"""
options = Options()
options.add_argument("window-size={width},{height}".format(
width=self.style.plot_width, height=self.style.plot_height))
options.add_argument("start-maximized")
options.add_argument("disable-infobars")
options.add_argument("disable-gpu")
options.add_argument('no-sandbox') # Required for use in docker.
options.add_argument("--disable-extensions")
options.add_argument('--headless')
options.add_argument('--hide-scrollbars')
driver = webdriver.Chrome(options=options)
return driver
def _figure_to_png(self):
"""Convert figure object to PNG
Bokeh can only save figure objects as html.
To convert to PNG the HTML file is opened in a headless browser.
"""
driver = self._initialize_webdriver()
# Save figure as HTML
html = file_html(self.figure, resources=INLINE, title="")
fp = tempfile.NamedTemporaryFile('w',
prefix='chartify',
suffix='.html',
encoding='utf-8')
fp.write(html)
fp.flush()
# Open html file in the browser.
driver.get("file:///" + fp.name)
driver.execute_script("document.body.style.margin = '0px';")
png = driver.get_screenshot_as_png()
driver.quit()
fp.close()
# Resize image if necessary.
image = Image.open(BytesIO(png))
target_dimensions = (self.style.plot_width, self.style.plot_height)
if image.size != target_dimensions:
image = image.resize(target_dimensions, resample=Image.LANCZOS)
return image
def _set_svg_backend_decorator(f):
"""Sets the chart backend to svg and resets
after the function has run."""
@wraps(f)
def wrapper(self, *args, **kwargs):
old_backend = self.figure.output_backend
self.figure.output_backend = 'svg'
return f(self, *args, **kwargs)
self.figure.output_backend = old_backend
return wrapper
@_set_svg_backend_decorator
def _show_svg(self):
"""Show the chart figure with an svg output backend."""
return bokeh.io.show(self.figure)
@_set_svg_backend_decorator
def _figure_to_svg(self):
"""
Convert the figure to an svg so that it can be saved to a file.
https://github.com/bokeh/bokeh/blob/master/bokeh/io/export.py
"""
driver = self._initialize_webdriver()
html = file_html(self.figure, resources=INLINE, title="")
fp = tempfile.NamedTemporaryFile('w',
prefix='chartify',
suffix='.html',
encoding='utf-8')
fp.write(html)
fp.flush()
driver.get("file:///" + fp.name)
svgs = driver.execute_script(_SVG_SCRIPT)
fp.close()
driver.quit()
return svgs[0]
def _save_svg(self, svg, filename):
"""Write the svg to a file"""
with io.open(filename, mode="w", encoding="utf-8") as f:
f.write(svg)
