-- Hoogle documentation, generated by Haddock -- See Hoogle, http://www.haskell.org/hoogle/ -- | Bindings to Matplotlib; a Python plotting library -- -- Matplotlib is probably the most full featured plotting library out -- there. These bindings provide a quick, easy, and extensible way to use -- it in Haskell. -- -- -- 
--   onscreen $ contourF (\a b -> sin (degreesRadians a) + cos (degreesRadians b)) (-100) 100 (-200) 200 10
--
@package matplotlib @version 0.4.1 -- | Internal representations of the Matplotlib data. These are not -- API-stable and may change. You can easily extend the provided bindings -- without relying on the internals exposed here but they are provided -- just in case. module Graphics.Matplotlib.Internal -- | A handy miscellaneous function to linearly map over a range of numbers -- in a given number of steps mapLinear :: (Double -> b) -> Double -> Double -> Double -> [b] -- | The wrapper type for a matplotlib computation. data Matplotlib Matplotlib :: Seq MplotCommand -> Maybe ([Option] -> MplotCommand) -> Seq MplotCommand -> Matplotlib -- | Resolved computations that have been transformed to commands [mpCommands] :: Matplotlib -> Seq MplotCommand -- | A pending computation that is affected by applied options [mpPendingOption] :: Matplotlib -> Maybe ([Option] -> MplotCommand) -- | Computations that follow the one that is pending [mpRest] :: Matplotlib -> Seq MplotCommand -- | A maplotlib command, right now we have a very shallow embedding -- essentially dealing in strings containing python code as well as the -- ability to load data. The loaded data should be a json object. data MplotCommand LoadData :: ByteString -> MplotCommand LoadImage :: x -> MplotCommand Exec :: String -> MplotCommand [es] :: MplotCommand -> String -- | Throughout the API we need to accept options in order to expose -- matplotlib's many configuration options. data Option -- | results in a=b K :: String -> String -> Option -- | just inserts the option verbatim as an argument at the end of the -- function P :: String -> Option -- | Convert an MplotCommand to python code, doesn't do much right -- now toPy :: MplotCommand -> String -- | Resolve the pending command with no options provided. resolvePending :: Matplotlib -> Matplotlib -- | The io action is given a list of python commands to execute (note that -- these are commands in the sense of lines of python code; each -- inidivudal line may not be parseable on its own withMplot :: Matplotlib -> ([String] -> IO a) -> IO a -- | Create a plot that executes the string as python code mplotString :: String -> Matplotlib -- | Create an empty plot. This the beginning of most plotting commands. mp :: Matplotlib -- | Load the given data into the python "data" array readData :: ToJSON a => a -> Matplotlib -- | Load the given image into python "img" variable readImage :: MplotImage i => i -> Matplotlib -- | Combine two matplotlib commands (%) :: Matplotlib -> Matplotlib -> Matplotlib infixl 5 % -- | Add Python code to the last matplotlib command (#) :: (MplotValue val) => Matplotlib -> val -> Matplotlib infixl 6 # -- | A string to be rendered in python as a string. In other words it is -- rendered as str. data S S :: String -> S -- | A string to be rendered in python as a raw string. In other words it -- is rendered as rstr. data R R :: String -> R -- | A string to be rendered in python as a raw literal/code. In other -- words it is inserted directly as is into the code. data L L :: String -> L -- | Values which can be combined together to form a matplotlib command. -- These specify how values are rendered in Python code. class MplotValue val where toPythonOpt = toPython -- | Render a value inline in Python code toPython :: MplotValue val => val -> String -- | Render a value as an optional parameter in Python code toPythonOpt :: MplotValue val => val -> String -- | The class of Haskell images or references to imagese which can be -- transferred to matplotlib. class MplotImage a saveHaskellImage :: MplotImage a => a -> FilePath -> IO String loadPythonImage :: MplotImage a => a -> String -> FilePath -> String -- | An image that is a string is a file path. -- | Add an option to the last matplotlib command. Commands can have only -- one option! optFn :: Matplotlib -> Matplotlib optFn :: ([Option] -> String) -> Matplotlib -> Matplotlib -- | Merge two commands with options between options :: Matplotlib -> Matplotlib -- | A combinator like # that also inserts an option (##) :: MplotValue val => Matplotlib -> val -> Matplotlib infixl 6 ## -- | An internal helper to convert a list of options to the python code -- that applies those options in a call. renderOptions :: [Option] -> [Char] -- | An internal helper that modifies the options of a plot. optionFn :: ([Option] -> [Option]) -> Matplotlib -> Matplotlib -- | Apply a list of options to a plot resolving any pending options. option :: Matplotlib -> [Option] -> Matplotlib -- | A combinator for option that applies a list of options to a -- plot (@@) :: Matplotlib -> [Option] -> Matplotlib infixl 6 @@ -- | Bind a list of default options to a plot. Positional options are kept -- in order and default that way as well. Keyword arguments are def :: Matplotlib -> [Option] -> Matplotlib -- | Merge two sets of options defFn :: [Option] -> [Option] -> [Option] -- | Run python given a code string. python :: Foldable t => t String -> IO (Either String String) pyBackend :: [Char] -> [Char] -- | The standard python includes of every plot pyIncludes :: String -> [[Char]] -- | The python command that reads external data into the python data array pyReadData :: [Char] -> [[Char]] -- | The python command that reads an image into the img variable pyReadImage :: [Char] -> [[Char]] -- | Detach python so we don't block (TODO This isn't working reliably) pyDetach :: [[Char]] -- | Python code to show a plot pyOnscreen :: [[Char]] -- | Python code that saves a figure pyFigure :: [Char] -> [[Char]] -- | Create a positional option o1 :: MplotValue val => val -> Option -- | Create a keyword option o2 :: MplotValue val => String -> val -> Option -- | Create a string that will be rendered as a python string str :: String -> S -- | Create a string that will be rendered as a raw python string raw :: String -> R -- | Create a literal that will inserted into the python code directly lit :: String -> L -- | Update axes. Should be called any time the state is changed. updateAxes :: Matplotlib -- | Update the figure and the axes. Should be called any time the state is -- changed. updateFigure :: Matplotlib -- | Smallest element of a list of lists minimum2 :: (Ord (t a), Ord a, Foldable t1, Foldable t) => t1 (t a) -> a -- | Largest element of a list of lists maximum2 :: (Ord (t a), Ord a, Foldable t1, Foldable t) => t1 (t a) -> a instance GHC.Classes.Ord Graphics.Matplotlib.Internal.L instance GHC.Classes.Eq Graphics.Matplotlib.Internal.L instance GHC.Show.Show Graphics.Matplotlib.Internal.L instance GHC.Classes.Ord Graphics.Matplotlib.Internal.R instance GHC.Classes.Eq Graphics.Matplotlib.Internal.R instance GHC.Show.Show Graphics.Matplotlib.Internal.R instance GHC.Classes.Ord Graphics.Matplotlib.Internal.S instance GHC.Classes.Eq Graphics.Matplotlib.Internal.S instance GHC.Show.Show Graphics.Matplotlib.Internal.S instance GHC.Classes.Ord Graphics.Matplotlib.Internal.Option instance GHC.Classes.Eq Graphics.Matplotlib.Internal.Option instance GHC.Show.Show Graphics.Matplotlib.Internal.Option instance Graphics.Matplotlib.Internal.MplotValue Graphics.Matplotlib.Internal.S instance Graphics.Matplotlib.Internal.MplotValue Graphics.Matplotlib.Internal.R instance Graphics.Matplotlib.Internal.MplotValue Graphics.Matplotlib.Internal.L instance Graphics.Matplotlib.Internal.MplotValue GHC.Base.String instance Graphics.Matplotlib.Internal.MplotValue [GHC.Base.String] instance Graphics.Matplotlib.Internal.MplotValue GHC.Types.Double instance Graphics.Matplotlib.Internal.MplotValue [GHC.Types.Double] instance Graphics.Matplotlib.Internal.MplotValue GHC.Integer.Type.Integer instance Graphics.Matplotlib.Internal.MplotValue [GHC.Integer.Type.Integer] instance Graphics.Matplotlib.Internal.MplotValue GHC.Types.Int instance Graphics.Matplotlib.Internal.MplotValue [GHC.Types.Int] instance Graphics.Matplotlib.Internal.MplotValue [Graphics.Matplotlib.Internal.R] instance Graphics.Matplotlib.Internal.MplotValue [Graphics.Matplotlib.Internal.S] instance Graphics.Matplotlib.Internal.MplotValue [Graphics.Matplotlib.Internal.L] instance Graphics.Matplotlib.Internal.MplotValue GHC.Types.Bool instance Graphics.Matplotlib.Internal.MplotValue x => Graphics.Matplotlib.Internal.MplotValue (x, x) instance Graphics.Matplotlib.Internal.MplotValue (x, y) => Graphics.Matplotlib.Internal.MplotValue [(x, y)] instance Graphics.Matplotlib.Internal.MplotValue x => Graphics.Matplotlib.Internal.MplotValue (GHC.Base.Maybe x) instance Graphics.Matplotlib.Internal.MplotValue [[GHC.Types.Double]] instance Graphics.Matplotlib.Internal.MplotImage GHC.Base.String instance Data.Aeson.Types.ToJSON.ToJSON a => Graphics.Matplotlib.Internal.MplotImage [[a]] -- | 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: -- -- -- -- 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 ## -- -- -- -- 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" module Graphics.Matplotlib -- | Show a plot, blocks until the figure is closed onscreen :: Matplotlib -> IO (Either String String) -- | Print the python code that would be executed code :: Matplotlib -> IO String -- | Save to a file file :: [Char] -> Matplotlib -> IO (Either String String) -- | Plot the cross-correlation and autocorrelation of several variables. -- TODO Due to a limitation in the options mechanism this takes explicit -- options. xacorr :: (ToJSON t, ToJSON a) => a -> t -> [Option] -> Matplotlib -- | Plot a histogram for the given values with bins histogram :: (MplotValue val, ToJSON t) => t -> val -> Matplotlib -- | Plot a 2D histogram for the given values with bins histogram2D :: ToJSON t => t -> t -> Matplotlib -- | Plot the given values as a scatter plot scatter :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib -- | Create a bar at a position with a height bar :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib -- | Plot a line line :: (ToJSON t1, ToJSON t) => t1 -> t -> Matplotlib -- | 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 errorbar :: (ToJSON t, ToJSON t1, ToJSON t2, ToJSON t3) => t3 -> t2 -> t1 -> t -> Matplotlib -- | 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. lineF :: (ToJSON a, ToJSON b) => (a -> b) -> [a] -> Matplotlib -- | Create a box plot for the given data boxplot :: ToJSON a => a -> Matplotlib -- | Create a violin plot for the given data violinplot :: ToJSON a => a -> Matplotlib -- | Given a grid of x and y values and a number of steps call the given -- function and plot the 3D contour contourF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib -- | Given a grid of x and y values and a number of steps call the given -- function and plot the 3D projection projectionsF :: (ToJSON val, MplotValue val, Ord val) => (Double -> Double -> val) -> Double -> Double -> Double -> Double -> Double -> Matplotlib -- | Plot x against y interpolating with n steps plotInterpolated :: (MplotValue val, ToJSON t, ToJSON t1) => t1 -> t -> val -> Matplotlib -- | A handy function to plot a line between two points give a function and -- a number o steps plotMapLinear :: ToJSON b => (Double -> b) -> Double -> Double -> Double -> Matplotlib -- | Plot a line between 0 and the length of the array with the given y -- values line1 :: (Foldable t, ToJSON (t a)) => t a -> Matplotlib -- | Plot a matrix matShow :: ToJSON a => a -> Matplotlib -- | Plot an image imshow :: MplotImage a => a -> Matplotlib -- | Plot a matrix pcolor :: ToJSON a => a -> Matplotlib -- | Plot a matrix pcolor3 :: (ToJSON t, ToJSON t1, ToJSON t2) => t2 -> t1 -> t -> Matplotlib -- | Create a non-uniform image from samples nonUniformImage :: (ToJSON t, ToJSON t1, ToJSON t2) => t2 -> t1 -> t -> Matplotlib -- | Create a pie chart pie :: (MplotValue val, ToJSON val) => val -> Matplotlib -- | Plot a KDE of the given functions; a good bandwith will be chosen -- automatically density :: [Double] -> Maybe (Double, Double) -> Matplotlib -- | Set an rc parameter rc :: String -> Matplotlib -- | Set an rcParams key-value setParameter :: MplotValue val => String -> val -> Matplotlib -- | Enable or disable TeX setTeX :: Bool -> Matplotlib -- | Enable or disable unicode setUnicode :: Bool -> Matplotlib -- | Plot the a and b entries of the data object dataPlot :: (MplotValue val, MplotValue val1) => val1 -> val -> Matplotlib -- | Plot the Haskell objects x and y as a line plot :: (ToJSON t, ToJSON t1) => t1 -> t -> Matplotlib streamplot :: (ToJSON t, ToJSON t1, ToJSON t2, ToJSON t3) => t3 -> t2 -> t1 -> t -> Matplotlib -- | 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. dateLine :: (ToJSON t1, ToJSON t2) => t1 -> t2 -> String -> (Int, Int, Int) -> Matplotlib -- | Create a histogram for the a entry of the data array dataHistogram :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Create a scatter plot accessing the given fields of the data array dataScatter :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Create a line accessing the given entires of the data array dataLine :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Create a 3D contour contour :: (Foldable t, Foldable t1, Foldable t2, Foldable t3, Foldable t4, Foldable t5, Ord (t val), Ord (t2 val1), Ord (t4 val2), Ord val, Ord val1, Ord val2, MplotValue val, MplotValue val2, MplotValue val1, ToJSON (t1 (t val)), ToJSON (t3 (t2 val1)), ToJSON (t5 (t4 val2))) => t5 (t4 val2) -> t3 (t2 val1) -> t1 (t val) -> Matplotlib -- | Create a 3D projection projections :: (Foldable t, Foldable t1, Foldable t2, Foldable t3, Foldable t4, Foldable t5, Ord (t val), Ord (t2 val1), Ord (t4 val2), Ord val, Ord val1, Ord val2, MplotValue val, MplotValue val2, MplotValue val1, ToJSON (t1 (t val)), ToJSON (t3 (t2 val1)), ToJSON (t5 (t4 val2))) => t5 (t4 val2) -> t3 (t2 val1) -> t1 (t val) -> Matplotlib -- | Plot a 3D wireframe accessing the given elements of the data array wireframe :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib -- | Plot a 3D surface accessing the given elements of the data array surface :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib -- | Plot a contour 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 -- | Draw a bag graph in a subplot TODO Why do we need this? subplotDataBar :: (MplotValue val, MplotValue val2, MplotValue val1) => val2 -> val1 -> val -> [Option] -> Matplotlib -- | The default bar with barDefaultWidth :: (Integral a1, Fractional a) => a1 -> a -- | Create a set of labelled bars of a given height subplotBarsLabelled :: (MplotValue val, Foldable t, ToJSON (t a)) => [t a] -> val -> [[Option]] -> Matplotlib -- | Create a subplot and a set of labelled bars TODO This is a mess.. subplotBars :: ToJSON a => [a] -> [[Option]] -> Matplotlib -- | Update the data array to linearly interpolate between array entries interpolate :: (MplotValue val, MplotValue val2, MplotValue val1) => val2 -> val1 -> val -> Matplotlib -- | Plot a KDE of the given functions with an optional start/end and a -- bandwidth h densityBandwidth :: [Double] -> Double -> Maybe (Double, Double) -> Matplotlib -- | Plot cross-correlation xcorr :: (ToJSON t, ToJSON t1) => t1 -> t -> Matplotlib -- | Plot auto-correlation acorr :: ToJSON a => a -> Matplotlib -- | A quiver plot; color is optional and can be nothing quiver :: (ToJSON t, ToJSON t1, ToJSON t2, ToJSON t3, ToJSON t4) => t4 -> t3 -> t2 -> t1 -> Maybe t -> Matplotlib -- | A key of a given size with a label for a quiver plot quiverKey :: (MplotValue val3, MplotValue val2, MplotValue val1, MplotValue val) => val3 -> val2 -> val1 -> val -> Matplotlib -- | Plot text at a specified location text :: (MplotValue val1, MplotValue val) => val1 -> val -> String -> Matplotlib -- | Add a text to a figure instead of a particular plot figText :: (MplotValue val1, MplotValue val) => val1 -> val -> String -> Matplotlib -- | Add an annotation annotate :: String -> Matplotlib -- | Square up the aspect ratio of a plot. setAspect :: Matplotlib -- | Square up the aspect ratio of a plot. squareAxes :: Matplotlib -- | Set the rotation of the labels on the x axis to the given number of -- degrees roateAxesLabels :: MplotValue val => val -> Matplotlib -- | Set the x labels to be vertical verticalAxes :: Matplotlib -- | Set the x scale to be logarithmic logX :: Matplotlib -- | Set the y scale to be logarithmic logY :: Matplotlib -- | Set limits on the x axis xlim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Set limits on the y axis ylim :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Add a horizontal line across the axis axhline :: MplotValue val => val -> Matplotlib -- | Insert a legend legend :: Matplotlib -- | Insert a color bar TODO This refers to the plot and not an axis. Might -- cause trouble with subplots colorbar :: Matplotlib -- | Add a title title :: String -> Matplotlib -- | Show/hide grid lines grid :: Bool -> Matplotlib -- | Enable 3D projection axis3DProjection :: Matplotlib -- | Label and set limits of a set of 3D axis TODO This is a mess, does -- both more and less than it claims. axis3DLabels :: (Foldable t, Foldable t1, Foldable t2, Foldable t3, Foldable t4, Foldable t5, Ord (t val), Ord (t2 val1), Ord (t4 val2), Ord val, Ord val1, Ord val2, MplotValue val, MplotValue val1, MplotValue val2) => t5 (t4 val2) -> t3 (t2 val1) -> t1 (t val) -> Matplotlib -- | Add a label to the x axis xlabel :: String -> Matplotlib -- | Add a label to the y axis ylabel :: String -> Matplotlib -- | Add a label to the z axis zlabel :: String -> Matplotlib setSizeInches :: (MplotValue val1, MplotValue val) => val1 -> val -> 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 -- | Set the spacing of ticks on the x axis axisXTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Set the labels on the x axis axisXTickLabels :: MplotValue val => val -> Matplotlib -- | Set the spacing of ticks on the y axis axisYTickSpacing :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib -- | Set the labels on the y axis axisYTickLabels :: MplotValue val => val -> Matplotlib axisXTicksPosition :: MplotValue val => val -> Matplotlib axisYTicksPosition :: MplotValue val => val -> Matplotlib spine :: MplotValue val => val -> Matplotlib spineSetBounds :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib spineSetVisible :: MplotValue val => val -> Matplotlib spineSetPosition :: (MplotValue val1, MplotValue val) => val1 -> val -> Matplotlib setAx :: Matplotlib -- | Create a subplot with the coordinates (r,c,f) addSubplot :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib -- | Access a subplot with the coordinates (r,c,f) getSubplot :: (MplotValue val2, MplotValue val1, MplotValue val) => val2 -> val1 -> val -> Matplotlib -- | Creates subplots and stores them in an internal variable subplots :: Matplotlib -- | Access a subplot setSubplot :: MplotValue val => val -> Matplotlib -- | Add axes to a plot axes :: Matplotlib -- | Add axes to a figure addAxes :: Matplotlib -- | Creates a new figure with the given id. If the Id is already in use it -- switches to that figure. figure :: Matplotlib -- | The wrapper type for a matplotlib computation. data Matplotlib -- | Throughout the API we need to accept options in order to expose -- matplotlib's many configuration options. data Option -- | A combinator for option that applies a list of options to a -- plot (@@) :: Matplotlib -> [Option] -> Matplotlib infixl 6 @@ -- | Combine two matplotlib commands (%) :: Matplotlib -> Matplotlib -> Matplotlib infixl 5 % -- | Create a positional option o1 :: MplotValue val => val -> Option -- | Create a keyword option o2 :: MplotValue val => String -> val -> Option -- | A combinator like # that also inserts an option (##) :: MplotValue val => Matplotlib -> val -> Matplotlib infixl 6 ## -- | Add Python code to the last matplotlib command (#) :: (MplotValue val) => Matplotlib -> val -> Matplotlib infixl 6 # -- | Create an empty plot. This the beginning of most plotting commands. mp :: Matplotlib -- | Bind a list of default options to a plot. Positional options are kept -- in order and default that way as well. Keyword arguments are def :: Matplotlib -> [Option] -> Matplotlib -- | Load the given data into the python "data" array readData :: ToJSON a => a -> Matplotlib -- | Load the given image into python "img" variable readImage :: MplotImage i => i -> Matplotlib -- | Create a string that will be rendered as a python string str :: String -> S -- | Create a string that will be rendered as a raw python string raw :: String -> R -- | Create a literal that will inserted into the python code directly lit :: String -> L -- | Update axes. Should be called any time the state is changed. updateAxes :: Matplotlib -- | Update the figure and the axes. Should be called any time the state is -- changed. updateFigure :: Matplotlib -- | A handy miscellaneous function to linearly map over a range of numbers -- in a given number of steps mapLinear :: (Double -> b) -> Double -> Double -> Double -> [b]