eladyaniv01

class MATester(sc2.BotAI):

    def __init__(self):
        super().__init__()
        self.map_data = MapData(self)

    async def on_step(self, iteration: int):
        reg1 = self.map_data.regions[1]
        reg7 = self.map_data.regions[7]
        p0 = reg1.center

eladyaniv01

D:\Users\elad\.virtualenvs\SC2MapAnalysis\Scripts\python.exe "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\pydevconsole.py" --mode=client --port=60982

import sys; print('Python %s on %s' % (sys.version, sys.platform))
sys.path.extend(['D:\\proj\\SC2MapAnalysis', 'D:/proj/SC2MapAnalysis'])

Python 3.7.6 (tags/v3.7.6:43364a7ae0, Dec 19 2019, 00:42:30) [MSC v.1916 64 bit (AMD64)]
Type 'copyright', 'credits' or 'license' for more information
IPython 7.16.1 -- An enhanced Interactive Python. Type '?' for help.
PyDev console: using IPython 7.16.1

eladyaniv01

radon # radon cc . -a -nb  (will dump only complexity score of B and below)
--
mutmut # mutmut run --paths-to-mutate <folder / files>
--
monkeytype # monkeytype run monkeytest.py 

monkeytest.py
-------------
import pytest
pytest.main()

eladyaniv01

from typing import Union, Tuple

import matplotlib.pyplot as plt
import numpy as np
from sc2 import BotAI
from sc2.position import Point2
from scipy.ndimage import binary_fill_holes, generate_binary_structure, label as ndlabel
from scipy.spatial import distance

from MapAnalyzer.constants import MIN_REGION_AREA, BINARY_STRUCTURE, MAX_REGION_AREA

eladyaniv01

from django.utils.translation import ugettext_lazy as _
from django.urls import reverse

from grappelli.dashboard import modules, Dashboard
from grappelli.dashboard.utils import get_admin_site_name


class CustomIndexDashboard(Dashboard):
    """ 
    Custom index dashboard for www.

eladyaniv01

from django.contrib import admin

from django_summernote.admin import SummernoteModelAdmin
from recms.models import *


class SupplierCmsObjectAdmin(SummernoteModelAdmin):  # instead of ModelAdmin

    summernote_fields = "__all__"

eladyaniv01

def solve_region_grid(self):

    grid = binary_fill_holes(self.game_info.placement_grid.data_numpy).astype(int)
    # chokes = np.where WORK IN PROGRESS    
    # compiled_grid = grid * (np.abs(scipy.ndimage.laplace(grid)) > 0)
    compiled_grid = grid

    s = generate_binary_structure(2, 2)
    labeled_array, num_features = label(compiled_grid, structure=s)

eladyaniv01

from Sc2botAI.BaseBot import BaseBot
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), "../.."))
import logging
import random
import sc2
from sc2 import Race, Difficulty
from sc2.constants import *
from sc2.player import Bot, Computer

eladyaniv01

Error/Loss calculation in depth

• https://towardsdatascience.com/how-to-select-the-right-evaluation-metric-for-machine-learning-models-part-1-regrression-metrics-3606e25beae0

eladyaniv01

from PIL import Image
import cv2
import numpy as np
import matplotlib.pyplot as plt
import pickle
from matplotlib import style
import time

style.use("ggplot")
SIZE = 10