aegis_sim.recording.simpleprogressrecorder

 1import time
 2import pathlib
 3
 4from .recorder import Recorder
 5from aegis_sim import variables
 6
 7from aegis_sim.parameterization import parametermanager
 8
 9class SimpleProgressRecorder(Recorder):
10    def __init__(self, odir: pathlib.Path):
11        self.odir = odir
12        self.init_odir()
13        self.time_start = time.time()
14
15        self.progress_path = self.odir / "simpleprogress.log"
16        self.write_one(0)
17        # self.init_headers()
18
19    # def init_headers(self):
20    #     content = ("step", "ETA", "t1M", "runtime", "steps/min", "popsize")
21    #     with open(self.odir / "progress.log", "ab") as f:
22    #         np.savetxt(f, [content], fmt="%-10s", delimiter="| ")
23
24    def write(self):
25        """Record some information about the time and speed of simulation."""
26
27        last_updated = self.check_when_last_updated(file_path=self.progress_path)
28        if last_updated > 1:
29            step = variables.steps
30            self.write_one(step)
31
32    def write_one(self, step):
33        message = f"{step}/{parametermanager.parameters.STEPS_PER_SIMULATION}"
34        with open(self.progress_path, "w") as file_:
35            file_.write(message)
36
37    @staticmethod
38    def check_when_last_updated(file_path: pathlib.Path):
39        last_modified_time = file_path.stat().st_mtime
40        time_since_modification = time.time() - last_modified_time
41        seconds = time_since_modification
42        return seconds
43
44
45        # # Get time estimations
46        # time_diff = time.time() - self.time_start
47
48        # seconds_per_100 = time_diff / step * 100
49        # eta = (parametermanager.parameters.STEPS_PER_SIMULATION - step) / 100 * seconds_per_100
50
51        # steps_per_min = int(step / (time_diff / 60))
52
53        # runtime = self.get_dhm(time_diff)
54        # time_per_1M = self.get_dhm(time_diff / step * 1000000)
55        # eta = self.get_dhm(eta)
56
57        # # Save time estimations
58        # content = (step, eta, time_per_1M, runtime, steps_per_min, popsize)
59        # self.write_to_progress_log(content)
60
61    # def write_to_progress_log(self, content):
62    #     """
63
64    #     # OUTPUT SPECIFICATION
65    #     path: /progress.log
66    #     filetype: txt
67    #     category: log
68    #     description: A table documenting the estimated time of simulation completion (ETA), time to run one million steps (t1M), time since simulation start (runtime), number of simulated steps per minute (stg/min) and population size (popsize).
69    #     trait granularity:
70    #  time granularity:
71    #  frequency parameter: A str table with custom separator (` | `).
72    #     """
73    #     with open(self.odir / "progress.log", "ab") as f:
74    #         np.savetxt(f, [content], fmt="%-10s", delimiter="| ")
75
76    # @staticmethod
77    # def get_dhm(timediff):
78    #     """Format time in a human-readable format."""
79    #     d = int(timediff / 86400)
80    #     timediff %= 86400
81    #     h = int(timediff / 3600)
82    #     timediff %= 3600
83    #     m = int(timediff / 60)
84    #     return f"{d}`{h:02}:{m:02}"