import _plotly_utils.basevalidators

class ZsrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='zsrc', parent_name='volume', **kwargs):

super(ZsrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class ZValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(self, plotly_name='z', parent_name='volume', **kwargs):

super(ZValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc+clearAxisTypes'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class YsrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='ysrc', parent_name='volume', **kwargs):

super(YsrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class YValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(self, plotly_name='y', parent_name='volume', **kwargs):

super(YValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc+clearAxisTypes'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class XsrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='xsrc', parent_name='volume', **kwargs):

super(XsrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class XValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(self, plotly_name='x', parent_name='volume', **kwargs):

super(XValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc+clearAxisTypes'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class VisibleValidator(_plotly_utils.basevalidators.EnumeratedValidator):

def __init__(self, plotly_name='visible', parent_name='volume', **kwargs):

super(VisibleValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

values=kwargs.pop('values', [True, False, 'legendonly']),

**kwargs

)

import _plotly_utils.basevalidators

class ValuesrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='valuesrc', parent_name='volume', **kwargs):

super(ValuesrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class ValueValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(self, plotly_name='value', parent_name='volume', **kwargs):

super(ValueValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc+clearAxisTypes'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator):

def __init__(

self, plotly_name='uirevision', parent_name='volume', **kwargs

):

super(UirevisionValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class UidValidator(_plotly_utils.basevalidators.StringValidator):

def __init__(self, plotly_name='uid', parent_name='volume', **kwargs):

super(UidValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

anim=kwargs.pop('anim', True),

edit_type=kwargs.pop('edit_type', 'plot'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class TextsrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='textsrc', parent_name='volume', **kwargs):

super(TextsrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class TextValidator(_plotly_utils.basevalidators.StringValidator):

def __init__(self, plotly_name='text', parent_name='volume', **kwargs):

super(TextValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

array_ok=kwargs.pop('array_ok', True),

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class SurfaceValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='surface', parent_name='volume', **kwargs):

super(SurfaceValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Surface'),

data_docs=kwargs.pop(

'data_docs', """

count

Sets the number of iso-surfaces between minimum

and maximum iso-values. By default this value

is 2 meaning that only minimum and maximum

surfaces would be drawn.

fill

Sets the fill ratio of the iso-surface. The

default fill value of the surface is 1 meaning

that they are entirely shaded. On the other

hand Applying a `fill` ratio less than one

would allow the creation of openings parallel

to the edges.

pattern

Sets the surface pattern of the iso-surface 3-D

sections. The default pattern of the surface is

`all` meaning that the rest of surface elements

would be shaded. The check options (either 1 or

2) could be used to draw half of the squares on

the surface. Using various combinations of

capital `A`, `B`, `C`, `D` and `E` may also be

used to reduce the number of triangles on the

iso-surfaces and creating other patterns of

interest.

show

Hides/displays surfaces between minimum and

maximum iso-values.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class StreamValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='stream', parent_name='volume', **kwargs):

super(StreamValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Stream'),

data_docs=kwargs.pop(

'data_docs', """

maxpoints

Sets the maximum number of points to keep on

the plots from an incoming stream. If

`maxpoints` is set to 50, only the newest 50

points will be displayed on the plot.

token

The stream id number links a data trace on a

plot with a stream. See

https://plot.ly/settings for more details.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class SpaceframeValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(

self, plotly_name='spaceframe', parent_name='volume', **kwargs

):

super(SpaceframeValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Spaceframe'),

data_docs=kwargs.pop(

'data_docs', """

fill

Sets the fill ratio of the `spaceframe`

elements. The default fill value is 1 meaning

that they are entirely shaded. Applying a

`fill` ratio less than one would allow the

creation of openings parallel to the edges.

show

Displays/hides tetrahedron shapes between

minimum and maximum iso-values. Often useful

when either caps or surfaces are disabled or

filled with values less than 1.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class SlicesValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='slices', parent_name='volume', **kwargs):

super(SlicesValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Slices'),

data_docs=kwargs.pop(

'data_docs', """

x

plotly.graph_objs.volume.slices.X instance or

dict with compatible properties

y

plotly.graph_objs.volume.slices.Y instance or

dict with compatible properties

z

plotly.graph_objs.volume.slices.Z instance or

dict with compatible properties

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class ShowscaleValidator(_plotly_utils.basevalidators.BooleanValidator):

def __init__(

self, plotly_name='showscale', parent_name='volume', **kwargs

):

super(ShowscaleValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class SceneValidator(_plotly_utils.basevalidators.SubplotidValidator):

def __init__(self, plotly_name='scene', parent_name='volume', **kwargs):

super(SceneValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

dflt=kwargs.pop('dflt', 'scene'),

edit_type=kwargs.pop('edit_type', 'calc+clearAxisTypes'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class ReversescaleValidator(_plotly_utils.basevalidators.BooleanValidator):

def __init__(

self, plotly_name='reversescale', parent_name='volume', **kwargs

):

super(ReversescaleValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'style'),

**kwargs

)

import _plotly_utils.basevalidators

class OpacityscaleValidator(_plotly_utils.basevalidators.AnyValidator):

def __init__(

self, plotly_name='opacityscale', parent_name='volume', **kwargs

):

super(OpacityscaleValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'style'),

**kwargs

)

import _plotly_utils.basevalidators

class OpacityValidator(_plotly_utils.basevalidators.NumberValidator):

def __init__(self, plotly_name='opacity', parent_name='volume', **kwargs):

super(OpacityValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

max=kwargs.pop('max', 1),

min=kwargs.pop('min', 0),

role=kwargs.pop('role', 'style'),

**kwargs

)

import _plotly_utils.basevalidators

class NameValidator(_plotly_utils.basevalidators.StringValidator):

def __init__(self, plotly_name='name', parent_name='volume', **kwargs):

super(NameValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'style'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class MetasrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='metasrc', parent_name='volume', **kwargs):

super(MetasrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class MetaValidator(_plotly_utils.basevalidators.AnyValidator):

def __init__(self, plotly_name='meta', parent_name='volume', **kwargs):

super(MetaValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

array_ok=kwargs.pop('array_ok', True),

edit_type=kwargs.pop('edit_type', 'plot'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class LightpositionValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(

self, plotly_name='lightposition', parent_name='volume', **kwargs

):

super(LightpositionValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Lightposition'),

data_docs=kwargs.pop(

'data_docs', """

x

Numeric vector, representing the X coordinate

for each vertex.

y

Numeric vector, representing the Y coordinate

for each vertex.

z

Numeric vector, representing the Z coordinate

for each vertex.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class LightingValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='lighting', parent_name='volume', **kwargs):

super(LightingValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Lighting'),

data_docs=kwargs.pop(

'data_docs', """

ambient

Ambient light increases overall color

visibility but can wash out the image.

diffuse

Represents the extent that incident rays are

reflected in a range of angles.

facenormalsepsilon

Epsilon for face normals calculation avoids

math issues arising from degenerate geometry.

fresnel

Represents the reflectance as a dependency of

the viewing angle; e.g. paper is reflective

when viewing it from the edge of the paper

(almost 90 degrees), causing shine.

roughness

Alters specular reflection; the rougher the

surface, the wider and less contrasty the

shine.

specular

Represents the level that incident rays are

reflected in a single direction, causing shine.

vertexnormalsepsilon

Epsilon for vertex normals calculation avoids

math issues arising from degenerate geometry.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class IsominValidator(_plotly_utils.basevalidators.NumberValidator):

def __init__(self, plotly_name='isomin', parent_name='volume', **kwargs):

super(IsominValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class IsomaxValidator(_plotly_utils.basevalidators.NumberValidator):

def __init__(self, plotly_name='isomax', parent_name='volume', **kwargs):

super(IsomaxValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class IdssrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(self, plotly_name='idssrc', parent_name='volume', **kwargs):

super(IdssrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class IdsValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(self, plotly_name='ids', parent_name='volume', **kwargs):

super(IdsValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

anim=kwargs.pop('anim', True),

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class HovertextsrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(

self, plotly_name='hovertextsrc', parent_name='volume', **kwargs

):

super(HovertextsrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class HovertextValidator(_plotly_utils.basevalidators.StringValidator):

def __init__(

self, plotly_name='hovertext', parent_name='volume', **kwargs

):

super(HovertextValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

array_ok=kwargs.pop('array_ok', True),

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class HovertemplatesrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(

self, plotly_name='hovertemplatesrc', parent_name='volume', **kwargs

):

super(HovertemplatesrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class HovertemplateValidator(_plotly_utils.basevalidators.StringValidator):

def __init__(

self, plotly_name='hovertemplate', parent_name='volume', **kwargs

):

super(HovertemplateValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

array_ok=kwargs.pop('array_ok', True),

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class HoverlabelValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(

self, plotly_name='hoverlabel', parent_name='volume', **kwargs

):

super(HoverlabelValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Hoverlabel'),

data_docs=kwargs.pop(

'data_docs', """

align

Sets the horizontal alignment of the text

content within hover label box. Has an effect

only if the hover label text spans more two or

more lines

alignsrc

Sets the source reference on plot.ly for align

.

bgcolor

Sets the background color of the hover labels

for this trace

bgcolorsrc

Sets the source reference on plot.ly for

bgcolor .

bordercolor

Sets the border color of the hover labels for

this trace.

bordercolorsrc

Sets the source reference on plot.ly for

bordercolor .

font

Sets the font used in hover labels.

namelength

Sets the default length (in number of

characters) of the trace name in the hover

labels for all traces. -1 shows the whole name

regardless of length. 0-3 shows the first 0-3

characters, and an integer >3 will show the

whole name if it is less than that many

characters, but if it is longer, will truncate

to `namelength - 3` characters and add an

ellipsis.

namelengthsrc

Sets the source reference on plot.ly for

namelength .

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class HoverinfosrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(

self, plotly_name='hoverinfosrc', parent_name='volume', **kwargs

):

super(HoverinfosrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator):

def __init__(

self, plotly_name='hoverinfo', parent_name='volume', **kwargs

):

super(HoverinfoValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

array_ok=kwargs.pop('array_ok', True),

edit_type=kwargs.pop('edit_type', 'calc'),

extras=kwargs.pop('extras', ['all', 'none', 'skip']),

flags=kwargs.pop('flags', ['x', 'y', 'z', 'text', 'name']),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class FlatshadingValidator(_plotly_utils.basevalidators.BooleanValidator):

def __init__(

self, plotly_name='flatshading', parent_name='volume', **kwargs

):

super(FlatshadingValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'style'),

**kwargs

)

import _plotly_utils.basevalidators

class CustomdatasrcValidator(_plotly_utils.basevalidators.SrcValidator):

def __init__(

self, plotly_name='customdatasrc', parent_name='volume', **kwargs

):

super(CustomdatasrcValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'none'),

role=kwargs.pop('role', 'info'),

**kwargs

)

import _plotly_utils.basevalidators

class CustomdataValidator(_plotly_utils.basevalidators.DataArrayValidator):

def __init__(

self, plotly_name='customdata', parent_name='volume', **kwargs

):

super(CustomdataValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

role=kwargs.pop('role', 'data'),

**kwargs

)

import _plotly_utils.basevalidators

class ContourValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='contour', parent_name='volume', **kwargs):

super(ContourValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'Contour'),

data_docs=kwargs.pop(

'data_docs', """

color

Sets the color of the contour lines.

show

Sets whether or not dynamic contours are shown

on hover

width

Sets the width of the contour lines.

"""

),

**kwargs

)

import _plotly_utils.basevalidators

class ColorscaleValidator(_plotly_utils.basevalidators.ColorscaleValidator):

def __init__(

self, plotly_name='colorscale', parent_name='volume', **kwargs

):

super(ColorscaleValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

edit_type=kwargs.pop('edit_type', 'calc'),

implied_edits=kwargs.pop(

'implied_edits', {'autocolorscale': False}

),

role=kwargs.pop('role', 'style'),

**kwargs

)

import _plotly_utils.basevalidators

class ColorBarValidator(_plotly_utils.basevalidators.CompoundValidator):

def __init__(self, plotly_name='colorbar', parent_name='volume', **kwargs):

super(ColorBarValidator, self).__init__(

plotly_name=plotly_name,

parent_name=parent_name,

data_class_str=kwargs.pop('data_class_str', 'ColorBar'),

data_docs=kwargs.pop(

'data_docs', """

bgcolor

Sets the color of padded area.

bordercolor

Sets the axis line color.

borderwidth

Sets the width (in px) or the border enclosing

this color bar.

dtick

Sets the step in-between ticks on this axis.

Use with `tick0`. Must be a positive number, or

special strings available to "log" and "date"

axes. If the axis `type` is "log", then ticks

are set every 10^(n*dtick) where n is the tick

number. For example, to set a tick mark at 1,

10, 100, 1000, ... set dtick to 1. To set tick

marks at 1, 100, 10000, ... set dtick to 2. To

set tick marks at 1, 5, 25, 125, 625, 3125, ...

set dtick to log_10(5), or 0.69897000433. "log"

has several special values; "L<f>", where `f`

is a positive number, gives ticks linearly

spaced in value (but not position). For example

`tick0` = 0.1, `dtick` = "L0.5" will put ticks

at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10

plus small digits between, use "D1" (all

digits) or "D2" (only 2 and 5). `tick0` is

ignored for "D1" and "D2". If the axis `type`

is "date", then you must convert the time to

milliseconds. For example, to set the interval

between ticks to one day, set `dtick` to

86400000.0. "date" also has special values

"M<n>" gives ticks spaced by a number of

months. `n` must be a positive integer. To set

ticks on the 15th of every third month, set

`tick0` to "2000-01-15" and `dtick` to "M3". To

set ticks every 4 years, set `dtick` to "M48"

exponentformat

Determines a formatting rule for the tick

exponents. For example, consider the number

1,000,000,000. If "none", it appears as

1,000,000,000. If "e", 1e+9. If "E", 1E+9. If

"power", 1x10^9 (with 9 in a super script). If

"SI", 1G. If "B", 1B.

len

Sets the length of the color bar This measure

excludes the padding of both ends. That is, the

color bar length is this length minus the

padding on both ends.

lenmode

Determines whether this color bar's length

(i.e. the measure in the color variation

direction) is set in units of plot "fraction"

or in *pixels. Use `len` to set the value.

nticks

Specifies the maximum number of ticks for the

particular axis. The actual number of ticks

will be chosen automatically to be less than or

equal to `nticks`. Has an effect only if

`tickmode` is set to "auto".

outlinecolor

Sets the axis line color.

outlinewidth

Sets the width (in px) of the axis line.

separatethousands

If "true", even 4-digit integers are separated

showexponent

If "all", all exponents are shown besides their

significands. If "first", only the exponent of

the first tick is shown. If "last", only the

exponent of the last tick is shown. If "none",

no exponents appear.

showticklabels

Determines whether or not the tick labels are

drawn.

showtickprefix

If "all", all tick labels are displayed with a

prefix. If "first", only the first tick is

displayed with a prefix. If "last", only the

last tick is displayed with a suffix. If

"none", tick prefixes are hidden.

showticksuffix

Same as `showtickprefix` but for tick suffixes.

thickness

Sets the thickness of the color bar This

measure excludes the size of the padding, ticks

and labels.

thicknessmode

Determines whether this color bar's thickness

(i.e. the measure in the constant color

direction) is set in units of plot "fraction"

or in "pixels". Use `thickness` to set the

value.

tick0

Sets the placement of the first tick on this

axis. Use with `dtick`. If the axis `type` is

"log", then you must take the log of your

starting tick (e.g. to set the starting tick to

100, set the `tick0` to 2) except when

`dtick`=*L<f>* (see `dtick` for more info). If

the axis `type` is "date", it should be a date

string, like date data. If the axis `type` is

"category", it should be a number, using the

scale where each category is assigned a serial

number from zero in the order it appears.

tickangle

Sets the angle of the tick labels with respect

to the horizontal. For example, a `tickangle`

of -90 draws the tick labels vertically.

tickcolor

Sets the tick color.

tickfont

Sets the color bar's tick label font

tickformat

Sets the tick label formatting rule using d3

formatting mini-languages which are very

similar to those in Python. For numbers, see: h

ttps://github.com/d3/d3-format/blob/master/READ

ME.md#locale_format And for dates see:

https://github.com/d3/d3-time-

format/blob/master/README.md#locale_format We

add one item to d3's date formatter: "%{n}f"

for fractional seconds with n digits. For

example, *2016-10-13 09:15:23.456* with

tickformat "%H~%M~%S.%2f" would display

"09~15~23.46"

tickformatstops

plotly.graph_objs.volume.colorbar.Tickformatsto

p instance or dict with compatible properties

tickformatstopdefaults

When used in a template (as layout.template.dat

a.volume.colorbar.tickformatstopdefaults), sets

the default property values to use for elements

of volume.colorbar.tickformatstops

ticklen

Sets the tick length (in px).

tickmode

Sets the tick mode for this axis. If "auto",

the number of ticks is set via `nticks`. If