Changed loading function, and only create folder with save.

src/squish/__init__.py

@@ -1,2 +1,3 @@
-from .common import DomainParams, Energy, Simulation
+from .common import DomainParams, Energy
+from .simulation import Simulation
 from .diagram import Diagram

src/squish/common.py

@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import List, Union, Optional, Iterator
+from typing import List, Union, Optional, Iterator, Generator
 import pickle, numpy as np
 from pathlib import Path
 from _squish import AreaEnergy, RadialALEnergy, RadialTEnergy
@@ -101,142 +101,4 @@ class Energy:
 
 	@property
 	def title_str(self) -> str:
-		return self.mode.title_str
+		return self.mode.title_str
-
-
-class Simulation:
-	"""Generic container for simulations.
-
-	Attributes:
-		domain (DomainParams): Domain Parameters for this simulation.
-		energy (Energy): energy being used for caluclations.
-		path (Path): Path to location of where to store simulation files.
-		frames (List[VoronoiContainer]): Stores frames of the simulation.
-
-	"""
-
-	__slots__ = ['domain', 'energy', 'path', 'frames']
-
-	def __init__(self, domain: DomainParams, energy: Energy, name: Optional[str] = None) -> None:
-		self.domain, self.energy = domain, energy
-		self.frames = []
-
-		if name is None:
-			self.path = generate_filepath(self, OUTPUT_DIR)
-		else:
-			self.path = OUTPUT_DIR / name
-
-		self.path.mkdir()
-
-
-	def __iter__(self) -> Iterator:
-		return iter(self.frames)
-
-	def __getitem__(self, key: int) -> Energy:
-		return self.frames[key]
-
-
-	def __len__(self) -> int:
-		return len(self.frames)
-
-
-	def add_frame(self, points: Optional[numpy.ndarray]) -> None:
-		if points is None:
-			points = np.random.random_sample((self.domain.n, 2)) * self.domain.dim
-		else:
-			if points.shape[1] != 2 or len(points.shape) > 2:
-				raise ValueError("Sites should be 2 dimensional!")
-
-			if points.shape[0] != self.domain.n:
-				raise ValueError("Number of sites provided do not match the array!")
-
-		self.frames.append(self.energy.mode(*self.domain, points % self.domain.dim))
-
-
-	def get_distinct(self) -> List[int]:
-		"""Gets the distinct configurations based on the average radii of the sites.
-		and returns the number of configurations for each distinct configuration.
-		"""
-
-		distinct_avg_radii, distinct_count, new_frames = [], [], []
-
-		for frame in self.frames:
-			avg_radii = np.sort(frame.stats["avg_radius"])
-			is_in = False
-			for i, dist_radii in enumerate(distinct_avg_radii):
-				if np.allclose(avg_radii, dist_radii, atol=1e-5):
-					is_in = True
-					distinct_count[i] += 1
-					break
-
-			if not is_in:
-				distinct_avg_radii.append(avg_radii)
-				new_frames.append(frame)
-
-		self.frames = new_frames
-		return distinct_count
-
-
-	def save(self, info: Dict) -> None:
-		path = self.path / 'data.squish'
-
-		with open(path, 'wb') as out:
-			pickle.dump(info, out, pickle.HIGHEST_PROTOCOL)
-
-
-	def frame_data(self, index: int) -> None:
-		f = self[index]
-		info = {
-			"arr": f.site_arr,
-			"domain": (f.n, f.h, f.w, f.r),
-			"energy": f.attr_str,
-			"stats": f.stats
-		}
-		return info
-
-		# all_info = []
-		# for frame in self.frames:
-		# 	frame_info = dict()
-		# 	frame_info["arr"] = frame.site_arr
-		# 	frame_info["energy"] = {AreaEnergy: "area", RadialALEnergy: "radial-al",
-		# 							RadialTEnergy: "radial-t"}[self.energy]
-		# 	frame_info["params"] = (frame.n, frame.w, frame.h, frame.r)
-		# 	all_info.append(frame_info)
-
-		# class_name = {Flow: "flow", Search: "search", Shrink: "shrink"}[self.__class__]
-
-		# with open(path, 'wb') as output:
-		# 	pickle.dump((all_info, class_name), output, pickle.HIGHEST_PROTOCOL)
-		# print("Wrote to " + path, flush=True)
-
-
-	@staticmethod
-	def load(path: str) -> Simulation:
-		with open(path, 'rb') as infile:
-			while True:
-				try:
-					yield pickle.load(infile)
-				except EOFError:
-					break
-
-
-	@staticmethod
-	def load_old(filename: str) -> Simulation:
-		"""
-		Loads the points at every point into a file.
-		:param filename: [str] name of the file
-		"""
-		frames = []
-		with open(filename, 'rb') as data:
-			all_info, sim_class = pickle.load(data)
-			if type(sim_class) == str:
-				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"]
-
-			sim.frames = frames
-		return sim

src/squish/simulation.py

@@ -5,7 +5,154 @@ import pickle, numpy as np
 from scipy.linalg import null_space
 from timeit import default_timer as timer
 
-from .common import DomainParams, Energy, Simulation
+from .common import DomainParams, Energy, generate_filepath, OUTPUT_DIR
+
+
+class Simulation:
+	"""Generic container for simulations.
+
+	Attributes:
+		domain (DomainParams): Domain Parameters for this simulation.
+		energy (Energy): energy being used for caluclations.
+		path (Path): Path to location of where to store simulation files.
+		frames (List[VoronoiContainer]): Stores frames of the simulation.
+
+	"""
+
+	__slots__ = ['domain', 'energy', 'path', 'frames']
+
+	def __init__(self, domain: DomainParams, energy: Energy, name: Optional[str] = None) -> None:
+		self.domain, self.energy = domain, energy
+		self.frames = []
+
+		if name is None:
+			self.path = generate_filepath(self, OUTPUT_DIR)
+		else:
+			self.path = OUTPUT_DIR / name
+
+
+	def __iter__(self) -> Iterator:
+		return iter(self.frames)
+
+	def __getitem__(self, key: int) -> Energy:
+		return self.frames[key]
+
+
+	def __len__(self) -> int:
+		return len(self.frames)
+
+
+	def add_frame(self, points: Optional[numpy.ndarray]) -> None:
+		if points is None:
+			points = np.random.random_sample((self.domain.n, 2)) * self.domain.dim
+		else:
+			if points.shape[1] != 2 or len(points.shape) > 2:
+				raise ValueError("Sites should be 2 dimensional!")
+
+			if points.shape[0] != self.domain.n:
+				raise ValueError("Number of sites provided do not match the array!")
+
+		self.frames.append(self.energy.mode(*self.domain, points % self.domain.dim))
+
+
+	def get_distinct(self) -> List[int]:
+		"""Gets the distinct configurations based on the average radii of the sites.
+		and returns the number of configurations for each distinct configuration.
+		"""
+
+		distinct_avg_radii, distinct_count, new_frames = [], [], []
+
+		for frame in self.frames:
+			avg_radii = np.sort(frame.stats["avg_radius"])
+			is_in = False
+			for i, dist_radii in enumerate(distinct_avg_radii):
+				if np.allclose(avg_radii, dist_radii, atol=1e-5):
+					is_in = True
+					distinct_count[i] += 1
+					break
+
+			if not is_in:
+				distinct_avg_radii.append(avg_radii)
+				new_frames.append(frame)
+
+		self.frames = new_frames
+		return distinct_count
+
+
+	def save(self, info: Dict) -> None:
+		self.path.mkdir(exist_ok=True)
+		path = self.path / 'data.squish'
+
+		with open(path, 'ab') as out:
+			pickle.dump(info, out, pickle.HIGHEST_PROTOCOL)
+
+
+	def frame_data(self, index: int) -> None:
+		f = self[index]
+		info = {
+			"arr": f.site_arr,
+			"domain": (f.n, f.h, f.w, f.r),
+			"energy": f.energy,
+			"stats": f.stats
+		}
+		return info
+
+		# all_info = []
+		# for frame in self.frames:
+		# 	frame_info = dict()
+		# 	frame_info["arr"] = frame.site_arr
+		# 	frame_info["energy"] = {AreaEnergy: "area", RadialALEnergy: "radial-al",
+		# 							RadialTEnergy: "radial-t"}[self.energy]
+		# 	frame_info["params"] = (frame.n, frame.w, frame.h, frame.r)
+		# 	all_info.append(frame_info)
+
+		# class_name = {Flow: "flow", Search: "search", Shrink: "shrink"}[self.__class__]
+
+		# with open(path, 'wb') as output:
+		# 	pickle.dump((all_info, class_name), output, pickle.HIGHEST_PROTOCOL)
+		# print("Wrote to " + path, flush=True)
+
+
+	@staticmethod
+	def load(path: str) -> Tuple[Simulation, Generator]:
+		def frames() -> Dict:
+			with open(path, 'rb') as infile:
+				while True:
+					try:
+						yield pickle.load(infile)
+					except EOFError:
+						break
+
+		with open(path, 'rb') as infile:
+			sim_info = pickle.load(infile)
+
+			domain = DomainParams(*sim_info["domain"])
+			energy = Energy(sim_info["energy"])
+			sim = STR_TO_SIM[sim_info["mode"]](domain, energy, *list(sim_info.values())[3:])
+
+			return sim, frames()
+
+
+	@staticmethod
+	def load_old(filename: str) -> Simulation:
+		"""
+		Loads the points at every point into a file.
+		:param filename: [str] name of the file
+		"""
+		frames = []
+		with open(filename, 'rb') as data:
+			all_info, sim_class = pickle.load(data)
+			if type(sim_class) == str:
+				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"]
+
+			sim.frames = frames
+		return sim
 
 
 class Flow(Simulation):
@@ -36,6 +183,8 @@ class Flow(Simulation):
 	def initial_data(self) -> Dict:
 		info = {
 			"mode": self.attr_str,
+			"domain": (self.domain.n, self.domain.w, self.domain.h, self.domain.r),
+			"energy": self.energy.attr_str,
 			"step_size": self.step_size,
 			"thres": self.thres,
 			"accel": self.accel
@@ -126,6 +275,8 @@ class Search(Simulation):
 	def initial_data(self) -> Dict:
 		info = {
 			"mode": self.attr_str,
+			"domain": (self.domain.n, self.domain.w, self.domain.h, self.domain.r),
+			"energy": self.energy.attr_str,
 			"step_size": self.step_size,
 			"thres": self.thres,
 			"accel": self.accel,
@@ -205,6 +356,8 @@ class Shrink(Simulation):
 	def initial_data(self) -> Dict:
 		info = {
 			"mode": self.attr_str,
+			"domain": (self.domain.n, self.domain.w, self.domain.h, self.domain.r),
+			"energy": self.energy.attr_str,
 			"step_size": self.step_size,
 			"thres": self.thres,
 			"accel": self.accel,
@@ -241,3 +394,9 @@ class Shrink(Simulation):
 
 			width -= self.delta
 			i += 1
+
+STR_TO_SIM = {
+	"flow": Flow,
+	"search": Search,
+	"shrink": Shrink
+}

src/squish/squish.py

@@ -45,9 +45,6 @@ def check_params(container: Dict, needed: List[str], valid: Dict) -> None:
 
 def main():
 	# Loading configuration and settings.
-	Path('simulations').mkdir(exist_ok=True)
-	Path('figures').mkdir(exist_ok=True)
-
 	parser = argparse.ArgumentParser("PackSim")
 	parser.add_argument('sim_conf', metavar='/path/to/config.json',
 						help="configuration file for a simulation")