Whole bunch of new SVGs.
Finished rough anatomical sketch. Combined anatomy and flowchart (WIP).
This commit is contained in:
j-hartling
@@ -4,35 +4,27 @@ plt.rcParams['text.usetex'] = True
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plt.rcParams['font.family'] = 'computer modern roman'
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plt.rcParams['mathtext.fontset'] = 'cm'
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plt.rcParams['mathtext.default'] = 'regular'
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# Targets:
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texts = {
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'BP': ('BP', 25),
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'LP': ('LP', 25),
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'HP': ('HP', 25),
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'tympanum': ('Tympanal\nMembrane', 13),
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'receptors': ('Receptor\nNeurons', 13),
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'interneurons': ('Local\nInterneurons', 13),
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'ascending': ('Ascending\nNeurons', 13),
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'threshold': ('Threshold\nNonlinearity', 13),
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'brain': ('Central\nBrain', 13),
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}
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plt.rcParams['svg.fonttype'] = 'path'
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plt.rc('text.latex', preamble=r'\usepackage{amsmath}')
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# Settings:
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fs_chart = 70
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fs_legend = 40
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show_figs = True
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grid_props = dict(left=0, right=1, top=1, bottom=0)
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fig_props = {
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'figsize': (1, 1),
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'figsize': (3, 3),
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'facecolor': 'none',
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'edgecolor': 'none',
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'frameon': False,
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'rasterized': True,
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# 'rasterized': True,
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}
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ax_props = {
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'facecolor': 'none',
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'frame_on': False,
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'rasterized': True,
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# 'rasterized': True,
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}
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text_props = {
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@@ -41,21 +33,44 @@ text_props = {
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'y': 0.5,
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'ha': 'center',
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'va': 'center',
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'rasterized': True,
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# 'rasterized': True,
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}
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# Prepare variables:
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grid_props = dict(left=0, right=1, top=1, bottom=0)
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# Targets:
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texts = {
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'filt': (r'$x_{\text{filt}}$', fs_chart),
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'env': (r'$x_{\text{env}}$', fs_chart),
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'db': (r'$x_{\text{dB}}$', fs_chart),
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'envdb': (r'$\begin{array}{c}x_{\text{env}}\\x_{\text{dB}}\end{array}$', fs_chart),
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'adapt': (r'$x_{\text{adapt}}$', fs_chart),
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'conv1': (r'$c_1$', fs_chart),
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'conv2': (r'$c_2$', fs_chart),
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'conv3': (r'$c_3$', fs_chart),
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'bi1': (r'$b_{1, \Theta}$', fs_chart),
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'bi2': (r'$b_{2, \Theta}$', fs_chart),
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'bi3': (r'$b_{3, \Theta}$', fs_chart),
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'feat1': (r'$f_{1, \Theta}$', fs_chart),
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'feat2': (r'$f_{2, \Theta}$', fs_chart),
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'feat3': (r'$f_{3, \Theta}$', fs_chart),
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'BP': ('BP', fs_chart),
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'LP': ('LP', fs_chart),
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'HP': ('HP', fs_chart),
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'tympanum': ('Tympanal\nMembrane', fs_legend),
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'receptors': ('Receptor\nNeurons', fs_legend),
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'interneurons': ('Local\nInterneurons', fs_legend),
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'ascending': ('Ascending\nNeurons', fs_legend),
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'threshold': ('Threshold\nNonlinearity', fs_legend),
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'integration': ('Temporal\nAveraging', fs_legend),
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'brain': ('Central\nBrain', fs_legend),
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}
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# Save each target string:
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for name, (text, fs) in texts.items():
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# print(f'Saving text figure for: {name}')
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# print(name, text, fs)
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fig, ax = plt.subplots(1, 1, gridspec_kw=grid_props, **fig_props)
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ax.set(**ax_props)
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ax.axis('off')
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ax.text(s=text, fontsize=fs, **text_props)
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fig.savefig(f'../figures/{name}_text.svg',
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fig.savefig(f'../figures/{name}_text.svg', dpi=300,
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bbox_inches='tight', pad_inches=0)
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if show_figs:
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plt.show()
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@@ -64,131 +79,131 @@ for name, (text, fs) in texts.items():
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def text_box(ax, text, xy, width, height, transform=None,
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ha='center', va='center', **kwargs):
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""" Maximizes fontsize of text to fit into a given bounding box.
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Calculated fontsize depends on the aspect ratio of the bounding box,
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the aspect ratio and alignment of the text, and the resolution and size
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of the underlying figure. Text is not updated when resizing the figure.
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# def text_box(ax, text, xy, width, height, transform=None,
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# ha='center', va='center', **kwargs):
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# """ Maximizes fontsize of text to fit into a given bounding box.
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# Calculated fontsize depends on the aspect ratio of the bounding box,
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# the aspect ratio and alignment of the text, and the resolution and size
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# of the underlying figure. Text is not updated when resizing the figure.
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Parameters
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----------
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ax : matplotlib axes object
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Target subplot to annotate the text.
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text : str
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Text to fit into the specified bounding box under the given alignments.
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xy : tuple of floats or ints (2,)
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Text position in the coordinate system specified by transform.
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width : float or int
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Rectangle width in the coordinate system specified by transform.
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height : float or int
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Rectangle height in the coordinate system specified by transform.
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transform : matplotlib transform, optional
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Underlying coordinate system of the bounding box. Determines the
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interpretation of xy, width, and height. Falls back to data coordinates
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if unspecified. The default is None.
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ha : str, optional
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Horizontal alignment of bounding box and text relative to the given xy.
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The default is 'center'.
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va : str, optional
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Vertical alignment of bounding box and text relative to the given xy.
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The default is 'center'.
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**kwargs : dict, optional
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Additional keyword arguments passed to ax.annotate() for specifying
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different font properties of the returned text object.
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# Parameters
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# ----------
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# ax : matplotlib axes object
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# Target subplot to annotate the text.
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# text : str
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# Text to fit into the specified bounding box under the given alignments.
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# xy : tuple of floats or ints (2,)
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# Text position in the coordinate system specified by transform.
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# width : float or int
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# Rectangle width in the coordinate system specified by transform.
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# height : float or int
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# Rectangle height in the coordinate system specified by transform.
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# transform : matplotlib transform, optional
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# Underlying coordinate system of the bounding box. Determines the
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# interpretation of xy, width, and height. Falls back to data coordinates
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# if unspecified. The default is None.
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# ha : str, optional
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# Horizontal alignment of bounding box and text relative to the given xy.
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# The default is 'center'.
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# va : str, optional
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# Vertical alignment of bounding box and text relative to the given xy.
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# The default is 'center'.
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# **kwargs : dict, optional
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# Additional keyword arguments passed to ax.annotate() for specifying
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# different font properties of the returned text object.
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Returns
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-------
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t : matplotlib text object
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Annotated text object with adjusted fontsize to fit the bounding box.
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"""
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# Input interpretation:
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if transform is None:
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transform = ax.transData
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fig = ax.get_figure()
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x, y = xy
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# Alignment-specific anchor points:
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x_align1, x_align2 = {
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'center': (x - width / 2, x + width / 2),
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'left': (x, x + width),
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'right': (x - width, x),
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}[ha]
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y_align1, y_align2 = {
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'center': (y - height / 2, y + height / 2),
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'bottom': (y, y + height),
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'top': (y - height, y),
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}[va]
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# Anchor points in pixel:
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left_corner = transform.transform((x_align1, y_align1))
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right_corner = transform.transform((x_align2, y_align2))
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# Bounding rectangle size in pixel:
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pixel_width = right_corner[0] - left_corner[0]
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pixel_height = right_corner[1] - left_corner[1]
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# Adjust fontsize to box height (inch):
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dpi = fig.dpi
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rect_height = pixel_height / dpi
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fs_initial = rect_height * 72
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# Plot first draft of the text:
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t = ax.annotate(text, xy, ha=ha, va=va, xycoords=transform, **kwargs)
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t.set_fontsize(fs_initial)
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# Adjust fontsize to box width (inch):
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bbox = t.get_window_extent(fig.canvas.get_renderer())
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fs_adjusted = fs_initial * pixel_width / bbox.width
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t.set_fontsize(fs_adjusted)
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return t
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# Returns
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# -------
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# t : matplotlib text object
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# Annotated text object with adjusted fontsize to fit the bounding box.
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# """
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# # Input interpretation:
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# if transform is None:
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# transform = ax.transData
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# fig = ax.get_figure()
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# x, y = xy
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# # Alignment-specific anchor points:
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# x_align1, x_align2 = {
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# 'center': (x - width / 2, x + width / 2),
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# 'left': (x, x + width),
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# 'right': (x - width, x),
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# }[ha]
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# y_align1, y_align2 = {
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# 'center': (y - height / 2, y + height / 2),
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# 'bottom': (y, y + height),
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# 'top': (y - height, y),
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# }[va]
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# # Anchor points in pixel:
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# left_corner = transform.transform((x_align1, y_align1))
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# right_corner = transform.transform((x_align2, y_align2))
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# # Bounding rectangle size in pixel:
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# pixel_width = right_corner[0] - left_corner[0]
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# pixel_height = right_corner[1] - left_corner[1]
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# # Adjust fontsize to box height (inch):
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# dpi = fig.dpi
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# rect_height = pixel_height / dpi
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# fs_initial = rect_height * 72
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# # Plot first draft of the text:
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# t = ax.annotate(text, xy, ha=ha, va=va, xycoords=transform, **kwargs)
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# t.set_fontsize(fs_initial)
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# # Adjust fontsize to box width (inch):
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# bbox = t.get_window_extent(fig.canvas.get_renderer())
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# fs_adjusted = fs_initial * pixel_width / bbox.width
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# t.set_fontsize(fs_adjusted)
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# return t
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def text_graph(text, save_str=None, size=None, ax=None, show=False,
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close=False, **kwargs):
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""" Turns entire subplot into a text box that displays the given text.
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Fontsize is maximized to fit the available bounding box. Text is always
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centered in the subplot. Meant for creating scalable text elements that
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comply with the style of other plot elements, especially for posters.
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# def text_graph(text, save_str=None, size=None, ax=None, show=False,
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# close=False, **kwargs):
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# """ Turns entire subplot into a text box that displays the given text.
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# Fontsize is maximized to fit the available bounding box. Text is always
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# centered in the subplot. Meant for creating scalable text elements that
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# comply with the style of other plot elements, especially for posters.
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Parameters
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----------
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text : str
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Text to be displayed. Can be multiline. Text fontsize is maximized by
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text_box() to fit a bounding box that covers the entire axes area.
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save_str : str, optional
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If specified, saves the underlying figure under the given path. For
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best results, use a vector format such as .svg). The default is None.
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size : tuple of floats or ints (2,), optional
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If specified, creates a new figure with given size in inches and a
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single subplot. Indirectly controls the aspect ratio of the text box.
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Must be specified if ax is None. The default is None.
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ax : matplotlib axes object, optional
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If specified, the target subplot to turn into a text box. Can be used
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to set more properties such as the background color of the text box.
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Must be specified if size is None. The default is None.
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show : bool, optional
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If True, displays the figure before returning. Else, returns without
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showing the figure. The default is False.
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**kwargs : dict, optional
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Keyword arguments passed to text_box() and further to ax.annotate() for
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specifying additional font properties of the displayed text.
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# Parameters
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# ----------
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# text : str
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# Text to be displayed. Can be multiline. Text fontsize is maximized by
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# text_box() to fit a bounding box that covers the entire axes area.
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# save_str : str, optional
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# If specified, saves the underlying figure under the given path. For
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# best results, use a vector format such as .svg). The default is None.
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# size : tuple of floats or ints (2,), optional
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# If specified, creates a new figure with given size in inches and a
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# single subplot. Indirectly controls the aspect ratio of the text box.
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# Must be specified if ax is None. The default is None.
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# ax : matplotlib axes object, optional
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# If specified, the target subplot to turn into a text box. Can be used
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# to set more properties such as the background color of the text box.
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# Must be specified if size is None. The default is None.
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# show : bool, optional
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# If True, displays the figure before returning. Else, returns without
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# showing the figure. The default is False.
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# **kwargs : dict, optional
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# Keyword arguments passed to text_box() and further to ax.annotate() for
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# specifying additional font properties of the displayed text.
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Raises
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------
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ValueError
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Breaks if neither size nor ax is specified to define a target subplot.
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"""
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# Input interpretation:
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if size is not None:
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fig, ax = plt.subplots(figsize=size)
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elif ax is not None:
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fig = ax.get_figure()
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else:
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raise ValueError('Either size or ax must be specified.')
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# Turn drawable area of axes into a single text box:
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text_box(ax, text, (0.5, 0.5), 1, 1, ax.transAxes, **kwargs)
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# Hide other axes elements:
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ax.xaxis.set_visible(False)
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ax.yaxis.set_visible(False)
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ax.spines[:].set_visible(False)
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# Return options:
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if save_str is not None:
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fig.savefig(save_str, bbox_inches='tight')
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if show:
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plt.show()
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return None
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# Raises
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# ------
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# ValueError
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# Breaks if neither size nor ax is specified to define a target subplot.
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# """
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# # Input interpretation:
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# if size is not None:
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# fig, ax = plt.subplots(figsize=size)
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# elif ax is not None:
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# fig = ax.get_figure()
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# else:
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# raise ValueError('Either size or ax must be specified.')
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# # Turn drawable area of axes into a single text box:
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# text_box(ax, text, (0.5, 0.5), 1, 1, ax.transAxes, **kwargs)
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# # Hide other axes elements:
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# ax.xaxis.set_visible(False)
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# ax.yaxis.set_visible(False)
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# ax.spines[:].set_visible(False)
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# # Return options:
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# if save_str is not None:
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# fig.savefig(save_str, bbox_inches='tight')
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# if show:
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# plt.show()
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# return None
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Block a user