Safe Haskell	None
Language	Haskell2010

Graphics.Matplotlib

Contents

Creating custom plots and applying options

Description

Matplotlib bindings and an interface to easily bind to new portions of the API. The most essential parts of Matplotlib are wrapped and exposed to Haskell through an interface that allows extenisbility. Code is generated on the fly and python is called.

This is not a very Haskell-ish library. Type safety is non-existent, it's easy to generate incorrect Python code, in exchange for being able to bind to arbitrary matplotlib APIs with ease, so it's also easy to generate correct python code.

The generated code follows a few simple conventions. data is always loaded into a data variable that is a python array. Data is transffered via json. This data variable is indexed by various rendering commands.

Functions which start with the word data operate on the data array, arguments are python code that should access that array. Most other functions take haskell objects and load them into python.

This module should expose enough tools so that you can bind any part of the matplotlib API. A binding with options, such as that of plot, looks like:

  readData (x, y)
  % mp # "p = plot.plot(data[" # a # "], data[" # b # "]" ## ")"
  % mp # "plot.xlabel(" # str label # ")"

Where important functions are:

readData: Load the given data into the python data array by serializing it to JSON.
%: Sequence two plots
mp: Create an empty plot
#: Append python code to the last command in a plot
##: Just like # but also adds in a placeholder for an options list

You can call this plot with

plot [1,2,3,4,5,6] [1,3,2,5,2] @@ [o1 "go-", o2 "linewidth" 2]

where @@ applies an options list replacing the last ##

o1: A single positional option. The value is rendered into python as the appropriate datatype. Strings become python strings, bools become bools, etc. If you want to insert code verbatim into an option use lit. If you want to have a raw string with no escapes use raw.
o2: A keyword option. The key is always a string, the value is treated the same way that the option in o1 is treated.

Right now there's no easy way to bind to an option other than the last one unless you want to pass options in as parameters.

The generated Python code should follow some invariants. It must maintain the current figure in "fig", all available axes in "axes", and the current axis in "ax". Plotting commands should use the current axis, never the plot itself; the two APIs are almost identical. When creating low-level bindings one must remember to call "plot.sci" to set the current image when plotting a graph. The current spine of the axes that's being manipulated is in "spine". The current quiver is in "q"

Synopsis

onscreen :: Matplotlib -> IO ()
code :: Matplotlib -> IO String
file :: [Char] -> Matplotlib -> IO (Either String String)
toSvg :: Matplotlib -> IO (Either String String)
xacorr :: (ToJSON a, ToJSON b) => a -> b -> [Option] -> Matplotlib
histogram :: (MplotValue val, ToJSON t) => t -> val -> Matplotlib
histogram2D :: ToJSON a => a -> a -> Matplotlib
scatter :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib
bar :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib
line :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib
errorbar :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d) => a -> b -> c -> d -> Matplotlib
lineF :: (ToJSON a, ToJSON b) => (a -> b) -> [a] -> Matplotlib
boxplot :: ToJSON a => a -> Matplotlib
violinplot :: ToJSON a => a -> Matplotlib
contourF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib
projectionsF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib
plotInterpolated :: (MplotValue val, ToJSON t, ToJSON t1) => t1 -> t -> val -> Matplotlib
plotMapLinear :: ToJSON b => (Double -> b) -> Double -> Double -> Double -> Matplotlib
line1 :: (Foldable t, ToJSON (t a)) => t a -> Matplotlib
matShow :: ToJSON a => a -> Matplotlib
imshow :: MplotImage a => a -> Matplotlib
pcolor :: ToJSON a => a -> Matplotlib
pcolor3 :: (ToJSON a, ToJSON b, ToJSON c) => a -> b -> c -> Matplotlib
nonUniformImage :: (ToJSON a, ToJSON b, ToJSON c) => a -> b -> c -> Matplotlib
pie :: (ToJSON val, MplotValue val) => val -> Matplotlib
density :: [Double] -> Maybe (Double, Double) -> Matplotlib
rc :: String -> Matplotlib
setParameter :: MplotValue val => String -> val -> Matplotlib
setTeX :: Bool -> Matplotlib
dataPlot :: (MplotValue val, MplotValue val1) => val1 -> val -> Matplotlib
plot :: (ToJSON t, ToJSON t1) => t1 -> t -> Matplotlib
streamplot :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d) => a -> b -> c -> d -> Matplotlib
dateLine :: (ToJSON t1, ToJSON t2) => t1 -> t2 -> String -> (Int, Int, Int) -> Matplotlib
dataHistogram :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
dataScatter :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
dataLine :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
contour :: (ToJSON (t2 (t3 val1)), ToJSON (t4 (t5 val2)), ToJSON (t6 (t7 val3)), MplotValue val2, MplotValue val1, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t3 val1), Ord (t5 val2), Ord (t7 val3), Foldable t2, Foldable t3, Foldable t4, Foldable t5, Foldable t6, Foldable t7) => t2 (t3 val1) -> t4 (t5 val2) -> t6 (t7 val3) -> Matplotlib
projections :: (ToJSON (t2 (t3 val1)), ToJSON (t4 (t5 val2)), ToJSON (t6 (t7 val3)), MplotValue val2, MplotValue val1, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t3 val1), Ord (t5 val2), Ord (t7 val3), Foldable t2, Foldable t3, Foldable t4, Foldable t5, Foldable t6, Foldable t7) => t2 (t3 val1) -> t4 (t5 val2) -> t6 (t7 val3) -> Matplotlib
wireframe :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib
surface :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib
contourRaw :: (MplotValue val1, MplotValue val2, MplotValue val5, MplotValue val4, MplotValue val3, MplotValue val) => val5 -> val4 -> val3 -> val2 -> val1 -> val -> Matplotlib
subplotDataBar :: (MplotValue val1, MplotValue val2, MplotValue val3) => val2 -> val1 -> val3 -> [Option] -> Matplotlib
barDefaultWidth :: (Fractional a1, Integral a2) => a2 -> a1
subplotBarsLabelled :: (ToJSON (t a), Foldable t, MplotValue val) => [t a] -> val -> [[Option]] -> Matplotlib
subplotBars :: ToJSON a => [a] -> [[Option]] -> Matplotlib
interpolate :: (MplotValue val, MplotValue val2, MplotValue val1) => val2 -> val1 -> val -> Matplotlib
densityBandwidth :: [Double] -> Double -> Maybe (Double, Double) -> Matplotlib
xcorr :: (ToJSON a, ToJSON b) => a -> b -> Matplotlib
acorr :: ToJSON a => a -> Matplotlib
quiver :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d, ToJSON e) => a -> b -> c -> d -> Maybe e -> Matplotlib
quiverKey :: (MplotValue val1, MplotValue val2, MplotValue val3, MplotValue val4) => val4 -> val3 -> val2 -> val1 -> Matplotlib
text :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> String -> Matplotlib
figText :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> String -> Matplotlib
annotate :: String -> Matplotlib
setAspect :: Matplotlib
squareAxes :: Matplotlib
roateAxesLabels :: MplotValue val => val -> Matplotlib
verticalAxes :: Matplotlib
logX :: Matplotlib
logY :: Matplotlib
xlim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
ylim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
axhline :: MplotValue val => val -> Matplotlib
legend :: Matplotlib
colorbar :: Matplotlib
title :: String -> Matplotlib
grid :: Bool -> Matplotlib
axis3DProjection :: Matplotlib
axis3DLabels :: (MplotValue val1, MplotValue val2, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t2 val1), Ord (t3 val2), Ord (t4 val3), Foldable t5, Foldable t2, Foldable t6, Foldable t3, Foldable t7, Foldable t4) => t5 (t2 val1) -> t6 (t3 val2) -> t7 (t4 val3) -> Matplotlib
xlabel :: String -> Matplotlib
ylabel :: String -> Matplotlib
zlabel :: String -> Matplotlib
setSizeInches :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib
tightLayout :: Matplotlib
xkcd :: Matplotlib
xticks :: MplotValue val => val -> Matplotlib
yticks :: MplotValue val => val -> Matplotlib
zticks :: MplotValue val => val -> Matplotlib
xtickLabels :: MplotValue val => val -> Matplotlib
ytickLabels :: MplotValue val => val -> Matplotlib
ztickLabels :: MplotValue val => val -> Matplotlib
axisXTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
axisXTickLabels :: MplotValue val => val -> Matplotlib
axisYTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib
axisYTickLabels :: MplotValue val => val -> Matplotlib
axisXTicksPosition :: MplotValue val => val -> Matplotlib
axisYTicksPosition :: MplotValue val => val -> Matplotlib
spine :: MplotValue val => val -> Matplotlib
spineSetBounds :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib
spineSetVisible :: MplotValue val => val -> Matplotlib
spineSetPosition :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib
setAx :: Matplotlib
addSubplot :: (MplotValue val1, MplotValue val2, MplotValue val3) => val3 -> val2 -> val1 -> Matplotlib
getSubplot :: (MplotValue val1, MplotValue val2, MplotValue val3) => val3 -> val2 -> val1 -> Matplotlib
subplots :: Matplotlib
setSubplot :: MplotValue val => val -> Matplotlib
axes :: Matplotlib
addAxes :: Matplotlib
figure :: Matplotlib
data Matplotlib
data Option
(@@) :: Matplotlib -> [Option] -> Matplotlib
(%) :: Matplotlib -> Matplotlib -> Matplotlib
o1 :: MplotValue val => val -> Option
o2 :: MplotValue val => String -> val -> Option
(##) :: MplotValue val => Matplotlib -> val -> Matplotlib
(#) :: MplotValue val => Matplotlib -> val -> Matplotlib
mp :: Matplotlib
def :: Matplotlib -> [Option] -> Matplotlib
readData :: ToJSON a => a -> Matplotlib
readImage :: MplotImage i => i -> Matplotlib
str :: String -> S
raw :: String -> R
lit :: String -> L
updateAxes :: Matplotlib
updateFigure :: Matplotlib
mapLinear :: (Double -> b) -> Double -> Double -> Double -> [b]

Documentation

onscreen :: Matplotlib -> IO () Source #

Show a plot, blocks until the figure is closed

code :: Matplotlib -> IO String Source #

Print the python code that would be executed

file :: [Char] -> Matplotlib -> IO (Either String String) Source #

Save to a file

toSvg :: Matplotlib -> IO (Either String String) Source #

Get the SVG for a figure

xacorr :: (ToJSON a, ToJSON b) => a -> b -> [Option] -> Matplotlib Source #

Plot the cross-correlation and autocorrelation of several variables. TODO Due to a limitation in the options mechanism this takes explicit options.

histogram :: (MplotValue val, ToJSON t) => t -> val -> Matplotlib Source #

Plot a histogram for the given values with bins

histogram2D :: ToJSON a => a -> a -> Matplotlib Source #

Plot a 2D histogram for the given values with bins

scatter :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib Source #

Plot the given values as a scatter plot

bar :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib Source #

Create a bar at a position with a height

line :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib Source #

Plot a line

errorbar :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d) => a -> b -> c -> d -> Matplotlib Source #

Like plot but takes an error bar value per point errorbar :: (ToJSON x, ToJSON y, ToJSON xs, ToJSON ys) => x -> y -> Maybe xs -> Maybe ys -> Matplotlib

lineF :: (ToJSON a, ToJSON b) => (a -> b) -> [a] -> Matplotlib Source #

Plot a line given a function that will be executed for each element of given list. The list provides the x values, the function the y values.

boxplot :: ToJSON a => a -> Matplotlib Source #

Create a box plot for the given data

violinplot :: ToJSON a => a -> Matplotlib Source #

Create a violin plot for the given data

contourF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib Source #

Given a grid of x and y values and a number of steps call the given function and plot the 3D contour

projectionsF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib Source #

Given a grid of x and y values and a number of steps call the given function and plot the 3D projection

plotInterpolated :: (MplotValue val, ToJSON t, ToJSON t1) => t1 -> t -> val -> Matplotlib Source #

Plot x against y interpolating with n steps

plotMapLinear :: ToJSON b => (Double -> b) -> Double -> Double -> Double -> Matplotlib Source #

A handy function to plot a line between two points give a function and a number o steps

line1 :: (Foldable t, ToJSON (t a)) => t a -> Matplotlib Source #

Plot a line between 0 and the length of the array with the given y values

matShow :: ToJSON a => a -> Matplotlib Source #

Plot a matrix

imshow :: MplotImage a => a -> Matplotlib Source #

Plot an image

pcolor :: ToJSON a => a -> Matplotlib Source #

Plot a matrix

pcolor3 :: (ToJSON a, ToJSON b, ToJSON c) => a -> b -> c -> Matplotlib Source #

Plot a matrix

nonUniformImage :: (ToJSON a, ToJSON b, ToJSON c) => a -> b -> c -> Matplotlib Source #

Create a non-uniform image from samples

pie :: (ToJSON val, MplotValue val) => val -> Matplotlib Source #

Create a pie chart

density :: [Double] -> Maybe (Double, Double) -> Matplotlib Source #

Plot a KDE of the given functions; a good bandwith will be chosen automatically

rc :: String -> Matplotlib Source #

Set an rc parameter

setParameter :: MplotValue val => String -> val -> Matplotlib Source #

Set an rcParams key-value

setTeX :: Bool -> Matplotlib Source #

Enable or disable TeX

dataPlot :: (MplotValue val, MplotValue val1) => val1 -> val -> Matplotlib Source #

Plot the a and b entries of the data object

plot :: (ToJSON t, ToJSON t1) => t1 -> t -> Matplotlib Source #

Plot the Haskell objects x and y as a line

streamplot :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d) => a -> b -> c -> d -> Matplotlib Source #

dateLine :: (ToJSON t1, ToJSON t2) => t1 -> t2 -> String -> (Int, Int, Int) -> Matplotlib Source #

Plot x against y where x is a date. xunit is something like weeks, yearStart, monthStart, dayStart are an offset to x. TODO This isn't general enough; it's missing some settings about the format. The call is also a mess.

dataHistogram :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Create a histogram for the a entry of the data array

dataScatter :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Create a scatter plot accessing the given fields of the data array

dataLine :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Create a line accessing the given entires of the data array

contour :: (ToJSON (t2 (t3 val1)), ToJSON (t4 (t5 val2)), ToJSON (t6 (t7 val3)), MplotValue val2, MplotValue val1, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t3 val1), Ord (t5 val2), Ord (t7 val3), Foldable t2, Foldable t3, Foldable t4, Foldable t5, Foldable t6, Foldable t7) => t2 (t3 val1) -> t4 (t5 val2) -> t6 (t7 val3) -> Matplotlib Source #

Create a 3D contour

projections :: (ToJSON (t2 (t3 val1)), ToJSON (t4 (t5 val2)), ToJSON (t6 (t7 val3)), MplotValue val2, MplotValue val1, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t3 val1), Ord (t5 val2), Ord (t7 val3), Foldable t2, Foldable t3, Foldable t4, Foldable t5, Foldable t6, Foldable t7) => t2 (t3 val1) -> t4 (t5 val2) -> t6 (t7 val3) -> Matplotlib Source #

Create a 3D projection

wireframe :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib Source #

Plot a 3D wireframe accessing the given elements of the data array

surface :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib Source #

Plot a 3D surface accessing the given elements of the data array

contourRaw :: (MplotValue val1, MplotValue val2, MplotValue val5, MplotValue val4, MplotValue val3, MplotValue val) => val5 -> val4 -> val3 -> val2 -> val1 -> val -> Matplotlib Source #

Plot a contour accessing the given elements of the data array

subplotDataBar :: (MplotValue val1, MplotValue val2, MplotValue val3) => val2 -> val1 -> val3 -> [Option] -> Matplotlib Source #

Draw a bag graph in a subplot TODO Why do we need this?

barDefaultWidth :: (Fractional a1, Integral a2) => a2 -> a1 Source #

The default bar with

subplotBarsLabelled :: (ToJSON (t a), Foldable t, MplotValue val) => [t a] -> val -> [[Option]] -> Matplotlib Source #

Create a set of labelled bars of a given height

subplotBars :: ToJSON a => [a] -> [[Option]] -> Matplotlib Source #

Create a subplot and a set of labelled bars TODO This is a mess..

interpolate :: (MplotValue val, MplotValue val2, MplotValue val1) => val2 -> val1 -> val -> Matplotlib Source #

Update the data array to linearly interpolate between array entries

densityBandwidth :: [Double] -> Double -> Maybe (Double, Double) -> Matplotlib Source #

Plot a KDE of the given functions with an optional start/end and a bandwidth h

xcorr :: (ToJSON a, ToJSON b) => a -> b -> Matplotlib Source #

Plot cross-correlation

acorr :: ToJSON a => a -> Matplotlib Source #

Plot auto-correlation

quiver :: (ToJSON a, ToJSON b, ToJSON c, ToJSON d, ToJSON e) => a -> b -> c -> d -> Maybe e -> Matplotlib Source #

A quiver plot; color is optional and can be nothing

quiverKey :: (MplotValue val1, MplotValue val2, MplotValue val3, MplotValue val4) => val4 -> val3 -> val2 -> val1 -> Matplotlib Source #

A key of a given size with a label for a quiver plot

text :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> String -> Matplotlib Source #

Plot text at a specified location

figText :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> String -> Matplotlib Source #

Add a text to a figure instead of a particular plot

annotate :: String -> Matplotlib Source #

Add an annotation

setAspect :: Matplotlib Source #

Square up the aspect ratio of a plot.

squareAxes :: Matplotlib Source #

Square up the aspect ratio of a plot.

roateAxesLabels :: MplotValue val => val -> Matplotlib Source #

Set the rotation of the labels on the x axis to the given number of degrees

verticalAxes :: Matplotlib Source #

Set the x labels to be vertical

logX :: Matplotlib Source #

Set the x scale to be logarithmic

logY :: Matplotlib Source #

Set the y scale to be logarithmic

xlim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Set limits on the x axis

ylim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Set limits on the y axis

axhline :: MplotValue val => val -> Matplotlib Source #

Add a horizontal line across the axis

legend :: Matplotlib Source #

Insert a legend

colorbar :: Matplotlib Source #

Insert a color bar TODO This refers to the plot and not an axis. Might cause trouble with subplots

title :: String -> Matplotlib Source #

Add a title

grid :: Bool -> Matplotlib Source #

Show/hide grid lines

axis3DProjection :: Matplotlib Source #

Enable 3D projection

axis3DLabels :: (MplotValue val1, MplotValue val2, MplotValue val3, Ord val1, Ord val2, Ord val3, Ord (t2 val1), Ord (t3 val2), Ord (t4 val3), Foldable t5, Foldable t2, Foldable t6, Foldable t3, Foldable t7, Foldable t4) => t5 (t2 val1) -> t6 (t3 val2) -> t7 (t4 val3) -> Matplotlib Source #

Label and set limits of a set of 3D axis TODO This is a mess, does both more and less than it claims.

xlabel :: String -> Matplotlib Source #

Add a label to the x axis

ylabel :: String -> Matplotlib Source #

Add a label to the y axis

zlabel :: String -> Matplotlib Source #

Add a label to the z axis

setSizeInches :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib Source #

tightLayout :: Matplotlib Source #

xkcd :: Matplotlib Source #

xticks :: MplotValue val => val -> Matplotlib Source #

yticks :: MplotValue val => val -> Matplotlib Source #

zticks :: MplotValue val => val -> Matplotlib Source #

xtickLabels :: MplotValue val => val -> Matplotlib Source #

ytickLabels :: MplotValue val => val -> Matplotlib Source #

ztickLabels :: MplotValue val => val -> Matplotlib Source #

axisXTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Set the spacing of ticks on the x axis

axisXTickLabels :: MplotValue val => val -> Matplotlib Source #

Set the labels on the x axis

axisYTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib Source #

Set the spacing of ticks on the y axis

axisYTickLabels :: MplotValue val => val -> Matplotlib Source #

Set the labels on the y axis

axisXTicksPosition :: MplotValue val => val -> Matplotlib Source #

axisYTicksPosition :: MplotValue val => val -> Matplotlib Source #

spine :: MplotValue val => val -> Matplotlib Source #

spineSetBounds :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib Source #

spineSetVisible :: MplotValue val => val -> Matplotlib Source #

spineSetPosition :: (MplotValue val1, MplotValue val2) => val2 -> val1 -> Matplotlib Source #

setAx :: Matplotlib Source #

addSubplot :: (MplotValue val1, MplotValue val2, MplotValue val3) => val3 -> val2 -> val1 -> Matplotlib Source #

Create a subplot with the coordinates (r,c,f)

getSubplot :: (MplotValue val1, MplotValue val2, MplotValue val3) => val3 -> val2 -> val1 -> Matplotlib Source #

Access a subplot with the coordinates (r,c,f)

subplots :: Matplotlib Source #

Creates subplots and stores them in an internal variable

setSubplot :: MplotValue val => val -> Matplotlib Source #

Access a subplot

axes :: Matplotlib Source #

Add axes to a plot

addAxes :: Matplotlib Source #

Add axes to a figure

figure :: Matplotlib Source #

Creates a new figure with the given id. If the Id is already in use it switches to that figure.

Creating custom plots and applying options

data Matplotlib Source #

The wrapper type for a matplotlib computation.

Instances

Instances details

Semigroup Matplotlib Source #
Instance details Defined in Graphics.Matplotlib.Internal Methods (<>) :: Matplotlib -> Matplotlib -> Matplotlib # sconcat :: NonEmpty Matplotlib -> Matplotlib # stimes :: Integral b => b -> Matplotlib -> Matplotlib #
Monoid Matplotlib Source #	Monoid instance for Matplotlib type
Instance details Defined in Graphics.Matplotlib.Internal Methods mempty :: Matplotlib # mappend :: Matplotlib -> Matplotlib -> Matplotlib # mconcat :: [Matplotlib] -> Matplotlib #
NFData Matplotlib Source #
Instance details Defined in Graphics.Matplotlib.Internal Methods rnf :: Matplotlib -> () #

data Option Source #

Throughout the API we need to accept options in order to expose matplotlib's many configuration options.

Instances

Instances details

Eq Option Source #
Instance details Defined in Graphics.Matplotlib.Internal Methods (==) :: Option -> Option -> Bool # (/=) :: Option -> Option -> Bool #
Ord Option Source #
Instance details Defined in Graphics.Matplotlib.Internal Methods compare :: Option -> Option -> Ordering # (<) :: Option -> Option -> Bool # (<=) :: Option -> Option -> Bool # (>) :: Option -> Option -> Bool # (>=) :: Option -> Option -> Bool # max :: Option -> Option -> Option # min :: Option -> Option -> Option #
Show Option Source #
Instance details Defined in Graphics.Matplotlib.Internal Methods showsPrec :: Int -> Option -> ShowS # show :: Option -> String # showList :: [Option] -> ShowS #