import scanf
import itertools
import matrix
from matrix import ppmx as pmx
import numpy as np
import pandas as pd
import shared
from pprint import pprint as pp

class Oragami:
    def __init__(self, name):
        lines = []
        with open(name, "r") as f:
            for line in f.readlines():
                lines.append(line.rstrip())
        splitter = lines.index("")
        coords, folds = lines[:splitter], lines[splitter + 1 :]
        self.coords = [list(map(int, c.split(","))) for c in coords]
        print(self.coords[:6])
        self.parse_folds(folds)
        self.max()
        self.new_matrix()


    def parse_folds(self, folds):
        self.folds = []
        for fold in folds:
            axis, index = scanf.scanf("fold along %s=%d", fold)
            self.folds.append({'axis':axis, 'index':index})

    def max(self):
        by_x = max([x['index'] for x in self.folds if x['axis'] == 'x'])
        by_y = max([x['index'] for x in self.folds if x['axis'] == 'y'])
        self.max_width = by_x*2+1
        self.max_height = by_y*2+1

    def new_matrix(self):
        self.matrix = matrix.matrix_of_size(width=self.max_width, height=self.max_height)
        for c, r in self.coords:
            self.matrix[r][c] = 1

    def process_folds(self):
        for idx, fold in enumerate(self.folds):
            print('---')
            if fold['axis'] == 'y':
                self.fold_y(fold['index'])
            else:
                self.fold_x(fold['index'])
            self.count()
        pmx(self.matrix,pad=False,space=False)

    def fold_y(self, cut):
        #folding on y removes the y row
        bottom = self.matrix[cut+1:]
        bottom = list(reversed(bottom))
        self.matrix = self.matrix[:cut]
        self.copy_from(bottom)

    def fold_x(self, cut):
        #folding on X removes the x column
        left, right = [], []
        removed = 0
        for r, row in enumerate(self.matrix):
            left.append(row[:cut])
            right.append(list(reversed(row[cut+1:])))
            if row[cut] == 1:
                removed += 1
        self.matrix = left
        self.copy_from(right)

    def copy_from(self, source):
        for r, row in enumerate(source):
            for c, col in enumerate(row):
                if col == 1:
                    self.matrix[r][c] = 1
        print("")

    def count(self):
        flat = np.ravel(np.array(self.matrix))
        print(sum(flat))


def main():
    o = Oragami(shared.get_fname(13))
    o.process_folds()


if __name__ == "__main__":
    main()