{-# language ExtendedDefaultRules, ScopedTypeVariables, QuasiQuotes, ParallelListComp #-} import Test.Tasty import Test.Tasty.Runners import Test.Tasty.HUnit import Test.Tasty.ExpectedFailure import System.IO.Unsafe import Graphics.Matplotlib import System.IO.Temp import System.Random import Text.RawString.QQ import Data.List import Data.List.Split import Control.Monad import Test.Tasty.Golden.Advanced import qualified Data.ByteString as BS import System.Process import System.IO import Numeric.AD import System.Directory -- * Random values for testing uniforms :: (Random a, Num a) => [a] uniforms = randoms (mkStdGen 42) uniforms' lo hi = randomRs (lo,hi) (mkStdGen 42) -- * Not so random values to enable some fully-reproducible tests xs = [-0.54571992, 1.48409716, -0.57545561, 2.13058156, -0.75740497, -1.27879086, -0.96008858, -1.65482373, -1.69086194, -1.41925464, 0.68144401, 1.44847131, 1.12124327, 1.32056244, -0.4555279 , 1.96002923, -1.34810771, 0.01513306, 1.25298883, -1.07541677, 0.60920278, -0.13978163, 0.3975209 , -0.15211044, 0.0534633 , -0.39498474, -1.15320186, 0.6795936 , 0.50704333, 1.52951037, 0.90867393, -0.24833115, 1.39816295, -0.28642814, 0.96951915, -1.20438266, -0.32642955, -0.62982941, 0.7245042 , -1.03169685, -0.00542761, 0.54247125, -1.11559132, -2.6829048 , -0.13370841, -0.74111166, 0.59198725, 2.73711931, 1.82122485, -0.73915212, 0.88290489, -1.17307876, 0.06753304, 0.40150672, 1.54455801, -0.31133243, 1.66844302, -0.1290924 , 0.89657699, 0.41181393, 2.13382656, 1.58577659, -1.02449069, -1.10245954, -0.59691196, -0.63040161, -0.51541836, 0.04139408, 0.54203055, -2.09082082, -0.41295376, -0.77509336, 0.47612065, -1.69680096, 0.90195265, 0.23798858, -0.05112783, 1.00645056, -0.67012513, 0.52017487, -0.42251472, 0.96513844, 1.00298933, 0.18257527, 0.54599979, -1.50321042, 0.03949817, 0.35286613, 1.86994544, 1.16249707, 0.57421291, 1.21151469, 1.74863421, 0.42287859, -1.22785845, -0.61650528, 1.76743253, -0.45818694, -1.16560907, 0.0677502 ] ys = [ 1.28231455, 1.13480471, 0.57738712, 0.10268954, 1.00162163, -0.85453571, -1.61049343, 1.33194242, 0.12054943, -0.56568776, 2.11550009, 0.03663454, 0.24889313, 0.85458325, 0.77326592, 0.58815223, -0.79997005, 0.54979418, 0.47711544, 0.73004143, -0.65704545, 1.1946521 , -0.31119444, -0.0958055 , 0.37838453, 1.01281301, -0.53364162, 2.84609607, 0.09363483, -0.14821451, -0.0481863 , -3.58277731, -1.7168244 , -0.87526525, -0.65430073, 1.0284506 , -0.81397895, 0.34868379, -0.51671293, 0.92879285, 0.04099886, 1.0828335 , 1.25991492, -1.48901447, 0.43657503, 0.78191509, 0.16633587, 1.99411663, -0.25542794, -0.43377353, -0.82871869, -0.0402321 , -0.06278027, 0.28066445, 0.01185443, 1.42640101, -0.16627931, 0.82021257, -0.66684095, -0.21289723, -1.25974667, -0.28681327, -2.11039334, -0.2722768 , -0.51622958, 0.01324637, -0.29277708, 1.35916036, -0.09089638, -1.00619256, 0.62707331, 1.17105748, -0.85636353, -0.6243519 , 0.1720141 , -0.15715394, 1.13488465, 2.43996937, 2.08224839, -0.23676918, -0.24924999, 1.21629376, -0.12748227, 0.78319565, -0.10528614, 0.60177749, -1.03490762, -0.59163218, 0.16414076, 2.22783012, -0.55178235, -0.69915414, 1.35454045, 0.42931902, -1.33656935, -0.8023867 , -2.81354854, 0.39553427, -0.22235586, -1.34302011] -- * Generate normally distributed random values; taken from normaldistribution==1.1.0.3 -- | Box-Muller method for generating two normally distributed -- independent random values from two uniformly distributed -- independent random values. boxMuller :: Floating a => a -> a -> (a,a) boxMuller u1 u2 = (r * cos t, r * sin t) where r = sqrt (-2 * log u1) t = 2 * pi * u2 -- | Convert a list of uniformly distributed random values into a -- list of normally distributed random values. The Box-Muller -- algorithms converts values two at a time, so if the input list -- has an uneven number of element the last one will be discarded. boxMullers :: Floating a => [a] -> [a] boxMullers (u1:u2:us) = n1:n2:boxMullers us where (n1,n2) = boxMuller u1 u2 boxMullers _ = [] -- | Plural variant of 'normal', producing an infinite list of -- random values instead of returning a new generator. This function -- is analogous to 'Random.randoms'. normals = boxMullers $ randoms (mkStdGen 42) -- | Analogous to 'normals' but uses the supplied (mean, standard -- deviation). normals' (mean, sigma) g = map (\x -> x * sigma + mean) $ normals pdfBivariateNormal x y sigmax sigmay mux muy sigmaxy = 1/(2*pi*sigmax*sigmay*(sqrt(1-rho^2)))*exp(-z/(2*(1-rho^2))) where rho = sigmaxy/(sigmax*sigmay) z = (x-mux)^2/sigmax^2-(2*rho*(x-mux)*(y-muy))/(sigmax*sigmay)+(y-muy)^2/sigmay^2 -- * Tests main = do createDirectoryIfMissing False "/tmp/imgs/" defaultMain $ tests "All tests" testPlot main' = do createDirectoryIfMissing False "/tmp/imgs/" defaultMain $ tests "Golden tests" testPlotGolden main'' = do createDirectoryIfMissing False "/tmp/imgs/" defaultMain $ testGroup "All tests" [tests "Execution tests" testPlot , toneDownTests "Unreliable across machines" $ tests "Golden tests" testPlotGolden] tests name f = testGroup name [basicTests f, toneDownTests "Can fail with old matplotlib or data" $ fragileTests f, ignoreTest $ failingTests f] toneDownTests reason tests = wrapTest (liftM (\x -> x { resultOutcome = Success , resultShortDescription = case resultOutcome x of Success -> resultShortDescription x _ -> reason ++ ": " ++ resultShortDescription x })) tests testPlotGolden name fn = unsafePerformIO $ tmp (\filename -> return $ goldenTest name (BS.readFile ref) (file filename fn >> BS.readFile filename) (\g n -> tmp (\gfile -> tmp (\nfile -> do BS.writeFile gfile g BS.writeFile nfile n (code, stdout, stderr) <- readProcessWithExitCode "/usr/bin/compare" ["-metric" ,"PSNR" ,gfile ,nfile ,"null"] "" case (stderr, reads stderr) of ("inf", _) -> return Nothing (_, [(x :: Double, _)]) -> if x < 25 then return $ Just $ "Images very different; PSNR too low " ++ show x else return Nothing))) (BS.writeFile ref)) where ref = "imgs/" ++ name ++ ".png" tmp f = withSystemTempFile "a.png" (\filename h -> hClose h >> f filename) -- | Test one plot; right now we just test that the command executed without -- errors. We should visually compare plots somehow. testPlot' name fn = testCase name $ tryit fn @?= Right "" where tryit fn = unsafePerformIO $ withSystemTempFile "a.png" (\filename _ -> file filename fn) -- | This generates examples from the test cases testPlot name fn = testCase name $ tryit fn name @?= Right "" where tryit fn name = unsafePerformIO $ do file ("/tmp/imgs/" ++ name ++ ".png") fn basicTests f = testGroup "Basic tests" [ f "histogram" mhistogram , f "cumulative" mcumulative , f "scatter" mscatter , f "contour" mcontour , f "labelled-histogram" mlabelledHistogram , f "density-bandwidth" mdensityBandwidth , f "density" mdensity , f "line-function" mlineFunction , f "quadratic" mQuadratic , f "projections" mProjections , f "line-options" mlineOptions , f "corr" mxcorr , f "show-matrix" mmat , f "legend" mlegend , f "hist2DLog" mhist2DLog , f "eventplot" meventplot , f "errorbar" merrorbar , f "scatterhist" mscatterHist , f "histMulti" mhistMulti , f "spines" mspines , f "hists" mhists , f "hinton" mhinton , f "integral" mintegral , f "quiver" mquiver , f "quiver-fancy" mquiverFancy , f "polar" mpolar , f "bivariateNormal" mbivariateNormal , f "pcolorlog" mpcolorlog , f "pie" mpie , f "stacked" mstacked , f "annotation" mannotation , f "streamplot" mstreamplot ] fragileTests f = testGroup "Fragile tests" [ f "tex" mtex -- TODO Fails on circle ci (with latex) -- TODO Fails on circle ci (labels is not valid; matplotlib too old) , f "boxplot" mboxplot -- TODO Fails on circle ci (no violin plots; matplotlib too old) , f "violinplot" mviolinplot -- TODO Needs a fairly recent matplotlib; too old for circleci , f "griddata" mgriddata -- TODO Needs access to a data file , f "images" mimages ] failingTests f = testGroup "Failing tests" [ -- TODO This test case is broken f "sub-bars" msubBars ] -- * These tests are fully-reproducible, the output must be identical every time mhistogram :: Matplotlib mhistogram = histogram xs 8 mcumulative = histogram xs 8 @@ [o2 "cumulative" True] mscatter = scatter xs ys degreesRadians a = a * pi / 180.0 radiansDegrees a = a * 180.0 / pi mcontour = contourF (\a b -> sin (degreesRadians a) + cos (degreesRadians b)) (-100) 100 (-200) 200 10 mlabelledHistogram = histogram xs 7 % ylabel "number of queries" % xlabel "true positives" -- TODO Broken test msubBars = subplotBarsLabelled [[40, 50, 20, 50], [10, 20, 30, 40], [40, 50, 20, 50]] ["a", "b", "c", "d"] [] % title "Wee a title" % xlabel "X" % ylabel "Y" mdensityBandwidth = densityBandwidth [2.1, 1.3, 0.4, 1.9, 5.1, 6.2] 1.5 (Just (-6, 11)) % ylim 0 0.2 mdensity = density [2.1, 1.3, 0.4, 1.9, 5.1, 6.2] (Just (-6, 11)) mlineFunction = lineF (\x -> x**2) [0,0.01..1] mQuadratic = plotMapLinear (\x -> x**2) (-2) 2 100 @@ [o1 "."] % title "Quadratic function" mProjections = projectionsF (\a b -> cos (degreesRadians a) + sin (degreesRadians b)) (-100) 100 (-200) 200 10 mlineOptions = plot [1,2,3,4,5,6] [1,3,2,5,2,4] @@ [o1 "go-", o2 "linewidth" 2] -- * These tests can be random and may not be exactly the same every time -- | http://matplotlib.org/examples/pylab_examples/xcorr_demo.html mxcorr = xacorr xs ys [o2 "usevlines" True, o2 "maxlags" 50, o2 "normed" True, o2 "lw" 2] where (xs :: [Double]) = take 100 normals (ys :: [Double]) = take 100 normals -- | http://matplotlib.org/examples/pylab_examples/tex_unicode_demo.html mtex = setTeX True % figure % addSubplot 1 1 1 % plotMapLinear cos 0 1 100 % xlabel [r|\textbf{time (s)}|] % ylabel "\\textit{Velocity (°/sec)}" @@ [o2 "fontsize" 16] % title [r|\TeX\ is Number $\displaystyle\sum_{n=1}^\infty\frac{-e^{i\pi}}{2^n}$!"|] @@ [o2 "fontsize" 16, o2 "color" "r"] % grid True mmat = pcolor (take 10 $ chunksOf 8 uniforms) @@ [o2 "edgecolors" "k", o2 "linewidth" 1] -- | http://matplotlib.org/examples/pylab_examples/legend_demo3.html mlegend = plotMapLinear (\x -> x ** 2) 0 1 100 @@ [o2 "label" "x^2"] % plotMapLinear (\x -> x ** 3) 0 1 100 @@ [o2 "label" "x^3"] % legend @@ [o2 "fancybox" True, o2 "shadow" True, o2 "title" "Legend", o2 "loc" "upper left"] -- | http://matplotlib.org/examples/pylab_examples/hist2d_log_demo.html mhist2DLog = histogram2D x y @@ [o2 "bins" 40, o2 "norm" $ lit "mcolors.LogNorm()"] % setAx % colorbar where (x:y:_) = chunksOf 10000 normals meventplot = plot xs ys % mp # "ax.add_collection(mcollections.EventCollection(data[0], linelength=0.05))" % mp # "ax.add_collection(mcollections.EventCollection(data[1], orientation='vertical', linelength=0.05))" % text 0.1 0.6 "Ticks mark the actual data points" where xs = sort $ take 10 uniforms ys = map (\x -> x ** 2) xs merrorbar = errorbar xs ys (Nothing :: Maybe [Double]) (Just errs) @@ [o2 "errorevery" 2] where xs = [0.1,0.2..4] ys = map (\x -> exp $ -x) xs errs = [map (\x -> 0.1 + 0.1 * sqrt x) xs, map (\x -> 0.1 + 0.1 * sqrt x) ys] mboxplot = subplots @@ [o2 "ncols" 2, o2 "sharey" True] % setSubplot "0" % boxplot (take 3 $ chunksOf 10 $ map (* 2) $ normals) @@ [o2 "labels" ["X", "Y", "Z"]] % setSubplot "1" % boxplot (take 3 $ chunksOf 10 $ map (* 2) $ normals) @@ [o2 "labels" ["A", "B", "C"], o2 "showbox" False, o2 "showcaps" False] mviolinplot = subplots @@ [o2 "ncols" 2, o2 "sharey" True] % setSubplot "0" % violinplot (take 3 $ chunksOf 100 $ map (* 2) $ normals) % setSubplot "1" % violinplot (take 3 $ chunksOf 100 $ map (* 2) $ normals) @@ [o2 "showmeans" True, o2 "showmedians" True, o2 "vert" False] -- | http://matplotlib.org/examples/pylab_examples/scatter_hist.html mscatterHist = figure @@ [o1 0] % setSizeInches 8 8 -- The scatter plot % axes @@ [o1 ([left, bottom', width, height] :: [Double])] % scatter x y % xlim (-lim) lim % ylim (-lim) lim -- The histogram on the right (x) % axes @@ [o1 [left, bottom_h, width, 0.2]] % mp # "ax.xaxis.set_major_formatter(mticker.NullFormatter())" % histogram x bins % xlim (-lim) lim -- The histogram on top (y) % axes @@ [o1 [left_h, bottom', 0.2, height]] % mp # "ax.yaxis.set_major_formatter(mticker.NullFormatter())" % histogram y bins @@ [o2 "orientation" "horizontal"] % ylim (-lim) lim where left = 0.1 width = 0.65 bottom' = 0.1 height = 0.65 bottom_h = left + width + 0.02 left_h = left + width + 0.02 [x, y] = take 2 $ chunksOf 1000 $ map (* 2) $ normals binwidth = 0.25 xymax = maximum [maximum $ map abs x, maximum $ map abs y] lim = ((fromIntegral $ round $ xymax / binwidth) + 1) * binwidth bins = [-lim,-lim+binwidth..(lim + binwidth)] mhistMulti = subplots @@ [o2 "nrows" 2, o2 "ncols" 2] % setSubplot 0 % histogram x nrBins @@ [o2 "density" 1, o2 "histtype" "bar", o2 "color" ["red", "tan", "lime"], o2 "label" ["red", "tan", "lime"]] % legend @@ [o2 "prop" $ lit "{'size': 10}"] % title "bars with legend" % setSubplot 1 % histogram x nrBins @@ [o2 "density" 1, o2 "histtype" "bar", o2 "stacked" True] % title "stacked bar" % setSubplot 2 % histogram x nrBins @@ [o2 "histtype" "step", o2 "stacked" True, o2 "fill" False] % title "stacked bar" % setSubplot 3 % histogram (map (\x -> take x normals) [2000, 5000, 10000]) nrBins @@ [o2 "histtype" "bar"] % title "different sample sizes" % tightLayout where nrBins = 10 x = take 3 $ chunksOf 1000 $ normals mspines = plot x y @@ [o1 "k--"] % plot x y' @@ [o1 "ro"] % xlim 0 (2 * pi) % xticks [0 :: Double, pi, 2*pi] % xtickLabels (map raw ["0", "$\\pi$", "2$\\pi$"]) % ylim (-1.5) 1.5 % yticks [-1 :: Double, 0, 1] % spine "left" % spineSetBounds (-1) 1 % spine "right" % spineSetVisible False % spine "top" % spineSetVisible False % axisYTicksPosition "left" % axisXTicksPosition "bottom" where x = mapLinear (\x -> x) 0 (2 * pi) 50 y = map sin x y' = zipWith (\a b -> a + 0.1*b) y normals mhists = h 10 1.5 % h 4 1 % h 15 2 % h 6 0.5 where ns mu var = map (\x -> mu + x * var) $ take 1000 normals h mu var = histogram (ns mu var) 25 @@ [o2 "histtype" "stepfilled" ,o2 "alpha" 0.8 ,o2 "density" True] mhinton = mp # "ax.patch.set_facecolor('gray')" % setAspect @@ [o1 "equal", o1 "box"] % mp # "ax.xaxis.set_major_locator(plot.NullLocator())" % mp # "ax.yaxis.set_major_locator(plot.NullLocator())" % foldl (\a (x,y,w) -> a % f x y w) mp m % mp # "ax.autoscale_view()" % mp # "ax.invert_yaxis()" where m = [ (x,y,w) | x <- [0..19], y <- [0..19] | w <- (map (\x -> x - 0.5) normals) ] maxWeight = maximum $ map (\(_,_,v) -> abs v) m f x y w = mp # "ax.add_patch(plot.Rectangle(" # "[" # (x - size / 2) # "," # (y - size / 2) # "]" # ", " # size # ", " # size # ", facecolor='" # color # "', edgecolor='" # color # "'))" where color = if w > 0 then "white" else "black" size = sqrt $ abs w / maxWeight mintegral = subplots % plot x y @@ [o1 "r", o2 "linewidth" 2] % ylim 0 (maximum y) % mp # "ax.add_patch(plot.Polygon(" # ([(a, 0)] ++ zip ix iy ++ [(b,0)]) ## "))" @@ [o2 "facecolor" "0.9", o2 "edgecolor" "0.5"] % text (0.5 * (a + b)) 30 [r|$\int_a^b f(x)\mathrm{d}x$|] @@ [o2 "horizontalalignment" "center", o2 "fontsize" 20] % figText 0.9 0.05 "$x$" % figText 0.1 0.9 "$y$" % spine "right" % spineSetVisible False % spine "top" % spineSetVisible False % axisXTicksPosition "bottom" % xticks (a, b) % xtickLabels (raw "$a$", raw "$b$") % yticks ([] :: [Double]) where func x = (x - 3) * (x - 5) * (x - 7) + 85 -- integral limits a = 2 :: Double b = 9 :: Double (x :: [Double]) = mapLinear (\x -> x) 0 10 100 y = map func x -- shaded region (ix :: [Double]) = mapLinear (\x -> x) a b 100 iy = map func ix mquiver = quiver x y u v (Nothing :: Maybe [Double]) @@ [o2 "units" "width"] % quiverKey 0.9 0.93 2 (raw [r|$2 \frac{m}{s}$|]) @@ [o2 "labelpos" "E", o2 "coordinates" "figure"] % xlim (-0.2) 6.4 % ylim (-0.2) 6.4 where m = [ (x,y,cos x,sin y) | x <- [0,0.2..2*pi], y <- [0,0.2..2*pi] ] x = map (\(x,_,_,_) -> x) m y = map (\(_,x,_,_) -> x) m u = map (\(_,_,x,_) -> x) m v = map (\(_,_,_,x) -> x) m mquiverFancy = quiver x y u v (Just mag) @@ [o2 "units" "x" ,o2 "pivot" "tip" ,o2 "width" 0.022 ,o2 "scale" (1 / 0.15)] % quiverKey 0.9 0.93 1 (raw [r|$2 \frac{m}{s}$|]) @@ [o2 "labelpos" "E", o2 "coordinates" "figure"] % scatter x y @@ [o2 "color" "k", o2 "s" 5] % xlim (-0.2) 6.4 % ylim (-0.2) 6.4 where m = [ (x,y,cos x,sin y) | x <- [0,0.2..2*pi], y <- [0,0.2..2*pi] ] x = map (\(x,_,_,_) -> x) m y = map (\(_,x,_,_) -> x) m u = map (\(_,_,x,_) -> x) m v = map (\(_,_,_,x) -> x) m mag = zipWith (\x x' -> sqrt(x**2 + x'**2)) u v mpolar = rc "grid" @@ [o2 "color" "#316931", o2 "linewidth" 1, o2 "linestyle" "-"] % rc "xtick" @@ [o2 "labelsize" 15] % rc "ytick" @@ [o2 "labelsize" 15] % figure @@ [o2 "figsize" (8::Int,8::Int)] % addAxes @@ [o1 [0.1, 0.1, 0.8, 0.8::Double], o2 "projection" "polar" -- TODO My matplotlib doesn't seem to have this property -- , o2 "facecolor" "#d5de9c" ] % plot theta r @@ [o2 "color" "#ee8d18", o2 "lw" 3, o2 "label" "a line"] % plot (map (\x -> 0.5*x) theta) r @@ [o2 "color" "blue", o2 "ls" "--", o2 "lw" 3, o2 "label" "another line"] % legend where r = [0,0.01..3.0] theta = map (\x -> 2*pi*x) r mbivariateNormal = imshow vs @@ [o2 "interpolation" "bilinear" ,o2 "cmap" $ raw "RdYlGn" ,o2 "origin" "lower" ,o2 "extent" [-3::Double, 3, -3, 3] ,o2 "vmin" $ (0-) $ maximum $ map abs vs' ,o2 "vmax" $ maximum $ map abs vs'] where delta = 0.025::Double xs = [-3.0,-3.0+delta..3.0] ys = [-3.0,-3.0+delta..3.0] vs = [[pdfBivariateNormal x y 1.5 0.5 1.0 1.0 0.0 - pdfBivariateNormal x y 1.0 1.0 0.0 0.0 0.0 | x <- xs] | y <- ys] vs' = foldl' (++) [] vs -- TODO This is subtly broken mimages = -- figure @@ [o2 "figsize" (10::Int,10::Int)] -- % subplots @@ [o2 "nrows" 1, o2 "ncols" 2] % setSubplot 0 % imshow "data/heightmap.png" @@ [o2 "interpolation" "nearest"] % setSubplot 1 % mp # "ls = mcolors.LightSource(azdeg=315, altdeg=45)" % mp # "ax.imshow(ls.shade(img, cmap=cm.gist_earth))" -- TODO This doesn't work on my matplab version -- vert_exag=0.05, --, blend_mode='overlay' % xlabel "overlay blend mode" mpcolorlog = figure % addSubplot 2 1 1 % pcolor3 xs' ys' vs @@ [o2 "cmap" $ raw "PuBu_r"] % colorbar % addSubplot 2 1 2 % pcolor3 xs' ys' vs @@ [o2 "norm" (lit $ "mcolors.LogNorm(vmin="++(show $ minimum vs')++ ", vmax="++(show $ maximum vs')++")") ,o2 "cmap" $ raw "PuBu_r"] % colorbar where delta = 0.1::Double xs = [-3.0,-3.0+delta..3.0] ys = [-3.0,-3.0+delta..3.0] vs = [[pdfBivariateNormal x y 0.1 0.2 1.0 1.0 0.0 + 0.1 * pdfBivariateNormal x y 1.0 1.0 0.0 0.0 0.0 | x <- xs] | y <- ys] xs' = [[ x | x <- xs]| y <- ys] ys' = [[ y | x <- xs]| y <- ys] vs' = foldl' (++) [] vs mpie = pie [15, 30, 45, 10 :: Double] @@ [o2 "explode" [0, 0.05, 0, 0 :: Double] ,o2 "labels" ["Frogs", "Hogs", "Dogs", "Logs"] ,o2 "autopct" "%.0f%%" ,o2 "shadow" True] -- | http://matplotlib.org/examples/pylab_examples/bar_stacked.html mstacked = -- TODO The locations of the bars is off bar [0..4] ms @@ [o1 width, o2 "color" "#d62728", o2 "yerr" mStd, o2 "label" "ms"] % bar [0..4] ws @@ [o1 width, o2 "bottom" ms, o2 "yerr" wStd, o2 "label" "ws"] % xticks [0..4 :: Int] % xtickLabels "['G1', 'G2', 'G3', 'G4', 'G5']" % title "Scores" % ylabel "Score" % yticks [0,10..80 :: Int] % legend where ms = [20 :: Double, 35, 30, 35, 27] ws = [25 :: Double, 32, 34, 20, 25] mStd = [2 :: Double, 3, 4, 1, 2] wStd = [3 :: Double, 5, 2, 3, 3] width = 0.35 :: Double mannotation = -- figure @@ [o2 "figsize" (10::Int,10::Int)] -- TODO This is subtly broken -- TODO Dictionaries plot t s @@ [o2 "lw" 3] % xlim (-1) 5 % ylim (-4) 3 % annotate "straight" @@ [o2 "xy" [0, 1::Double], o2 "xycoords" "data", o2 "xytext" [-50, 30 :: Double] ,o2 "textcoords" "offset points", o2 "arrowprops" (lit "dict(arrowstyle='->')")] % annotate "arc3,\\nrad 0.2" @@ [o2 "xy" [0.5, -1::Double], o2 "xycoords" "data", o2 "xytext" [-80, -60 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='arc3,rad=.2')")] % annotate "arc,\\nangle 50" @@ [o2 "xy" [1, 1::Double], o2 "xycoords" "data", o2 "xytext" [-90, 50 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='arc,angleA=0,armA=50,rad=10')")] % annotate "arc,\\narms" @@ [o2 "xy" [1.5, -1::Double], o2 "xycoords" "data", o2 "xytext" [-80, -60 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='arc,angleA=0,armA=40,angleB=-90,armB=30,rad=7')")] % annotate "angle,\\nangle 90" @@ [o2 "xy" [2, 1::Double], o2 "xycoords" "data", o2 "xytext" [-70, 30 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='angle,angleA=0,angleB=90,rad=10')")] % annotate "angle3,\\nangle -90" @@ [o2 "xy" [2.5, -1::Double], o2 "xycoords" "data", o2 "xytext" [-80, -60 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='angle3,angleA=0,angleB=-90')")] % annotate "angle,\\nround" @@ [o2 "xy" [3, 1::Double], o2 "xycoords" "data", o2 "xytext" [-60, 30 :: Double] ,o2 "textcoords" "offset points" ,o2 "bbox" (lit "dict(boxstyle='round', fc='0.8')") ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='angle,angleA=0,angleB=90,rad=10')")] % annotate "angle,\\nround4" @@ [o2 "xy" [3.5, -1::Double], o2 "xycoords" "data", o2 "xytext" [-70, -80 :: Double] ,o2 "textcoords" "offset points" ,o2 "bbox" (lit "dict(boxstyle='round4,pad=.5', fc='0.8')") ,o2 "size" 20 ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='angle,angleA=0,angleB=-90,rad=10')")] % annotate "angle,\\nshrink" @@ [o2 "xy" [4, 1::Double], o2 "xycoords" "data", o2 "xytext" [-60, 30 :: Double] ,o2 "textcoords" "offset points" ,o2 "bbox" (lit "dict(boxstyle='round', fc='0.8')") ,o2 "arrowprops" (lit "dict(arrowstyle='->', connectionstyle='angle,angleA=0,angleB=90,rad=10')")] -- TODO This annotation doesn't render correctly on my matplotlib version % annotate "" @@ [o2 "xy" [4, 1::Double], o2 "xycoords" "data", o2 "xytext" [4.5, -1 :: Double] ,o2 "textcoords" "offset points" ,o2 "arrowprops" (lit "dict(arrowstyle='<->', connectionstyle='bar', ec='k', shrinkA=5, shrinkB=5)")] where t = [0, 0.01 .. 5.0 :: Double] s = map (\x -> cos $ 2*pi*x) t mstreamplot = streamplot xs ys xs' ys' @@ [o2 "linewidth" mag'] -- useful for seeing the energy landscape -- pcolor3 xmat ymat vs where delta = 0.05::Double xs = [-3.0,-3.0+delta..3.0] ys = [-3.0,-3.0+delta..3.0] xmat = [[ x | x <- xs]| y <- ys] ymat = [[ y | x <- xs]| y <- ys] ms = [[grad' (\[xv,yv] -> pdfBivariateNormal xv yv 0.4 0.7 1.0 1.0 0.0 + pdfBivariateNormal xv yv 1.0 1.0 (-1.0) (-1.0) 0.0) [x,y] | x <- xs] | y <- ys] :: [[(Double, [Double])]] vs = map2 (\(v, _) -> v) ms xs' = map2 (\(_, [x, _]) -> x) ms ys' = map2 (\(_, [_, y]) -> y) ms mag' = zipWith (\lx ly -> zipWith (\x y -> 5 * (log $ 1 + (sqrt $ x*x + y*y))) lx ly) xs' ys' map2 f l = map (\r -> map f r) l mgriddata = readData (x, y, z, xi, yi) -- TODO This requires a lot of manual indexing. Next big API change will be to -- have references to loaded data. % mp # "data.append(interpolate.griddata((data[0], data[1]), data[2], tuple(np.meshgrid(data[3], data[4])), method='linear', rescale=True))" % mp # "plot.contour(data[3], data[4], data[5], 15, linewidths=0.5, colors='k')" % mp # "plot.contourf(data[3], data[4], data[5], 15, extend='both')" % colorbar % scatter x y @@ [o2 "marker" "o", o2 "s" 5, o2 "zorder" 10] % xlim (-2) 2 % ylim (-2) 2 % title "Grid interpolation" where [x, y] = take 2 $ chunksOf 200 $ map (\x -> 4 * (x - 0.5)) $ uniforms z = zipWith (\x y -> x*(exp $ -(x**2) - y**2)) x y xi = mapLinear (\x -> x) (-2.1) 2.1 300 yi = mapLinear (\x -> x) (-2.1) 2.1 300