Final hackathon files

.gitignore

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+*./assets
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

LICENSE

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+MIT License
+
+Copyright (c) 2023 Philippe Cochin
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Plotter.py

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+import numpy as np
+import matplotlib.pylab as plt
+
+import matplotlib.cm as cm
+import matplotlib.colors as colors
+
+import matplotlib.colorbar as colorbar
+
+from scipy.stats import norm
+
+from matplotlib import patheffects
+#plt.rcParams['path.effects'] = [patheffects.withStroke(linewidth=4, foreground='b')]
+
+from PIL import Image, ImageFilter
+
+
+def Entropy(probabilities):
+    if type(probabilities) is list:
+        probabilities = np.array(probabilities)
+    s = -probabilities*np.log(probabilities)
+    s[np.isnan(s)] = 0
+    return np.sum(s)
+
+
+
+def PolarPlotmaker(probabilities, labels=None, figsize = (5,5), dpi = 120, background = None, debug = False, tick_color = 'chartreuse', linelength = 10, pad = 8, save_name = None, show = False, has_error = True, offwhite_cutoff=170, labelsize = 8):
+
+    labels_type = 'string'
+
+    if has_error:
+        if probabilities[-1]==0:
+            probabilities = probabilities[:-1]
+            has_error = False
+
+    n_qubits = len(probabilities)
+
+    if has_error:
+        n_qubits+=-1
+
+    n_labels = n_qubits
+
+    if has_error:
+        n_labels+=1
+
+
+    angles = np.linspace(0,2*np.pi-2*np.pi/(n_labels-1),n_labels)
+    angles = np.concatenate((angles,[angles[0]]))
+    probabilities = np.concatenate((probabilities,[probabilities[0]]))
+
+    if debug:
+        print(f'Angles (length {len(angles)}): {np.round(angles,4)}')
+        print(f'Probabilities (length {len(probabilities)}): {np.round(probabilities,4)}')
+        print(f'Has Errors: {has_error}')
+
+
+
+    if labels is not None:
+        if len(labels)>=n_qubits:
+            labels = labels[:n_qubits]
+        if len(labels)!=n_qubits:
+            labels = np.arange(0,n_qubits)
+            labels = labels.tolist()
+
+            if has_error:
+                labels += ["Can't Remember"]
+            labels_type = 'int'
+            labels_modified =  labels
+
+
+    if labels is None:
+        labels = np.arange(0,n_qubits)
+        labels = labels.tolist()
+        if has_error:
+            labels += ["Can't Remember"]
+        labels_type = 'int'
+        labels_modified =  labels
+
+
+    if labels_type == 'string':
+        if has_error:
+            labels += ["Can't Remember"]
+        labels_modified = []
+        for label in labels:
+            new_label = ""
+            lines = 1
+            first_step = True
+            for i, letter in enumerate(label):
+                if lines == 3:
+                    new_label = new_label[:-4]
+                    new_label += '...'
+                    break
+                if i % linelength == 0 and not first_step:
+                    lines+=1
+                    if new_label[-1] != ' ':
+                        new_label +='-'
+                    new_label += '\n'
+                new_label += letter
+                first_step = False
+            if new_label[:2] == "A " or new_label[:2] == "a ":
+                new_label=new_label[2:]
+            labels_modified.append(new_label)
+
+
+    plt.xkcd(scale=2, length=0)
+    plt.figure(figsize=figsize, dpi = dpi)
+
+    ax = plt.subplot(111, polar=True)
+
+    z = angles
+    normalize = colors.Normalize(vmin=z.min(), vmax=z.max())
+
+    cmap = colors.LinearSegmentedColormap.from_list("", ["aqua","mediumslateblue","orchid",'magenta', 'mediumorchid', 'mediumpurple','dodgerblue']*2)
+
+    ax.plot(angles, probabilities, linewidth=1, linestyle='solid')
+
+    # Fill area
+    #ax.fill(angles, values, 'b', alpha=0.1)
+
+    ax.set_yticklabels([])
+    ax.get_yaxis().set_ticks([])
+
+    for i in range(len(probabilities)-1):
+        ax.fill_between([angles[i], angles[i+1]], [probabilities[i], probabilities[i+1]], color=cmap(normalize(z[i])))
+
+    ax.set_xticks(angles[:-1])
+
+    color_list = [tick_color]*(n_labels)
+    if has_error:
+        color_list[-1] = 'red'
+    for xtick, color in zip(ax.get_xticklabels(), color_list):
+        xtick.set_color(color)
+
+    ax.set_xticklabels(labels_modified)
+
+    #ax.set_xticklabels(labels_modified, color = tick_color)
+
+    ax.xaxis.set_tick_params(grid_linewidth = 1, grid_color = tick_color, pad = pad, labelsize = 8)
+
+    ax.set_axisbelow('True')
+
+    ax.spines['polar'].set_color(tick_color)
+
+    ax.set_ylim(0,max(probabilities))
+
+    #ax.set_facecolor(background)
+
+
+    ax.set_theta_zero_location("N")
+    ax.set_theta_direction(-1)
+    # Show the graph
+
+    error_entropy = 'None!'
+    if has_error:
+        probabilities_for_entropy = probabilities[:-2]
+        error_prob = probabilities[-2]
+        error_entropy = np.round(Entropy([error_prob]),2)
+    if not has_error:
+        probabilities_for_entropy = probabilities[:-1]
+    plt.figtext(0.5,-0.1,f'Entropy of what you remember: {round(Entropy(probabilities_for_entropy),2)}\nResidual: {error_entropy}', color=tick_color, horizontalalignment='center')
+
+    plt.tight_layout()
+
+    if type(save_name)==str:
+        plt.savefig(save_name+'.png', transparent = True,bbox_inches = "tight")
+
+    if show:
+        plt.show()
+
+    if type(save_name)==str:
+        img = Image.open(save_name+'.png')
+        img = img.convert("RGBA")
+
+        pixdata = img.load()
+
+        width, height = img.size
+        for y in range(height):
+            for x in range(width):
+                dat =  pixdata[x, y]
+                if dat[-1]!=0:
+                    dat = np.array(dat[:-1])
+                    dat_tf = dat>offwhite_cutoff
+                    if  dat_tf[0] and dat_tf[1] and dat_tf[2]:
+                        pixdata[x, y] = (0,0,0,0)
+
+        img.save(save_name+'.png', "PNG")