aegis_sim.recording.envdriftmaprecorder 

 1import pathlib
 2import numpy as np
 3
 4from .recorder import Recorder
 5from aegis_sim import submodels
 6
 7
 8class Envdriftmaprecorder(Recorder):
 9    """
10
11    Records once.
12    """
13
14    def __init__(self, odir: pathlib.Path):
15        self.odir = odir
16        self.init_odir()
17
18    def write(self, step):
19        """
20
21        # OUTPUT SPECIFICATION
22        path: /envdriftmap.csv
23        filetype: csv
24        category: genotype
25        description: XOR map for genome (0 = original phenotypic effect, 1 = opposite phenotypic effect). Recorded every ENVDRIFT_RATE steps.
26        trait granularity: N/A
27        time granularity: N/A
28        frequency parameter: ENVDRIFT_RATE
29        header: None
30        structure: row: record, column: genome position, value: 0 or 1
31        """
32        envdrift = submodels.architect.envdrift
33
34        will_evolve = envdrift.will_evolve(step)
35
36        if will_evolve:
37            map_ = envdrift.map.flatten()
38            with open(self.odir / "envdriftmap.csv", "ab") as f:
39                array = np.array(map_)
40                np.savetxt(f, [array], delimiter=",", fmt="%i")
class Envdriftmaprecorder(aegis_sim.recording.recorder.Recorder): 
 9class Envdriftmaprecorder(Recorder):
10    """
11
12    Records once.
13    """
14
15    def __init__(self, odir: pathlib.Path):
16        self.odir = odir
17        self.init_odir()
18
19    def write(self, step):
20        """
21
22        # OUTPUT SPECIFICATION
23        path: /envdriftmap.csv
24        filetype: csv
25        category: genotype
26        description: XOR map for genome (0 = original phenotypic effect, 1 = opposite phenotypic effect). Recorded every ENVDRIFT_RATE steps.
27        trait granularity: N/A
28        time granularity: N/A
29        frequency parameter: ENVDRIFT_RATE
30        header: None
31        structure: row: record, column: genome position, value: 0 or 1
32        """
33        envdrift = submodels.architect.envdrift
34
35        will_evolve = envdrift.will_evolve(step)
36
37        if will_evolve:
38            map_ = envdrift.map.flatten()
39            with open(self.odir / "envdriftmap.csv", "ab") as f:
40                array = np.array(map_)
41                np.savetxt(f, [array], delimiter=",", fmt="%i")

Records once.

Envdriftmaprecorder(odir: pathlib.Path) 
15    def __init__(self, odir: pathlib.Path):
16        self.odir = odir
17        self.init_odir()
odir
def write(self, step): 
19    def write(self, step):
20        """
21
22        # OUTPUT SPECIFICATION
23        path: /envdriftmap.csv
24        filetype: csv
25        category: genotype
26        description: XOR map for genome (0 = original phenotypic effect, 1 = opposite phenotypic effect). Recorded every ENVDRIFT_RATE steps.
27        trait granularity: N/A
28        time granularity: N/A
29        frequency parameter: ENVDRIFT_RATE
30        header: None
31        structure: row: record, column: genome position, value: 0 or 1
32        """
33        envdrift = submodels.architect.envdrift
34
35        will_evolve = envdrift.will_evolve(step)
36
37        if will_evolve:
38            map_ = envdrift.map.flatten()
39            with open(self.odir / "envdriftmap.csv", "ab") as f:
40                array = np.array(map_)
41                np.savetxt(f, [array], delimiter=",", fmt="%i")

OUTPUT SPECIFICATION

path: /envdriftmap.csv filetype: csv category: genotype description: XOR map for genome (0 = original phenotypic effect, 1 = opposite phenotypic effect). Recorded every ENVDRIFT_RATE steps. trait granularity: N/A time granularity: N/A frequency parameter: ENVDRIFT_RATE header: None structure: row: record, column: genome position, value: 0 or 1

Inherited Members
aegis_sim.recording.recorder.Recorder
init_odir
init_dir