Module `quantum_inferno.plot_templates.plot_base`

Base classes, constants, and functions used to create plots

Functions

def mesh_colormap_limits(mesh_array: numpy.ndarray, colormap_scaling: str = 'auto', color_range: float = 16.0) ‑> Tuple[float, float]: Find colormap limits for plotting

:param mesh_array: array with mesh :param colormap_scaling: one of: "auto" (max/min of input mesh), "range" (max of input mesh - color range given) or "abs" (absolute max/min of input mesh). Default "auto" :param color_range: range of colors. Default is 16.0 :return: colormap min and max values

Classes

class CwPanel (sig: numpy.ndarray, time: numpy.ndarray, y_units: str = 'Norm', x_units: str = 's', title: str = 'CW')

Panel for Continuous Waveform plots

Attributes

sig: np.ndarray, the signal to plot. Required
time: np.ndarray, the timestamps of the data. Required
y_units: str, units of the signal. Default "Norm"
x_units: str, label for the time axis. Default "s"
title: str, title for the panel. Default "CW"

Expand source code

@dataclass
class CwPanel:
    """
    Panel for Continuous Waveform plots

    Attributes:
        sig: np.ndarray, the signal to plot.  Required
        time: np.ndarray, the timestamps of the data.  Required
        y_units: str, units of the signal.  Default "Norm"
        x_units: str, label for the time axis.  Default "s"
        title: str, title for the panel.  Default "CW"
    """
    sig: np.ndarray
    time: np.ndarray
    y_units: str = "Norm"
    x_units: str = "s"
    title: str = "CW"

    def is_no_data(self) -> bool:
        """
        :return: True if no data, False otherwise
        """
        return self.time[0] == self.time[-1]

Class variables

var sig : numpy.ndarray
var time : numpy.ndarray
var title : str
var x_units : str
var y_units : str

Methods

def is_no_data(self) ‑> bool: :return: True if no data, False otherwise

class CwPowerPlotBase (params_tfr: AudioParams = <quantum_inferno.plot_templates.figure_attributes.AudioParams object>, figure_title_show: bool = True)

Base class for plotting CW and Power plots.

Attributes

params_tfr: AudioParams, parameters for plotting data. Default AudioParams()
figure_title_show: bool, if True, show the figure title. Default True

Expand source code

@dataclass
class CwPowerPlotBase:
    """
    Base class for plotting CW and Power plots.

    Attributes:
        params_tfr: AudioParams, parameters for plotting data.  Default AudioParams()
        figure_title_show: bool, if True, show the figure title.  Default True
    """
    params_tfr: AudioParams = AudioParams()
    figure_title_show: bool = True

Class variables

var figure_title_show : bool
var params_tfr : AudioParams

class MeshBase (time: numpy.ndarray, frequency: numpy.ndarray, frequency_scaling: str = 'log', shading: str = 'auto', frequency_hz_ymin: Optional[float] = None, frequency_hz_ymax: Optional[float] = None, colormap: Optional[str] = None, units_frequency: str = 'Hz')

Base class for Mesh plots. Independent of PlotBase.

Attributes

time: np.ndarray of the timestamps. Required
frequency: np.ndarray of the frequency data. Required
frequency_scaling: str, scaling for the frequency. refer to AXIS_SCALE_VALS for options. Default "log"
shading: str, shading of the plot. options: "auto", "gouraud", "flat", "nearest". Default "auto"
frequency_hz_ymin: optional float, minimum frequency. Default None
frequency_hz_ymax: optional float, maximum frequency. Default None
colormap: Optional str, colormap. Default None
units_frequency: str, units of the frequency. Default "Hz"

Expand source code

@dataclass
class MeshBase:
    """
    Base class for Mesh plots.  Independent of PlotBase.

    Attributes:
        time: np.ndarray of the timestamps.  Required
        frequency: np.ndarray of the frequency data.  Required
        frequency_scaling: str, scaling for the frequency.  refer to AXIS_SCALE_VALS for options.  Default "log"
        shading: str, shading of the plot.  options: "auto", "gouraud", "flat", "nearest".  Default "auto"
        frequency_hz_ymin: optional float, minimum frequency.  Default None
        frequency_hz_ymax: optional float, maximum frequency.  Default None
        colormap: Optional str, colormap.  Default None
        units_frequency: str, units of the frequency.  Default "Hz"
    """
    time: np.ndarray
    frequency: np.ndarray
    frequency_scaling: str = "log"
    shading: str = "auto"
    frequency_hz_ymin: Optional[float] = None
    frequency_hz_ymax: Optional[float] = None
    colormap: Optional[str] = None
    units_frequency: str = "Hz"

    def __post_init__(self):
        # Autoscale to mesh frequency range
        if self.frequency_hz_ymax is None:
            self.frequency_hz_ymax = self.frequency[-1]
        if self.frequency_hz_ymin is None:
            self.frequency_hz_ymin = self.frequency[0]
        if self.frequency_scaling not in AXIS_SCALE_VALS:
            self.frequency_scaling = "log"
        if self.shading not in MESH_SHADING_VALS:
            self.shading = "auto"

    def get_shading_as_literal(self) -> Literal["auto", "gouraud", "flat", "nearest"]:
        """
        :return: Literal value of the shading
        """
        return cast(Literal, self.shading)

    def get_colormesh_params(self) -> Tuple[Optional[np.ndarray], Optional[np.ndarray], Optional[str]]:
        """
        :return: time, frequency, and shading for colormesh.  All three could be None
        """
        if self.shading in ["auto", "gouraud"]:
            return self.time, self.frequency, self.get_shading_as_literal()
        return None, None, None

Class variables

var colormap : Optional[str]
var frequency : numpy.ndarray
var frequency_hz_ymax : Optional[float]
var frequency_hz_ymin : Optional[float]
var frequency_scaling : str
var shading : str
var time : numpy.ndarray
var units_frequency : str

Methods

def get_colormesh_params(self) ‑> Tuple[Optional[numpy.ndarray], Optional[numpy.ndarray], Optional[str]]: :return: time, frequency, and shading for colormesh. All three could be None
def get_shading_as_literal(self) ‑> Literal['auto', 'gouraud', 'flat', 'nearest']: :return: Literal value of the shading

class MeshPanel (tfr: numpy.ndarray, colormap_scaling: str = 'auto', color_max: float = 15.0, color_range: float = 15.0, color_min: float = 0.0, cbar_units: str = 'bits', ytick_style: str = 'sci')

Panel for Mesh plots

Attributes

tfr: np.ndarray of the data to plot. Required
colormap_scaling: str, scaling for the colormap. options: "auto", "range", "else". Default "auto"
color_max: float, maximum color value. Default 15
color_range: float, range of color values. Default 15
color_min: float, minimum color value. Default 0
cbar_units: str, units to display for colorbar. Default "bits"
ytick_style: str, style for yticks. options: "sci", "scientific", "plain". Default "sci"

Expand source code

@dataclass
class MeshPanel:
    """
    Panel for Mesh plots

    Attributes:
        tfr: np.ndarray of the data to plot.  Required
        colormap_scaling: str, scaling for the colormap.  options: "auto", "range", "else".  Default "auto"
        color_max: float, maximum color value.  Default 15
        color_range: float, range of color values.  Default 15
        color_min: float, minimum color value.  Default 0
        cbar_units: str, units to display for colorbar.  Default "bits"
        ytick_style: str, style for yticks.  options: "sci", "scientific", "plain".  Default "sci"
    """
    tfr: np.ndarray
    colormap_scaling: str = "auto"
    color_max: float = 15.
    color_range: float = 15.
    color_min: float = 0.
    cbar_units: str = "bits"
    ytick_style: str = "sci"

    def __post_init__(self):
        if self.colormap_scaling not in COLORMAP_SCALING_VALS:
            self.colormap_scaling = "else"
        else:
            self.set_color_min_max()
        if self.ytick_style not in YTICK_STYLE_VALS:
            self.ytick_style = "sci"

    def set_color_min_max(self):
        """
        Set color min-max if the colormap_scaling is "auto" or "range"
        """
        if self.is_auto_color_min_max():
            self.color_min, self.color_max = mesh_colormap_limits(self.tfr, self.colormap_scaling, self.color_range)

    def is_auto_color_min_max(self) -> bool:
        """
        :return: True if colormap_scaling is "auto" or "range", which auto-sets the color range
        """
        return self.colormap_scaling in ["auto", "range"]

Class variables

var cbar_units : str
var color_max : float
var color_min : float
var color_range : float
var colormap_scaling : str
var tfr : numpy.ndarray
var ytick_style : str

Methods

def is_auto_color_min_max(self) ‑> bool: :return: True if colormap_scaling is "auto" or "range", which auto-sets the color range
def set_color_min_max(self): Set color min-max if the colormap_scaling is "auto" or "range"

class PlotBase (station_id: str, figure_title: str, figure_title_show: bool = True, start_time_epoch: float = 0.0, params_tfr: AudioParams = <quantum_inferno.plot_templates.figure_attributes.AudioParams object>, units_time: str = 's')

Plotting base class with parameters used by all plots

Attributes

station_id: str, id of the station being plotted. Required
figure_title: str, the title of the plot. Required
figure_title_show: bool, if True, show the figure title. Default True
start_time_epoch: float, the epoch start time of the data. Default 0.
params_tfr: AudioParams, parameters for plotting audio data. Default AudioParams()
units_time: str, label of units for time component. Default "s"

Expand source code

@dataclass
class PlotBase:
    """
    Plotting base class with parameters used by all plots

    Attributes:
        station_id: str, id of the station being plotted.  Required
        figure_title: str, the title of the plot.  Required
        figure_title_show: bool, if True, show the figure title.  Default True
        start_time_epoch: float, the epoch start time of the data.  Default 0.
        params_tfr: AudioParams, parameters for plotting audio data.  Default AudioParams()
        units_time: str, label of units for time component.  Default "s"
    """
    station_id: str
    figure_title: str
    figure_title_show: bool = True
    start_time_epoch: float = 0.
    params_tfr: AudioParams = AudioParams()
    units_time: str = "s"

Subclasses

WaveformPlotBase

Class variables

var figure_title : str
var figure_title_show : bool
var params_tfr : AudioParams
var start_time_epoch : float
var station_id : str
var units_time : str

class PowerPanel (panel_data: List[PowerPanelData], y_units: str = 'Power/Var(signal)', x_units: str = 'Frequency, Hz', title: str = 'Power')

Panel for Power plots

Attributes

panel_data: List of PowerPanelData objects to plot. Required
y_units: str, unit label for y-axis. Default "Power/Var(signal)"
x_units: str, unit label for x-axis. Default "Frequency, Hz"
title: str, title of the panel. Default "Power"

Expand source code

@dataclass
class PowerPanel:
    """
    Panel for Power plots

    Attributes:
        panel_data: List of PowerPanelData objects to plot.  Required
        y_units: str, unit label for y-axis.  Default "Power/Var(signal)"
        x_units: str, unit label for x-axis.  Default "Frequency, Hz"
        title: str, title of the panel.  Default "Power"
    """
    panel_data: List[PowerPanelData]
    y_units: str = "Power/Var(signal)"
    x_units: str = "Frequency, Hz"
    title: str = "Power"

Class variables

var panel_data : List[PowerPanelData]
var title : str
var x_units : str
var y_units : str

class PowerPanelData (sig: numpy.ndarray, freq: numpy.ndarray, linestyle: str, linewidth: float, sig_label: str)

Data to be plotted in a PowerPanel. All values are required

Attributes

sig: np.ndarray, the signal to plot.
freq: np.ndarray, the frequencies to plot.
linestyle: str, linestyle; all possible values: [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | '-' | '–' | '-.' | ':' | 'None' | ' ' | ''].
linewidth: float, linewidth.
sig_label: str, label for the signal.

Expand source code

@dataclass
class PowerPanelData:
    """
    Data to be plotted in a PowerPanel.  All values are required

    Attributes:
        sig: np.ndarray, the signal to plot.
        freq: np.ndarray, the frequencies to plot.
        linestyle: str, linestyle; all possible values:
            [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''].
        linewidth: float, linewidth.
        sig_label: str, label for the signal.
    """
    sig: np.ndarray
    freq: np.ndarray
    linestyle: str
    linewidth: float
    sig_label: str

Class variables

var freq : numpy.ndarray
var linestyle : str
var linewidth : float
var sig : numpy.ndarray
var sig_label : str

class WaveformPanel (sig: numpy.ndarray, time: numpy.ndarray, units: str = 'Norm', label: str = '(wf)', yscaling: str = 'auto', ytick_style: str = 'plain')

Panel for Waveform plots

Attributes

sig: np.ndarray, the signal to plot. Required
time: np.ndarray, the timestamps of the data. Required
units: str, units of the signal. Default "Norm"
label: str, label for the data. Default "(wf)"
yscaling: str, scaling for y-axis. options: "auto", "symmetric", "positive", "else". Default "auto"mesh_
ytick_style: str, style for yticks. options: "sci", "scientific", "plain". Default "plain"

Expand source code

@dataclass
class WaveformPanel:
    """
    Panel for Waveform plots

    Attributes:
        sig: np.ndarray, the signal to plot.  Required
        time: np.ndarray, the timestamps of the data.  Required
        units: str, units of the signal.  Default "Norm"
        label: str, label for the data.  Default "(wf)"
        yscaling: str, scaling for y-axis.  options: "auto", "symmetric", "positive", "else".  Default "auto"mesh_
        ytick_style: str, style for yticks.  options: "sci", "scientific", "plain".  Default "plain"
    """
    sig: np.ndarray
    time: np.ndarray
    units: str = "Norm"
    label: str = "(wf)"
    yscaling: str = "auto"
    ytick_style: str = "plain"

    def __post_init__(self):
        if self.ytick_style not in YTICK_STYLE_VALS:
            self.ytick_style = "plain"
        if self.yscaling not in WF_Y_SCALING_VALS:
            self.yscaling = "else"

    def set_y_lims(self, axis: plt.Axes):
        """
        :param axis: the axis to update y limits for
        :return: updated axis with new y limits
        """
        if self.yscaling == "auto":
            axis.set_ylim(np.min(self.sig), np.max(self.sig))
            self.ytick_style = "plain"
        elif self.yscaling == "symmetric":
            axis.set_ylim(-np.max(np.abs(self.sig)), np.max(np.abs(self.sig)))
        elif self.yscaling == "positive":
            axis.set_ylim(0, np.max(np.abs(self.sig)))
        else:
            axis.set_ylim(-10, 10)

Class variables

var label : str
var sig : numpy.ndarray
var time : numpy.ndarray
var units : str
var yscaling : str
var ytick_style : str

Methods

def set_y_lims(self, axis: matplotlib.axes._axes.Axes): :param axis: the axis to update y limits for :return: updated axis with new y limits

class WaveformPlotBase (station_id: str, figure_title: str, figure_title_show: bool = True, start_time_epoch: float = 0.0, params_tfr: AudioParams = <quantum_inferno.plot_templates.figure_attributes.AudioParams object>, units_time: str = 's', label_panel_show: bool = False, labels_fontweight: Optional[str] = None, waveform_color: Optional[str] = None)

Base class for Waveform plots. Extends PlotBase; refer to PlotBase for additional attributes

Attributes

label_panel_show: bool, if True, show the label. Default False
labels_fontweight: optional str, font weight of the labels. Default None
waveform_color: optional str, color of the waveform. Default None

Expand source code

@dataclass
class WaveformPlotBase(PlotBase):
    """
    Base class for Waveform plots.  Extends PlotBase; refer to PlotBase for additional attributes

    Attributes:
        label_panel_show: bool, if True, show the label.  Default False
        labels_fontweight: optional str, font weight of the labels.  Default None
        waveform_color: optional str, color of the waveform.  Default None
    """
    label_panel_show: bool = False
    labels_fontweight: Optional[str] = None
    waveform_color: Optional[str] = None

Ancestors

PlotBase

Class variables

var label_panel_show : bool
var labels_fontweight : Optional[str]
var waveform_color : Optional[str]