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Theme Modules

Custom Bruker Nanoscope colorscale.

Colormap

Class for setting the Colormap.

Parameters

name : str Name of colormap to use.

Source code in topostats/theme.py 
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class Colormap:
    """
    Class for setting the Colormap.

    Parameters
    ----------
    name : str
        Name of colormap to use.
    """

    def __init__(self, name: str = "nanoscope"):
        """
        Initialise the class.

        Parameters
        ----------
        name : str
            Name of colormap to use.
        """
        self.name = name
        self.cmap = None
        self.set_cmap(self.name)

    def __str__(self) -> str:
        """
        Return string representation of object.

        Returns
        -------
        str
            String detailing the colormap.
        """
        return f"TopoStats Colormap: {self.name}"

    def set_cmap(self, name: str) -> None:
        """
        Set the ColorMap.

        Parameters
        ----------
        name : str
            Name of the colormap to return.
        """
        if name.lower() == "nanoscope":
            self.cmap = self.nanoscope()
        elif name.lower() == "gwyddion":
            self.cmap = self.gwyddion()
        elif name.lower() == "blue":
            self.cmap = self.blue()
        elif name.lower() == "blue_purple_green":
            self.cmap = self.blue_purple_green()
        else:
            # Get one of the matplotlib colormaps
            self.cmap = mpl.colormaps[name]
        LOGGER.debug(f"[theme] Colormap set to : {name}")

    def get_cmap(self) -> matplotlib.cm:
        """
        Return the matplotlib.cm colormap object.

        Returns
        -------
        matplotlib.cm
            Matplotlib Color map object.
        """
        return self.cmap

    @staticmethod
    def nanoscope() -> LinearSegmentedColormap:
        """
        Matplotlib compatible colormap that replicates the Bruker Nanoscope colorscale.

        The colormap is implemented in Gwyddion's GwyGradient via 'Nanoscope.txt'.

        Returns
        -------
        LinearSegmentedColormap
            MatplotLib LinearSegmentedColourmap that replicates Bruker Nanoscope colorscale.
        """
        cdict = {
            "red": (
                (0.0, 0.0, 0.0),
                (0.124464, 0.0, 0.0),
                (0.236052, 0.0670103, 0.0670103),
                (0.371245, 0.253338, 0.253338),
                (0.472103, 0.392344, 0.392344),
                (0.611588, 0.584587, 0.584587),
                (0.708155, 0.717678, 0.717678),
                (0.714052, 0.725806, 0.725806),
                (0.890558, 0.969072, 0.969072),
                (0.933476, 0.987464, 0.987464),
                (0.944709, 0.992278, 0.992278),
                (0.965682, 0.995207, 0.995207),
                (0.971401, 0.996006, 0.996006),
                (1, 1, 1),
            ),
            "green": (
                (0.0, 0.0, 0.0),
                (0.124464, 0.0, 0.0),
                (0.236052, 0.0, 0.0),
                (0.371245, 0.0, 0.0),
                (0.472103, 0.0721649, 0.0721649),
                (0.611588, 0.334114, 0.334114),
                (0.708155, 0.515464, 0.515464),
                (0.714052, 0.527471, 0.527471),
                (0.890558, 0.886843, 0.886843),
                (0.933476, 0.974227, 0.974227),
                (0.944709, 0.980523, 0.980523),
                (0.965682, 0.992278, 0.992278),
                (0.971401, 0.993565, 0.993565),
                (1, 1, 1),
            ),
            "blue": (
                (0.0, 0.0, 0.0),
                (0.124464, 0.0, 0.0),
                (0.236052, 0.0, 0.0),
                (0.371245, 0.0, 0.0),
                (0.472103, 0.0, 0.0),
                (0.611588, 0.0, 0.0),
                (0.708155, 0.252575, 0.252575),
                (0.714052, 0.268, 0.268),
                (0.890558, 0.76343, 0.76343),
                (0.933476, 0.883897, 0.883897),
                (0.944709, 0.915426, 0.915426),
                (0.965682, 0.974293, 0.974293),
                (0.971401, 0.990347, 0.990347),
                (1, 1, 1),
            ),
        }

        return LinearSegmentedColormap("nanoscope", cdict)

    @staticmethod
    def gwyddion() -> LinearSegmentedColormap:
        """
        Set RGBA colour map for the Gwyddion.net colour gradient.

        Returns
        -------
        LinearSegmentedColormap
            The 'gwyddion' colormap.
        """
        N = 4  # Number of values
        vals = np.ones((N, 4))  # Initialise the array to be full of 1.0
        vals[0] = [0.0, 0.0, 0.0, 1]
        vals[1] = [168 / 256, 40 / 256, 15 / 256, 1.0]
        vals[2] = [243 / 256, 194 / 256, 93 / 256, 1.0]
        vals[3] = [1.0, 1.0, 1.0, 1.0]

        return LinearSegmentedColormap.from_list("gwyddion", vals, N=256)

    @staticmethod
    def blue() -> ListedColormap:
        """
        Set RGBA colour map of just the colour blue.

        Returns
        -------
        ListedColormap
            The 'blue' colormap.
        """
        return ListedColormap([[32 / 256, 226 / 256, 205 / 256]], "blue", N=256)

    @staticmethod
    def blue_purple_green() -> ListedColormap:
        """
        RGBA colour map of just the colour blue/purple/green.

        Returns
        -------
        ListedColormap
            The 'blue/purple/green' colormap.
        """
        return ListedColormap(
            [[0 / 256, 157 / 256, 229 / 256], [255 / 256, 100 / 256, 225 / 256], [0 / 256, 1, 139 / 256]],
            "blue_purple_green",
            N=3,
        )

__init__(name='nanoscope')

Initialise the class.

Parameters

name : str Name of colormap to use.

Source code in topostats/theme.py 
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def __init__(self, name: str = "nanoscope"):
    """
    Initialise the class.

    Parameters
    ----------
    name : str
        Name of colormap to use.
    """
    self.name = name
    self.cmap = None
    self.set_cmap(self.name)

__str__()

Return string representation of object.

Returns

str String detailing the colormap.

Source code in topostats/theme.py 
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def __str__(self) -> str:
    """
    Return string representation of object.

    Returns
    -------
    str
        String detailing the colormap.
    """
    return f"TopoStats Colormap: {self.name}"

blue() staticmethod

Set RGBA colour map of just the colour blue.

Returns

ListedColormap The 'blue' colormap.

Source code in topostats/theme.py 
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@staticmethod
def blue() -> ListedColormap:
    """
    Set RGBA colour map of just the colour blue.

    Returns
    -------
    ListedColormap
        The 'blue' colormap.
    """
    return ListedColormap([[32 / 256, 226 / 256, 205 / 256]], "blue", N=256)

blue_purple_green() staticmethod

RGBA colour map of just the colour blue/purple/green.

Returns

ListedColormap The 'blue/purple/green' colormap.

Source code in topostats/theme.py 
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@staticmethod
def blue_purple_green() -> ListedColormap:
    """
    RGBA colour map of just the colour blue/purple/green.

    Returns
    -------
    ListedColormap
        The 'blue/purple/green' colormap.
    """
    return ListedColormap(
        [[0 / 256, 157 / 256, 229 / 256], [255 / 256, 100 / 256, 225 / 256], [0 / 256, 1, 139 / 256]],
        "blue_purple_green",
        N=3,
    )

get_cmap()

Return the matplotlib.cm colormap object.

Returns

matplotlib.cm Matplotlib Color map object.

Source code in topostats/theme.py 
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def get_cmap(self) -> matplotlib.cm:
    """
    Return the matplotlib.cm colormap object.

    Returns
    -------
    matplotlib.cm
        Matplotlib Color map object.
    """
    return self.cmap

gwyddion() staticmethod

Set RGBA colour map for the Gwyddion.net colour gradient.

Returns

LinearSegmentedColormap The 'gwyddion' colormap.

Source code in topostats/theme.py 
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@staticmethod
def gwyddion() -> LinearSegmentedColormap:
    """
    Set RGBA colour map for the Gwyddion.net colour gradient.

    Returns
    -------
    LinearSegmentedColormap
        The 'gwyddion' colormap.
    """
    N = 4  # Number of values
    vals = np.ones((N, 4))  # Initialise the array to be full of 1.0
    vals[0] = [0.0, 0.0, 0.0, 1]
    vals[1] = [168 / 256, 40 / 256, 15 / 256, 1.0]
    vals[2] = [243 / 256, 194 / 256, 93 / 256, 1.0]
    vals[3] = [1.0, 1.0, 1.0, 1.0]

    return LinearSegmentedColormap.from_list("gwyddion", vals, N=256)

nanoscope() staticmethod

Matplotlib compatible colormap that replicates the Bruker Nanoscope colorscale.

The colormap is implemented in Gwyddion's GwyGradient via 'Nanoscope.txt'.

Returns

LinearSegmentedColormap MatplotLib LinearSegmentedColourmap that replicates Bruker Nanoscope colorscale.

Source code in topostats/theme.py 
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@staticmethod
def nanoscope() -> LinearSegmentedColormap:
    """
    Matplotlib compatible colormap that replicates the Bruker Nanoscope colorscale.

    The colormap is implemented in Gwyddion's GwyGradient via 'Nanoscope.txt'.

    Returns
    -------
    LinearSegmentedColormap
        MatplotLib LinearSegmentedColourmap that replicates Bruker Nanoscope colorscale.
    """
    cdict = {
        "red": (
            (0.0, 0.0, 0.0),
            (0.124464, 0.0, 0.0),
            (0.236052, 0.0670103, 0.0670103),
            (0.371245, 0.253338, 0.253338),
            (0.472103, 0.392344, 0.392344),
            (0.611588, 0.584587, 0.584587),
            (0.708155, 0.717678, 0.717678),
            (0.714052, 0.725806, 0.725806),
            (0.890558, 0.969072, 0.969072),
            (0.933476, 0.987464, 0.987464),
            (0.944709, 0.992278, 0.992278),
            (0.965682, 0.995207, 0.995207),
            (0.971401, 0.996006, 0.996006),
            (1, 1, 1),
        ),
        "green": (
            (0.0, 0.0, 0.0),
            (0.124464, 0.0, 0.0),
            (0.236052, 0.0, 0.0),
            (0.371245, 0.0, 0.0),
            (0.472103, 0.0721649, 0.0721649),
            (0.611588, 0.334114, 0.334114),
            (0.708155, 0.515464, 0.515464),
            (0.714052, 0.527471, 0.527471),
            (0.890558, 0.886843, 0.886843),
            (0.933476, 0.974227, 0.974227),
            (0.944709, 0.980523, 0.980523),
            (0.965682, 0.992278, 0.992278),
            (0.971401, 0.993565, 0.993565),
            (1, 1, 1),
        ),
        "blue": (
            (0.0, 0.0, 0.0),
            (0.124464, 0.0, 0.0),
            (0.236052, 0.0, 0.0),
            (0.371245, 0.0, 0.0),
            (0.472103, 0.0, 0.0),
            (0.611588, 0.0, 0.0),
            (0.708155, 0.252575, 0.252575),
            (0.714052, 0.268, 0.268),
            (0.890558, 0.76343, 0.76343),
            (0.933476, 0.883897, 0.883897),
            (0.944709, 0.915426, 0.915426),
            (0.965682, 0.974293, 0.974293),
            (0.971401, 0.990347, 0.990347),
            (1, 1, 1),
        ),
    }

    return LinearSegmentedColormap("nanoscope", cdict)

set_cmap(name)

Set the ColorMap.

Parameters

name : str Name of the colormap to return.

Source code in topostats/theme.py 
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def set_cmap(self, name: str) -> None:
    """
    Set the ColorMap.

    Parameters
    ----------
    name : str
        Name of the colormap to return.
    """
    if name.lower() == "nanoscope":
        self.cmap = self.nanoscope()
    elif name.lower() == "gwyddion":
        self.cmap = self.gwyddion()
    elif name.lower() == "blue":
        self.cmap = self.blue()
    elif name.lower() == "blue_purple_green":
        self.cmap = self.blue_purple_green()
    else:
        # Get one of the matplotlib colormaps
        self.cmap = mpl.colormaps[name]
    LOGGER.debug(f"[theme] Colormap set to : {name}")

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