540 lines
24 KiB
Python
540 lines
24 KiB
Python
### MatPlotLib Graph Wrapper
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#### Written by Cal.W 2020, originally for MECH2700 but continually
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#### expanded upon.
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#### 2023 - Added UQ Colors
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#### 2023 - Added pltKeyClose function
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#### 2023 - Added UQ Default Colours to MatPlotLib
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#### 2024 - Added Annotation & Fill
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__author__ = "Cal Wing"
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__version__ = "0.1.11"
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from collections.abc import Iterator
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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import matplotlib.colors as colors
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from mpl_toolkits.axes_grid1 import make_axes_locatable
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from cycler import cycler
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import colorsys
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# Define the UQ Colours
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UQ_COLOURS_DICT = {
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# Primary
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"purple": "#51247A",
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"white" : "#FFFFFF",
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"black" : "#000000",
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# Secondary
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"light_purple": "#962A8B",
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"red" : "#E62645",
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"green" : "#2EA836",
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"gold" : "#BB9D65",
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"neutral" : "#D7D1CC",
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"orange" : "#EB602B",
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"yellow" : "#FBB800",
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"blue" : "#4085C6",
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"aqua" : "#00A2C7",
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"dark_grey" : "#999490"
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}
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# Define a colour object that can do neat conversions & things, by default stores as hex value
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class ColourValue(str):
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def __new__(self, name, value):
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self.name = name
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self._orig_value = value
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self.value = colors.to_hex(self._orig_value, True)
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return super().__new__(self, self.value)
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def __str__(self) -> str:
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return self.value
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def __repr__(self) -> str:
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return self.name + " " + self.value + " " + str(self.rgba())
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def rgba(self, alpha = None) -> tuple[float, float, float, float]:
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return colors.to_rgba(self.value, alpha)
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def rgb(self) -> tuple[float, float, float]:
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return colors.to_rgb(self._orig_value)
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def hex(self) -> str:
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return self.value
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def hsv(self) -> np.ndarray:
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return colors.rgb_to_hsv(self.rgb())
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def hls(self) -> tuple[float, float, float]:
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return colorsys.rgb_to_hls(*self.rgb())
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def lighten(self, amount=0.5) -> tuple[float, float, float]:
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hls = self.hls()
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return colorsys.hls_to_rgb(hls[0], max(0, min(1, amount * hls[1])), hls[2])
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def hex_lighten(self, amount=0.5) -> str:
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return colors.to_hex(self.lighten(amount), True)
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# Define the UQ Colours in a nicer object
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class ColourList(object):
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def __init__(self, colours: dict) -> None:
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self.colours = {}
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for key, value in colours.items():
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self.colours[key] = ColourValue(key, value)
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setattr(self, key, self.colours[key])
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def __getitem__(self, key: str) -> str:
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if key.replace(" ", "_") in self.colours.keys():
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key = key.replace(" ", "_")
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return self.colours[key]
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def items(self):
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return self.colours.items()
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def __repr__(self) -> str:
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return f"Colour List of {len(self.colours)} colour{'s' if len(self.colours) > 0 else ''}: " + str(list(self.colours.keys()))
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UQ_COLOURS = ColourList(UQ_COLOURS_DICT)
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# Load UQ Colours into MatPlotLib
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# UQ colours are prefaced with 'uq:', so UQ red is 'uq:red'
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# Note: Any names That have a _ also have a version with spaces so both "uq:light_purple" and "uq:light purple" work
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uq_colour_mapping = {'uq:' + name: value for name, value in list(UQ_COLOURS.items()) + [(x[0].replace("_", " "), x[1]) for x in UQ_COLOURS.items() if "_" in x[0]]}
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colors.get_named_colors_mapping().update( uq_colour_mapping )
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## UQ Colour Cycler
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# +-----------------------------+-----------------------------+
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# | Default (Tab) | UQ |
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# +-----------------------------+-----------------------------+
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# | C00 | #1f77b4 -> tab:blue | #51247A -> uq:purple |
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# | C01 | #ff7f0e -> tab:orange | #4085C6 -> uq:blue |
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# | C02 | #2ca02c -> tab:green | #2EA836 -> uq:green |
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# | C03 | #d62728 -> tab:red | #E62645 -> uq:red |
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# | C04 | #9467bd -> tab:purple | #962A8B -> uq:light_purple |
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# | C05 | #8c564b -> tab:brown | #999490 -> uq:dark_grey |
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# | C06 | #e377c2 -> tab:pink | #EB602B -> uq:orange |
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# | C07 | #7f7f7f -> tab:grey | #FBB800 -> uq:yellow |
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# | C08 | #bcbd22 -> tab:olive | #00A2C7 -> uq:aqua |
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# | C09 | #17becf -> tab:cyan | #BB9D65 -> uq:gold |
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# | C10 | | #D7D1CC -> uq:neutral |
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# +-----------------------------+-----------------------------+
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# Build a colour cycler
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uq_colour_cycler_factory = lambda: cycler(color=[
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UQ_COLOURS["purple"], #51247A -> C00 -> uq:purple
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UQ_COLOURS["blue"], #4085C6 -> C01 -> uq:blue
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UQ_COLOURS["green"], #2EA836 -> C02 -> uq:green
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UQ_COLOURS["red"], #E62645 -> C03 -> uq:red
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UQ_COLOURS["light_purple"], #962A8B -> C04 -> uq:light_purple
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UQ_COLOURS["dark_grey"], #999490 -> C05 -> uq:dark_grey
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UQ_COLOURS["orange"], #EB602B -> C06 -> uq:orange
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UQ_COLOURS["yellow"], #FBB800 -> C07 -> uq:yellow
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UQ_COLOURS["aqua"], #00A2C7 -> C08 -> uq:aqua
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UQ_COLOURS["gold"], #BB9D65 -> C09 -> uq:gold
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UQ_COLOURS["neutral"] #D7D1CC -> C10 -> uq:neutral
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])
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# Tell MatPlotLib to use said cycler
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plt.rc('axes', prop_cycle=uq_colour_cycler_factory())
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## UQ Colour Gradient (Not very good :( )
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uq_colour_map_grad = [
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UQ_COLOURS["purple"],
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UQ_COLOURS["light_purple"],
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UQ_COLOURS["light_purple"],
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UQ_COLOURS["blue"],
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UQ_COLOURS["blue"],
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UQ_COLOURS["aqua"],
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UQ_COLOURS["green"],
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UQ_COLOURS["green"],
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UQ_COLOURS["green"],
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UQ_COLOURS["yellow"],
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UQ_COLOURS["yellow"]
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]
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#Convert to RGB values
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uq_colour_map_grad = [colors.to_rgb(c) for c in uq_colour_map_grad]
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#Populate the working dict
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uq_colour_dict = {
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"red": [],
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"green": [],
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"blue": [],
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}
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for i, c in enumerate(uq_colour_map_grad):
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offset = i / (len(uq_colour_map_grad) - 1)
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uq_colour_dict["red"].append( (offset, c[0], c[0]) )
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uq_colour_dict["green"].append( (offset, c[1], c[1]) )
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uq_colour_dict["blue"].append( (offset, c[2], c[2]) )
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#Define & register the colour map itself
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uq_cmap = colors.LinearSegmentedColormap('uq',segmentdata=uq_colour_dict)
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matplotlib.colormaps.register(uq_cmap)
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# Set the colour map - Not a very good default so not doing that
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#plt.set_cmap("uq")
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## Colorbar Function by Joseph Long & Mike Lampton
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# Retrieved from https://joseph-long.com/writing/colorbars/ on 31/10/2021
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# Minor Modifications made by Cal.W 2021
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def colorbar(mappable, size="5%", pad=0.05, lsize=None, lpad=None, lax=True, **kwargs):
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last_axes = plt.gca()
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ax = mappable.axes
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fig = ax.figure
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divider = make_axes_locatable(ax)
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if lax:
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lsize = lsize if lsize is not None else size
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lpad = lpad if lpad is not None else pad
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dax = divider.append_axes("left", size=lsize, pad=lpad)
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dax.set_frame_on(False)
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dax.grid(False)
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dax.set_yticks([])
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dax.set_xticks([])
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cax = divider.append_axes("right", size=size, pad=pad)
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cbar = fig.colorbar(mappable, cax=cax, **kwargs)
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plt.sca(last_axes)
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return cbar
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## Make Graph Function
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def makeGraph(graphData, showPlot=True, doProgramBlock=True, figSavePath=None, hideEmptyAxis=False, closeFig=False) -> tuple[matplotlib.figure.Figure, tuple[matplotlib.axes.Axes, ...]]:
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""" Generate a matplotlib graph based on a simple dictionary object
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Input:
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dict(graphData): The dictionary containing all the graph data - see example for more info
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bool(showPlot[True]): Should the function display the plot
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bool(doProgramBlock[True]): Should the function block the main python thread
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str(figSavePath[None]): The path to save a copy of the figure, calls fig.savefig if not None
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Returns: The the figure and axes from matplotlib.pyplot.subplots()
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From 'matplotlib.pyplot.subplots():
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fig : `matplotlib.figure.Figure`
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ax : `matplotlib.axes.Axes` or array of Axes
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*ax* can be either a single `~matplotlib.axes.Axes` object or an
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array of Axes objects if more than one subplot was created.
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Example:
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makeGraph({
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"title": "Simple Plot",
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"xLabel": "x label",
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"yLabel": "y label",
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"plots": [
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{"x":[0,1,2,3,4], "y":[0,1,2,3,4], "label":"Linear"},
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{"x":[0,1,2,3,4], "y":[5,5,5,5,5]},
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{"x":[4,3,2,1,0], "y":[4,3,2,1,0], "label":"Linear2"},
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{"x":0, "type":"axvLine", "label":"Red Vertical Line", "color":"red"},
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{"y":6, "type":"axhLine", "label":"Dashed Horizontal Line", "args":{"linestyle":"--"}},
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{"type":"scatter", "x":4, "y":4, "label":"A Random Point", "colour":"purple", "args":{"zorder":2}}
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]
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})
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"""
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doKeyCopy = True
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plotDim = (1,)
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if "subPlots" in graphData:
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if "plotDim" in graphData: plotDim = graphData["plotDim"]
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else: plotDim = (1,len(graphData["subPlots"]))
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else:
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graphData["subPlots"] = [graphData]
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doKeyCopy = False
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figSize = graphData["figSize"] if "figSize" in graphData else None
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fig, axes = plt.subplots(*plotDim, figsize=figSize) # Create a figure and an axes.
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#if len(graphData["subPlots"]) <= 1:
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# axes = [axes]
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#Makes everything nice and linear
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# IE ((1,2), (3,4)) = (1,2,3,4)
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flatAxes = np.array(axes).flatten().tolist()
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loopKeys = [
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"xLabel", "yLabel", "title", "axis", "grid", "xPos", "yPos",
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"xLabelPos", "yLabelPos", "xTickPos", "yTickPos", "xScale", "yScale",
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"xTickMap", "yTickMap", "plots", "xLim", "yLim", "ledgLoc", "y2Label",
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"ticklabel"
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]
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#Feel like this could be optimized
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if doKeyCopy:
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for key in loopKeys:
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if key not in graphData: continue
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if key in graphData:
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for axGraphData in graphData["subPlots"]:
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if key not in axGraphData:
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axGraphData[key] = graphData[key]
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for i, axGraphData in enumerate(graphData["subPlots"]):
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ax1 = flatAxes[i]
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if bool(sum([("y2" in pData) for pData in axGraphData["plots"]])):
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ax2 = ax1.twinx()
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else:
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ax2 = None
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# Duct Tape
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ax = ax1
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#Draw many plots as needed
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# Also provide functions for drawing other types of lines
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if "plots" in axGraphData:
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for pData in axGraphData["plots"]:
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getSafeValue = lambda key, result=None: pData[key] if key in pData else result #Only return the key-value if present in pData
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getSafeValue2 = lambda key, key2, result=None: pData[key][key2] if key in pData and key2 in pData[key] else result
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getSafeColour = getSafeValue("colour") or getSafeValue("color") #Frigen American Spelling
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optArgs = getSafeValue("args", {}) #Allow for other args to be passed in
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if "x" in pData:
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xData = pData["x"]
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if "y" in pData:
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yData = pData["y"]
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elif "y2" in pData:
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yData = pData["y2"]
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ax = ax2
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if "type" not in pData or pData["type"] == "plot":
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ax.plot(xData, yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "point":
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ax.scatter(xData, yData,
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marker=getSafeValue("marker"), label=getSafeValue("label"),
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color=getSafeColour, zorder=getSafeValue("zorder", 2),
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**optArgs )
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elif pData["type"] == "hLine":
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ax.hlines(yData, *xData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "vLine":
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ax.vlines(xData, *yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "axvLine":
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if "y" not in pData: yData = (0, 1) #Span the whole graph
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ax.axvline(xData, *yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "axhLine":
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if "x" not in pData: xData = (0, 1) #Span the whole graph
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ax.axhline(yData, *xData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "scatter":
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ax.scatter(xData, yData, marker=getSafeValue("marker"), label=getSafeValue("label"), color=getSafeColour, **optArgs)
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elif pData["type"] == "contour":
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cs = ax.contour(getSafeValue("x"), getSafeValue("y"), pData["z"], levels=getSafeValue("levels"), colors=getSafeColour, **optArgs)
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if "label" in pData: cs.collections[0].set_label(getSafeValue("label"))
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elif pData["type"] == "matshow":
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ms = ax.matshow(pData["matrix"], origin=getSafeValue("origin"), label=getSafeValue("label"), **optArgs)
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if "colourBar" in pData:
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colorbar(ms, extend=getSafeValue2("colourBar", "extend"))
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elif pData["type"] == "pColourMesh":
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mesh = []
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if "X" in pData or "Y" in pData:
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mesh = [xData, yData, pData["Z"]]
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if "x" in pData or "y" in pData:
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x = xData; y = yData
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if type(x) in [int, float]: x = (0, x, None)
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if type(y) in [int, float]: y = (0, x, None)
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x = tuple(x); y = tuple(y)
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if len(x) < 3: x = (x[0], x[1], None)
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if len(y) < 3: y = (y[0], y[1], None)
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x = np.arange(x[0], x[1], x[2])
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y = np.arange(y[0], y[1], y[2])
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X, Y = np.meshgrid(x, y)
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mesh = [X, Y, pData["Z"]]
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else:
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mesh = [pData["Z"]]
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cNorm = None
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if "norm" in pData:
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cNorm = colors.LogNorm(vmin=pData["norm"][0], vmax=pData["norm"][1])
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pcMesh = ax.pcolormesh(*mesh, norm=cNorm, shading=getSafeValue("shading"), label=getSafeValue("label"), **optArgs)
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#pcMesh = ax.imshow(pData["Z"], norm=cNorm, origin="lower")
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if "colourBar" in pData:
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cBarOptArgs = pData["colourBar"]["optArgs"] if "optArgs" in pData["colourBar"] else {}
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fig.colorbar(pcMesh, ax=ax, extend=getSafeValue2("colourBar", "extend"), **cBarOptArgs)
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elif pData["type"] == "imshow":
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cNorm = None
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if "norm" in pData:
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cNorm = colors.LogNorm(vmin=pData["norm"][0], vmax=pData["norm"][1])
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ims = ax.imshow(pData["data"], norm=cNorm, origin=getSafeValue("origin"), label=getSafeValue("label"), **optArgs)
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if "colourBar" in pData:
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cBarOptArgs = pData["colourBar"]["optArgs"] if "optArgs" in pData["colourBar"] else {}
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colorbar(ims, extend=getSafeValue2("colourBar", "extend"), **cBarOptArgs)
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elif pData["type"] == "text":
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if not "props" in pData:
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props = {
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"boxstyle" : getSafeValue("boxstyle", "round"),
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"facecolor": getSafeValue("facecolor", getSafeValue("facecolour", "wheat")),
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"alpha" : getSafeValue("alpha", 0.5)
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}
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align = (
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getSafeValue("valign", None),
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getSafeValue("halign", None),
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)
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align = getSafeValue("align", align)
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ax.text(getSafeValue("x", 0.05), getSafeValue("y", 0.95), pData["text"], transform=ax.transAxes, fontsize=getSafeValue("fontsize", None), va=align[0], ha=align[1], bbox=props)
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elif pData["type"] == "annotate":
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if type(pData["label"]) == str:
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if "pos" in pData:
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pData["x"] = pData["pos"][0]
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pData["y"] = pData["pos"][1]
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ax.annotate(
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pData["label"], # this is the text
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(pData["x"],pData["y"]), # these are the coordinates to position the label
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textcoords=getSafeValue("offType", "offset points"), # how to position the text
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xytext=getSafeValue("offset", (0,10)), # distance from text to points (x,y)
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ha=getSafeValue("align", 'center') # horizontal alignment can be left, right or center
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)
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else:
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if "pos" not in pData:
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pData["pos"] = list(zip(pData['x'], pData['y']))
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for i, label in enumerate(pData["label"]):
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ax.annotate(
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label, # this is the text
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(pData["pos"][i][0], pData["pos"][i][1]), # these are the coordinates to position the label
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textcoords=getSafeValue("offType", "offset points"), # how to position the text
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xytext=getSafeValue("offset", (0,10)), # distance from text to points (x,y)
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ha=getSafeValue("align", 'center') # horizontal alignment can be left, right or center
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)
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elif pData["type"] == "fill":
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ax.fill_between(list(pData["x"]), list(pData["y"]), color=getSafeColour, alpha=getSafeValue("alpha", 1), linewidth=getSafeValue("linewidth", None))
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#ax.fill_between(xA, yA, color="w")
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#Set extra options as needed
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ax = ax1
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if "xLabel" in axGraphData: ax.set_xlabel(axGraphData["xLabel"]) # Add an x-label to the axes.
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if "yLabel" in axGraphData: ax.set_ylabel(axGraphData["yLabel"]) # Add an y-label to the axes.
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if "y2Label" in axGraphData: ax2.set_ylabel(axGraphData["y2Label"]) # Add a y2-label to the axes.
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if "title" in axGraphData: ax.set_title(axGraphData["title"]) # Add an title to the axes.
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if "axis" in axGraphData: ax.axis(axGraphData["axis"]) # Set the axis type
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if "grid" in axGraphData: ax.grid(axGraphData["grid"]) # Add grids to the graph
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if "xPos" in axGraphData: # Add the abilty to move the x axis label and ticks
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ax.xaxis.set_label_position(axGraphData["xPos"])
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ax.xaxis.set_ticks_position(axGraphData["xPos"])
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if "yPos" in axGraphData: # Add the abilty to move the y axis label and ticks
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ax.yaxis.set_label_position(axGraphData["yPos"])
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ax.yaxis.set_ticks_position(axGraphData["yPos"])
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if "xLabelPos" in axGraphData: ax.xaxis.set_label_position(axGraphData["xLabelPos"]) # Add the ability to move the x axis label
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if "yLabelPos" in axGraphData: ax.yaxis.set_label_position(axGraphData["yLabelPos"]) # Add the ability to move the y axis label
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if "xTickPos" in axGraphData: ax.xaxis.set_ticks_position(axGraphData["xTickPos"]) # Add the ability to move the x axis ticks
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if "yTickPos" in axGraphData: ax.yaxis.set_ticks_position(axGraphData["yTickPos"]) # Add the ability to move the y axis ticks
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if "xScale" in axGraphData: ax.set_xscale(axGraphData["xScale"]) #Add x axis scaling if needed
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if "yScale" in axGraphData: ax.set_yscale(axGraphData["yScale"]) #Add y axis scaling if needed
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if "xLim" in axGraphData:
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xLimit = ()
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if type(axGraphData["xLim"]) in [int, float]:
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xLimit = (0, axGraphData["xLim"])
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else:
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xLimit = axGraphData["xLim"]
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ax.set_xlim(xLimit)
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if "yLim" in axGraphData:
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yLimit = ()
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if type(axGraphData["yLim"]) in [int, float]:
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yLimit = (0, axGraphData["yLim"])
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else:
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yLimit = axGraphData["yLim"]
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ax.set_ylim(yLimit)
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if "xTickMap" in axGraphData: #Allow for the mapping / transformation of the xAxis Ticks
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xTicks = matplotlib.ticker.FuncFormatter(lambda x, pos: '{0:g}'.format(axGraphData["xTickMap"](x)))
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ax.xaxis.set_major_formatter(xTicks)
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if "yTickMap" in axGraphData: #Allow for the mapping / transformation of the yAxis Ticks
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yTicks = matplotlib.ticker.FuncFormatter(lambda y, pos: '{0:g}'.format(axGraphData["yTickMap"](y)))
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ax.yaxis.set_major_formatter(yTicks)
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if "plots" in axGraphData and bool(sum([("label" in pData) for pData in axGraphData["plots"]])):
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locPoint = axGraphData["ledgLoc"] if "ledgLoc" in axGraphData else None
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lines1, labels1 = ax1.get_legend_handles_labels()
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if ax2:
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lines2, labels2 = ax2.get_legend_handles_labels()
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ax2.legend(lines1 + lines2, labels1 + labels2, loc=locPoint)
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else:
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ax1.legend(lines1, labels1, loc=locPoint)
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if "ticklabel" in axGraphData:
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style = axGraphData["ticklabel"]["style"] if "style" in axGraphData["ticklabel"] else ""
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axis = axGraphData["ticklabel"]["axis"] if "axis" in axGraphData["ticklabel"] else "both"
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limits = axGraphData["ticklabel"]["limits"] if "limits" in axGraphData["ticklabel"] else None
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optArgs = axGraphData["ticklabel"]["optArgs"] if "optArgs" in axGraphData["ticklabel"] else {}
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ax.ticklabel_format(axis=axis, style=style, scilimits=limits, **optArgs)
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|
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#Should work?
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|
if hideEmptyAxis:
|
|
if not ax.collections and not ax.lines:
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|
ax.set_axis_off()
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|
|
|
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if "title" in graphData and not "figTitle" in graphData: fig.canvas.manager.set_window_title(graphData["title"].replace("\n", " ")) #Set the figure title correctly
|
|
if "figTitle" in graphData:
|
|
getSafeValue = lambda key: graphData[key] if key in graphData else None #Only return the key-value if present in graphData
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|
|
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fig.suptitle(graphData["figTitle"], fontsize=getSafeValue("figTitleFontSize"))
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fig.canvas.manager.set_window_title(graphData["figTitle"].replace("\n", " "))
|
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if "windowTitle" in graphData:
|
|
fig.canvas.manager.set_window_title(graphData["windowTitle"].replace("\n", " "))
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|
|
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fig.tight_layout() #Fix labels being cut off sometimes
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|
|
|
#Very big hack
|
|
if hideEmptyAxis:
|
|
flatAxes[-1].set_axis_off()
|
|
|
|
if figSavePath:
|
|
fig.savefig(figSavePath.format(fig.canvas.manager.get_window_title()))
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|
|
|
if showPlot:
|
|
plt.show(block=doProgramBlock) #Show the plot and also block the program - doing things OO style allow for more flexible programs
|
|
|
|
if closeFig:
|
|
matplotlib.pyplot.close(fig)
|
|
|
|
return fig, axes
|
|
|
|
# [TODO] Make this Async so the closure of all graphs exits
|
|
def pltKeyClose():
|
|
'''Show all plots and wait for user input to close them all.'''
|
|
plt.show(block=False)
|
|
input('Press any key to close all graphs...')
|
|
plt.close()
|
|
|
|
if __name__ == '__main__':
|
|
#This is an example of drawing 4 plots by generating them
|
|
graphData = {
|
|
"figTitle": "Simple Plot",
|
|
"figTitleFontSize": 16,
|
|
"figSize": (8,8), #Yay America, this is in inches :/ # Note: cm = 1/2.54
|
|
"xLabel": "x label",
|
|
"yLabel": "y label",
|
|
"plotDim": (2,2),
|
|
"subPlots":[]
|
|
}
|
|
|
|
#Create 4 identical plots with different names
|
|
for i in range(4):
|
|
newPlot = {
|
|
"title": f"Graph {i+1}",
|
|
"plots": [
|
|
{"x":[0,1,2,3,4], "y":[0,1,2,3,4], "label":"Linear"},
|
|
{"x":[0,1,2,3,4], "y":[5,5,5,5,5]},
|
|
{"x":[4,3,2,1,0], "y":[4,3,2,1,0], "label":"Linear2"},
|
|
{"x":0, "type":"axvLine", "label":"Red Vertical Line", "color":"uq:red"},
|
|
{"y":6, "type":"axhLine", "label":"Dashed Horizontal Line", "args":{"linestyle":"--"}},
|
|
{"type":"point", "x":4, "y":4, "label":"A Random Point", "colour":"uq:purple"}
|
|
]
|
|
}
|
|
graphData["subPlots"].append(newPlot)
|
|
|
|
makeGraph(graphData) |