holoviews.plotting Package ¶
plotting
Package
¶
HoloViews plotting sub-system the defines the interface to be used by any third-party plotting/rendering package.
This file defines the HTML tags used to wrap renderered output for display in the IPython Notebook (optional).
-
class
holoviews.plotting.
Plot
( **params ) [source] ¶ -
Bases:
param.parameterized.Parameterized
Base class of all Plot classes in HoloViews, designed to be general enough to use any plotting package or backend.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
inspect_value
= <functools.partial object> ¶
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
update
( key ) [source] ¶ -
Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
-
class
holoviews.plotting.
Renderer
( **params ) [source] ¶ -
Bases:
holoviews.core.io.Exporter
The job of a Renderer is to turn the plotting state held within Plot classes into concrete, visual output in the form of the PNG, SVG, MP4 or WebM formats (among others). Note that a Renderer is a type of Exporter and must therefore follow the Exporter interface.
The Renderer needs to be able to use the .state property of the appropriate Plot classes associated with that renderer in order to generate output. The process of ‘drawing’ is execute by the Plots and the Renderer turns the final plotting state into output.
-
param Dict
post_render_hooks
( allow_None=False, constant=False, default={u’svg’: [], u’png’: []}, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False ) - Optional dictionary of hooks that are applied to the rendered data (according to the output format) before it is returned. Each hook is passed the rendered data and the object that is being rendered. These hooks allow post-processing of renderered data before output is saved to file or displayed.
-
param ObjectSelector
holomap
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=auto, instantiate=False, objects=[u’scrubber’, u’widgets’, None, u’auto’], pickle_default_value=True, precedence=None, readonly=False ) - Output render multi-frame (typically animated) format. If None, no multi-frame rendering will occur.
-
param Integer
dpi
( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - The render resolution in dpi (dots per inch)
-
param ObjectSelector
mode
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=default, instantiate=False, objects=[u’default’], pickle_default_value=True, precedence=None, readonly=False ) - The available rendering modes. As a minimum, the ‘default’ mode must be supported.
-
param Callable
info_fn
( allow_None=True, constant=True, instantiate=True, pickle_default_value=True, precedence=None, readonly=False ) - Renderers do not support the saving of object info metadata
-
param ObjectSelector
fig
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=auto, instantiate=False, objects=[u’auto’], pickle_default_value=True, precedence=None, readonly=False ) - Output render format for static figures. If None, no figure rendering will occur.
-
param Number
fps
( allow_None=False, bounds=None, constant=False, default=20, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - Rendered fps (frames per second) for animated formats.
-
param ObjectSelector
widget_mode
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=embed, instantiate=False, objects=[u’embed’, u’live’], pickle_default_value=True, precedence=None, readonly=False ) - The widget mode determining whether frames are embedded or generated ‘live’ when interacting with the widget.
-
param Callable
key_fn
( allow_None=True, constant=True, default=None, instantiate=True, pickle_default_value=True, precedence=None, readonly=False ) - Renderers do not support the saving of object key metadata
-
param String
backend
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default=, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The full, lowercase name of the rendering backend or third part plotting package used e.g ‘matplotlib’ or ‘cairo’.
-
param Dict
css
( allow_None=False, constant=False, default={}, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False ) - Dictionary of CSS attributes and values to apply to HTML output
-
param Integer
size
( allow_None=False, bounds=None, constant=False, default=100, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - The rendered size as a percentage size
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
encode
( entry ) ¶ -
Classmethod that applies conditional encoding based on mime-type. Given an entry as returned by __call__ return the data in the appropriate encoding.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
html
( obj , fmt=None , css=None , comm=True , **kwargs ) [source] ¶ -
Renders plot or data structure and wraps the output in HTML. The comm argument defines whether the HTML output includes code to initialize a Comm, if the plot supplies one.
-
classmethod
html_assets
( core=True , extras=True , backends=None ) [source] ¶ -
Returns JS and CSS and for embedding of widgets.
-
inspect_value
= <functools.partial object> ¶
-
instance
= <functools.partial object> ¶
-
classmethod
load_nb
( inline=True ) [source] ¶ -
Loads any resources required for display of plots in the Jupyter notebook
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
classmethod
plot_options
( obj , percent_size ) [source] ¶ -
Given an object and a percentage size (as supplied by the %output magic) return all the appropriate plot options that would be used to instantiate a plot class for that element.
Default plot sizes at the plotting class level should be taken into account.
-
classmethod
plotting_class
( obj ) [source] ¶ -
Given an object or Element class, return the suitable plotting class needed to render it with the current renderer.
-
pprint
( imports=None , prefix='\n ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
Same as Parameterized.pprint, except that X.classname(Y is replaced with X.classname.instance(Y
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Same as Parameterized.script_repr, except that X.classname(Y is replaced with X.classname.instance(Y
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
classmethod
state
( *args , **kwds ) [source] ¶ -
Context manager to handle global state for a backend, allowing Plot classes to temporarily override that state.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
static_html
( obj , fmt=None , template=None ) [source] ¶ -
Generates a static HTML with the rendered object in the supplied format. Allows supplying a template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Dict
-
class
holoviews.plotting.
Cycle
( cycle=None , **params ) [source] ¶ -
Bases:
param.parameterized.Parameterized
A simple container class that specifies cyclic options. A typical example would be to cycle the curve colors in an Overlay composed of an arbitrary number of curves. The values may be supplied as an explicit list or a key to look up in the default cycles attribute.
-
param List
values
( allow_None=False, bounds=(0, None), constant=False, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False ) - The values the cycle will iterate over.
-
param String
key
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default=default_colors, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The key in the default_cycles dictionary used to specify the color cycle if values is not supplied.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
inspect_value
= <functools.partial object> ¶
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param List
comms
Module
¶
-
class
holoviews.plotting.comms.
Comm
( plot , id=None , on_msg=None ) [source] ¶ -
Bases:
object
Comm encompasses any uni- or bi-directional connection between a python process and a frontend allowing passing of messages between the two. A Comms class must implement methods send data and handle received message events.
If the Comm has to be set up on the frontend a template to handle the creation of the comms channel along with a message handler to process incoming messages must be supplied.
The template must accept three arguments:
-
id - A unique id to register to register the comm under.
-
- msg_handler - JS code which has the msg variable in scope and
-
performs appropriate action for the supplied message.
-
init_frame - The initial frame to render on the frontend.
-
-
class
holoviews.plotting.comms.
JupyterComm
( plot , id=None , on_msg=None ) [source] ¶ -
Bases:
holoviews.plotting.comms.Comm
JupyterComm provides a Comm for the notebook which is initialized the first time data is pushed to the frontend.
-
class
holoviews.plotting.comms.
JupyterCommJS
( plot , id=None , on_msg=None ) [source] ¶ -
Bases:
holoviews.plotting.comms.JupyterComm
JupyterCommJS provides a comms channel for the Jupyter notebook, which is initialized on the frontend. This allows sending events initiated on the frontend to python.
-
decode
( msg ) ¶ -
Decodes messages following Jupyter messaging protocol. If JSON decoding fails data is assumed to be a regular string.
-
-
class
holoviews.plotting.comms.
StandardOutput
[source] ¶ -
Bases:
list
Context manager to capture standard output for any code it is wrapping and make it available as a list, e.g.:
>>> with StandardOutput() as stdout: ... print('This gets captured') >>> print(stdout[0]) This gets captured
-
append
( ) ¶ -
L.append(object) – append object to end
-
count
( value ) → integer -- return number of occurrences of value ¶
-
extend
( ) ¶ -
L.extend(iterable) – extend list by appending elements from the iterable
-
index
( value [ , start [ , stop ] ] ) → integer -- return first index of value. ¶ -
Raises ValueError if the value is not present.
-
insert
( ) ¶ -
L.insert(index, object) – insert object before index
-
pop
( [ index ] ) → item -- remove and return item at index (default last). ¶ -
Raises IndexError if list is empty or index is out of range.
-
remove
( ) ¶ -
L.remove(value) – remove first occurrence of value. Raises ValueError if the value is not present.
-
reverse
( ) ¶ -
L.reverse() – reverse IN PLACE
-
sort
( ) ¶ -
L.sort(cmp=None, key=None, reverse=False) – stable sort IN PLACE ; cmp(x, y) -> -1, 0, 1
-
plot
Module
¶
Public API for all plots supported by HoloViews, regardless of plotting package or backend. Every plotting classes must be a subclass of this Plot baseclass.
-
class
holoviews.plotting.plot.
DimensionedPlot
( keys=None , dimensions=None , layout_dimensions=None , uniform=True , subplot=False , adjoined=None , layout_num=0 , style=None , subplots=None , dynamic=False , renderer=None , **params ) [source] ¶ -
Bases:
holoviews.plotting.plot.Plot
DimensionedPlot implements a number of useful methods to compute dimension ranges and titles containing the dimension values.
-
param Boolean
normalize
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.
-
param String
title_format
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default={label} {group} {dimensions}, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The formatting string for the title of this plot, allows defining a label group separator and dimension labels.
-
param Parameter
fontsize
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Specifies various fontsizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys reverts to the default sizes, e.g: {‘ticks’:20, ‘title’:15, ‘ylabel’:5, ‘xlabel’:5, ‘legend’:8, ‘legend_title’:13} You can set the fontsize of both ‘ylabel’ and ‘xlabel’ together using the ‘labels’ key.
-
param Boolean
show_title
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to display the plot title.
-
param Parameter
projection
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom projection objects may be supplied.
-
compute_ranges
( obj , key , ranges ) [source] ¶ -
Given an object, a specific key and the normalization options this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
initialize_plot
( ranges=None ) ¶ -
Initialize the matplotlib figure.
-
inspect_value
= <functools.partial object> ¶
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
refresh
( **kwargs ) [source] ¶ -
Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
traverse
( fn=None , specs=None , full_breadth=True ) [source] ¶ -
Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Boolean
-
class
holoviews.plotting.plot.
GenericElementPlot
( element , keys=None , ranges=None , dimensions=None , batched=False , overlaid=0 , cyclic_index=0 , zorder=0 , style=None , overlay_dims={} , stream_sources=[] , **params ) [source] ¶ -
Bases:
holoviews.plotting.plot.DimensionedPlot
Plotting baseclass to render contents of an Element. Implements methods to get the correct frame given a HoloMap, axis labels and extents and titles.
-
param Boolean
normalize
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.
-
param Boolean
apply_extents
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to apply extent overrides on the Elements
-
param String
title_format
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default={label} {group} {dimensions}, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The formatting string for the title of this plot, allows defining a label group separator and dimension labels.
-
param Boolean
apply_ranges
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute the plot bounds from the data itself.
-
param Parameter
fontsize
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Specifies various fontsizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys reverts to the default sizes, e.g: {‘ticks’:20, ‘title’:15, ‘ylabel’:5, ‘xlabel’:5, ‘legend’:8, ‘legend_title’:13} You can set the fontsize of both ‘ylabel’ and ‘xlabel’ together using the ‘labels’ key.
-
param Boolean
show_title
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to display the plot title.
-
param Parameter
projection
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom projection objects may be supplied.
-
compute_ranges
( obj , key , ranges ) ¶ -
Given an object, a specific key and the normalization options this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_extents
( view , ranges ) [source] ¶ -
Gets the extents for the axes from the current View. The globally computed ranges can optionally override the extents.
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
get_zorder
( overlay , key , el ) [source] ¶ -
Computes the z-order of element in the NdOverlay taking into account possible batching of elements.
-
init_comm
( ) ¶ -
Initializes comm and attaches streams.
-
initialize_plot
( ranges=None ) ¶ -
Initialize the matplotlib figure.
-
inspect_value
= <functools.partial object> ¶
-
matches
( spec ) ¶ -
Matches a specification against the current Plot.
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
push
( ) ¶ -
Pushes updated plot data via the Comm.
-
refresh
( **kwargs ) ¶ -
Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
traverse
( fn=None , specs=None , full_breadth=True ) ¶ -
Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.
-
update_frame
( key , ranges=None ) [source] ¶ -
Set the plot(s) to the given frame number. Operates by manipulating the matplotlib objects held in the self._handles dictionary.
If n is greater than the number of available frames, update using the last available frame.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Boolean
-
class
holoviews.plotting.plot.
GenericLayoutPlot
( layout , **params ) [source] ¶ -
Bases:
holoviews.plotting.plot.GenericCompositePlot
A GenericLayoutPlot accepts either a Layout or a NdLayout and displays the elements in a cartesian grid in scanline order.
-
param Boolean
normalize
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.
-
param Boolean
transpose
( allow_None=False, bounds=(0, 1), constant=False, default=False, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to transpose the layout when plotting. Switches from row-based left-to-right and top-to-bottom scanline order to column-based top-to-bottom and left-to-right order.
-
param String
title_format
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default={label} {group} {dimensions}, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The formatting string for the title of this plot, allows defining a label group separator and dimension labels.
-
param Parameter
fontsize
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Specifies various fontsizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys reverts to the default sizes, e.g: {‘ticks’:20, ‘title’:15, ‘ylabel’:5, ‘xlabel’:5, ‘legend’:8, ‘legend_title’:13} You can set the fontsize of both ‘ylabel’ and ‘xlabel’ together using the ‘labels’ key.
-
param Boolean
show_title
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to display the plot title.
-
param Parameter
projection
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom projection objects may be supplied.
-
compute_ranges
( obj , key , ranges ) ¶ -
Given an object, a specific key and the normalization options this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
init_comm
( ) ¶ -
Initializes comm and attaches streams.
-
initialize_plot
( ranges=None ) ¶ -
Initialize the matplotlib figure.
-
inspect_value
= <functools.partial object> ¶
-
matches
( spec ) ¶ -
Matches a specification against the current Plot.
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
push
( ) ¶ -
Pushes updated plot data via the Comm.
-
refresh
( **kwargs ) ¶ -
Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
traverse
( fn=None , specs=None , full_breadth=True ) ¶ -
Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Boolean
-
class
holoviews.plotting.plot.
GenericOverlayPlot
( overlay , ranges=None , batched=True , keys=None , **params ) [source] ¶ -
Bases:
holoviews.plotting.plot.GenericElementPlot
Plotting baseclass to render (Nd)Overlay objects. It implements methods to handle the creation of ElementPlots, coordinating style groupings and zorder for all layers across a HoloMap. It also allows collapsing of layers via the Compositor.
-
param Boolean
normalize
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.
-
param Boolean
apply_extents
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to apply extent overrides on the Elements
-
param Integer
legend_limit
( allow_None=False, bounds=None, constant=False, default=25, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - Number of rendered glyphs before legends are disabled.
-
param String
title_format
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default={label} {group} {dimensions}, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The formatting string for the title of this plot, allows defining a label group separator and dimension labels.
-
param Boolean
apply_ranges
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to compute the plot bounds from the data itself.
-
param Boolean
show_legend
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to show legend for the plot.
-
param Parameter
fontsize
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Specifies various fontsizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys reverts to the default sizes, e.g: {‘ticks’:20, ‘title’:15, ‘ylabel’:5, ‘xlabel’:5, ‘legend’:8, ‘legend_title’:13} You can set the fontsize of both ‘ylabel’ and ‘xlabel’ together using the ‘labels’ key.
-
param Boolean
show_title
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to display the plot title.
-
param Boolean
batched
( allow_None=False, bounds=(0, 1), constant=False, default=True, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Whether to plot Elements NdOverlay in a batched plotting call if possible. Disables legends and zorder may not be preserved.
-
param Integer
style_grouping
( allow_None=False, bounds=None, constant=False, default=2, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - The length of the type.group.label spec that will be used to group Elements into style groups, i.e. a style_grouping value of 1 will group just by type, a value of 2 will group by type and group and a value of 3 will group by the full specification.
-
param Parameter
projection
( allow_None=True, constant=False, default=None, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom projection objects may be supplied.
-
compute_ranges
( obj , key , ranges ) ¶ -
Given an object, a specific key and the normalization options this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
get_zorder
( overlay , key , el ) ¶ -
Computes the z-order of element in the NdOverlay taking into account possible batching of elements.
-
init_comm
( ) ¶ -
Initializes comm and attaches streams.
-
initialize_plot
( ranges=None ) ¶ -
Initialize the matplotlib figure.
-
inspect_value
= <functools.partial object> ¶
-
matches
( spec ) ¶ -
Matches a specification against the current Plot.
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
push
( ) ¶ -
Pushes updated plot data via the Comm.
-
refresh
( **kwargs ) ¶ -
Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
traverse
( fn=None , specs=None , full_breadth=True ) ¶ -
Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.
-
update_frame
( key , ranges=None ) ¶ -
Set the plot(s) to the given frame number. Operates by manipulating the matplotlib objects held in the self._handles dictionary.
If n is greater than the number of available frames, update using the last available frame.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Boolean
-
class
holoviews.plotting.plot.
Plot
( **params ) [source] ¶ -
Bases:
param.parameterized.Parameterized
Base class of all Plot classes in HoloViews, designed to be general enough to use any plotting package or backend.
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
inspect_value
= <functools.partial object> ¶
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
pprint
( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Variant of __repr__ designed for generating a runnable script.
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
state
¶ -
The plotting state that gets updated via the update method and used by the renderer to generate output.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
update
( key ) [source] ¶ -
Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
renderer
Module
¶
Public API for all plotting renderers supported by HoloViews, regardless of plotting package or backend.
-
class
holoviews.plotting.renderer.
Renderer
( **params ) [source] ¶ -
Bases:
holoviews.core.io.Exporter
The job of a Renderer is to turn the plotting state held within Plot classes into concrete, visual output in the form of the PNG, SVG, MP4 or WebM formats (among others). Note that a Renderer is a type of Exporter and must therefore follow the Exporter interface.
The Renderer needs to be able to use the .state property of the appropriate Plot classes associated with that renderer in order to generate output. The process of ‘drawing’ is execute by the Plots and the Renderer turns the final plotting state into output.
-
param Dict
post_render_hooks
( allow_None=False, constant=False, default={u’svg’: [], u’png’: []}, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False ) - Optional dictionary of hooks that are applied to the rendered data (according to the output format) before it is returned. Each hook is passed the rendered data and the object that is being rendered. These hooks allow post-processing of renderered data before output is saved to file or displayed.
-
param ObjectSelector
holomap
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=auto, instantiate=False, objects=[u’scrubber’, u’widgets’, None, u’auto’], pickle_default_value=True, precedence=None, readonly=False ) - Output render multi-frame (typically animated) format. If None, no multi-frame rendering will occur.
-
param Integer
dpi
( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - The render resolution in dpi (dots per inch)
-
param ObjectSelector
mode
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=default, instantiate=False, objects=[u’default’], pickle_default_value=True, precedence=None, readonly=False ) - The available rendering modes. As a minimum, the ‘default’ mode must be supported.
-
param Callable
info_fn
( allow_None=True, constant=True, instantiate=True, pickle_default_value=True, precedence=None, readonly=False ) - Renderers do not support the saving of object info metadata
-
param ObjectSelector
fig
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=auto, instantiate=False, objects=[u’auto’], pickle_default_value=True, precedence=None, readonly=False ) - Output render format for static figures. If None, no figure rendering will occur.
-
param Number
fps
( allow_None=False, bounds=None, constant=False, default=20, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - Rendered fps (frames per second) for animated formats.
-
param ObjectSelector
widget_mode
( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=embed, instantiate=False, objects=[u’embed’, u’live’], pickle_default_value=True, precedence=None, readonly=False ) - The widget mode determining whether frames are embedded or generated ‘live’ when interacting with the widget.
-
param Callable
key_fn
( allow_None=True, constant=True, default=None, instantiate=True, pickle_default_value=True, precedence=None, readonly=False ) - Renderers do not support the saving of object key metadata
-
param String
backend
( allow_None=False, basestring=<type ‘basestring’>, constant=False, default=, instantiate=False, pickle_default_value=True, precedence=None, readonly=False ) - The full, lowercase name of the rendering backend or third part plotting package used e.g ‘matplotlib’ or ‘cairo’.
-
param Dict
css
( allow_None=False, constant=False, default={}, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False ) - Dictionary of CSS attributes and values to apply to HTML output
-
param Integer
size
( allow_None=False, bounds=None, constant=False, default=100, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> ) - The rendered size as a percentage size
-
debug
( msg , *args , **kw ) ¶ -
Print msg merged with args as a debugging statement.
See Python’s logging module for details of message formatting.
-
defaults
( ) ¶ -
Return {parameter_name:parameter.default} for all non-constant Parameters.
Note that a Parameter for which instantiate==True has its default instantiated.
-
encode
( entry ) ¶ -
Classmethod that applies conditional encoding based on mime-type. Given an entry as returned by __call__ return the data in the appropriate encoding.
-
force_new_dynamic_value
= <functools.partial object> ¶
-
get_param_values
( onlychanged=False ) ¶ -
Return a list of name,value pairs for all Parameters of this object.
If onlychanged is True, will only return values that are not equal to the default value.
-
get_value_generator
= <functools.partial object> ¶
-
html
( obj , fmt=None , css=None , comm=True , **kwargs ) [source] ¶ -
Renders plot or data structure and wraps the output in HTML. The comm argument defines whether the HTML output includes code to initialize a Comm, if the plot supplies one.
-
classmethod
html_assets
( core=True , extras=True , backends=None ) [source] ¶ -
Returns JS and CSS and for embedding of widgets.
-
inspect_value
= <functools.partial object> ¶
-
instance
= <functools.partial object> ¶
-
classmethod
load_nb
( inline=True ) [source] ¶ -
Loads any resources required for display of plots in the Jupyter notebook
-
message
( msg , *args , **kw ) ¶ -
Print msg merged with args as a message.
See Python’s logging module for details of message formatting.
-
params
( parameter_name=None ) ¶ -
Return the Parameters of this class as the dictionary {name: parameter_object}
Includes Parameters from this class and its superclasses.
-
classmethod
plot_options
( obj , percent_size ) [source] ¶ -
Given an object and a percentage size (as supplied by the %output magic) return all the appropriate plot options that would be used to instantiate a plot class for that element.
Default plot sizes at the plotting class level should be taken into account.
-
classmethod
plotting_class
( obj ) [source] ¶ -
Given an object or Element class, return the suitable plotting class needed to render it with the current renderer.
-
pprint
( imports=None , prefix='\n ' , unknown_value='<?>' , qualify=False , separator='' ) ¶ -
Same as Parameterized.pprint, except that X.classname(Y is replaced with X.classname.instance(Y
-
print_param_defaults
( ) ¶ -
Print the default values of all cls’s Parameters.
-
print_param_values
( ) ¶ -
Print the values of all this object’s Parameters.
-
script_repr
( imports=[] , prefix=' ' ) ¶ -
Same as Parameterized.script_repr, except that X.classname(Y is replaced with X.classname.instance(Y
-
set_default
( param_name , value ) ¶ -
Set the default value of param_name.
Equivalent to setting param_name on the class.
-
set_dynamic_time_fn
= <functools.partial object> ¶
-
set_param
= <functools.partial object> ¶
-
classmethod
state
( *args , **kwds ) [source] ¶ -
Context manager to handle global state for a backend, allowing Plot classes to temporarily override that state.
-
state_pop
( ) ¶ -
Restore the most recently saved state.
See state_push() for more details.
-
state_push
( ) ¶ -
Save this instance’s state.
For Parameterized instances, this includes the state of dynamically generated values.
Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().
Generally, this method is used by operations that need to test something without permanently altering the objects’ state.
-
static_html
( obj , fmt=None , template=None ) [source] ¶ -
Generates a static HTML with the rendered object in the supplied format. Allows supplying a template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’.
-
verbose
( msg , *args , **kw ) ¶ -
Print msg merged with args as a verbose message.
See Python’s logging module for details of message formatting.
-
warning
( msg , *args , **kw ) ¶ -
Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.
See Python’s logging module for details of message formatting.
-
param Dict
util
Module
¶
-
holoviews.plotting.util.
attach_streams
( plot , obj , precedence=1.1 ) [source] ¶ -
Attaches plot refresh to all streams on the object.
-
holoviews.plotting.util.
closest_match
( match , specs , depth=0 ) [source] ¶ -
Recursively iterates over type, group, label and overlay key, finding the closest matching spec.
-
holoviews.plotting.util.
compute_overlayable_zorders
( obj , path=[] ) [source] ¶ -
Traverses an overlayable composite container to determine which objects are associated with specific (Nd)Overlay layers by z-order, making sure to take DynamicMap Callables into account. Returns a mapping between the zorders of each layer and a corresponding lists of objects.
Used to determine which overlaid subplots should be linked with Stream callbacks.
-
holoviews.plotting.util.
compute_sizes
( sizes , size_fn , scaling_factor , scaling_method , base_size ) [source] ¶ -
Scales point sizes according to a scaling factor, base size and size_fn, which will be applied before scaling.
-
holoviews.plotting.util.
dim_axis_label
( dimensions , separator=u' , ' ) [source] ¶ -
Returns an axis label for one or more dimensions.
-
holoviews.plotting.util.
displayable
( obj ) [source] ¶ -
Predicate that returns whether the object is displayable or not (i.e whether the object obeys the nesting hierarchy
-
holoviews.plotting.util.
dynamic_update
( plot , subplot , key , overlay , items ) [source] ¶ -
Given a plot, subplot and dynamically generated (Nd)Overlay find the closest matching Element for that plot.
-
holoviews.plotting.util.
get_dynamic_mode
( composite ) [source] ¶ -
Returns the common mode of the dynamic maps in given composite object
-
holoviews.plotting.util.
get_min_distance
( element ) [source] ¶ -
Gets the minimum sampling distance of the x- and y-coordinates in a grid.
-
holoviews.plotting.util.
get_plot_frame
( map_obj , key_map , cached=False ) [source] ¶ -
Returns an item in a HoloMap or DynamicMap given a mapping key dimensons and their values.
-
holoviews.plotting.util.
get_sideplot_ranges
( plot , element , main , ranges ) [source] ¶ -
Utility to find the range for an adjoined plot given the plot, the element, the Element the plot is adjoined to and the dictionary of ranges.
-
holoviews.plotting.util.
initialize_dynamic
( obj ) [source] ¶ -
Initializes all DynamicMap objects contained by the object
-
holoviews.plotting.util.
initialize_unbounded
( obj , dimensions , key ) [source] ¶ -
Initializes any DynamicMaps in unbounded mode.
-
holoviews.plotting.util.
isoverlay_fn
( obj ) [source] ¶ -
Determines whether object is a DynamicMap returning (Nd)Overlay types.
-
holoviews.plotting.util.
map_colors
( arr , crange , cmap , hex=True ) [source] ¶ -
Maps an array of values to RGB hex strings, given a color range and colormap.
-
holoviews.plotting.util.
overlay_depth
( obj ) [source] ¶ -
Computes the depth of a DynamicMap overlay if it can be determined otherwise return None.
-
holoviews.plotting.util.
save_frames
( obj , filename , fmt=None , backend=None , options=None ) [source] ¶ -
Utility to export object to files frame by frame, numbered individually. Will use default backend and figure format by default.
-
holoviews.plotting.util.
traverse_setter
( obj , attribute , value ) [source] ¶ -
Traverses the object and sets the supplied attribute on the object. Supports Dimensioned and DimensionedPlot types.


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Copy from the publisher's testbank and paste into the input textbox
Use the star buttons to select questions, use the edit button to edit them.
Use the button in the top right to download the quiz.
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Welcome to your new project
{{inc}} ({{version}})
The current documentation can be found @ http://neoan.us/neoan3docs
When using the neoan3-cli tool, open a terminal (e.g. cmd on windows), navigate to this installation ({{installation}}) and type "neoan3 new component test".
Then, click here.


Experiment Information
Specify Experiment Title/Description, Organism, and Pubmed ID for keeping track of uploaded data.
What is this?
At PATRIC, you can upload your own pre-processed differential expression datasets generated by microarray, RNA-Seq, or proteomic technologies to your workspace and analyze them using annotations and analysis tools. Currently, PATRIC only supports differential gene expression data in the form of log ratios, generated by comparing samples/conditions/time points. You may also compare your data with other transcriptomics datasets available at PATRIC. Data uploaded in your workspace is private and protected.
Experiment Data
Upload a data file containing differential gene expression values in the form of log ratios. The file should be in one of the supported formats described below. Optionally, you may also upload metadata related to sample comparisons in the prescribed format to help later in the data analysis.
Supported IDs
File Format
Currently, PATRIC allows you to upload your transcriptomics datasets in the form of differential gene expression measured as log ratios. Data can be uploaded in multiple file formats: comma separated values (.csv), tab delimited values (.txt), or Excel (.xls or .xlsx). Click to download Sample Data template in Gene Matrix Format. Files should contain data in one of the following formats:
1. Gene Matrix:
| Gene ID | Comparison1 | Comparison2 |
|---|---|---|
| b0002 | 0.767 | -1.316 |
| b0003 | 0.815 | -1.841 |
| b0004 | 0.856 | -1.643 |
2. Gene List:
Data is presented in three columns: Gene ID, Sample ID, and expression value. Expression value should be in the form of log ratio (i.e. log2 (test/control)). Below is an example of transcriptomics data in Gene List format:
| Gene ID | Comparison ID | Log Ratio |
| b0002 | Comparison1 | 0.767 |
| b0003 | Comparison1 | 0.815 |
| b0002 | Comparison2 | -1.316 |
Experiment Type
This field specifies the the experiment type Transcriptomics, Proteomics, or Phenomics.
ID Type
In order to take full advantage of PATRIC data, gene ID's provided in the experiment data are mapped to PATRIC. Due to differences in annotation that may exist some genes may go unmapped. Unmapped genes will be excluded from subsequent analysis.
File Type
This field specifies whether the uploaded Experiment Data File is tab/comma delimited or an excel file.
Optional Metadata
PATRIC allows you to upload an additional file containing key metadata attributes about the comparisons. This will enhance your analysis when using the Heatmap and clustering tools. The metadata table can be uploaded as a tab/comma delimited or Excel file. Note: The column names should be the same as in the example template. Also, comparison IDs in the metadata file should match those in the data file. Click to download Metadata Template. To see more detailed information go to the FAQs page.


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Flatland
by Edwin A. Abbott
Part 1, Section 6: Of Recognition by Sight
Additional Information
- Year Published: 1885
- Language: English
- Country of Origin: England
- Source: Abbott, E. A. (1885). Flatland.Boston, MA: Roberts Brothers.
-
Readability:
- Flesch–Kincaid Level: 12.0
- Word Count: 1,795
- Genre: Fantasy
- Keywords: geometry
- ✎ Cite This
Downloads
I am about to appear very inconsistent. In the previous sections I have said that all figures in Flatland present the appearance of a straight line; and it was added or implied, that it is consequently impossible to distinguish by the visual organ between individuals of different classes: yet now I am about to explain to my Spaceland critics how we are able to recognize one another by the sense of sight.
If however the Reader will take the trouble to refer to the passage in which Recognition by Feeling is stated to be universal, he will find this qualification — "among the lower classes." It is only among the higher classes and in our more temperate climates that Sight Recognition is practised.
That this power exists in any regions and for any classes is the result of Fog; which prevails during the greater part of the year in all parts save the torrid zones. That which is with you in Spaceland an unmixed evil, blotting out the landscape, depressing the spirits, and enfeebling the health, is by us recognized as a blessing scarcely inferior to air itself, and as the Nurse of arts and Parent os sciences. But let me explain my meaning, without further eulogies on this beneficent Element.
If Fog were non-existent, all lines would appear equally and indistinguishably clear; and this is actually the case in those unhappy countries in which the atmosphere is perfectly dry and transparent. But wherever there is a rich supply of Fog, objects that are at a distance, say of three feet, are appreciably dimmer than those at the distance of two feet eleven inches; and the result is that by careful and constant experimental observation of comparative dimness and constant experimental observation of comparative dimness and clearness, we are enabled to infer with great exactness the configuration of the object observed.
An instance will do more than a volume of generalities to make my meaning clear.
Suppose I see two individuals approaching whose rank I wish to ascertain. They are, we will suppose, a Merchant and a Physician, or in other words, an Equilaterial Triangle and a Pentagon; how am I to distinuish them?
It will be obvious, to every child in Spaceland who has touched the threshold of Geometrical Studies, that, if I can bring my eye so that its glance may bisect an angle (A) of the approaching stranger, my view will lie as it were evenly between the two sides that are next to me (viz. CA and AB), so that I shall contemplate the two impartially, and both will appear of the same size.
Now in the case of (1) the Merchant, what shall I see? I shall see a straight line DAE, in which the middle point (A) will be very bright because it is nearest to me; but on either side the line will shade away rapidly to dimness, because the sides AC and AB recede rapidly into the fog and what appear to me as the Merchant's extremities, viz. D and E, will be very dim indeed.
On the other hand in the case of (2) the Physician, though I shall here also see a line (D'A'E') with a bright centre (A'), yet it will shade away less rapidly to dimness, because the sides (A'C', A'B') recede less rapidly into the fog: and what appear to me the Physician's extremities, viz. D' and E', will not be not so dim as the extremities of the Merchant.
The Reader will probably understand from these two instances how - - after a very long training supplemented by constant experience — it is possible for the well-educated classes among us to discriminate with fair accuracy between the middle and lowest orders, by the sense of sight. If my Spaceland Patrons have grasped this general conception, so far as to conceive the possibility of it and not to reject my account as altogether incredible — I shall have attained all I can reasonably expect. Were I to attempt further details I should only perplex. Yet for the sake of the young and inexperienced, who may perchance infer — from the two simple instances I have given above, of the manner in which I should recognize my Father and my Sons — that Recognition by sight is an easy affair, it may be needful to point out that in actual life most of the problems of Sight Recognition are far more subtle and complex.
If for example, when my Father, the Triangle, approaches me, he happens to present his side to me instead of his angle, then, until I have asked him to rotate, or until I have edged my eye around him, I am for the moment doubtful whether he may not be a Straight Line, or, in other words, a Woman. Again, when I am in the company of one of my two hexagonal Grandsons, contemplating one of his sides (AB) full front, it will be evident from the accompanying diagram that I shall see one whole line (AB) in comparative brightness (shading off hardly at all at the ends) and two smaller lines (CA and BD) dim throughout and shading away into greater dimness towards the extremities C and D.
But I must not give way to the temptating of enlarging on these topics. The meanest mathematician in Spaceland will readily believe me when I assert that the problems of life, which present themselves to the well-educated — when they are themselves in motion, rotating, advancing or retreating, and at the same time attempting to discriminate by the sense of sight between a number of Polygons of high rank moving in different directions, as for example in a ball- room or conversazione — must be of a nature to task the angularity of the most intellectual, and amply justify the rich endowments of the Learned Professors of Geometry, both Static and Kinetic, in the illustrious University of Wentbridge, where the Science and Art of Sight Recognition are regularly taught to large classes of the elite of the States.
It is only a few of the scions of our noblest and wealthies houses, who are able to give the time and money necessary for the thorough prosecution of this noble and valuable Art. Even to me, a Mathematician of no mean standing, and the Granddfather of two most hopeful and perfectly regular Hexagons, to find myself in the midst of a crowd of rotating Polygons of the higher classes, is occasionally very perplexing. And of course to a common Tradesman, or Serf, such a sight is almost as unintelligible as it would be to you, my Reader, were you suddenly transported to my country.
In such a crowd you could see on all sides of you nothing but a Line, apparently straight, but of which the parts would vary irregularly and perpetually in brightness or dimness. Even if you had completed your third year in the Pentagonal and Hexagonal classes in the University, and were perfect in the theory of the subject, you would still find there was need of many years of experience, before you could move in a fashionable crowd without jostling against your betters, whom it is against etiquette to ask to "feel," and who, by their superior culture and breeding, know all about your movements, while you know very little or nothing about theirs. in a word, to comport oneself with perfect propriety in Polygonal society, one ought to be a Polygon oneself. Such at least is the painful teaching of my experience.
It is astonishing how much the Art — or I may almost call it instinct — of Sight Recognition is developed by the habitual practice of it and by the avoidance of the custom of "Feeling." Just as, with you, the deaf and dumb, if once allowed to gesticulate and to use the hand-alphabet, will never acquire the more difficult but far more valuable art of lip-speech and lip-reading, so it is with us as regards "Seeing" and "Feeling." None who in early life resort to "Feeling" will ever learn "Seeing" in perfection.
For this reason, among our Higher Classes, "Feeling" is discouraged or absolutely forbidden. From the cradle their children, instead of going to the Public Elementary schools (where the art of Feeling is taught,) are sent to higher Seminaries of an exclusive character; and at our illustrius University, to "feel" is regarded as a most serious fault, involving Rustication for the first offence, and Expulsion for the second.
But among the lower classes the art of Sight Recognition is regarded as an unattainable luxury. A common Tradesman cannot afford to let his son spend a third of his life in abstract studies. The children of the poor are therefore allowed to "feel" from their earliest years, and they gain thereby a precocity and an early vivacity which contrast at first most favourably with the inert, undeveloped, and listless behaviour of the half-instructed youths of the Polygonal class; but when the latter have at last completed their University course, and are prepared to put their theory into practice, the change that comes over them may almost be described as a new birth, and in every art, science, and social pursuit they rapidly overtake and distance their Triangular competitors.
Only a few of the Polygonal Class fail to pass the Final Test or Leaving Examination at the University. The condition of the unsuccessful minority is truly pitiable. Rejected from the higher class, they are also despised by the lower. They have neither the matured and systematically trained powers of the Polygonal Bachelors and Masters of Arts, nor yet the native precocity and mercurial versatility of the youthful Tradesman. The professions, the public services, are closed against them, and though in most States they are not actually debarred from marriage, yet they have the greatest difficulty in forming suitable alliances, as experience shews that the offspring of such unfortunate and ill-endowed parents is generally itself unfortunate, if not positively Irregular.
It is from these specimens of the refuse of our Nobility that the great Tumults and Seditions of past ages have generally derived their leaders; and so great is the mischief thence arising that an increasing minotiry of our more progressive Statesmen are of opinion that true mercy would dictate their entire suppression, by enacting that all who fail to pass the Final Examination of the University should be either imprisoned for life, or extinguished by a painless death.
But I find myself digressing into the subect of Irregularities, a matter of such vital interest that it demans a separate section.


Delhi Fire tragedy: Court sends property owner, manager to 14-day police custody
by Anand Mohan JWritten by Anand Mohan J | New Delhi | Updated: December 9, 2019 10:26:30 pm
The fire in Delhi’s Anaj Mandi area claimed 43 lives on Sunday. (Express photo)
A Delhi court on Friday sent to 14-days police custody, the property owner of the four-storey building and a manager who were arrested by the police in the aftermath of the Anaj Mandi blaze, which killed 43 people.
The two accused were identified as Rehan, the owner of the building and Fukhran. The police told the court that they needed the two accused person’s custody to ascertain the identity of the people who were given rooms on rent by the accused persons.
“43 innocent people from Bihar, Purnia, Samastipur have died in this blaze. It is a very sensitive issue. We may also have a law and order problem on our hands. We arrested them yesterday and we need their custody otherwise it would be injustice,” Inspector Kumar told the court.
The police have booked them under section 304 and 308 of IPC at Sadar Bazar police station.
The two accused persons were produced around 3:30 pm before Metropolitan Magistrate Manoj Kumar today. The IO in the case, told the court that various units housed in the building mainly compromised of bag making and plastic frame moulding units where around 70-80 people worked.
The police said both the accused persons are childhood friends and have been working together since 2003. They also have prepared a list of various properties that have been given to other people and told the court that some of their names and addresses are not yet ascertained.
Several of the dead are yet to be identified. The police also informed that FSL teams have been deputed to the spot, the premises have been sealed for further investigation.
For all the latest Delhi News, download Indian Express App
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- Tags:
- Delhi fire


IACHAR(3) - [CHARACTER:CONVERSION] Return integer ASCII code of a character
result = iachar(c [,kind])
elemental integer(kind=KIND) function iachar(c,kind)character(len=1),intent(in) :: c integer(kind=**),intent(in),optional :: KIND
NOTE: : a kind designated as ** may be any supported kind for the type
o C is a single character o The return value is of type integer and of kind KIND. If KIND is absent, the return value is of default integer kind.
IACHAR(3) returns the code for the ASCII character in the first character position of C.
o C : A character to determine the ASCII code of. : A common extension is to allow strings but all but the first character is then ignored. o KIND : A constant initialization expression indicating the kind parameter of the result.
the result is the position of the character C in the ASCII collating sequence. It is nonnegative and less than or equal to 127.
By ASCII, it is meant that C is in the collating sequence defined by the codes specified in ISO/IEC 646:1991 (International Reference Version).
The value of the result is processor dependent if C is not in the ASCII collating sequence.
The results are consistent with the LGE(3), LGT(3), LLE(3), and LLT(3) comparison functions. For example, if LLE(C, D) is true, IACHAR(C) <= IACHAR (D) is true where C and D are any two characters representable by the processor.
Sample program:
program demo_iachar implicit none ! basic usage ! just does a string one character long write(*,*)iachar(A) ! elemental: can do an array of letters write(*,*)iachar([A,Z,a,z])Results:! convert all characters to lowercase write(*,(a))lower(abcdefg ABCDEFG) contains ! pure elemental function lower(str) result (string) ! Changes a string to lowercase character(*), intent(In) :: str character(len(str)) :: string integer :: i string = str ! step thru each letter in the string in specified range do i = 1, len(str) select case (str(i:i)) case (A:Z) ! change letter to miniscule string(i:i) = char(iachar(str(i:i))+32) case default end select end do end function lower ! end program demo_iachar
65 65 90 97 122 abcdefg abcdefg
Fortran 95 , with KIND argument - Fortran 2003
ACHAR(3), CHAR(3), ICHAR(3)
See ICHAR(3) in particular for a discussion of converting between numerical values and formatted string representations.
Functions that perform operations on character strings, return lengths of arguments, and search for certain arguments:
fortran-lang intrinsic descriptions (license: MIT) @urbanjost
o ELEMENTAL: ADJUSTL(3), ADJUSTR(3), INDEX(3), SCAN(3), VERIFY(3) o NONELEMENTAL: LEN_TRIM(3), LEN(3), REPEAT(3), TRIM(3)
| Nemo Release 3.1 | iachar (3) | July 22, 2023 |


| head 1 | head 2 | head 4 | head 5 |
|---|---|---|---|
| row 0 | 9 | page 1 | filter A |
| row 1 | 8 | page 1 | filter A |
| row 2 | 7 | page 1 | filter C |
| row 3 | 6 | page 1 | filter A |
| row 4 | 5 | page 2 | filter A |
| row 5 | 4 | page 2 | filter B |
| row 6 | 3 | page 2 | filter B |
| row 7 | 2 | page 2 | filter B |
| row 8 | 1 | page 3 | filter B p |
| row 9 | 0 | page 3 | filter B p |


Universal artifact metadata
Store, query, and retrieve critical metadata about all of your software artifacts, regardless of their type and where they are stored. Get 360-degree visibility across a variety of environments, including on-premises, private, and public cloud clusters.


from django.conf.urls import include, url
from django.contrib import admin
urlpatterns = [
url(r'^polls/', include('polls.urls')),
url(r'^admin/', admin.site.urls),
]
# This global object represents the default admin site, for the common case.
# You can instantiate AdminSite in your own code to create a custom admin site.
site = AdminSite()
THis is where your model ends up if you register it
Protip, remove the 'Delete multiple' action for a nicer layout
from django.contrib import admin
admin.site.disable_action('delete_selected')
def admin_view(self, view, cacheable=False):
"""
Decorator to create an admin view attached to this ``AdminSite``. This
wraps the view and provides permission checking by calling
``self.has_permission``.
You'll want to use this from within ``AdminSite.get_urls()``:
class MyAdminSite(AdminSite):
def get_urls(self):
from django.conf.urls import url
urls = super().get_urls()
urls += [
url(r'^my_view/$', self.admin_view(some_view))
]
return urls
By default, admin_views are marked non-cacheable using the
``never_cache`` decorator. If the view can be safely cached, set
cacheable=True.
"""
def get_urls(self):
...
return urlpatterns
@never_cache
def index(self, request, extra_context=None):
...
return TemplateResponse(request, self.index_template or 'admin/index.html', context)
def each_context(self, request):
"""
Return a dictionary of variables to put in the template context for
*every* page in the admin site.
For sites running on a subpath, use the SCRIPT_NAME value if site_url
hasn't been customized.
"""
def get_urls(self):
..
urlpatterns = [
url(r'^$', wrap(self.changelist_view), name='%s_%s_changelist' % info),
url(r'^add/$', wrap(self.add_view), name='%s_%s_add' % info),
url(r'^(.+)/history/$', wrap(self.history_view), name='%s_%s_history' % info),
url(r'^(.+)/delete/$', wrap(self.delete_view), name='%s_%s_delete' % info),
url(r'^(.+)/change/$', wrap(self.change_view), name='%s_%s_change' % info),
# For backwards compatibility (was the change url before 1.9)
url(r'^(.+)/$', wrap(RedirectView.as_view(
pattern_name='%s:%s_%s_change' % ((self.admin_site.name,) + info)
))),
]
return urlpatterns
@csrf_protect_m
def changelist_view(self, request, extra_context=None):
"""
The 'change list' admin view for this model.
"""
...
return TemplateResponse(request, self.change_list_template or [
'admin/%s/%s/change_list.html' % (app_label, opts.model_name),
'admin/%s/change_list.html' % app_label,
'admin/change_list.html'
], context)
def url_for_result(self, result):
pk = getattr(result, self.pk_attname)
return reverse('admin:%s_%s_change' % (self.opts.app_label,
self.opts.model_name),
args=(quote(pk),),
current_app=self.model_admin.admin_site.name)
Very useful if you'r working with Polymorphic models, also useful if you use the above mentioned proxy model trick but want to keep a single model admin to reduce maintenance
url(r'^add/$', wrap(self.add_view), name='%s_%s_add' % info),
url(r'^(.+)/change/$', wrap(self.change_view), name='%s_%s_change' % info),
Add view and change view both return:
return self.changeform_view(request, None, form_url, extra_context)
return self.changeform_view(request, object_id, form_url, extra_context)
def _changeform_view(self, request, object_id, form_url, extra_context):
...
return self.render_change_form(request, context, add=add, change=not add,
obj=obj, form_url=form_url)
def render_change_form(self, request, context, add=False, change=False, form_url='', obj=None):
...
return TemplateResponse(request, form_template or [
"admin/%s/%s/change_form.html" % (app_label, opts.model_name),
"admin/%s/change_form.html" % app_label,
"admin/change_form.html"
], context)
Easy to extend, add another form to the context page, do validation, etc
Returns a template response
Template response (can be found in django.template.response) contains all the information required to render a template
Easy to read or extend context if you wish
Can be though of as a Formview
Form is generated in def get_form
FunFact, Django just uses a modelform_factory internally
Options can be found in the documentation, no easy way to pass kwargs or overwrite defaults unless you extend this function
Don't get to fancy with shoehorning a lot of stuff into the form, it's usually better to add another form to the page
def get_changeform_initial_data(self, request):
"""
Get the initial form data from the request's GET params.
"""
initial = dict(request.GET.items())
for k in initial:
try:
f = self.model._meta.get_field(k)
except FieldDoesNotExist:
continue
# We have to special-case M2Ms as a list of comma-separated PKs.
if isinstance(f, models.ManyToManyField):
initial[k] = initial[k].split(",")
return initial
Cool Trick, you can prefill fields with URL parameters, e.g ?name=Target%20Holding, see
def get_object(self, request, object_id, from_field=None):
"""
Return an instance matching the field and value provided, the primary
key is used if no field is provided. Return ``None`` if no match is
found or the object_id fails validation.
"""
queryset = self.get_queryset(request)
model = queryset.model
field = model._meta.pk if from_field is None else model._meta.get_field(from_field)
try:
object_id = field.to_python(object_id)
return queryset.get(**{field.name: object_id})
except (model.DoesNotExist, ValidationError, ValueError):
return None
Helper function that return the object
Great place to do customization for non Django admins, e.g exclude debug/test accounts, etc
Cavecat, you cannot register a model twice, use a Proxy model if you want to have filtered views of the same QS
Suprise! The Django admin actually contains a quite decent and robust Admin logging system
Silently logs the Add/Change and Delete actions of all users
Can be really usefull on production sites to debug 'weird' issues. E.g user A changing an option, B reverting the change and then both open an issue that something is broken :)
DO spice it up and log user actions, we use it to log ExamResults recalculations, reseting exams, e.g. Helps to cover your ass and you get if for free!
def log_addition(self, request, object, message):
"""
Log that an object has been successfully added.
The default implementation creates an admin LogEntry object.
"""
def log_change(self, request, object, message):
"""
Log that an object has been successfully changed.
The default implementation creates an admin LogEntry object.
"""
def log_deletion(self, request, object, object_repr):
"""
Log that an object will be deleted. Note that this method must be
called before the deletion.
The default implementation creates an admin LogEntry object.
"""
def history_view(self, request, object_id, extra_context=None):
"The 'history' admin view for this model."
...
return TemplateResponse(request, self.object_history_template or [
"admin/%s/%s/object_history.html" % (app_label, opts.model_name),
"admin/%s/object_history.html" % app_label,
"admin/object_history.html"
], context)
Pro tip: you can easily register django.contrib.admin.models.LogEntry in the admin
Really straight forward, exactly what you would expect from a delete view :)
@csrf_protect_m
def delete_view(self, request, object_id, extra_context=None):
with transaction.atomic(using=router.db_for_write(self.model)):
return self._delete_view(request, object_id, extra_context)
def _delete_view(self, request, object_id, extra_context):
"The 'delete' admin view for this model."
...
return self.render_delete_form(request, context)
Templates are surprisingly easy to overwrite, can be a bit dense at first
'Fairly' safe to do and you can get huge UX wins with small changes
@register(School)
class SchoolAdmin(AccessInlinesAndFieldSetByName, admin.ModelAdmin):
...
class Media:
css = {'screen': ('pretty.css',),
'tv,projector': ('lo_res.css',),
'print': ('newspaper.css',)}
js = ('animations.js', 'actions.js')
from django.utils.text import slugify
class AccessInlinesAndFieldSetByName(object):
"""
This mixin allows you to access both inlines and fieldsets by name instead of
just iterating over them in the template
"""
def render_change_form(self, request, context, add=False, change=False, form_url='', obj=None):
fieldset_dict = {slugify(fieldset.name).replace('-', '_'): fieldset for fieldset in context['adminform']}
context['adminform'].fieldsets = fieldset_dict
inline_admin_formsets_by_name = {type(inline_admin_formset.opts).__name__: inline_admin_formset
for inline_admin_formset in context['inline_admin_formsets']}
context['inline_admin_formsets_by_name'] = inline_admin_formsets_by_name
return super().render_change_form(request, context, add=add, change=change, form_url=form_url, obj=None)
{% extends "admin/change_form.html" %}
{% block field_sets %}
{% with fieldset=adminform.fieldsets.schoolgegevens %}
{% include "admin/includes/fieldset.html" %}
{% endwith %}
{% with inline_admin_formset=inline_admin_formsets_by_name.SchoolContactInlineAdmin %}
{% include inline_admin_formset.opts.template %}
{% endwith %}
{% endblock %}


Lee County announces Principal of the Year and Assistant Principal of the Year
by WFTX Digital TeamFORT MYERS, Fla. -- The School District of Lee County has announced their Principal of the Year and Assistant Principal of the Year for 2019.
Their Principal of the Year is Melissa Robery of East Lee County High School. Robery was appointed to her position in January 2018 and quickly developed a plan. “After reviewing all of the school data, we determined that our focus had to be on individual students. We were going to build relationships, address the needs of individual students, track student data and most importantly tell students every day that we believed in them.”
Five months later, 81% of the senior class got their diplomas and the school missed a “C” grade by .03%. At the end of the 2018-2019 school year East Lee had improved enough to easily earn a “C” and be removed from state supervision.
“More importantly,” Robery says, “Staff and students are excited to come to school, student attendance percentages continue to increase from the previous year’s attendance, each cycle, and the total number of discipline referrals have dropped dramatically.”
The Assistant Pricipal of the Year is Jackson Morgan of Lehigh Elementary. He was appointed in 2014 after ten years of teaching in various elementary schools.
At the time, he says scores were on the decline, behavior was interfering with instruction and teachers were unhappy. “As a former special education teacher,” Jackson says, “I was particularly keen on helping my teachers become better teachers for those students. I immediately began working with these teachers and our academic coaches to support them. I focused on providing teachers with professional development in the curriculum they used and provided coaching support.”
Teacher retention is now at all-time high at Lehigh Elementary, while student performance and behavior are improving.
Nominations for Robery as Florida Principal of the Year and Morgan as Florida Assistant Principal of the Year will be sent to the Florida Department of Education by Superintendent Dr. Greg Adkins.
The DOE will announce the finalists in January and the winners by early March. Each award comes with a $5,000 cash prize.


2D Platformer
Here is a list of all documented class members with links to the class documentation for each member:
- m -
m_body :
PhysicalThing
m_Bullets :
Game
m_BulletTexture :
Game
m_chests :
Game
m_ChestTexture :
Game
m_code :
Game
m_coins :
Game
m_CoinTexture :
Game
m_debug :
Game
m_debugDraw :
Game
,
SFMLDebugDraw
m_delete :
Bullet
,
Coins
,
EnemyBullet
,
EnemyMarkI
m_Direction :
Game
m_direction :
Ray
m_EBullets :
Game
m_Enemy :
Game
m_esensor :
Game
m_kinematicBlocks :
Game
m_line :
Ray
m_listener :
Game
m_mainView :
Game
m_maxLength :
Ray
m_numberState :
Hud
m_PlayerOne :
Game
m_pWorld :
Game
,
Ray
,
SFMLDebugDraw
m_ray :
Game
m_shapes :
DebugDraw
m_staticBlocks :
Game
m_stopped :
Player
m_type :
EnemyMarkI
m_worldSize :
Game
mk_fDensity :
PhysicalThing
mk_fFriction :
PhysicalThing
mk_fRestitution :
PhysicalThing
mk_gravity :
Game
mk_iPosIterations :
Game
mk_iVelIterations :
Game
Generated by
1.8.16


#assign subtitle = "ServerConfig"> <#assign serverconfig = "true">
Configuration of EbeanServer instances is defined by the ServerConfig
bean. It has a series of
getters and setters for all the configuration options available.
In code terms a new ServerConfig instance is created and configured by either caller setter methods or
loading configuration from ebean.properties or external properties. Finally EbeanServerFactory
is used to take the ServerConfig and create an EbeanServer
instance.
The ServerConfig.loadFromProperties()
loads configuration from ebean.properties
file.
This is can be used where some properties are set via code (calling setter methods on ServerConfig)
and some from ebean.properties.
ServerConfig config = new ServerConfig(); config.setName("pg"); ... // load configuration from ebean.properties // using "pg" as the server name config.loadFromProperties(); ... EbeanServer server = EbeanServerFactory.create(config);
You can have an external mechanism for loading Properties
and supply this to ServerConfig via:
ServerConfig.loadFromProperties(Properties)
. This is can be used where some configuration is set
via the externally loaded properties and some is set via code (calling setter methods on ServerConfig).
// load properties externally Properties externalProps = ...; ServerConfig config = new ServerConfig(); config.setName("pg"); ... // load configuration from external properties // using "pg" as the server name config.loadFromProperties(externalProps); ... EbeanServer server = EbeanServerFactory.create(config);
By default ServerConfig has register=true and this means that the EbeanServer instance is registered with
the Ebean singleton and can be later accessed via Ebean.getServer(serverName)
You need to explicitly ServerConfig.setRegister(false) if you don't this feature.
ServerConfig config = new ServerConfig(); config.setName("pg"); ... EbeanServer server = EbeanServerFactory.create(config); ... // Later on we can get the server instance // using it's name via Ebean EbeanServer server = Ebean.getServer("pg");
You can set ServerConfig.setDefaultServer(true) to indicate that the EbeanServer instance created should
be the 'default' EbeanServer and can be later accessed via Ebean.getDefaultServer()
ServerConfig config = new ServerConfig(); config.setName("pg"); config.setDefaultServer(true); ... EbeanServer server = EbeanServerFactory.create(config); ... // Later on we can get the server instance ... EbeanServer server = Ebean.getDefaultServer(); // Note: serverName of null is the same as getting the default server EbeanServer server = Ebean.getServer(null);
For dependency injection with Guice, Spring and similar DI frameworks typically a "provider" or "factory"
is required that creates a ServerConfig, configures it as required perhaps using ebean.properties or
external properties and then uses EbeanServerFactory
to create the EbeanServer instance.
It is common and expected that you want to be able to both @Inject
EbeanServer
instances in the traditional DI coding style and also use the active record style. This can be done
when the EbeanServer instances are created with register
as true and one instance marked
as the default server
.


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We're glad you've visited NM Outdoors! Our goal with this web application is to serve outdoor enthusiasts everywhere in their search for recreational areas in the great state of New Mexico, and find activities associated with those sites. We invite users to also create profiles within the application and leave ratings and comments on recreational areas as a way to contribute information to the local outdoor community.
Sarah is a Software Developer who has eagerly jumped into the tech world head first. She lives on the family ranch and still considers herself a cow whisperer. She continues to pursue coding opportunities in personal projects and group projects and thoroughly enjoyed the process of NM-Outdoors. She hopes it will be a great application for outdoor adventurers like herself!
Ryo is a Web Dev, Designer, and Front-End Engineer who loves working on creating new user interaction and interfaces merging creativity and intuitiveness to deliver totally new digital experiences. He's based out of Albuquerque, and loves any chance to work with the tech community and learn new things! Check out his site below 👇
Mr. Bashir Shafii, is the co-founder and CTO of Black Swan Solutions, Inc in Bloomington, MN. He is a seasoned technology professional who has helped Fortune 500 companies implement major technology projects. He has consulted for clients such as CIGNA, Merrill, Cargill, Ameriprise, UCare, Prime Therapeutics, Optum, Questar and Blue Cross Blue Shield of MN. He holds the following certifications: IIBA Certified Business Analysis Professional, ITIL V3 Foundation, Microsoft SQL Server and Scrum Master. Mr. Shafii earned a Bachelor of Science in Psychology from the University of North Dakota at Grand Forks, ND and is a candidate for the Master of Software Engineering at North Dakota State University.
Joy is actively transitioning from a military career into the software development industry, honing her technical skills in the languages and tools required of a fullstack software developer. There is little she loves more than being presented with a problem and being challenged to find a way to overcome it. This passion manifests itself in a love for knowledge and education, for creating and developing solutions, and even for activities such as exploring the world (to include the great outdoors!) or solving escape rooms. To find out more about Joy, view her professional profile at the link below.


FFBE Rank
Home
(current)
Physical
Mages
Supports
Tanks
Unit Listing
Clear List
Unit Rankings
Physical Chainers:
Rank the Units Here
Physical Finishers:
Magical Chainers:
Magical Finisher:
Healers:
Buffers:
Breakers:
Physical Cover:
Magical Cover:
Provoke: