From 0e063a9e3693b77f348956a59c0b0cea3ede6947 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Fri, 1 Jan 2021 16:06:30 +0000 Subject: [PATCH 1/8] Added initial version of 2D cmap ability --- swiftsimio/visualisation/tools/__init__.py | 0 swiftsimio/visualisation/tools/cmaps.py | 216 +++++++++++++++++++++ tests/test_vistools.py | 28 +++ 3 files changed, 244 insertions(+) create mode 100644 swiftsimio/visualisation/tools/__init__.py create mode 100644 swiftsimio/visualisation/tools/cmaps.py create mode 100644 tests/test_vistools.py diff --git a/swiftsimio/visualisation/tools/__init__.py b/swiftsimio/visualisation/tools/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/swiftsimio/visualisation/tools/cmaps.py b/swiftsimio/visualisation/tools/cmaps.py new file mode 100644 index 00000000..8a85a957 --- /dev/null +++ b/swiftsimio/visualisation/tools/cmaps.py @@ -0,0 +1,216 @@ +""" +Two-dimensional colour map support, along with example colour maps. +""" + +from typing import List, Optional, Iterable + +import numpy as np + +from swiftsimio.accelerated import jit + +COLOR_MAP_GRID_SIZE = 256 + + +def ensure_rgba(input_color: Iterable[float]) -> np.array: + """ + Ensures a colour is RGBA compliant. + + Default alpha if missing: 1.0. + + Parameters + ---------- + + input_color: iterable + An iterable of maximum length 4, with RGBA values + encoded as floating point 0.0 -> 1.0. + + + Returns + ------- + + array_color: np.array + An array of length 4 as an RGBA color. + + """ + + array_color = np.zeros(4, dtype=np.float32) + array_color[-1] = 1.0 + + for index, rgba in enumerate(input_color): + array_color[index] = rgba + + return array_color + + +@jit(nopython=True, fastmath=True) +def apply_color_map(first_values, second_values, map_grid): + """ + Applies a 2D colour map by providing a 2D linear interpolation + to the known fixed grid points. Not to be called on its own, + as the map itself is provided by the ``LinearSegmentedCmap2D``, + but this is provided separately so it can be ``numba``-accelerated. + + Parameters + ---------- + + first_values: iterable[float] + Array or list to loop over, containing floats ranging from 0.0 + to 1.0. Provides the normalisation for the horizontal + component. Must be one-dimensional. + + second_values: iterable[float] + Array or list to loop over, containing floats ranging from 0.0 + to 1.0. Provides the normalisation for the vertical + component. Must be one-dimensional. + + map_grid: np.ndarray + 2D numpy array proided by ``LinearSegmentedCmap2D``. + + + Returns + ------- + + np.ndarray + An N by 4 array (where N is the length of ``first_value`` and + ``second_value``) of RGBA components. + """ + + number_of_values = len(first_values) + output_values = np.empty(number_of_values * 4, dtype=np.float32).reshape( + (number_of_values, 4) + ) + + for index in range(number_of_values): + horizontal = COLOR_MAP_GRID_SIZE * min(max(first_values[index], 0.0), 1.0) + vertical = COLOR_MAP_GRID_SIZE * min(max(second_values[index], 0.0), 1.0) + + horizontal_base = np.int32(horizontal) + vertical_base = np.int32(vertical) + + # Could do some more fancy interpolation but I'm sure this will do. + output_values[index] = map_grid[horizontal_base, vertical_base] + + return output_values + + +class LinearSegmentedCmap2D(object): + """ + A two dimensional implementation of the linear segmented + colour map. + """ + + _color_map_grid: Optional[np.array] = None + + def __init__( + self, + colors: List[List[float]], + coordinates: List[List[float]], + name: Optional[str] = None, + ): + self.colors = colors + self.coordinates = coordinates + self.name = name + + return + + @property + def color_map_grid(self): + """ + Generates, or gets, the color map grid. + """ + + if self._color_map_grid is None: + # Better make it! + self._color_map_grid = np.zeros( + COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE * 4, dtype=np.float32 + ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE, 4)) + + # Set initial alpha values to 1.0 + self._color_map_grid[:, :, 3] = 1.0 + + x, y = np.meshgrid(*[np.linspace(0, 1, COLOR_MAP_GRID_SIZE)] * 2) + + # Need to loop through each colour, giving the grid each component + # in turn. + for color, coordinate in zip(self.colors, self.coordinates): + array_color = ensure_rgba(color) + + dx = x - coordinate[0] + dy = y - coordinate[1] + + r = np.sqrt(dx * dx + dy * dy) + + weights = np.maximum(1.0 - r, 0.0) + + for x_ind in range(COLOR_MAP_GRID_SIZE): + for y_ind in range(COLOR_MAP_GRID_SIZE): + # Screen blend mode + self._color_map_grid[x_ind, y_ind, :] = 1.0 - ( + 1.0 - self._color_map_grid[x_ind, y_ind, :] + ) * (1.0 - weights[x_ind, y_ind] * array_color) + + return self._color_map_grid + + def plot(self, ax, include_points: bool = False): + """ + Plot the color map on axes. + + Parameters + ---------- + + ax: matplotlib.Axis + Axis to be plotted on. + + include_points: bool, optional + If true, plot the individual colours as points that make + up the color map. Default: False. + """ + + ax.imshow(self.color_map_grid, origin="lower", extent=[0, 1, 0, 1]) + ax.set_xlabel("Horizontal Value (first index)") + ax.set_ylabel("Vertical Value (second index)") + + if include_points: + for color, coordinate in zip(self.colors, self.coordinates): + rgba_color = ensure_rgba(color) + + ax.scatter(*coordinate, color=rgba_color, edgecolor="white") + + return + + def __call__(self, horizontal_values, vertical_values): + """ + Apply the 2D color map to some data. Both sets of values + must be of the same shape. + + Parameters + ---------- + + horizontal_values: iterable + Values for the first parameter in the color map + + vertical_values: iterable + Values for the second parameter in the color map + + Returns + ------- + + mapped: np.ndarray + RGBA array using the internal colour map. + """ + + if isinstance(horizontal_values, list) or isinstance(horizontal_values, tuple): + horizontal_values = np.array(horizontal_values) + + if isinstance(vertical_values, list) or isinstance(vertical_values, tuple): + vertical_values = np.array(vertical_values) + + values = apply_color_map( + first_values=horizontal_values.flatten(), + second_values=vertical_values.flatten(), + map_grid=self.color_map_grid, + ) + + values.reshape(horizontal_values.shape + (4,)) + + return values diff --git a/tests/test_vistools.py b/tests/test_vistools.py new file mode 100644 index 00000000..d684ce15 --- /dev/null +++ b/tests/test_vistools.py @@ -0,0 +1,28 @@ +""" +Tests the visualisation tools. +""" + +from swiftsimio.visualisation.tools.cmaps import LinearSegmentedCmap2D +import numpy as np + + +def test_basic_linear_2d(): + x = LinearSegmentedCmap2D( + colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], + coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], + ) + + x.color_map_grid + + return + + +def test_apply_to_data_2d(): + x = LinearSegmentedCmap2D( + colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], + coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], + ) + + x(np.linspace(0, 1, 10), np.linspace(0.2, 0.8, 10)) + + return From 386008fd28313106abc4de92ba517aefa6be61b8 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 11:20:46 +0000 Subject: [PATCH 2/8] Refactoring color map 2D code --- swiftsimio/visualisation/tools/cmaps.py | 203 +++++++++++++++++++----- tests/test_vistools.py | 25 ++- 2 files changed, 184 insertions(+), 44 deletions(-) diff --git a/swiftsimio/visualisation/tools/cmaps.py b/swiftsimio/visualisation/tools/cmaps.py index 8a85a957..34ba0f73 100644 --- a/swiftsimio/visualisation/tools/cmaps.py +++ b/swiftsimio/visualisation/tools/cmaps.py @@ -5,6 +5,7 @@ from typing import List, Optional, Iterable import numpy as np +from matplotlib.colors import rgb_to_hsv, hsv_to_rgb from swiftsimio.accelerated import jit @@ -80,9 +81,12 @@ def apply_color_map(first_values, second_values, map_grid): (number_of_values, 4) ) + norm_x = np.float32(len(map_grid[0]) - 1) + norm_y = np.float32(len(map_grid) - 1) + for index in range(number_of_values): - horizontal = COLOR_MAP_GRID_SIZE * min(max(first_values[index], 0.0), 1.0) - vertical = COLOR_MAP_GRID_SIZE * min(max(second_values[index], 0.0), 1.0) + horizontal = norm_x * min(max(first_values[index], 0.0), 1.0) + vertical = norm_y * min(max(second_values[index], 0.0), 1.0) horizontal_base = np.int32(horizontal) vertical_base = np.int32(vertical) @@ -93,23 +97,30 @@ def apply_color_map(first_values, second_values, map_grid): return output_values -class LinearSegmentedCmap2D(object): +class Cmap2D(object): """ - A two dimensional implementation of the linear segmented - colour map. + A generic two dimensional implementation of a colour map. """ _color_map_grid: Optional[np.array] = None def __init__( - self, - colors: List[List[float]], - coordinates: List[List[float]], - name: Optional[str] = None, + self, name: Optional[str] = None, description: Optional[str] = None, ): - self.colors = colors - self.coordinates = coordinates self.name = name + self.description = description + + return + + def generate_color_map_grid(self): + """ + Generates the colour map grid and stores it in + ``_color_map_grid``. Imeplementation dependent. + """ + + self._color_map_grid = np.empty( + (COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE), dtype=np.float32 + ) return @@ -121,33 +132,7 @@ def color_map_grid(self): if self._color_map_grid is None: # Better make it! - self._color_map_grid = np.zeros( - COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE * 4, dtype=np.float32 - ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE, 4)) - - # Set initial alpha values to 1.0 - self._color_map_grid[:, :, 3] = 1.0 - - x, y = np.meshgrid(*[np.linspace(0, 1, COLOR_MAP_GRID_SIZE)] * 2) - - # Need to loop through each colour, giving the grid each component - # in turn. - for color, coordinate in zip(self.colors, self.coordinates): - array_color = ensure_rgba(color) - - dx = x - coordinate[0] - dy = y - coordinate[1] - - r = np.sqrt(dx * dx + dy * dy) - - weights = np.maximum(1.0 - r, 0.0) - - for x_ind in range(COLOR_MAP_GRID_SIZE): - for y_ind in range(COLOR_MAP_GRID_SIZE): - # Screen blend mode - self._color_map_grid[x_ind, y_ind, :] = 1.0 - ( - 1.0 - self._color_map_grid[x_ind, y_ind, :] - ) * (1.0 - weights[x_ind, y_ind] * array_color) + self.generate_color_map_grid() return self._color_map_grid @@ -203,7 +188,9 @@ def __call__(self, horizontal_values, vertical_values): horizontal_values = np.array(horizontal_values) if isinstance(vertical_values, list) or isinstance(vertical_values, tuple): - vertical_values = np.array(vertical_values) + vertical_values = np.ndarray(vertical_values) + + output_shape = horizontal_values.shape + (4,) values = apply_color_map( first_values=horizontal_values.flatten(), @@ -211,6 +198,140 @@ def __call__(self, horizontal_values, vertical_values): map_grid=self.color_map_grid, ) - values.reshape(horizontal_values.shape + (4,)) + return values.reshape(output_shape) + + +class LinearSegmentedCmap2D(Cmap2D): + """ + A two dimensional implementation of the linear segmented + colour map. + """ + + _color_map_grid: Optional[np.array] = None + + def __init__( + self, + colors: List[List[float]], + coordinates: List[List[float]], + name: Optional[str] = None, + description: Optional[str] = None, + ): + super().__init__(name, description) + + self.colors = colors + self.coordinates = coordinates + + return + + def generate_color_map_grid(self): + """ + Generates the color map grid. + """ + rgba_grid = np.zeros( + COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE * 4, dtype=np.float32 + ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE, 4)) + + values = np.linspace(0, 1, COLOR_MAP_GRID_SIZE) + + rgba_values = [ensure_rgba(color) for color in self.colors] + + for x_ind in range(COLOR_MAP_GRID_SIZE): + for y_ind in range(COLOR_MAP_GRID_SIZE): + weights = 0.0 + + for rgba, coordinate in zip(rgba_values, self.coordinates): + dx = values[y_ind] - coordinate[0] + dy = values[x_ind] - coordinate[1] + + r = np.sqrt(dx * dx + dy * dy) + + weight = np.maximum(1.0 - r, 0.0) + + rgba_grid[x_ind, y_ind] += rgba * weight + weights += weight + + rgba_grid[x_ind, y_ind] /= weights * 1.0001 + + self._color_map_grid = rgba_grid + + return self._color_map_grid + + +class LinearSegmentedCmap2DHSV(Cmap2D): + """ + A two dimensional implementation of the linear segmented + colour map, using the HSV space to combine the colours. + """ + + _color_map_grid: Optional[np.array] = None + + def __init__( + self, + colors: List[List[float]], + coordinates: List[List[float]], + name: Optional[str] = None, + description: Optional[str] = None, + ): + super().__init__(name, description) + + self.colors = colors + self.coordinates = coordinates + + return + + def generate_color_map_grid(self): + """ + Generates the color map grid. + """ + hsv_grid = np.zeros( + COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE * 3, dtype=np.float32 + ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE, 3)) + + a_grid = np.zeros( + COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE, dtype=np.float32 + ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE)) + + values = np.linspace(0, 1, COLOR_MAP_GRID_SIZE) + + hsv_values = [ + np.array(rgb_to_hsv(ensure_rgba(color)[:-1])) for color in self.colors + ] + a_values = [ensure_rgba(color)[-1] for color in self.colors] + + for x_ind in range(COLOR_MAP_GRID_SIZE): + for y_ind in range(COLOR_MAP_GRID_SIZE): + weights = 0.0 + + for hsv, a, coordinate in zip(hsv_values, a_values, self.coordinates): + dx = values[y_ind] - coordinate[0] + dy = values[x_ind] - coordinate[1] + + r = np.sqrt(dx * dx + dy * dy) + + weight = np.maximum(1.0 - r, 0.0) + + hsv_grid[x_ind, y_ind] += hsv * weight + a_grid[x_ind, y_ind] += a * weight + + weights += weight + + hsv_grid[x_ind, y_ind] /= weights * 1.0001 + a_grid[x_ind, y_ind] /= weights * 1.0001 + + self._color_map_grid = np.empty( + COLOR_MAP_GRID_SIZE * COLOR_MAP_GRID_SIZE * 4, dtype=np.float32 + ).reshape((COLOR_MAP_GRID_SIZE, COLOR_MAP_GRID_SIZE, 4)) + + self._color_map_grid[:, :, :-1] = hsv_to_rgb(hsv_grid) + self._color_map_grid[:, :, -1] = a_grid + + return self._color_map_grid + + +# Define built in color maps. - return values +bower = LinearSegmentedCmap2D( + colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], + coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], + name="bower", +) diff --git a/tests/test_vistools.py b/tests/test_vistools.py index d684ce15..e4a7fae6 100644 --- a/tests/test_vistools.py +++ b/tests/test_vistools.py @@ -2,7 +2,10 @@ Tests the visualisation tools. """ -from swiftsimio.visualisation.tools.cmaps import LinearSegmentedCmap2D +from swiftsimio.visualisation.tools.cmaps import ( + LinearSegmentedCmap2D, + LinearSegmentedCmap2DHSV, +) import numpy as np @@ -18,11 +21,27 @@ def test_basic_linear_2d(): def test_apply_to_data_2d(): - x = LinearSegmentedCmap2D( + bower = LinearSegmentedCmap2D( + colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], + coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], + ) + + bower_hsv = LinearSegmentedCmap2DHSV( colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], ) - x(np.linspace(0, 1, 10), np.linspace(0.2, 0.8, 10)) + def vertical_func(x): + return abs(1.0 - 2.0 * x) + + def horizontal_func(y): + return y ** 2 + + raster_at = np.linspace(0, 1, 1024) + + x, y = np.meshgrid(horizontal_func(raster_at), vertical_func(raster_at)) + + imaged = bower(x, y) + imaged_hsv = bower_hsv(x, y) return From cdcdc5098831f14cdcf35ab1e37014705974b167 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 11:53:52 +0000 Subject: [PATCH 3/8] Added docs --- swiftsimio/visualisation/tools/cmaps.py | 115 ++++++++++++++++++++++-- 1 file changed, 110 insertions(+), 5 deletions(-) diff --git a/swiftsimio/visualisation/tools/cmaps.py b/swiftsimio/visualisation/tools/cmaps.py index 34ba0f73..380c0c6d 100644 --- a/swiftsimio/visualisation/tools/cmaps.py +++ b/swiftsimio/visualisation/tools/cmaps.py @@ -100,10 +100,16 @@ def apply_color_map(first_values, second_values, map_grid): class Cmap2D(object): """ A generic two dimensional implementation of a colour map. + + Developer use only. """ _color_map_grid: Optional[np.array] = None + # Properties for color maps that generate + colors: List[List[float]] = None + coordinates: List[List[float]] = None + def __init__( self, name: Optional[str] = None, description: Optional[str] = None, ): @@ -155,7 +161,7 @@ def plot(self, ax, include_points: bool = False): ax.set_xlabel("Horizontal Value (first index)") ax.set_ylabel("Vertical Value (second index)") - if include_points: + if include_points and self.colors is not None: for color, coordinate in zip(self.colors, self.coordinates): rgba_color = ensure_rgba(color) @@ -207,8 +213,6 @@ class LinearSegmentedCmap2D(Cmap2D): colour map. """ - _color_map_grid: Optional[np.array] = None - def __init__( self, colors: List[List[float]], @@ -216,6 +220,32 @@ def __init__( name: Optional[str] = None, description: Optional[str] = None, ): + """ + Parameters + ---------- + + colors: List[List[float]] + Individual colors (at ``coordinates`` below) that make up + the color map. + + coordinates: List[List[float]] + 2D coordinates in the plane to place the above ``colors`` + at. + + name: str, optional + Name of this color map (metadata) + + description: str, optional + Optional metadata description of this colour map. + + + See Also + -------- + + ``LinearSegmentedCmap2DHSV``, a cousin of this class that + combines colours using the HSV space rather than RGB used + here. + """ super().__init__(name, description) self.colors = colors @@ -261,10 +291,33 @@ class LinearSegmentedCmap2DHSV(Cmap2D): """ A two dimensional implementation of the linear segmented colour map, using the HSV space to combine the colours. + + Parameters + ---------- + + colors: List[List[float]] + Individual colors (at ``coordinates`` below) that make up + the color map. + + coordinates: List[List[float]] + 2D coordinates in the plane to place the above ``colors`` + at. + + name: str, optional + Name of this color map (metadata) + + description: str, optional + Optional metadata description of this colour map. + + + See Also + -------- + + ``LinearSegmentedCmap2D``, a cousin of this class that + combines colours using the RGB space rather than HSV used + here. """ - _color_map_grid: Optional[np.array] = None - def __init__( self, colors: List[List[float]], @@ -328,6 +381,58 @@ def generate_color_map_grid(self): return self._color_map_grid +class ImageCmap2D(Cmap2D): + """ + Creates a 2D color map from an image loaded from disk. + """ + + def __init__( + self, + filename: str, + name: Optional[str] = None, + description: Optional[str] = None, + ): + """ + Parameters + ---------- + + file_path: str + Path to the image to use as the color map. + + name: str, optional + Name of this color map (metadata) + + description: str, optional + Optional metadata description of this colour map. + """ + + super().__init__(name=name, description=description) + + self.filename = filename + + return + + def generate_color_map_grid(self): + """ + Loads the image from file and stores it as the internal + array. + """ + + try: + from PIL import Image + except: + raise ImportError( + "Unable to import pillow, which must be installed " + "to use color maps generated from images." + ) + + self._color_map_grid = ( + np.array(Image.open(self.filename)).astype(np.float32) / 255.0 + ) + + return + + # Define built in color maps. bower = LinearSegmentedCmap2D( From 7dfb609dcb2290fbf1d1aa327bfe82980c74dd37 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 12:26:25 +0000 Subject: [PATCH 4/8] Added docs for 2D cmaps --- docs/source/visualisation/bower_cmap.png | Bin 0 -> 123728 bytes docs/source/visualisation/index.rst | 1 + docs/source/visualisation/millenium_cmap.png | Bin 0 -> 52649 bytes .../visualisation/test_2d_cmap_output.png | Bin 0 -> 89704 bytes .../test_2d_cmap_output_mill.png | Bin 0 -> 118182 bytes docs/source/visualisation/tools.rst | 78 ++++++++++++++++++ 6 files changed, 79 insertions(+) create mode 100644 docs/source/visualisation/bower_cmap.png create mode 100644 docs/source/visualisation/millenium_cmap.png create mode 100644 docs/source/visualisation/test_2d_cmap_output.png create mode 100644 docs/source/visualisation/test_2d_cmap_output_mill.png create mode 100644 docs/source/visualisation/tools.rst diff --git a/docs/source/visualisation/bower_cmap.png b/docs/source/visualisation/bower_cmap.png new file mode 100644 index 0000000000000000000000000000000000000000..6b857f2b960bc262b4a245a57a573dc6e7dfcbe6 GIT binary patch literal 123728 zcmeFZd0f)z-aky!%(OUWO;eU@)|8c{ZD{Vzm|5mhnNo_VIch>`iW?%*G-a8kV`=1` z=8_AL87eB`luNl$ZYVC4sECN<0?6v`OP(|5JooFq?>XoEp4ao&!|SDj--Yk>xjxrt zeZQ}Sb53@u>owMcKp@pKr%zr0f!5prfxdaV_FLdT)D+kt@aJpf&u1>K1zxdhf4K{M zUU&WUWh4k>xJ&u7D!R}*68PuwaNA4aE+PKmQ9faQpdg>{>(@fUuLWM&5$P9(3=9cA zYIwx($blVK!^5we85#ZKxM4_GfYD>!`w1Y>4$zsCKV6K@ni)aA$GdtS|18i_i>X=q z?O|f*rjvH$w><}+`5{qJut&d6%Zc(?P1R~J-X zHG)pWj=_M;Zz^@4P@Iavhb4>F^80t@LNO&sh0B$OD1p>n0=?3W_0nbgy9 zs4D0yU>v~9dm`vk(8@m>PhSElMG3sNty5|I@&*Lj_5a^=MH2sC%5LSY`8IIHi#ui7g{(vzE$WIFkz_gLpcgRj3l-E-Pkhh7AGR9!oR^NhS)yV!lU#}DWE zxM8W;sHkqX79pjnSuK4GXFV`6EUa3i8+%CpL05iW@^Ovzld5Zj4|&Lszpg1_ED3G10v-`#@7i6=P98%!E14BPwh9zAFD zvyW9S)o}@RMZ1zMj%dd%eG2R;a@=fPH+IjU8#tOeTf<7SI{VF+yG-5x#@pKmJyX&8 z^6Y6MdW72@LHDed3yK^wyVqDR{Sn@(9aT_9Y%udgc7i!c=Ch~y*k!5y)|<-<*2_mJ z3IWmU)Vr10>>FIY?GmolN?5@e@J)6EE`-KR9?eY$E~*KCqiRy{$jK})5R3t2?XjtK*N-i)T zol9CIL{SiT4)dd1&AZbBa>#PQI{mEQ4I7rmy5K7_KJ}YY7VS`wVj4otNHUv#&Lc)K zF{1FHpz1>9xXkY>#oDbVf3H>;1Xzray2%Vg_oq9$qnGh3GVrWibLd64m0~X0x!y|9 z>%ulv6fM5ZeHqtR1_OVH97VBR@v2`=eHya$#;<9@cg}HPV}f`3xmrmWV7!OsBsWzI zpI_Mg<($TsfcbE98>-?Mc!}Fi4gn9mG0A$aX|p~ID{l94QtY?-a^8zJz&06hi!y`l zMZ-v%kY2}cK*zk^oCBP_^zpZz;5r^4gsPyS?t|6C7f7eRTy(?gGH~;LlZLqm3G_AE z;qPma4y_LC6;WK;t$aEXutI=iI?*3%ky_UqSDAOLTlqeFW5YVojSEWQG;v3OKO?3^ zzD3B#jM@l9tz0-n-?EU+kJZP_C3-n5^Oxn+S9BP<@V5Dg>#mnrA|(XQtYRg_n{ z{efa<&$E#@7*-R{^Zqhm|f57Bq6*`&oUM-eFC~(iibSTo%446zR zaYFZky|ZF;Ik-5+nF@3E2!sZzl3Eh`H*T-w&%yg&>}MUkVDn3dE7?EaH%YEVn8)b8 z(+=`To7?&hd~0DM$AgC^a7B#MhI~=tMA%46t4Bfn!{Nl=Ar9Dv9&t%?9&pc^T92o@F_rvpeL~ms3IJo0&=#`(ur6R^&(ooky$=8hRXD z%PG1pb2J%Aoh7q#zO1k)Y3j-a2AzP-eVI{o#!fq;_vFxS9Q6AnDqte@VY(5$=Su=J z_LEk8>;dIcEu@U^HcF3{r_*BhXqk_Q3XL#M}78clT|-cD9RR?GxbUzul;s8S687qh6R0>r2HP> zVa{^^qdBCI%+~Rp0&+3J;hIXCmATRgNV%+JYb)*0rcK$sYrlN?dv%q@#;3;|kIpe| z)jf}yOnUNT=uKQvgNVXe$X%9Y$gKf$S6JC)hREl29Hkv7RsV9G_i5#_@{WMU&NXvJ z(fsVd<#`;{Vom})`q^ChOhBcnkcnNMX11^@c+f z5rywaT}q@ri3F?`U^#&&Jd2&z$37etR#g`Qe(E|}mIzzSUzD+}sc^>?X|=z96*Od6 zx7Hi174}w-0~iwby{!l@DPu7uIrf*%T$9f67Cm)Xv`@_FLXL?E-~vS0;s8tTWlp?i z@RO@dz-RR2-O$;DU2mVn6i zU`)ZCDNOVh)J3-BB*SetpneXbOKA)UW)$c7|Io{|;BZfLl34SUDx8Tztf(!-Ab1`4 z*y`s#X>4K-gUZ(rGM{59y_7a;JOv?K^HjHC)pz$_$4PlO!}`y!!-2VWh}|UyWa^k{ z64KS8g<1T-*_^x7v|}q4nbBM1->Ehb_i0L>@M9EDW4c$z)C`czDMC8a?~q$be|GkA z&noZhfV;ilqSR%;YrPEbzZ_5qxE^e0oRm++ngK)XDa64tHkeI4)%m-de;fi@?PD?; 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--git a/docs/source/visualisation/tools.rst b/docs/source/visualisation/tools.rst new file mode 100644 index 00000000..d4244927 --- /dev/null +++ b/docs/source/visualisation/tools.rst @@ -0,0 +1,78 @@ +Tools +===== + +:mod:`swiftsimio` includes a few tools to help you make your visualisations +'prettier'. Below we describe these tools and their use. + +2D Color Maps +------------- + +The :mod:`swiftsimio.visualisation.tools.cmaps` module includes three +objects that can be used to deploy two dimensional colour maps. The first, +:class:`swiftsimio.visualisation.tools.cmaps.LinearSegmentedCmap2D`, and second +:class:`swiftsimio.visualisation.tools.cmaps.LinearSegmentedCmap2DHSV`, allow +you to generate new color maps from sets of colors and coordinates. + +.. code-block:: python + + bower = LinearSegmentedCmap2D( + colors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [0.0, 0.0, 0.0]], + coordinates=[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]], + name="bower" + ) + +This generates a color map that is a quasi-linear interpolation between all +of the points. The map can be displayed using the ``plot`` method, + +.. code-block:: python + + fig, ax = plt.subplots() + + bower.plot(ax) + +Which generates: + +.. image:: bower_cmap.png + +Finally, the color map can be applied to data by calling it: + +.. code-block:: python + + def vertical_func(x): + return abs(1.0 - 2.0 * x) + + def horizontal_func(y): + return y ** 2 + + raster_at = np.linspace(0, 1, 1024) + + x, y = np.meshgrid(horizontal_func(raster_at), vertical_func(raster_at)) + + imaged = bower(x, y) + + plt.imsave("test_2d_cmap_output.png", imaged) + +Where here ``imaged`` is an RGBA array. This outputs: + +.. image:: test_2d_cmap_output.png + +The final type of 2D color map is loaded from an image, such as the one displayed +below which is similar to the famous color map used for the Millenium simulation. + +.. image:: millenium_cmap.png + +This can be loaded using the +:class:`swiftsimio.visualisation.tools.cmaps.ImageCmap2D` class, as follows: + +.. code-block:: python + + mill = ImageCmap2D(filename="millenium_cmap.png") + +and can be used similarly to the other color maps. For the example above, this +outputs the following: + +.. image:: test_2d_cmap_output_mill.png + +This is the recommended way to use two dimensional color maps, as their +generation can be quite complex and best left to image-generation programs +such as GIMP or Photoshop. From bed9d3b78026a740d91a6bf40275aa6526d6f842 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 12:26:49 +0000 Subject: [PATCH 5/8] Array ordering fix --- swiftsimio/visualisation/tools/cmaps.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/swiftsimio/visualisation/tools/cmaps.py b/swiftsimio/visualisation/tools/cmaps.py index 380c0c6d..c42e1b4c 100644 --- a/swiftsimio/visualisation/tools/cmaps.py +++ b/swiftsimio/visualisation/tools/cmaps.py @@ -81,8 +81,8 @@ def apply_color_map(first_values, second_values, map_grid): (number_of_values, 4) ) - norm_x = np.float32(len(map_grid[0]) - 1) - norm_y = np.float32(len(map_grid) - 1) + norm_x = np.float32(len(map_grid) - 1) + norm_y = np.float32(len(map_grid[0]) - 1) for index in range(number_of_values): horizontal = norm_x * min(max(first_values[index], 0.0), 1.0) From 5872ca7815bac576ec3a19174de4a9593665c9cd Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 12:27:28 +0000 Subject: [PATCH 6/8] Added tools --- index.rst | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 index.rst diff --git a/index.rst b/index.rst new file mode 100644 index 00000000..f122319f --- /dev/null +++ b/index.rst @@ -0,0 +1,36 @@ +Visualisation +============= + +:mod:`swiftsimio` provides visualisation routines accelerated with the +:mod:`numba` module. They work without this module, but we strongly recommend +installing it for the best performance (1000x+ speedups). These are provided +in the :mod:`swiftismio.visualisation` sub-modules. + +The three built-in rendering types (described below) have the following +common interface: + +.. code-block:: python + + {render_func_name}_gas( + data=data, # SWIFTsimIO dataset + resolution=1024, # Resolution along one axis of the output image + project="masses", # Variable to project, e.g. masses, temperatures, etc. + parallel=False, # Construct the image in (thread) parallel? + region=None, # None, or a list telling which region to render_func_name + ) + +The output of these functions comes with associated units and has the correct +dimensions. There are lower-level APIs (also documented here) that provide +additional functionality. + +Finally, we also describe here the integration with :mod:`py-sphviewer`. + +.. toctree:: + :maxdepth: 2 + + projection + slice + volume_render + tools + py-sphviewer + From 0023786ab2b715244784c6ece1b83914cd4c26bb Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 12:28:54 +0000 Subject: [PATCH 7/8] Removed accidentally copied file --- index.rst | 36 ------------------------------------ 1 file changed, 36 deletions(-) delete mode 100644 index.rst diff --git a/index.rst b/index.rst deleted file mode 100644 index f122319f..00000000 --- a/index.rst +++ /dev/null @@ -1,36 +0,0 @@ -Visualisation -============= - -:mod:`swiftsimio` provides visualisation routines accelerated with the -:mod:`numba` module. They work without this module, but we strongly recommend -installing it for the best performance (1000x+ speedups). These are provided -in the :mod:`swiftismio.visualisation` sub-modules. - -The three built-in rendering types (described below) have the following -common interface: - -.. code-block:: python - - {render_func_name}_gas( - data=data, # SWIFTsimIO dataset - resolution=1024, # Resolution along one axis of the output image - project="masses", # Variable to project, e.g. masses, temperatures, etc. - parallel=False, # Construct the image in (thread) parallel? - region=None, # None, or a list telling which region to render_func_name - ) - -The output of these functions comes with associated units and has the correct -dimensions. There are lower-level APIs (also documented here) that provide -additional functionality. - -Finally, we also describe here the integration with :mod:`py-sphviewer`. - -.. toctree:: - :maxdepth: 2 - - projection - slice - volume_render - tools - py-sphviewer - From 08710e851a304d53694d58c6ed23a0efe0aaa9b5 Mon Sep 17 00:00:00 2001 From: Josh Borrow Date: Sat, 2 Jan 2021 12:30:31 +0000 Subject: [PATCH 8/8] Revved version --- CHANGELOG.txt | 5 +++++ swiftsimio/__version__.py | 2 +- 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.txt b/CHANGELOG.txt index cd37daa4..5ccc7411 100644 --- a/CHANGELOG.txt +++ b/CHANGELOG.txt @@ -1,6 +1,11 @@ SWIFTsimIO Changelog ==================== +v 4.5.0 +------- + ++ Added new 2D color map functionality! + v 4.4.0 ------- diff --git a/swiftsimio/__version__.py b/swiftsimio/__version__.py index ecdb1cef..9faa2c2d 100644 --- a/swiftsimio/__version__.py +++ b/swiftsimio/__version__.py @@ -1 +1 @@ -__version__ = "4.4.0" +__version__ = "4.5.0"