Remove 3d randomwalk (#17)

* Erase 3D random walks

* Hard-code moves

* Update examples

README.md

@@ -106,10 +106,9 @@ plt.savefig("example_images/lyapunov_ex.png")
 Image produced with this code:
 
 ```python
-basis = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
-moves = pf.construct_moves(basis)
-res = pf.randomwalk(moves, niter=5000000, width=4, height=3, depth=10, dpi=300)
-pf.images.randomwalk_image(res, cmap=colormaps["gist_yarg"], gamma=1.0)
+moves = pf.construct_moves((1, 0), (0, 1))
+res = pf.randomwalk(moves, niter=1000000, width=4, height=3, dpi=300)
+pf.images.image(res, cmap=colormaps["gnuplot"], gamma=1.0)
 plt.savefig("example_images/randomwalk_ex.png")
 ```
 
@@ -140,13 +139,12 @@ plt.savefig("example_images/buddhabrot_ex.png")
 * Julia
 * Buddhabrot
 * Markus-Lyapunov
-* 3D random walks
+* 2D random walks
 
 ## Image Creation
 * Function `image` wrapping `matplotlib.pyplot.imshow`
 * Function `nebula_image` for Buddhabrot ["nebula"](https://en.wikipedia.org/wiki/Buddhabrot#Nuances) coloration
 * Function `markus_lyapunov_image` for [Markus-Lyapunov](https://doi.org/10.1016/0097-8493(89)90019-8) coloration
-* Function `randomwalk_image` for coloring 3D random walks with depth
 * Function `save_animation` for animating a sequence of results
 
 ## More than Quadratic Polynomials

examples.py

@@ -103,10 +103,8 @@ def lyapunov_example() -> None:
 
 def randomwalk_example() -> None:
     start_time = time.time()
-    basis = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
-    moves = pf.construct_moves(basis)
-    res = pf.randomwalk(moves, niter=5000000, width=4, height=3, depth=10, dpi=300)
-    pf.images.randomwalk_image(res, cmap=colormaps["gist_yarg"], gamma=1.0)
+    res = pf.randomwalk(niter=1000000, width=4, height=3, dpi=300)
+    pf.images.image(res, cmap=colormaps["gnuplot"], gamma=1.0)
     plt.savefig("example_images/randomwalk_ex.png")
     print(f"calculation took {round((time.time() - start_time), 2)} seconds")
 

pyfracgen/__init__.py

@@ -5,7 +5,7 @@
 from .julia import julia
 from .lyapunov import lyapunov
 from .mandelbrot import mandelbrot
-from .randomwalk import construct_moves, randomwalk
+from .randomwalk import randomwalk
 
 __all__ = [
     "buddhabrot",
@@ -15,7 +15,6 @@
     "lyapunov",
     "mandelbrot",
     "randomwalk",
-    "construct_moves",
     "Result",
     "Canvas",
     "funcs",

pyfracgen/common.py

@@ -9,7 +9,7 @@
 
 import numpy as np
 
-from pyfracgen.types import Bound, Lattice, Lattice3D
+from pyfracgen.types import Bound, Lattice
 
 RESULT_DEFAULT_SAVE = Path("save.pickle")
 
@@ -48,14 +48,6 @@ def paint(self, *args: Any, **kwargs: Any) -> None:
         raise NotImplementedError
 
 
-class Canvas3D(Canvas):
-    def __init__(self, width: int, height: int, depth: int, dpi: int) -> None:
-        super().__init__(width, height, dpi)
-        self.lattice: Lattice3D = np.dstack(
-            [np.zeros(self.lattice.shape) for _ in range(depth)]
-        )
-
-
 class CanvasBounded(Canvas):
     def __init__(
         self, width: int, height: int, dpi: int, xbound: Bound, ybound: Bound

pyfracgen/images/images.py

@@ -96,31 +96,6 @@ def markus_lyapunov_image(
     return fig, ax0
 
 
-def randomwalk_image(
-    res: Result,
-    cmap: colors.Colormap = DEFAULT_COLORMAP,
-    ticks: bool = False,
-    gamma: float = 0.3,
-    alpha_scale: float = 1.0,
-) -> tuple[Figure, Axes]:
-    fig, ax0 = plt.subplots(figsize=figaspect(res.image_array[:, :, 0]), dpi=res.dpi)
-    fig.subplots_adjust(0, 0, 1, 1)
-    max_ind = float(res.image_array.shape[-1] + 1)
-    for i in range(res.image_array.shape[-1]):
-        im = res.image_array[..., i]
-        im = np.ma.masked_where(im == 0, im)  # type: ignore[no-untyped-call]
-        alpha = alpha_scale * (1 - (i + 1) / max_ind)
-        norm = colors.PowerNorm(gamma)
-        ax0.imshow(
-            im, origin="lower", alpha=alpha, cmap=cmap, norm=norm, interpolation=None
-        )
-    if not ticks:
-        plt.axis(ticks)
-    fs = plt.gcf()
-    fs.set_size_inches(res.width_inches, res.height_inches)
-    return fig, ax0
-
-
 def save_animation(
     series: Sequence[Result],
     cmap: colors.Colormap = DEFAULT_COLORMAP,

pyfracgen/randomwalk.py

@@ -5,50 +5,39 @@
 from numpy import array
 from numpy.random import randint
 
-from pyfracgen.common import Canvas3D, Result
-from pyfracgen.types import Lattice3D, Moves3D
-
-
-def construct_moves(basis: Moves3D) -> Moves3D:
-    basis = np.r_[basis, -1 * basis, [array([0, 0, 0])]]
-    nonnull = list(
-        filter(lambda x: np.any(x), (b0 + b1 for b0, b1 in itt.combinations(basis, 2)))
-    )
-    moves: Moves3D = np.unique(nonnull, axis=0)
-    return moves
+from pyfracgen.common import Result, Canvas
+from pyfracgen.types import Moves, Lattice
 
 
 @jit(nopython=True)  # type: ignore[misc]
 def _randomwalk_paint(
-    lattice: Lattice3D,
-    moves: Moves3D,
+    lattice: Lattice,
+    moves: Moves,
     niter: int,
 ) -> None:
     nmoves = len(moves)
-    h, w, d = lattice.shape
-    indices = array([h, w, d]) / 2.0
+    h, w = lattice.shape
+    indices = array([h, w]) / 2.0
     for iteration in range(niter):
         move = moves[randint(0, nmoves)]
         indices += move
-        iy, ix, iz = int(indices[0] % h), int(indices[1] % w), int(indices[2] % d)
-        lattice[iy, ix, iz] = iteration
+        iy, ix = int(indices[0] % h), int(indices[1] % w)
+        lattice[iy, ix] = iteration
 
-    lattice /= np.amax(lattice)
 
+class RandomWalk(Canvas):
+    moves = np.array(list(itt.product([1, -1, 0], [1, -1, 0])))
 
-class RandomWalk(Canvas3D):
-    def paint(self, moves: Moves3D, niter: int) -> None:
-        _randomwalk_paint(self.lattice, moves, niter)
+    def paint(self, niter: int) -> None:
+        _randomwalk_paint(self.lattice, self.moves, niter)
 
 
 def randomwalk(
-    moves: Moves3D,
     niter: int,
     width: int = 5,
     height: int = 4,
-    depth: int = 1,
     dpi: int = 300,
 ) -> Result:
-    canvas = RandomWalk(width, height, depth, dpi)
-    canvas.paint(moves, niter)
+    canvas = RandomWalk(width, height, dpi)
+    canvas.paint(niter)
     return canvas.result

pyfracgen/types.py

@@ -7,8 +7,7 @@
 Depth = NewType("Depth", int)
 
 Lattice = NDArray[Shape["Height, Width"], Float64]
-Lattice3D = NDArray[Shape["Height, Width, Depth"], Float64]
-Moves3D = NDArray[Shape["*, 3"], Int64]
+Moves = NDArray[Shape["*, 2"], Int64]
 Boxes = NDArray[Shape["*, 2"], Float64]
 ComplexSequence = NDArray[Shape["*"], Complex128]