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Thesis/makeGraph.py

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Add initial python files
2024-09-30 14:48:16 +10:00
### MatPlotLib Graph Wrapper
#### Written by Cal.W 2020, originally for MECH2700 but continually
#### expanded upon.
#### 2023 - Added UQ Colors
#### 2023 - Added pltKeyClose function
#### 2023 - Added UQ Default Colours to MatPlotLib
#### 2024 - Added Annotation & Fill
__author__ = "Cal Wing"
__version__ = "0.1.11"
from collections.abc import Iterator
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from mpl_toolkits.axes_grid1 import make_axes_locatable
from cycler import cycler
import colorsys
# Define the UQ Colours
UQ_COLOURS_DICT = {
# Primary
"purple": "#51247A",
"white" : "#FFFFFF",
"black" : "#000000",
# Secondary
"light_purple": "#962A8B",
"red" : "#E62645",
"green" : "#2EA836",
"gold" : "#BB9D65",
"neutral" : "#D7D1CC",
"orange" : "#EB602B",
"yellow" : "#FBB800",
"blue" : "#4085C6",
"aqua" : "#00A2C7",
"dark_grey" : "#999490"
}
# Define a colour object that can do neat conversions & things, by default stores as hex value
class ColourValue(str):
def __new__(self, name, value):
self.name = name
self._orig_value = value
self.value = colors.to_hex(self._orig_value, True)
return super().__new__(self, self.value)
def __str__(self) -> str:
return self.value
def __repr__(self) -> str:
return self.name + " " + self.value + " " + str(self.rgba())
def rgba(self, alpha = None) -> tuple[float, float, float, float]:
return colors.to_rgba(self.value, alpha)
def rgb(self) -> tuple[float, float, float]:
return colors.to_rgb(self._orig_value)
def hex(self) -> str:
return self.value
def hsv(self) -> np.ndarray:
return colors.rgb_to_hsv(self.rgb())
def hls(self) -> tuple[float, float, float]:
return colorsys.rgb_to_hls(*self.rgb())
def lighten(self, amount=0.5) -> tuple[float, float, float]:
hls = self.hls()
return colorsys.hls_to_rgb(hls[0], max(0, min(1, amount * hls[1])), hls[2])
def hex_lighten(self, amount=0.5) -> str:
return colors.to_hex(self.lighten(amount), True)
# Define the UQ Colours in a nicer object
class ColourList(object):
def __init__(self, colours: dict) -> None:
self.colours = {}
for key, value in colours.items():
self.colours[key] = ColourValue(key, value)
setattr(self, key, self.colours[key])
def __getitem__(self, key: str) -> str:
if key.replace(" ", "_") in self.colours.keys():
key = key.replace(" ", "_")
return self.colours[key]
def items(self):
return self.colours.items()
def __repr__(self) -> str:
return f"Colour List of {len(self.colours)} colour{'s' if len(self.colours) > 0 else ''}: " + str(list(self.colours.keys()))
UQ_COLOURS = ColourList(UQ_COLOURS_DICT)
# Load UQ Colours into MatPlotLib
# UQ colours are prefaced with 'uq:', so UQ red is 'uq:red'
# Note: Any names That have a _ also have a version with spaces so both "uq:light_purple" and "uq:light purple" work
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]]}
colors.get_named_colors_mapping().update( uq_colour_mapping )
## UQ Colour Cycler
# +-----------------------------+-----------------------------+
# | Default (Tab) | UQ |
# +-----------------------------+-----------------------------+
# | C00 | #1f77b4 -> tab:blue | #51247A -> uq:purple |
# | C01 | #ff7f0e -> tab:orange | #4085C6 -> uq:blue |
# | C02 | #2ca02c -> tab:green | #2EA836 -> uq:green |
# | C03 | #d62728 -> tab:red | #E62645 -> uq:red |
# | C04 | #9467bd -> tab:purple | #962A8B -> uq:light_purple |
# | C05 | #8c564b -> tab:brown | #999490 -> uq:dark_grey |
# | C06 | #e377c2 -> tab:pink | #EB602B -> uq:orange |
# | C07 | #7f7f7f -> tab:grey | #FBB800 -> uq:yellow |
# | C08 | #bcbd22 -> tab:olive | #00A2C7 -> uq:aqua |
# | C09 | #17becf -> tab:cyan | #BB9D65 -> uq:gold |
# | C10 | | #D7D1CC -> uq:neutral |
# +-----------------------------+-----------------------------+
# Build a colour cycler
uq_colour_cycler_factory = lambda: cycler(color=[
UQ_COLOURS["purple"], #51247A -> C00 -> uq:purple
UQ_COLOURS["blue"], #4085C6 -> C01 -> uq:blue
UQ_COLOURS["green"], #2EA836 -> C02 -> uq:green
UQ_COLOURS["red"], #E62645 -> C03 -> uq:red
UQ_COLOURS["light_purple"], #962A8B -> C04 -> uq:light_purple
UQ_COLOURS["dark_grey"], #999490 -> C05 -> uq:dark_grey
UQ_COLOURS["orange"], #EB602B -> C06 -> uq:orange
UQ_COLOURS["yellow"], #FBB800 -> C07 -> uq:yellow
UQ_COLOURS["aqua"], #00A2C7 -> C08 -> uq:aqua
UQ_COLOURS["gold"], #BB9D65 -> C09 -> uq:gold
UQ_COLOURS["neutral"] #D7D1CC -> C10 -> uq:neutral
])
# Tell MatPlotLib to use said cycler
plt.rc('axes', prop_cycle=uq_colour_cycler_factory())
## UQ Colour Gradient (Not very good :( )
uq_colour_map_grad = [
UQ_COLOURS["purple"],
UQ_COLOURS["light_purple"],
UQ_COLOURS["light_purple"],
UQ_COLOURS["blue"],
UQ_COLOURS["blue"],
UQ_COLOURS["aqua"],
UQ_COLOURS["green"],
UQ_COLOURS["green"],
UQ_COLOURS["green"],
UQ_COLOURS["yellow"],
UQ_COLOURS["yellow"]
]
#Convert to RGB values
uq_colour_map_grad = [colors.to_rgb(c) for c in uq_colour_map_grad]
#Populate the working dict
uq_colour_dict = {
"red": [],
"green": [],
"blue": [],
}
for i, c in enumerate(uq_colour_map_grad):
offset = i / (len(uq_colour_map_grad) - 1)
uq_colour_dict["red"].append( (offset, c[0], c[0]) )
uq_colour_dict["green"].append( (offset, c[1], c[1]) )
uq_colour_dict["blue"].append( (offset, c[2], c[2]) )
#Define & register the colour map itself
uq_cmap = colors.LinearSegmentedColormap('uq',segmentdata=uq_colour_dict)
matplotlib.colormaps.register(uq_cmap)
# Set the colour map - Not a very good default so not doing that
#plt.set_cmap("uq")
## Colorbar Function by Joseph Long & Mike Lampton
# Retrieved from https://joseph-long.com/writing/colorbars/ on 31/10/2021
# Minor Modifications made by Cal.W 2021
def colorbar(mappable, size="5%", pad=0.05, lsize=None, lpad=None, lax=True, **kwargs):
last_axes = plt.gca()
ax = mappable.axes
fig = ax.figure
divider = make_axes_locatable(ax)
if lax:
lsize = lsize if lsize is not None else size
lpad = lpad if lpad is not None else pad
dax = divider.append_axes("left", size=lsize, pad=lpad)
dax.set_frame_on(False)
dax.grid(False)
dax.set_yticks([])
dax.set_xticks([])
cax = divider.append_axes("right", size=size, pad=pad)
cbar = fig.colorbar(mappable, cax=cax, **kwargs)
plt.sca(last_axes)
return cbar
## Make Graph Function
def makeGraph(graphData, showPlot=True, doProgramBlock=True, figSavePath=None, hideEmptyAxis=False, closeFig=False) -> tuple[matplotlib.figure.Figure, tuple[matplotlib.axes.Axes, ...]]:
""" Generate a matplotlib graph based on a simple dictionary object
Input:
dict(graphData): The dictionary containing all the graph data - see example for more info
bool(showPlot[True]): Should the function display the plot
bool(doProgramBlock[True]): Should the function block the main python thread
str(figSavePath[None]): The path to save a copy of the figure, calls fig.savefig if not None
Returns: The the figure and axes from matplotlib.pyplot.subplots()
From 'matplotlib.pyplot.subplots():
fig : `matplotlib.figure.Figure`
ax : `matplotlib.axes.Axes` or array of Axes
*ax* can be either a single `~matplotlib.axes.Axes` object or an
array of Axes objects if more than one subplot was created.
Example:
makeGraph({
"title": "Simple Plot",
"xLabel": "x label",
"yLabel": "y label",
"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":"red"},
{"y":6, "type":"axhLine", "label":"Dashed Horizontal Line", "args":{"linestyle":"--"}},
{"type":"scatter", "x":4, "y":4, "label":"A Random Point", "colour":"purple", "args":{"zorder":2}}
]
})
"""
doKeyCopy = True
plotDim = (1,)
if "subPlots" in graphData:
if "plotDim" in graphData: plotDim = graphData["plotDim"]
else: plotDim = (1,len(graphData["subPlots"]))
else:
graphData["subPlots"] = [graphData]
doKeyCopy = False
figSize = graphData["figSize"] if "figSize" in graphData else None
fig, axes = plt.subplots(*plotDim, figsize=figSize) # Create a figure and an axes.
#if len(graphData["subPlots"]) <= 1:
# axes = [axes]
#Makes everything nice and linear
# IE ((1,2), (3,4)) = (1,2,3,4)
flatAxes = np.array(axes).flatten().tolist()
loopKeys = [
"xLabel", "yLabel", "title", "axis", "grid", "xPos", "yPos",
"xLabelPos", "yLabelPos", "xTickPos", "yTickPos", "xScale", "yScale",
"xTickMap", "yTickMap", "plots", "xLim", "yLim", "ledgLoc", "y2Label",
"ticklabel"
]
#Feel like this could be optimized
if doKeyCopy:
for key in loopKeys:
if key not in graphData: continue
if key in graphData:
for axGraphData in graphData["subPlots"]:
if key not in axGraphData:
axGraphData[key] = graphData[key]
for i, axGraphData in enumerate(graphData["subPlots"]):
ax1 = flatAxes[i]
if bool(sum([("y2" in pData) for pData in axGraphData["plots"]])):
ax2 = ax1.twinx()
else:
ax2 = None
# Duct Tape
ax = ax1
#Draw many plots as needed
# Also provide functions for drawing other types of lines
if "plots" in axGraphData:
for pData in axGraphData["plots"]:
getSafeValue = lambda key, result=None: pData[key] if key in pData else result #Only return the key-value if present in pData
getSafeValue2 = lambda key, key2, result=None: pData[key][key2] if key in pData and key2 in pData[key] else result
getSafeColour = getSafeValue("colour") or getSafeValue("color") #Frigen American Spelling
optArgs = getSafeValue("args", {}) #Allow for other args to be passed in
if "x" in pData:
xData = pData["x"]
if "y" in pData:
yData = pData["y"]
elif "y2" in pData:
yData = pData["y2"]
ax = ax2
if "type" not in pData or pData["type"] == "plot":
ax.plot(xData, yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "point":
ax.scatter(xData, yData,
marker=getSafeValue("marker"), label=getSafeValue("label"),
color=getSafeColour, zorder=getSafeValue("zorder", 2),
**optArgs )
elif pData["type"] == "hLine":
ax.hlines(yData, *xData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "vLine":
ax.vlines(xData, *yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "axvLine":
if "y" not in pData: yData = (0, 1) #Span the whole graph
ax.axvline(xData, *yData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "axhLine":
if "x" not in pData: xData = (0, 1) #Span the whole graph
ax.axhline(yData, *xData, label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "scatter":
ax.scatter(xData, yData, marker=getSafeValue("marker"), label=getSafeValue("label"), color=getSafeColour, **optArgs)
elif pData["type"] == "contour":
cs = ax.contour(getSafeValue("x"), getSafeValue("y"), pData["z"], levels=getSafeValue("levels"), colors=getSafeColour, **optArgs)
if "label" in pData: cs.collections[0].set_label(getSafeValue("label"))
elif pData["type"] == "matshow":
ms = ax.matshow(pData["matrix"], origin=getSafeValue("origin"), label=getSafeValue("label"), **optArgs)
if "colourBar" in pData:
colorbar(ms, extend=getSafeValue2("colourBar", "extend"))
elif pData["type"] == "pColourMesh":
mesh = []
if "X" in pData or "Y" in pData:
mesh = [xData, yData, pData["Z"]]
if "x" in pData or "y" in pData:
x = xData; y = yData
if type(x) in [int, float]: x = (0, x, None)
if type(y) in [int, float]: y = (0, x, None)
x = tuple(x); y = tuple(y)
if len(x) < 3: x = (x[0], x[1], None)
if len(y) < 3: y = (y[0], y[1], None)
x = np.arange(x[0], x[1], x[2])
y = np.arange(y[0], y[1], y[2])
X, Y = np.meshgrid(x, y)
mesh = [X, Y, pData["Z"]]
else:
mesh = [pData["Z"]]
cNorm = None
if "norm" in pData:
cNorm = colors.LogNorm(vmin=pData["norm"][0], vmax=pData["norm"][1])
pcMesh = ax.pcolormesh(*mesh, norm=cNorm, shading=getSafeValue("shading"), label=getSafeValue("label"), **optArgs)
#pcMesh = ax.imshow(pData["Z"], norm=cNorm, origin="lower")
if "colourBar" in pData:
cBarOptArgs = pData["colourBar"]["optArgs"] if "optArgs" in pData["colourBar"] else {}
fig.colorbar(pcMesh, ax=ax, extend=getSafeValue2("colourBar", "extend"), **cBarOptArgs)
elif pData["type"] == "imshow":
cNorm = None
if "norm" in pData:
cNorm = colors.LogNorm(vmin=pData["norm"][0], vmax=pData["norm"][1])
ims = ax.imshow(pData["data"], norm=cNorm, origin=getSafeValue("origin"), label=getSafeValue("label"), **optArgs)
if "colourBar" in pData:
cBarOptArgs = pData["colourBar"]["optArgs"] if "optArgs" in pData["colourBar"] else {}
colorbar(ims, extend=getSafeValue2("colourBar", "extend"), **cBarOptArgs)
elif pData["type"] == "text":
if not "props" in pData:
props = {
"boxstyle" : getSafeValue("boxstyle", "round"),
"facecolor": getSafeValue("facecolor", getSafeValue("facecolour", "wheat")),
"alpha" : getSafeValue("alpha", 0.5)
}
align = (
Add canny args to _info.yaml
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getSafeValue("valign", "center"),
getSafeValue("halign", "center"),
Add initial python files
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)
align = getSafeValue("align", align)
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)
elif pData["type"] == "annotate":
if type(pData["label"]) == str:
if "pos" in pData:
pData["x"] = pData["pos"][0]
pData["y"] = pData["pos"][1]
ax.annotate(
pData["label"], # this is the text
(pData["x"],pData["y"]), # these are the coordinates to position the label
textcoords=getSafeValue("offType", "offset points"), # how to position the text
xytext=getSafeValue("offset", (0,10)), # distance from text to points (x,y)
ha=getSafeValue("align", 'center') # horizontal alignment can be left, right or center
)
else:
if "pos" not in pData:
pData["pos"] = list(zip(pData['x'], pData['y']))
for i, label in enumerate(pData["label"]):
ax.annotate(
label, # this is the text
(pData["pos"][i][0], pData["pos"][i][1]), # these are the coordinates to position the label
textcoords=getSafeValue("offType", "offset points"), # how to position the text
xytext=getSafeValue("offset", (0,10)), # distance from text to points (x,y)
ha=getSafeValue("align", 'center') # horizontal alignment can be left, right or center
)
elif pData["type"] == "fill":
ax.fill_between(list(pData["x"]), list(pData["y"]), color=getSafeColour, alpha=getSafeValue("alpha", 1), linewidth=getSafeValue("linewidth", None))
#ax.fill_between(xA, yA, color="w")
#Set extra options as needed
ax = ax1
if "xLabel" in axGraphData: ax.set_xlabel(axGraphData["xLabel"]) # Add an x-label to the axes.
if "yLabel" in axGraphData: ax.set_ylabel(axGraphData["yLabel"]) # Add an y-label to the axes.
if "y2Label" in axGraphData: ax2.set_ylabel(axGraphData["y2Label"]) # Add a y2-label to the axes.
if "title" in axGraphData: ax.set_title(axGraphData["title"]) # Add an title to the axes.
if "axis" in axGraphData: ax.axis(axGraphData["axis"]) # Set the axis type
if "grid" in axGraphData: ax.grid(axGraphData["grid"]) # Add grids to the graph
if "xPos" in axGraphData: # Add the abilty to move the x axis label and ticks
ax.xaxis.set_label_position(axGraphData["xPos"])
ax.xaxis.set_ticks_position(axGraphData["xPos"])
if "yPos" in axGraphData: # Add the abilty to move the y axis label and ticks
ax.yaxis.set_label_position(axGraphData["yPos"])
ax.yaxis.set_ticks_position(axGraphData["yPos"])
if "xLabelPos" in axGraphData: ax.xaxis.set_label_position(axGraphData["xLabelPos"]) # Add the ability to move the x axis label
if "yLabelPos" in axGraphData: ax.yaxis.set_label_position(axGraphData["yLabelPos"]) # Add the ability to move the y axis label
if "xTickPos" in axGraphData: ax.xaxis.set_ticks_position(axGraphData["xTickPos"]) # Add the ability to move the x axis ticks
if "yTickPos" in axGraphData: ax.yaxis.set_ticks_position(axGraphData["yTickPos"]) # Add the ability to move the y axis ticks
if "xScale" in axGraphData: ax.set_xscale(axGraphData["xScale"]) #Add x axis scaling if needed
if "yScale" in axGraphData: ax.set_yscale(axGraphData["yScale"]) #Add y axis scaling if needed
if "xLim" in axGraphData:
xLimit = ()
if type(axGraphData["xLim"]) in [int, float]:
xLimit = (0, axGraphData["xLim"])
else:
xLimit = axGraphData["xLim"]
ax.set_xlim(xLimit)
if "yLim" in axGraphData:
yLimit = ()
if type(axGraphData["yLim"]) in [int, float]:
yLimit = (0, axGraphData["yLim"])
else:
yLimit = axGraphData["yLim"]
ax.set_ylim(yLimit)
if "xTickMap" in axGraphData: #Allow for the mapping / transformation of the xAxis Ticks
xTicks = matplotlib.ticker.FuncFormatter(lambda x, pos: '{0:g}'.format(axGraphData["xTickMap"](x)))
ax.xaxis.set_major_formatter(xTicks)
if "yTickMap" in axGraphData: #Allow for the mapping / transformation of the yAxis Ticks
yTicks = matplotlib.ticker.FuncFormatter(lambda y, pos: '{0:g}'.format(axGraphData["yTickMap"](y)))
ax.yaxis.set_major_formatter(yTicks)
if "plots" in axGraphData and bool(sum([("label" in pData) for pData in axGraphData["plots"]])):
locPoint = axGraphData["ledgLoc"] if "ledgLoc" in axGraphData else None
lines1, labels1 = ax1.get_legend_handles_labels()
if ax2:
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines1 + lines2, labels1 + labels2, loc=locPoint)
else:
ax1.legend(lines1, labels1, loc=locPoint)
if "ticklabel" in axGraphData:
style = axGraphData["ticklabel"]["style"] if "style" in axGraphData["ticklabel"] else ""
axis = axGraphData["ticklabel"]["axis"] if "axis" in axGraphData["ticklabel"] else "both"
limits = axGraphData["ticklabel"]["limits"] if "limits" in axGraphData["ticklabel"] else None
optArgs = axGraphData["ticklabel"]["optArgs"] if "optArgs" in axGraphData["ticklabel"] else {}
ax.ticklabel_format(axis=axis, style=style, scilimits=limits, **optArgs)
#Should work?
if hideEmptyAxis:
if not ax.collections and not ax.lines:
ax.set_axis_off()
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
fig.suptitle(graphData["figTitle"], fontsize=getSafeValue("figTitleFontSize"))
fig.canvas.manager.set_window_title(graphData["figTitle"].replace("\n", " "))
if "windowTitle" in graphData:
fig.canvas.manager.set_window_title(graphData["windowTitle"].replace("\n", " "))
fig.tight_layout() #Fix labels being cut off sometimes
#Very big hack
if hideEmptyAxis:
flatAxes[-1].set_axis_off()
if figSavePath:
fig.savefig(figSavePath.format(fig.canvas.manager.get_window_title()))
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)
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