# pie_chart_python.py # September - 2026 # RJM Programming # Thanks to https://www.w3schools.com/python/default.asp from datetime import datetime import os import matplotlib import sys # Set backend to Agg before importing pyplot matplotlib.use('Agg') import matplotlib.pyplot as plt import matplotlib.image as mpimg from matplotlib.sankey import Sankey import numpy as np #import plotly.express as px from PIL import Image import matplotlib.dates as mdates defarrdates = ['2019-02-26', '2019-02-26', '2018-11-10', '2018-11-10', '2018-09-18', '2018-08-10', '2018-03-17', '2018-03-16', '2018-03-06', '2018-01-18', '2017-12-10', '2017-10-07', '2017-05-10', '2017-05-02', '2017-01-17', '2016-09-09', '2016-07-03', '2016-01-10', '2015-10-29', '2015-02-16', '2014-10-26', '2014-10-18', '2014-08-26'] timelinens = [] defarrreleases = ['2.2.4', '3.0.3', '3.0.2', '3.0.1', '3.0.0', '2.2.3', '2.2.2', '2.2.1', '2.2.0', '2.1.2', '2.1.1', '2.1.0', '2.0.2', '2.0.1', '2.0.0', '1.5.3', '1.5.2', '1.5.1', '1.5.0', '1.4.3', '1.4.2', '1.4.1', '1.4.0'] timelinecs = [] defarrlens = [12.2,9.1,12.2,22.9,0.9,36.6,9.1,30.5,6.1,2.7,0.9,2.7,27.1,3.4,5.5,21.0,7.9,1.2,4.6,1.5,7.9,2.0,45.7,12.2,30.5,15.2,30.5,1.8] dinolens = [] defarrdins = ['Acrocanthosaurus (top-spined lizard)','Albertosaurus (Alberta lizard)','Allosaurus (other lizard)','Apatosaurus (deceptive lizard)','Archaeopteryx (ancient wing)','Argentinosaurus (Argentina lizard)','Baryonyx (heavy claws)','Brachiosaurus (arm lizard)','Ceratosaurus (horned lizard)','Coelophysis (hollow form)','Compsognathus (elegant jaw)','Deinonychus (terrible claw)','Diplodocus (double beam)','Dromicelomimus (emu mimic)','Gallimimus (fowl mimic)','Mamenchisaurus (Mamenchi lizard)','Megalosaurus (big lizard)','Microvenator (small hunter)','Ornithomimus (bird mimic)','Oviraptor (egg robber)','Plateosaurus (flat lizard)','Sauronithoides (narrow-clawed lizard)','Seismosaurus (tremor lizard)','Spinosaurus (spiny lizard)','Supersaurus (super lizard)','Tyrannosaurus (tyrant lizard)','Ultrasaurus (ultra lizard)','Velociraptor (swift robber)'] dinolecs = [] defbubblens = "8.61,69.55,8.36,4.12,2.76,2.43" bubblens = [] defbubblels = "'firefox','chrome','safari','edge','ie','opera'" bubblels = [] defbubblecs = "'#5A69AF','#579E65','#F9C784','#FC944A','#F24C00','#00B825'" defarrbubblecs = ['#5A69AF','#579E65','#F9C784','#FC944A','#F24C00','#00B825','#69AF5A','#9E6557','#C784F9','#944AFC','#4C00F2','#B82500','#AF5A69','#65579E','#84F9C7','#4AFC94','#00F24C','#2500B8'] bubblecs = [] kbub = len(defarrbubblecs) ibub = 0 class BubbleChart: def __init__(self, area, bubble_spacing=0): """ Setup for bubble collapse. Parameters ---------- area : array-like Area of the bubbles. bubble_spacing : float, default: 0 Minimal spacing between bubbles after collapsing. Notes ----- If "area" is sorted, the results might look weird. """ area = np.asarray(area) r = np.sqrt(area / np.pi) self.bubble_spacing = bubble_spacing self.bubbles = np.ones((len(area), 4)) self.bubbles[:, 2] = r self.bubbles[:, 3] = area self.maxstep = 2 * self.bubbles[:, 2].max() + self.bubble_spacing self.step_dist = self.maxstep / 2 # calculate initial grid layout for bubbles length = np.ceil(np.sqrt(len(self.bubbles))) grid = np.arange(length) * self.maxstep gx, gy = np.meshgrid(grid, grid) self.bubbles[:, 0] = gx.flatten()[:len(self.bubbles)] self.bubbles[:, 1] = gy.flatten()[:len(self.bubbles)] self.com = self.center_of_mass() def center_of_mass(self): return np.average( self.bubbles[:, :2], axis=0, weights=self.bubbles[:, 3] ) def center_distance(self, bubble, bubbles): return np.hypot(bubble[0] - bubbles[:, 0], bubble[1] - bubbles[:, 1]) def outline_distance(self, bubble, bubbles): center_distance = self.center_distance(bubble, bubbles) return center_distance - bubble[2] - \ bubbles[:, 2] - self.bubble_spacing def check_collisions(self, bubble, bubbles): distance = self.outline_distance(bubble, bubbles) return len(distance[distance < 0]) def collides_with(self, bubble, bubbles): distance = self.outline_distance(bubble, bubbles) return np.argmin(distance, keepdims=True) def collapse(self, n_iterations=50): """ Move bubbles to the center of mass. Parameters ---------- n_iterations : int, default: 50 Number of moves to perform. """ for _i in range(n_iterations): moves = 0 for i in range(len(self.bubbles)): rest_bub = np.delete(self.bubbles, i, 0) # try to move directly towards the center of mass # direction vector from bubble to the center of mass dir_vec = self.com - self.bubbles[i, :2] # shorten direction vector to have length of 1 dir_vec = dir_vec / np.sqrt(dir_vec.dot(dir_vec)) # calculate new bubble position new_point = self.bubbles[i, :2] + dir_vec * self.step_dist new_bubble = np.append(new_point, self.bubbles[i, 2:4]) # check whether new bubble collides with other bubbles if not self.check_collisions(new_bubble, rest_bub): self.bubbles[i, :] = new_bubble self.com = self.center_of_mass() moves += 1 else: # try to move around a bubble that you collide with # find colliding bubble for colliding in self.collides_with(new_bubble, rest_bub): # calculate direction vector dir_vec = rest_bub[colliding, :2] - self.bubbles[i, :2] dir_vec = dir_vec / np.sqrt(dir_vec.dot(dir_vec)) # calculate orthogonal vector orth = np.array([dir_vec[1], -dir_vec[0]]) # test which direction to go new_point1 = (self.bubbles[i, :2] + orth * self.step_dist) new_point2 = (self.bubbles[i, :2] - orth * self.step_dist) dist1 = self.center_distance( self.com, np.array([new_point1])) dist2 = self.center_distance( self.com, np.array([new_point2])) new_point = new_point1 if dist1 < dist2 else new_point2 new_bubble = np.append(new_point, self.bubbles[i, 2:4]) if not self.check_collisions(new_bubble, rest_bub): self.bubbles[i, :] = new_bubble self.com = self.center_of_mass() if moves / len(self.bubbles) < 0.1: self.step_dist = self.step_dist / 2 def plot(self, ax, labels, colors): """ Draw the bubble plot. Parameters ---------- ax : matplotlib.axes.Axes labels : list Labels of the bubbles. colors : list Colors of the bubbles. """ for i in range(len(self.bubbles)): circ = plt.Circle(self.bubbles[i, :2], self.bubbles[i, 2], color=colors[i]) ax.add_patch(circ) ax.text(*self.bubbles[i, :2], labels[i], horizontalalignment='center', verticalalignment='center') oktries = [-1, 1, 0, 1, 1, 1, -1, -1, 0] nok = len(oktries) orients = [] pathls = [] nums = [] lbls = [] mytitle = "" sofar = 0 izero = 0 place = '' midsuff = '' if len(sys.argv[0].split('/')) > 1: fname = sys.argv[0].split(".py")[0].split('/')[-1 + len(sys.argv[0].split(".py")[0].split('/'))]; else: fname = sys.argv[0].split(".py")[0]; fname = fname.split("\\")[-1 + len(fname.split("\\"))].replace('_','').replace('_','').replace('_','').replace('_','').replace('_','').replace('_',''); fname = fname.split('_0')[0].split('_1')[0].split('_2')[0].split('_3')[0].split('_4')[0].split('_5')[0].split('_6')[0].split('_7')[0].split('_8')[0].split('_9')[0] fname = fname.split('0')[0].split('1')[0].split('2')[0].split('3')[0].split('4')[0].split('5')[0].split('6')[0].split('7')[0].split('8')[0].split('9')[0] if len(sys.argv) > 1: place = sys.argv[-1 + len(sys.argv)] if len(sys.argv) > 2: midsuff = sys.argv[-2 + len(sys.argv)].replace(fname,'').replace('.py','') if len(nums) <= 0: while sofar < 100 and sofar >= 0: if fname == "piechartpython": print(f"Enter your percentage value regarding a pie chart where so far {sofar} has already been allocated. Can append after a comma a pie chart sector label.") elif fname == "columnchartpython": print(f"Enter your value regarding a column chart and append after a comma a column chart label on X axis.") elif fname == "sankeychartpython": print(f"Enter your value regarding a sankey chart and append after a comma a sankey chart label.") elif fname == "scatterchartpython": print(f"Enter your X axis value regarding a scatter chart and append after a comma a scatter chart value on Y axis.") elif fname == "timelinechartpython": print(f"Enter your numerical YYYYMMDD date value regarding a timeline chart and append after a comma a timeline chart label regarding that date.") elif fname == "bubblechartpython": print(f"Enter your numerical value regarding a bubble chart and append after a comma a bubble chart label regarding that number.") elif fname == "histogramchartpython": print(f"Enter your numerical value regarding building up a histogram chart and optionally append after a comma a label that goes with that numerical.") elif fname == "stairschartpython": print(f"Enter your value regarding a stairs chart.") elif fname == "pseudocolourchartpython" or fname == "pseudocolorchartpython": print(f"Enter your value regarding a psedocolour chart.") elif fname == "hexbinchartpython": print(f"Enter your X axis value regarding a hexbin chart and append after a comma a hexbin chart value on Y axis.") elif fname == "stemchartpython": print(f"Enter your X axis value regarding a stem chart and append after a comma a stem chart value on Y axis.") elif fname == "barchartpython": print(f"Enter your value regarding a bar chart and append after a comma a bar chart label on Y axis.") anum = input() if anum == "": sofar = -1 elif "," in anum: x = anum.split(",") nums.append(int(x[0])) bubblens.append(int(x[0])) timelinens.append(str(int(x[0]))) lbls.append(anum.replace(x[0] + ',', '')) bubblels.append(anum.replace(x[0] + ',', '')) timelinecs.append(anum.replace(x[0] + ',', '')) bubblecs.append(defarrbubblecs[ibub % kbub]) ibub+=1 if fname == "piechartpython": sofar += int(x[0]) else: nums.append(int(anum)) bubblens.append(int(x[0])) timelinens.append(str(int(x[0]))) timelinecs.append('') lbls.append('') bubblels.append('') bubblecs.append(defarrbubblecs[ibub % kbub]) ibub+=1 if fname == "piechartpython": sofar += int(anum) y = np.array(nums) if fname == "hexbinchartpython" or fname == "stairschartpython" or fname == "pseudocolourchartpython" or fname == "pseudocolorchartpython": plt.style.use('_mpl-gallery-nogrid') if fname == "pseudocolourchartpython" or fname == "pseudocolorchartpython": X, Y = np.meshgrid(nums, np.linspace(-3, 3, 128)) Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2) fig, ax = plt.subplots() if len(mytitle) > 0: plt.title(mytitle) if fname == "scatterchartpython": ax.scatter(nums, lbls) elif fname == "stemchartpython": ax.stem(nums, lbls) elif fname == "hexbinchartpython": ax.hexbin(nums, lbls) elif fname == "stairschartpython": ax.stairs(nums) elif fname == "pseudocolourchartpython" or fname == "pseudocolorchartpython": ax.pcolormesh(X, Y, Z, vmin=-0.5, vmax=1.0) elif fname == "columnchartpython": ax.bar(lbls, nums) elif fname == "barchartpython": ax.barh(lbls, nums) elif fname == "histogramchartpython": ax.hist(nums, bins=8, linewidth=0.5, edgecolor="white") elif len(lbls) < len(nums) and fname == "piechartpython": ax.pie(y, autopct="%1.1f%%") elif fname == "piechartpython": ax.pie(y, labels=lbls) elif fname == "bubblechartpython": # Thanks to https://matplotlib.org/stable/gallery/misc/packed_bubbles.html browser_market_share = { 'browsers': bubblels, 'market_share': bubblens, 'color': bubblecs } bubble_chart = BubbleChart(area=browser_market_share['market_share'], bubble_spacing=0.1) bubble_chart.collapse() fig, ax = plt.subplots(subplot_kw=dict(aspect="equal")) bubble_chart.plot(ax, browser_market_share['browsers'], browser_market_share['color']) ax.axis("off") ax.relim() ax.autoscale_view() ax.set_title(mytitle) elif fname == "sankeychartpython": fig = plt.figure() ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[], title=mytitle) if len(orients) < len(nums): while len(orients) < len(nums): if izero >= len(oktries): oktries.append(oktries[izero % nok]) orients.append(oktries[izero]) pathls.append(0.25) izero+=1 sankey = Sankey(ax=ax, scale=0.01, offset=0.2, head_angle=180, format='%.0f', unit='') sankey.add(flows=nums, labels=lbls, orientations=orients, pathlengths=pathls, patchlabel=mytitle) # Arguments to matplotlib.patches.PathPatch diagrams = sankey.finish() diagrams[0].texts[-1].set_color('r') diagrams[0].text.set_fontweight('bold') elif fname == "timelinechartpython": # Thanks to https://matplotlib.org/stable/gallery/lines_bars_and_markers/timeline.html dates = [datetime.strptime(d, "%Y%m%d") for d in timelinens] # Convert strs to dates. releases = [tuple(release.split('.')) for release in timelinecs] # Split by component. dates, releases = zip(*sorted(zip(dates, releases))) # Sort by increasing date. # Choose some nice levels: alternate meso releases between top and bottom, and # progressively shorten the stems for micro releases. levels = [] macro_meso_releases = sorted({release[:2] for release in releases}) for release in releases: macro_meso = release[:2] micro = int(release[2]) h = 1 + 0.8 * (5 - micro) level = h if macro_meso_releases.index(macro_meso) % 2 == 0 else -h levels.append(level) def is_feature(release): """Return whether a version (split into components) is a feature release.""" return release[-1] == '0' # The figure and the axes. fig, ax = plt.subplots(figsize=(8.8, 4), layout="constrained") ax.set(title=mytitle) # The vertical stems. ax.vlines(dates, 0, levels, color=[("tab:red", 1 if is_feature(release) else .5) for release in releases]) # The baseline. ax.axhline(0, c="black") # The markers on the baseline. meso_dates = [date for date, release in zip(dates, releases) if is_feature(release)] micro_dates = [date for date, release in zip(dates, releases) if not is_feature(release)] ax.plot(micro_dates, np.zeros_like(micro_dates), "ko", mfc="white") ax.plot(meso_dates, np.zeros_like(meso_dates), "ko", mfc="tab:red") # Annotate the lines. for date, level, release in zip(dates, levels, releases): version_str = '.'.join(release) ax.annotate(version_str, xy=(date, level), xytext=(-3, np.sign(level)*3), textcoords="offset points", verticalalignment="bottom" if level > 0 else "top", weight="bold" if is_feature(release) else "normal", bbox=dict(boxstyle='square', pad=0, lw=0, fc=(1, 1, 1, 0.7))) ax.xaxis.set(major_locator=mdates.YearLocator(), major_formatter=mdates.DateFormatter("%Y")) # Remove the y-axis and some spines. ax.yaxis.set_visible(False) ax.spines[["left", "top", "right"]].set_visible(False) ax.margins(y=0.1) fig.savefig(place + "plot" + midsuff + ".png", bbox_inches="tight") # 1. Load the image img = mpimg.imread(place + 'plot' + midsuff + '.png') # 2. Process or manipulate the image (Optional) # For example, let's look at the shape or apply changes #print(f"Image shape: {img.shape}") # 3. Create the plot without displaying it plt.imshow(img) plt.axis('off') # Hide axis lines and labels # 4. Save the result to a file instead of showing it plt.savefig(place + 'output_image' + midsuff + '.png', bbox_inches='tight', pad_inches=0) plt.close() # Open the PNG image file with Image.open(place + "plot" + midsuff + ".png") as img: # Display the image using your system's default viewer img.show() # Optional: Load the data into memory so you can safely close the file img.load() exit()