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2025-11-30 08:30:10 +08:00
commit f0bd18fb4e
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--- a/skills/scientific-visualization/assets/color_palettes.py
+++ b/skills/scientific-visualization/assets/color_palettes.py
@@ -0,0 +1,197 @@
+"""
+Colorblind-Friendly Color Palettes for Scientific Visualization
+
+This module provides carefully curated color palettes optimized for
+scientific publications and accessibility.
+
+Usage:
+    from color_palettes import OKABE_ITO, apply_palette
+    import matplotlib.pyplot as plt
+
+    apply_palette('okabe_ito')
+    plt.plot([1, 2, 3], [1, 4, 9])
+"""
+
+# Okabe-Ito Palette (2008)
+# The most widely recommended colorblind-friendly palette
+OKABE_ITO = {
+    'orange': '#E69F00',
+    'sky_blue': '#56B4E9',
+    'bluish_green': '#009E73',
+    'yellow': '#F0E442',
+    'blue': '#0072B2',
+    'vermillion': '#D55E00',
+    'reddish_purple': '#CC79A7',
+    'black': '#000000'
+}
+
+OKABE_ITO_LIST = ['#E69F00', '#56B4E9', '#009E73', '#F0E442',
+                   '#0072B2', '#D55E00', '#CC79A7', '#000000']
+
+# Wong Palette (Nature Methods)
+WONG = ['#000000', '#E69F00', '#56B4E9', '#009E73',
+        '#F0E442', '#0072B2', '#D55E00', '#CC79A7']
+
+# Paul Tol Palettes (https://personal.sron.nl/~pault/)
+TOL_BRIGHT = ['#4477AA', '#EE6677', '#228833', '#CCBB44',
+              '#66CCEE', '#AA3377', '#BBBBBB']
+
+TOL_MUTED = ['#332288', '#88CCEE', '#44AA99', '#117733',
+             '#999933', '#DDCC77', '#CC6677', '#882255', '#AA4499']
+
+TOL_LIGHT = ['#77AADD', '#EE8866', '#EEDD88', '#FFAABB',
+             '#99DDFF', '#44BB99', '#BBCC33', '#AAAA00', '#DDDDDD']
+
+TOL_HIGH_CONTRAST = ['#004488', '#DDAA33', '#BB5566']
+
+# Sequential colormaps (for continuous data)
+SEQUENTIAL_COLORMAPS = [
+    'viridis',   # Default, perceptually uniform
+    'plasma',    # Perceptually uniform
+    'inferno',   # Perceptually uniform
+    'magma',     # Perceptually uniform
+    'cividis',   # Optimized for colorblind viewers
+    'YlOrRd',    # Yellow-Orange-Red
+    'YlGnBu',    # Yellow-Green-Blue
+    'Blues',     # Single hue
+    'Greens',    # Single hue
+    'Purples',   # Single hue
+]
+
+# Diverging colormaps (for data with meaningful center)
+DIVERGING_COLORMAPS_SAFE = [
+    'RdYlBu',    # Red-Yellow-Blue (reversed is common)
+    'RdBu',      # Red-Blue
+    'PuOr',      # Purple-Orange (excellent for colorblind)
+    'BrBG',      # Brown-Blue-Green (good for colorblind)
+    'PRGn',      # Purple-Green (use with caution)
+    'PiYG',      # Pink-Yellow-Green (use with caution)
+]
+
+# Diverging colormaps to AVOID (red-green combinations)
+DIVERGING_COLORMAPS_AVOID = [
+    'RdGn',      # Red-Green (problematic!)
+    'RdYlGn',    # Red-Yellow-Green (problematic!)
+]
+
+# Fluorophore colors (traditional - use with caution)
+FLUOROPHORES_TRADITIONAL = {
+    'DAPI': '#0000FF',    # Blue
+    'GFP': '#00FF00',     # Green (problematic for colorblind)
+    'RFP': '#FF0000',     # Red
+    'Cy5': '#FF00FF',     # Magenta
+    'YFP': '#FFFF00',     # Yellow
+}
+
+# Fluorophore colors (colorblind-friendly alternatives)
+FLUOROPHORES_ACCESSIBLE = {
+    'Channel1': '#0072B2',  # Blue
+    'Channel2': '#E69F00',  # Orange (instead of green)
+    'Channel3': '#D55E00',  # Vermillion (instead of red)
+    'Channel4': '#CC79A7',  # Magenta
+    'Channel5': '#F0E442',  # Yellow
+}
+
+# Genomics/Bioinformatics
+DNA_BASES = {
+    'A': '#00CC00',  # Green
+    'C': '#0000CC',  # Blue
+    'G': '#FFB300',  # Orange
+    'T': '#CC0000',  # Red
+}
+
+DNA_BASES_ACCESSIBLE = {
+    'A': '#009E73',  # Bluish Green
+    'C': '#0072B2',  # Blue
+    'G': '#E69F00',  # Orange
+    'T': '#D55E00',  # Vermillion
+}
+
+
+def apply_palette(palette_name='okabe_ito'):
+    """
+    Apply a color palette to matplotlib's default color cycle.
+
+    Parameters
+    ----------
+    palette_name : str
+        Name of the palette to apply. Options:
+        'okabe_ito', 'wong', 'tol_bright', 'tol_muted',
+        'tol_light', 'tol_high_contrast'
+
+    Returns
+    -------
+    list
+        List of colors in the palette
+
+    Examples
+    --------
+    >>> apply_palette('okabe_ito')
+    >>> plt.plot([1, 2, 3], [1, 4, 9])  # Uses Okabe-Ito colors
+    """
+    try:
+        import matplotlib.pyplot as plt
+    except ImportError:
+        print("matplotlib not installed")
+        return None
+
+    palettes = {
+        'okabe_ito': OKABE_ITO_LIST,
+        'wong': WONG,
+        'tol_bright': TOL_BRIGHT,
+        'tol_muted': TOL_MUTED,
+        'tol_light': TOL_LIGHT,
+        'tol_high_contrast': TOL_HIGH_CONTRAST,
+    }
+
+    if palette_name not in palettes:
+        available = ', '.join(palettes.keys())
+        raise ValueError(f"Palette '{palette_name}' not found. Available: {available}")
+
+    colors = palettes[palette_name]
+    plt.rcParams['axes.prop_cycle'] = plt.cycler(color=colors)
+    return colors
+
+
+def get_palette(palette_name='okabe_ito'):
+    """
+    Get a color palette as a list.
+
+    Parameters
+    ----------
+    palette_name : str
+        Name of the palette
+
+    Returns
+    -------
+    list
+        List of color hex codes
+    """
+    palettes = {
+        'okabe_ito': OKABE_ITO_LIST,
+        'wong': WONG,
+        'tol_bright': TOL_BRIGHT,
+        'tol_muted': TOL_MUTED,
+        'tol_light': TOL_LIGHT,
+        'tol_high_contrast': TOL_HIGH_CONTRAST,
+    }
+
+    if palette_name not in palettes:
+        available = ', '.join(palettes.keys())
+        raise ValueError(f"Palette '{palette_name}' not found. Available: {available}")
+
+    return palettes[palette_name]
+
+
+if __name__ == "__main__":
+    print("Available colorblind-friendly palettes:")
+    print(f"  - Okabe-Ito: {len(OKABE_ITO_LIST)} colors")
+    print(f"  - Wong: {len(WONG)} colors")
+    print(f"  - Tol Bright: {len(TOL_BRIGHT)} colors")
+    print(f"  - Tol Muted: {len(TOL_MUTED)} colors")
+    print(f"  - Tol Light: {len(TOL_LIGHT)} colors")
+    print(f"  - Tol High Contrast: {len(TOL_HIGH_CONTRAST)} colors")
+
+    print("\nOkabe-Ito palette (most recommended):")
+    for name, color in OKABE_ITO.items():
+        print(f"  {name:15s}: {color}")
--- a/skills/scientific-visualization/assets/nature.mplstyle
+++ b/skills/scientific-visualization/assets/nature.mplstyle
@@ -0,0 +1,63 @@
+# Nature journal style
+# Usage: plt.style.use('nature.mplstyle')
+#
+# Optimized for Nature journal specifications:
+# - Single column: 89 mm
+# - Double column: 183 mm
+# - High resolution requirements
+
+# Figure properties
+figure.dpi: 100
+figure.facecolor: white
+figure.constrained_layout.use: True
+figure.figsize: 3.5, 2.625  # 89 mm single column, 3:4 aspect
+
+# Font properties (Nature prefers smaller fonts)
+font.size: 7
+font.family: sans-serif
+font.sans-serif: Arial, Helvetica
+
+# Axes properties
+axes.linewidth: 0.5
+axes.labelsize: 8
+axes.titlesize: 8
+axes.labelweight: normal
+axes.spines.top: False
+axes.spines.right: False
+axes.edgecolor: black
+axes.axisbelow: True
+axes.grid: False
+axes.prop_cycle: cycler('color', ['E69F00', '56B4E9', '009E73', 'F0E442', '0072B2', 'D55E00', 'CC79A7'])
+
+# Tick properties
+xtick.major.size: 2.5
+xtick.minor.size: 1.5
+xtick.major.width: 0.5
+xtick.minor.width: 0.4
+xtick.labelsize: 6
+xtick.direction: out
+ytick.major.size: 2.5
+ytick.minor.size: 1.5
+ytick.major.width: 0.5
+ytick.minor.width: 0.4
+ytick.labelsize: 6
+ytick.direction: out
+
+# Line properties
+lines.linewidth: 1.2
+lines.markersize: 3
+lines.markeredgewidth: 0.4
+
+# Legend properties
+legend.fontsize: 6
+legend.frameon: False
+
+# Save properties (Nature requirements)
+savefig.dpi: 600  # 1000 for line art, 600 for combination
+savefig.format: pdf
+savefig.bbox: tight
+savefig.pad_inches: 0.05
+savefig.facecolor: white
+
+# Image properties
+image.cmap: viridis
--- a/skills/scientific-visualization/assets/presentation.mplstyle
+++ b/skills/scientific-visualization/assets/presentation.mplstyle
@@ -0,0 +1,61 @@
+# Presentation/Poster style
+# Usage: plt.style.use('presentation.mplstyle')
+#
+# Larger fonts and thicker lines for presentations,
+# posters, and projected displays
+
+# Figure properties
+figure.dpi: 100
+figure.facecolor: white
+figure.constrained_layout.use: True
+figure.figsize: 8, 6
+
+# Font properties (larger for visibility)
+font.size: 14
+font.family: sans-serif
+font.sans-serif: Arial, Helvetica, Calibri
+
+# Axes properties
+axes.linewidth: 1.5
+axes.labelsize: 16
+axes.titlesize: 18
+axes.labelweight: normal
+axes.spines.top: False
+axes.spines.right: False
+axes.edgecolor: black
+axes.axisbelow: True
+axes.grid: False
+axes.prop_cycle: cycler('color', ['E69F00', '56B4E9', '009E73', 'F0E442', '0072B2', 'D55E00', 'CC79A7'])
+
+# Tick properties
+xtick.major.size: 6
+xtick.minor.size: 4
+xtick.major.width: 1.5
+xtick.minor.width: 1.0
+xtick.labelsize: 12
+xtick.direction: out
+ytick.major.size: 6
+ytick.minor.size: 4
+ytick.major.width: 1.5
+ytick.minor.width: 1.0
+ytick.labelsize: 12
+ytick.direction: out
+
+# Line properties
+lines.linewidth: 2.5
+lines.markersize: 8
+lines.markeredgewidth: 1.0
+
+# Legend properties
+legend.fontsize: 12
+legend.frameon: False
+
+# Save properties
+savefig.dpi: 300
+savefig.format: png
+savefig.bbox: tight
+savefig.pad_inches: 0.1
+savefig.facecolor: white
+
+# Image properties
+image.cmap: viridis
--- a/skills/scientific-visualization/assets/publication.mplstyle
+++ b/skills/scientific-visualization/assets/publication.mplstyle
@@ -0,0 +1,68 @@
+# Publication-quality matplotlib style
+# Usage: plt.style.use('publication.mplstyle')
+#
+# This style provides clean, professional formatting suitable
+# for most scientific journals
+
+# Figure properties
+figure.dpi: 100
+figure.facecolor: white
+figure.autolayout: False
+figure.constrained_layout.use: True
+figure.figsize: 3.5, 2.5
+
+# Font properties
+font.size: 8
+font.family: sans-serif
+font.sans-serif: Arial, Helvetica, DejaVu Sans
+
+# Axes properties
+axes.linewidth: 0.5
+axes.labelsize: 9
+axes.titlesize: 9
+axes.labelweight: normal
+axes.spines.top: False
+axes.spines.right: False
+axes.spines.left: True
+axes.spines.bottom: True
+axes.edgecolor: black
+axes.labelcolor: black
+axes.axisbelow: True
+axes.grid: False
+axes.prop_cycle: cycler('color', ['E69F00', '56B4E9', '009E73', 'F0E442', '0072B2', 'D55E00', 'CC79A7', '000000'])
+
+# Tick properties
+xtick.major.size: 3
+xtick.minor.size: 2
+xtick.major.width: 0.5
+xtick.minor.width: 0.5
+xtick.labelsize: 7
+xtick.direction: out
+ytick.major.size: 3
+ytick.minor.size: 2
+ytick.major.width: 0.5
+ytick.minor.width: 0.5
+ytick.labelsize: 7
+ytick.direction: out
+
+# Line properties
+lines.linewidth: 1.5
+lines.markersize: 4
+lines.markeredgewidth: 0.5
+
+# Legend properties
+legend.fontsize: 7
+legend.frameon: False
+legend.loc: best
+
+# Save properties
+savefig.dpi: 300
+savefig.format: pdf
+savefig.bbox: tight
+savefig.pad_inches: 0.05
+savefig.transparent: False
+savefig.facecolor: white
+
+# Image properties
+image.cmap: viridis
+image.aspect: auto