mirror of
https://github.com/cdtools-developers/cdtools.git
synced 2026-09-27 20:52:08 +02:00
Update the docstrings on all the tools files and start laying out the docs for real
This commit is contained in:
Abe Levitan
+144
-81
@@ -1,3 +1,11 @@
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"""This module contains functions for plotting various important metrics
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All the plotting functions here can accept torch input or numpy input,
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to facilitate their use both for live inspection of running reconstructions
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and for after-the-fact analysis. Utilities for plotting complex valued
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images exist, as well as plotting scan patterns and nanomaps
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"""
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from __future__ import division, print_function, absolute_import
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from CDTools.tools import cmath
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@@ -7,8 +15,8 @@ import matplotlib.pyplot as plt
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from matplotlib.colors import hsv_to_rgb
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__all__ = ['colorize','plot_1D','plot_amplitude','plot_phase',
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'plot_colorized', 'plot_translations','get_units_factor',
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__all__ = ['colorize', 'plot_amplitude', 'plot_phase',
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'plot_colorized', 'plot_translations', 'get_units_factor',
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'plot_nanomap']
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@@ -18,11 +26,14 @@ def colorize(z):
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in a call to imshow based on an input complex numpy array (not a
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torch tensor representing a complex field)
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Args:
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z (array_like) : A complex-valued array
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Returns:
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list : A list of arrays for R,G, and B channels of an image.
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Parameters
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----------
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z : array
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A complex-valued array
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Returns
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-------
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rgb : list(array)
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A list of arrays for the R,G, and B channels of an image
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"""
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amp = np.abs(z)
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@@ -42,11 +53,15 @@ def colorize(z):
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def get_units_factor(units):
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"""Gets the multiplicative factor associated with a length unit
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Args:
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units (str) : The abbreviation for the unit type
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Parameters
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----------
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units : str
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The abbreviation for the unit type
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Returns:
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(float) : The factor meters / (unit)
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Returns
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-------
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factor : float
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The factor meters / (unit)
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"""
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u = units.lower()
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@@ -66,38 +81,35 @@ def get_units_factor(units):
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factor=1e12
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return factor
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def plot_1D(arr, fig = None, **kwargs):
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"""Simple 1D plotter
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Args:
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im (numpy array) : A 1D array with dimensions (,N)
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fig (matplotlib.figure.Figure) : A matplotlib figure to use to plot. If None,
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a new figure is created with an Axes subplot at 111.
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**kwargs: Can be used to set any keyword arguments for the matplotlib.axes.Axes class
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(see https://matplotlib.org/api/axes_api.html#the-axes-class)
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"""
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if fig is None:
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fig = plt.figure()
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ax = fig.add_subplot(111, **kwargs)
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else:
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plt.figure(fig.number)
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plt.gcf().clear()
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plt.scatter(np.arange(arr.shape[-1]), arr)
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def plot_amplitude(im, fig = None, basis=None, units='um', cmap='viridis', **kwargs):
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""" Plots the amplitude of a complex Tensor or numpy array with dimensions NxMx2.
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Args:
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im (t.Tensor) : An image with dimensions NxMx2.
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fig (matplotlib.figure.Figure) : A matplotlib figure to use to plot. If None,
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a new figure is created with an Axes subplot at 111.
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basis (numpy array) : Optional, the 3x2 probe basis, used to put the axis labels in real space units.
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units (str) : The units to convert the basis to
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cmap (str) : Default is 'viridis', the colormap to plot with
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**kwargs: Can be used to set any keyword arguments for the matplotlib.axes.Axes class
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(see https://matplotlib.org/api/axes_api.html#the-axes-class)
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"""Plots the amplitude of a complex array with dimensions NxM
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If a figure is given explicitly, it will clear that existing figure and
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plot over it. Otherwise, it will generate a new figure.
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If a basis is explicitly passed, the image will be plotted in real-space
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coordinates
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Parameters
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----------
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im : array
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An complex array with dimensions NxM
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fig : matplotlib.figure.Figure
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Default is a new figure, a matplotlib figure to use to plot
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basis : np.array
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Optional, the 3x2 probe basis
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units : str
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The length units to mark on the plot, default is um
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cmap : str
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Default is 'viridis', the colormap to plot with
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**kwargs
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All other args are passed to fig.add_subplot(111, **kwargs)
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Returns
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-------
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used_fig : matplotlib.figure.Figure
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The figure object that was actually plotted to.
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"""
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if fig is None:
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fig = plt.figure()
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@@ -137,15 +149,33 @@ def plot_amplitude(im, fig = None, basis=None, units='um', cmap='viridis', **kwa
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def plot_phase(im, fig=None, basis=None, units='um', cmap='auto', **kwargs):
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""" Plots the phase of a complex Tensor or numpy array with dimensions NxMx2.
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Args:
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im (t.Tensor) : An image with dimensions NxMx2.
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fig (matplotlib.figure.Figure) : A matplotlib figure to use to plot. If None,
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a new figure is created with an Axes subplot at 111.
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basis (numpy array) : Optional, the 3x2 probe basis, used to put the axis labels in real space units.
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cmap (str) : Default is 'auto', which chooses between twilight and hsv based on availability.
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**kwargs: Can be used to set any keyword arguments for the matplotlib.axes.Axes class
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(see https://matplotlib.org/api/axes_api.html#the-axes-class)
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""" Plots the phase of a complex array with dimensions NxMx2
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If a figure is given explicitly, it will clear that existing figure and
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plot over it. Otherwise, it will generate a new figure.
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If a basis is explicitly passed, the image will be plotted in real-space
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coordinates
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Parameters
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----------
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im : array
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An complex array with dimensions NxM
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fig : matplotlib.figure.Figure
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Default is a new figure, a matplotlib figure to use to plot
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basis : np.array
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Optional, the 3x2 probe basis
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units : str
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The length units to mark on the plot, default is um
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cmap : str
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Default is 'viridis', the colormap to plot with
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**kwargs
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All other args are passed to fig.add_subplot(111, **kwargs)
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Returns
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-------
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used_fig : matplotlib.figure.Figure
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The figure object that was actually plotted to.
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"""
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if fig is None:
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fig = plt.figure()
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@@ -188,23 +218,39 @@ def plot_phase(im, fig=None, basis=None, units='um', cmap='auto', **kwargs):
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else:
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plt.xlabel('j (pixels)')
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plt.ylabel('i (pixels)')
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return fig
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def plot_colorized(im, fig=None, basis=None, units='um', **kwargs):
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""" Plots the colorized version of a complex Tensor or numpy array with dimensions NxMx2.
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The darkness corresponds to the intensity of the image, and the color corresponds
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to the phase.
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""" Plots the colorized version of a complex array with dimensions NxM
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Args:
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im (t.Tensor) : An image with dimensions NxMx2.
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fig (matplotlib.figure.Figure) : A matplotlib figure to use to plot. If None,
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a new figure is created with an Axes subplot at 111.
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basis (numpy array) : Optional, the 3x2 probe basis, used to put the axis labels in real space units.
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**kwargs: Can be used to set any keyword arguments for the matplotlib.axes.Axes class
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(see https://matplotlib.org/api/axes_api.html#the-axes-class)
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The darkness corresponds to the intensity of the image, and the color
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corresponds to the phase.
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If a figure is given explicitly, it will clear that existing figure and
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plot over it. Otherwise, it will generate a new figure.
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If a basis is explicitly passed, the image will be plotted in real-space
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coordinates
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Parameters
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----------
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im : array
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An complex array with dimensions NxM
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fig : matplotlib.figure.Figure
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Default is a new figure, a matplotlib figure to use to plot
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basis : np.array
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Optional, the 3x2 probe basis
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units : str
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The length units to mark on the plot, default is um
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**kwargs
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All other args are passed to fig.add_subplot(111, **kwargs)
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Returns
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-------
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used_fig : matplotlib.figure.Figure
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The figure object that was actually plotted to.
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"""
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if fig is None:
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fig = plt.figure()
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@@ -240,24 +286,34 @@ def plot_colorized(im, fig=None, basis=None, units='um', **kwargs):
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def plot_translations(translations, fig=None, units='um', lines=True):
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def plot_translations(translations, fig=None, units='um', lines=True, **kwargs):
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"""Plots a set of probe translations in a nicely formatted way
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Args:
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translations: An Nx2 or Nx3 set of translations in real space
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fig : Optional, a figure to plot into
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units : Default is um, units to report in (assuming input in m)
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lines : Whether to plot the lines indicating the path
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Parameters
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----------
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translations : array
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An Nx2 or Nx3 set of translations in real space
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fig : matplotlib.figure.Figure
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Default is a new figure, a matplotlib figure to use to plot
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units : str
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Default is um, units to report in (assuming input in m)
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lines : bool
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Whether to plot lines indicating the path taken
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**kwargs
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All other args are passed to fig.add_subplot(111, **kwargs)
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Returns:
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None
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Returns
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-------
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used_fig : matplotlib.figure.Figure
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The figure object that was actually plotted to.
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"""
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factor = get_units_factor(units)
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if fig is None:
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax = fig.add_subplot(111, **kwargs)
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else:
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plt.figure(fig.number)
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plt.gcf().clear()
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@@ -272,21 +328,29 @@ def plot_translations(translations, fig=None, units='um', lines=True):
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plt.xlabel('X (' + units + ')')
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plt.ylabel('Y (' + units + ')')
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return fig
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def plot_nanomap(translations, values, fig=None, units='um', convention='probe'):
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"""Plots a set of nanomap data in a flexible way
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Args:
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translations : An Nx2 or Nx3 set of translations in real space
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values : a length-N object of values associated with the translations
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fig : Optional, a figure to plot into
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units : Default is um, units to report in (assuming input in m)
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lines : Whether to plot the lines indicating the path
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convention : 'probe' if the translations refer to probe translations, 'obj' if they refer to object translations
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Parameters
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----------
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translations : array
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An Nx2 or Nx3 set of translations in real space
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values : array
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A length-N object of values associated with the translations
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fig : matplotlib.figure.Figure
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Default is a new figure, a matplotlib figure to use to plot
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units : str
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Default is um, units to report in (assuming input in m)
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convention : str
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Default is 'probe', alternative is 'obj'. Whether the translations refer to the probe or object.
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Returns:
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None
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Returns
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-------
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used_fig : matplotlib.figure.Figure
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The figure object that was actually plotted to.
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"""
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if fig is None:
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@@ -316,10 +380,9 @@ def plot_nanomap(translations, values, fig=None, units='um', convention='probe')
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plt.scatter(factor * trans[:,0],factor * trans[:,1],s=s,c=values)
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plt.gca().invert_xaxis()
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plt.gca().set_facecolor('k')
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plt.xlabel('Translation x (' + units + ')')
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plt.ylabel('Translation y (' + units + ')')
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plt.colorbar()
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return fig
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