Reorganized as a Python package

.gitignore

@@ -1,12 +1,10 @@
-.venv
+.venv/
-__pycache__
+__pycache__/
-src/build
+build/
-src/packsim.c
+dist/
+*.egg-info
 
+src/packsim.c
 *.so
 
-figures
-simulations
-old_simulations
 
-*.json

build.sh

@@ -1,4 +0,0 @@
-rm -f packsim_core*
-cd src
-python3 setup.py build_ext --inplace --quiet
-mv *.so ../

docs/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/make.bat

@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.http://sphinx-doc.org/
+	exit /b 1
+)
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

docs/source/api.rst

@@ -0,0 +1,7 @@
+API
+===
+
+.. autosummary::
+   :toctree: generated
+
+   lumache

docs/source/conf.py

@@ -0,0 +1,35 @@
+# Configuration file for the Sphinx documentation builder.
+
+# -- Project information
+
+project = 'Lumache'
+copyright = '2021, Graziella'
+author = 'Graziella'
+
+release = '0.1'
+version = '0.1.0'
+
+# -- General configuration
+
+extensions = [
+    'sphinx.ext.duration',
+    'sphinx.ext.doctest',
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.intersphinx',
+]
+
+intersphinx_mapping = {
+    'python': ('https://docs.python.org/3/', None),
+    'sphinx': ('https://www.sphinx-doc.org/en/master/', None),
+}
+intersphinx_disabled_domains = ['std']
+
+templates_path = ['_templates']
+
+# -- Options for HTML output
+
+html_theme = 'sphinx_rtd_theme'
+
+# -- Options for EPUB output
+epub_show_urls = 'footnote'

docs/source/index.rst

@@ -0,0 +1,22 @@
+Welcome to Lumache's documentation!
+===================================
+
+**Lumache** (/lu'make/) is a Python library for cooks and food lovers
+that creates recipes mixing random ingredients.
+It pulls data from the `Open Food Facts database <https://world.openfoodfacts.org/>`_
+and offers a *simple* and *intuitive* API.
+
+Check out the :doc:`usage` section for further information, including
+how to :ref:`installation` the project.
+
+.. note::
+
+   This project is under active development.
+
+Contents
+--------
+
+.. toctree::
+
+   usage
+   api

docs/source/usage.rst

@@ -0,0 +1,34 @@
+Usage
+=====
+
+.. _installation:
+
+Installation
+------------
+
+To use Lumache, first install it using pip:
+
+.. code-block:: console
+
+   (.venv) $ pip install lumache
+
+Creating recipes
+----------------
+
+To retrieve a list of random ingredients,
+you can use the ``lumache.get_random_ingredients()`` function:
+
+.. autofunction:: lumache.get_random_ingredients
+
+The ``kind`` parameter should be either ``"meat"``, ``"fish"``,
+or ``"veggies"``. Otherwise, :py:func:`lumache.get_random_ingredients`
+will raise an exception.
+
+.. autoexception:: lumache.InvalidKindError
+
+For example:
+
+>>> import lumache
+>>> lumache.get_random_ingredients()
+['shells', 'gorgonzola', 'parsley']
+

packsim/__init__.py

@@ -0,0 +1 @@
+__all__ = ["simulation"]

packsim/scripts/check_width_exists.py

@@ -1,5 +1,3 @@
-#!/usr/bin/env python3
-
 from pathlib import Path
 import sys, numpy as np
 

packsim/scripts/simulate.py

@@ -5,7 +5,7 @@ from shutil import which
 from pathlib import Path
 from simulation import Diagram, Flow, Search, Shrink
 
-from packsim_core import RadialTEnergy
+from _packsim import RadialTEnergy
 
 dia_presets = {
 	"animate": [["voronoi"]],
@@ -91,7 +91,11 @@ def config_sim(args):
 
 	points = None
 	if "points" in dmn_params:
-		points = np.asarray(dmn_params["points"])
+		if type(dmn_params["points"]) is str:
+			with open(Path(dmn_params["points"]), 'rb') as f:
+				points = np.load(f)
+		else:
+			points = np.asarray(dmn_params["points"])
 
 	check_params(sim_params, ["mode", "step_size", "threshold", "save_sim"], {
 		"mode": ["flow", "search", "shrink"], "step_size": "positive", "threshold": "positive"

packsim/simulation.py

@@ -122,8 +122,8 @@ class Diagram():
 		ax.title.set_text('Energy vs. Time')
 		max_value = round(self.sim[0].energy)
 		min_value = round(self.sim[-1].energy)
-		diff = max_value-min_value
+		#diff = max_value-min_value
-		ax.set_yticks(np.arange(int(min_value-diff/5), int(max_value+diff/5), diff/25))
+		#ax.set_yticks(np.arange(int(min_value-diff/5), int(max_value+diff/5), diff/25))
 		ax.set_xlabel("Iterations")
 		ax.set_ylabel("Energy")
 		ax.grid()
@@ -494,7 +494,7 @@ class Simulation:
 		if filename is None:
 			path = gen_filepath(self, "sim", "simulations")
 		else:
-			path = f'new_simulations/{filename}.sim'
+			path = f'simulations/{filename}.sim'
 
 		all_info = []
 		for frame in self.frames:
@@ -521,8 +521,11 @@ class Simulation:
 		frames = []
 		with open(filename, 'rb') as data:
 			all_info, sim_class = pickle.load(data)
-			sim_class = {"flow": Flow, "search": Search, "shrink": Shrink}[sim_class]
+			if type(sim_class) == str:
-			sim = sim_class(*all_info[0]["params"], all_info[0]["energy"], 0,0,0,0)
+				sim_class = {"flow": Flow, "search": Search, "shrink": Shrink}[sim_class]
+
+
+			sim = sim_class(*all_info[0]["params"], "radial-t", 0,0)
 			for frame_info in all_info:
 				frames.append(sim.energy(*frame_info["params"], frame_info["arr"]))
 				#frames[-1].stats = frame_info["stats"]
@@ -575,35 +578,37 @@ class Flow(Simulation):
 			print(f'Find - N = {self.n}, R = {self.r}, {self.w} X {self.h}', flush=True)
 		i, grad_norm = 0, float('inf')
 
-		trial = 2
+		#trial = 2
-		while grad_norm > self.thres:	# Get to threshold.
+		j = 1
-			# Iterate and generate next frame using RK-3
+		while i*self.step_size <= 500:
+		#while grad_norm > self.thres:	# Get to threshold.
+			# Iterate and generate next frame using RK-2
 			start = timer()
-			change, grad = self.frames[i].iterate(self.step_size)
+			change, grad = self.frames[-1].iterate(self.step_size)
 			new_frame = self.energy(self.n, self.w, self.h, self.r,
-							self.frames[i].add_sites(change))
+							self.frames[-1].add_sites(change))
-			grad_norm = np.sum(np.absolute(grad))/self.n
+			grad_norm = np.linalg.norm(grad)
 			end = timer()
 
-			if new_frame.energy < self.frames[i].energy:	# If energy decreases.
+			# if new_frame.energy < self.frames[i].energy:	# If energy decreases.
-				if trial < 20:	# Try increasing step size for 10 times.
+			# 	if trial < 20:	# Try increasing step size for 10 times.
-					factor = 1 + .1**trial
+			# 		factor = 1 + .1**trial
 
-					test_frame = self.energy(self.n, self.w, self.h, self.r,
+			# 		test_frame = self.energy(self.n, self.w, self.h, self.r,
-											self.frames[i].add_sites(change*factor))
+			# 								self.frames[i].add_sites(change*factor))
-					# If increased step has less energy than original step.
+			# 		# If increased step has less energy than original step.
-					if test_frame.energy < new_frame.energy:
+			# 		if test_frame.energy < new_frame.energy:
-						self.step_size *= factor
+			# 			self.step_size *= factor
-						trial = max(2, trial-1)
+			# 			trial = max(2, trial-1)
-						new_frame = test_frame
+			# 			new_frame = test_frame
-					else:	# Otherwise, increases trials, and use original.
+			# 		else:	# Otherwise, increases trials, and use original.
-						trial += 1
+			# 			trial += 1
-			else:	# Step size too large, decrease and reset trial counter.
+			# else:	# Step size too large, decrease and reset trial counter.
-				trial = 2
+			# 	trial = 2
-				shrink_factor = 1.5
+			# 	shrink_factor = 1.5
-				new_frame = self.energy(self.n, self.w, self.h, self.r,
+			# 	new_frame = self.energy(self.n, self.w, self.h, self.r,
-								self.frames[i].add_sites(change/shrink_factor))
+			# 					self.frames[i].add_sites(change/shrink_factor))
-				self.step_size /= shrink_factor
+			# 	self.step_size /= shrink_factor
 
 			#self.step_size *= abs(.01/np.linalg.norm(error))**(1/3)
 			#self.step_size = max(10e-4, self.step_size)
@@ -611,10 +616,17 @@ class Flow(Simulation):
 
 			i += 1
 			if(log and i % log_steps == 0): 
-				print(f'Iteration: {i:05} | Energy: {self.frames[i].energy: .5f}' + \
+				print(f'Iteration: {i:05} | Energy: {self.frames[-1].energy: .5f}' + \
 				 	  f' | Gradient: {grad_norm:.8f} | Step: {self.step_size: .5f} | ' + \
 				 	  f'Time: {end-start: .3f}', flush=True)
 
+			if i % 5000 == 0:
+				new_frames = [self.frames[-1]]
+				self.frames = self.frames[:-1]
+				self.save(f"N200-{self.step_size}-part{j}")
+				j += 1
+				self.frames = new_frames
+
 
 class Search(Simulation):
 	"""
@@ -677,8 +689,6 @@ class Search(Simulation):
 				if zero_eigs != 2:
 					print("WARNING, 0 EIGS NOT 2", zero_eigs)
 
-				if i == self.iter-1:
-					break
 
 				if len(ns) <= 2:
 					new_sites = dim * np.random.random_sample((self.n, 2))
@@ -687,7 +697,10 @@ class Search(Simulation):
 					new_sites = self.frames[i].add_sites(self.kernel_step*vec.reshape((self.n, 2)))
 			
 				new_sites += (center - new_sites[fixed]) % 	dim # Offset
-			self.frames.append(None)
+
+			if i < self.iter-1:
+				self.frames.append(None)
+
 
 
 class Shrink(Simulation):

pyproject.toml

@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools >= 42", "wheel", "Cython", "numpy"]
+build-backend = "setuptools.build_meta"

setup.cfg

@@ -0,0 +1,36 @@
+[metadata]
+name = packsim-ksjdragon
+version = 0.1
+author = Kenneth Jao
+author_email = ksjdragon@gmail.com
+description = PackSim is a Python package that handles the simulations for Voronoi cells undergoing a gradient flow.
+long_description = file: README.md
+long_description_content_type = text/markdown
+url = https://github.com/ksjdragon/packsim
+project_urls =
+	Bug Tracker = https://github.com/ksjdragon/packsim/issues
+classifiers =
+	Programming Language :: Python :: 3.8
+	Programming Language :: Python :: 3.9
+	Programming Language :: Python :: 3.10
+	License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
+	Operating System :: OS Independent
+
+[options]
+zip_safe = False
+package_dir =
+	= packsim
+packages = find:
+python_requires = >= 3.8
+install_requires =
+	numpy == 1.21.2
+	scipy == 1.7.1
+	matplotlib == 3.4.3
+
+[options.packages.find]
+where = packsim
+
+[options.entry_points]
+console_scripts =
+	simulate = packsim.scripts.simulate:main
+	shrink_energy_comparison = packsim.scripts.shrink_energy_comparison:main

setup.py

@@ -2,19 +2,17 @@ from setuptools import Extension, setup
 from Cython.Build import cythonize
 import numpy
 
-MODULE_NAME = "packsim_core"
-
 ext_modules = [
     Extension(
-        MODULE_NAME,
+        "_packsim",
-        [f'{MODULE_NAME}.pyx'],
+        ["src/_packsim.pyx"],
         extra_compile_args=['-fopenmp'],
         extra_link_args=['-fopenmp']
     )
 ]
 
 setup(
-    name=MODULE_NAME,
+    name="packsim",
     ext_modules = cythonize(ext_modules, compiler_directives={
         'language_level': 3, 'boundscheck' : False, 'wraparound': False, 'cdivision' : True
     }),

src/core.pyx

@@ -6,7 +6,7 @@ from cpython cimport array
 from libc.stdlib cimport malloc, realloc, calloc, free
 from libc.math cimport isnan, NAN, pi as PI, M_PI_2 as PI_2, \
 				sqrt, log, sin, cos, tan, acos, fabs
-from packsim_core cimport INT_T, FLOAT_T, Init, IArray, FArray, BitSet, Vector2D, Matrix2x2, \
+from _packsim cimport INT_T, FLOAT_T, Init, IArray, FArray, BitSet, Vector2D, Matrix2x2, \
 					VectorSelfOps, VectorCopyOps, MatrixSelfOps, MatrixCopyOps, \
 					SiteCacheMap, EdgeCacheMap, VoronoiInfo, Site, HalfEdge
 

src/voronoi_dcel.pyx

@@ -1,4 +1,4 @@
-from packsim_core cimport SiteCacheMap, EdgeCacheMap, VoronoiInfo, Site, HalfEdge
+from _packsim cimport SiteCacheMap, EdgeCacheMap, VoronoiInfo, Site, HalfEdge
 
 #### Constants ####
 
@@ -405,12 +405,6 @@ cdef class VoronoiContainer:
 		self.common_cache()
 		self.precompute()
 		self.calc_grad()
-		self.get_statistics()
-
-		# #print(np.asarray(self.site_cache[0]))
-		# print(np.asarray(self.edges[:6]))
-		# #print(np.asarray(self.edge_cache[:6]))
-		# print(self.gradient)
 
 
 	cdef void calculate_voronoi(VoronoiContainer self, 
@@ -622,10 +616,7 @@ cdef class VoronoiContainer:
 		cache = self.site_cache[:self.n, :]
 
 		self.stats["site_areas"] = np.asarray(cache[:, SITE_CACHE_MAP.iarea])
-		#edge_count = self.sites[:, 2]np.empty((self.n,))
+		self.stats["site_edge_count"] = np.asarray(self.sites[:self.n, 2])
-		# for i in range(self.n):
-		# 	edge_count[i] = len(self.vor_data.regions[self.vor_data.point_region[i]])
-		self.stats["site_edge_count"] = self.sites[:self.n, 2]
 
 		self.stats["site_isos"] = np.asarray(cache[:, SITE_CACHE_MAP.iisoparam])
 		self.stats["site_energies"] = np.asarray(cache[:, SITE_CACHE_MAP.ienergy])
@@ -661,21 +652,29 @@ cdef class VoronoiContainer:
 	
 	def iterate(self, FLOAT_T step):
 		k1 = self.gradient
-
 		k2 = self.__class__(self.n, self.w, self.h, self.r,
-				self.add_sites(step*k1/2)
+				self.add_sites(step*k1)
 		).gradient
 
-		lower = step*(-k1+ 2*k2)
+		return (step/2)*(k1+k2), k1
-		k3 = self.__class__(self.n, self.w, self.h, self.r, 
+		# k1 = self.gradient
-				self.add_sites(lower)
+
-		).gradient
+		# k2 = self.__class__(self.n, self.w, self.h, self.r,
+		# 		self.add_sites(step*k1/2)
+		# ).gradient
+
+		# lower = step*(-k1+ 2*k2)
+		# k3 = self.__class__(self.n, self.w, self.h, self.r,
+		# 		self.add_sites(lower)
+		# ).gradient
+
+		# higher = (step/6)*(k1+2*k2+k3)
+
 
-		higher = (step/6)*(k1+2*k2+k3)
 		#new_sites = self.add_sites(higher)
 		#error = higher - lower
 		
-		return higher, k1
+		#return higher, k1
 
 	def hessian(self, d: float) -> np.ndarray:
 		"""

test_sim.json

@@ -1,19 +0,0 @@
-{
-  "domain": {
-    "n_objects": 100,
-    "width": 10.0,
-    "height": 10.0,
-    "natural_radius": 4.0,
-    "energy": "radial-t"
-  },
-  "simulation": {
-    "mode": "flow",
-    "step_size": 0.05,
-    "threshold": 0.00001,
-    "save_sim": true
-  },
-  "diagram": {
-    "filetype": "mp4",
-    "figures": "energy"
-  }
-}