Modification for wall and ditch matrix
Presentation:
Modification
Delete : Except for ditch_matrix, all varibles and code relevant with ditch are deleted.
Modify:
For initial_positon
python
if pos_type == 'wall':
'''
Applying: 1 to self.wall_matrix along the route
from the start point(start_x,start_y) to end point (end_x,end_y)
'''
self.apply_matrix_dots(start_x, start_y, end_x, end_y, 'wall')For apply_matrix_dots
python
if attri=='wall':
'''
Considering wall is initialized with two dots, finding out all the dots lying in the rectangular first,
then acquiring all the dots lying in the outer line.
'''
rectangle_dots=self.get_coordinates_in_range((start_x,start_y),(end_x,end_y))
ditch=self.get_rectangle_coordinates(start_x-1,start_y-1,end_x+1,end_y+1)
for x,y in rectangle_dots:
self.wall_matrix[x][y]=1
for x,y in ditch:
self.ditch_matrix[x][y]=1Full code
python
# 获取坐标文件
import numpy as np
import pandas as pd
class Evaluation():
def __init__(self):
# 获取偏移转化参数
x_shifting, y_shifting, x_scale, y_scale = 2850, 1500, 10, 10
road_positions_filename = f'./road.xlsx'
wall_positions_filename = f'./east_station.xlsx'
river_positions_filename = f'./river3.xlsx'
self.width,self.height=350,240
self.ditch_matrix = np.zeros((self.width, self.height)) # initializing ditch matrix
self.wall_matrix = np.zeros((self.width, self.height)) # initializing wall matrix
self.initial_position(wall_positions_filename, x_shifting, y_shifting, x_scale, y_scale, 'wall')
ditch_df = pd.DataFrame(self.ditch_matrix)
ditch_df.to_csv('.\\ditch_matrix.csv', index=False, header=False)
ditch_df = pd.DataFrame(self.wall_matrix)
ditch_df.to_csv('.\\wall_matrix.csv', index=False, header=False)
def initial_position(self, file_name, x_shifting, y_shifting, x_scale, y_scale, pos_type):
"""
参数：file_name(文件路径名字), pos_type(坐标类型)
进行坐标转换，初始化墙、内门以及出口坐标
"""
# 读取文件
if pos_type == 'road':
df = pd.read_excel(file_name, header=None)
tuple_list = []
# 遍历每一行
for index, row in df.iterrows():
tuple_row = []
col_index = 1 # 初始列索引
# 在每行内部，每次读取两列数据，直到读完所有列
while col_index < len(row):
data1 = row.iloc[col_index] # 第一列的数据
data2 = row.iloc[col_index + 1] # 第二列的数据
if pd.notna(data1) and pd.notna(data2):
tuple_row.append((data1, data2))
col_index += 2 # 更新列索引，跳过已读取的两列
if tuple_row:
tuple_list.append(tuple_row)
for sublist in tuple_list:
# 遍历每一行
maxy = -100000
col_index = 0
while col_index + 1 < len(sublist):
# 获取两列数据
data1 = sublist[col_index]
data2 = sublist[col_index + 1]
start_x, start_y, end_x, end_y = data1[0], data1[1], data2[0], data2[1]
end_x += x_shifting
end_x /= x_scale
# end_x *= self.grid.width
end_x = round(end_x)
end_y += y_shifting
end_y /= y_scale
# end_y *= self.grid.height
end_y = round(end_y)
start_x += x_shifting
start_x /= x_scale
start_x = round(start_x)
start_y += y_shifting
start_y /= y_scale
start_y = round(start_y)
self.roads.append({"start_x": start_x, "end_x": end_x, "start_y": start_y, "end_y": end_y})
'''
Applying 1 to self.road_matrix along the route
from the start point(star_x,star_y) to end point (end_x,end_x)
'''
self.apply_matrix_dots(start_x, start_y, end_x, end_y, 'road')
col_index += 1
elif pos_type == "river":
df = pd.read_excel(file_name)
num = df['x1'].notna().sum()
print(pos_type, "数量：", num)
# 坐标变化
for i in range(num):
start_x, start_y = df['x1'][i], df['y1'][i]
start_x += x_shifting
start_x /= x_scale
start_x = round(start_x)
# align with roads
start_x = start_x - 38
start_y += y_shifting
start_y /= y_scale
start_y = round(start_y)
# align with roads
start_y = start_y + 28
self.stream_pos.append((start_x, start_y))
if i > 0:
'''
Applyiing 1 to self.river_matrix along the route
from the start point(start0_x,start0_y) to end point (start_x,start_y)
'''
self.apply_matrix_dots(start0_x, start0_y, start_x, start_y, 'river')
start0_x, start0_y = start_x, start_y
num2 = df['x2'].notna().sum()
print(pos_type, "add 数量：", num2)
# 坐标变化
for i in range(num2):
start_x, start_y = df['x2'][i], df['y2'][i]
start_x += x_shifting
start_x /= x_scale
start_x = round(start_x)
# align with roads
start_x = start_x - 38
start_y += y_shifting
start_y /= y_scale
start_y = round(start_y)
# align with roads
start_y = start_y + 28
self.stream_pos2.append((start_x, start_y))
if i > 0:
'''
Applying 1 to self.river_matrix along the route
from the start point(start0_x,start0_y) to end point (start_x,start_y)
'''
self.apply_matrix_dots(start0_x, start0_y, start_x, start_y, 'river')
start0_x, start0_y = start_x, start_y
else:
df = pd.read_excel(file_name)
num = len(df['x1'])
print(pos_type, "数量：", num)
# 坐标变化
for i in range(num):
if pos_type == 'wall':
start_x, start_y, end_x, end_y = df['x1'][i], df['y1'][i], df['x2'][i], df['y2'][i]
end_x += x_shifting
end_x /= x_scale
end_x = round(end_x)
end_y += y_shifting
end_y /= y_scale
end_y = round(end_y)
else:
start_x, start_y = df['x1'][i], df['y1'][i]
start_x += x_shifting
start_x /= x_scale
start_x = round(start_x)
start_y += y_shifting
start_y /= y_scale
start_y = round(start_y)
if pos_type == 'wall':
'''
Applying: 1 to self.wall_matrix along the route
from the start point(start_x,start_y) to end point (end_x,end_y)
'''
self.apply_matrix_dots(start_x, start_y, end_x, end_y, 'wall')
elif pos_type == 'indoor':
self.indoors.append((start_x, start_y))
if i > 0:
'''
Applying 1 to self.indoor_matrix along the route
from the start point(start0_x,start0_y) to end point (start_x,start_y)
'''
self.apply_matrix_dots(start0_x, start0_y, start_x, start_y, 'indoor')
start0_x, start0_y = start_x, start_y
elif pos_type == 'exit':
if start_x == end_x:
for i in range(start_y, end_y + 1):
self.pos_exits.append((start_x, i))
# 920 apply coordinates to exits_matrix
self.exits_matrix[start_x][i] = 1
elif start_y == end_y:
for i in range(start_x, end_x + 1):
self.pos_exits.append((i, start_y))
# 920 apply coordinates to exits_matrix
self.exits_matrix[i][start_y] = 1
else:
continue
elif pos_type == "pillar":
pillar_positions = {"start_x": start_x, "end_x": end_x, "start_y": start_y, "end_y": end_y}
self.pillars.append(pillar_positions)
'''
Applying 1 to self.pillar_matrix along the route
from the start point(start_x,start_y) to end point (end_x,end_y)
'''
self.apply_matrix_dots(start_x, start_y, end_x, end_y, 'pillar')
else:
pass
# self.water_initial_pos.append((start_x, start_y))
def get_rectangle_coordinates(self, x1, y1, x2, y2):
'''
acquiring all the dots of outer line which is composed with two dots(x1,y1) (x2,y2)
:param x1:
:param y1:
:param x2:
:param y2:
:return:
'''
# Ensure (x1, y1) is the bottom-left corner and (x2, y2) is the top-right corner
x_min = min(x1, x2)
x_max = max(x1, x2)
y_min = min(y1, y2)
y_max = max(y1, y2)
# Calculate coordinates of the four corners
bottom_left = (x_min, y_min)
bottom_right = (x_max, y_min)
top_left = (x_min, y_max)
top_right = (x_max, y_max)
# Generate points along each edge
left_edge = [(x_min, y) for y in range(y_min, y_max + 1)]
right_edge = [(x_max, y) for y in range(y_min, y_max + 1)]
bottom_edge = [(x, y_min) for x in range(x_min, x_max + 1)]
top_edge = [(x, y_max) for x in range(x_min, x_max + 1)]
# Combine all the points
all_points = [bottom_left, bottom_right, top_left, top_right]
all_points.extend(left_edge)
all_points.extend(right_edge)
all_points.extend(bottom_edge)
all_points.extend(top_edge)
return list(set(all_points))
def get_coordinates_in_range(self, bottom_left, top_right):
'''
find the rectangle between the two dots
:param bottom_left:(x0,y0) left dot
:param top_right:(x1,y1) right dot
:return: a list containing all dots within the rectangle which is composed with two dots
'''
coordinates = []
for x in range(bottom_left[0], top_right[0] + 1):
for y in range(bottom_left[1], top_right[1] + 1):
coordinates.append((x, y))
return coordinates
def apply_matrix_dots(self, start_x, start_y, end_x, end_y, attri):
'''
Applying Bresenham's line algorithm to find out all the points along the route and updating all the location on matrix as 1.
Args:
start_x:
start_y:
end_x:
end_y:
attri: Utilized for determining which matrix should be modified.
Returns:
'''
# Get the points for the line between start and end
if attri!='wall':
points = self.bresenham_line(start_x, start_y, end_x, end_y)
if attri=='road':
# Update the road_matrix for each point on the line
for x, y in points:
self.road_matrix[x][y] = 1
if attri=='river':
for x, y in points:
self.river_matrix[x][y] = 1
if attri=='wall':
'''
Considering wall is initialized with two dots, finding out all the dots lying in the rectangular first,
then acquiring all the dots lying in the outer line.
'''
rectangle_dots=self.get_coordinates_in_range((start_x,start_y),(end_x,end_y))
ditch=self.get_rectangle_coordinates(start_x-1,start_y-1,end_x+1,end_y+1)
for x,y in rectangle_dots:
self.wall_matrix[x][y]=1
for x,y in ditch:
self.ditch_matrix[x][y]=1
if attri=='indoor':
# Question: what's the meaning of indoor? The output of inoor matrix contains nothing.
for x,y in points:
self.indoor_matrix[x][y]=1
if attri=='pillar':
# Question: what's the meaning of pillar? The output of pillar matrix contains nothing.
for x,y in points:
self.pillar_matrix[x][y]=1
def bresenham_line(self,x0, y0, x1, y1):
"""Bresenham's Line Algorithm
Produces a list of tuples from start and end points
This is used to determine the points of an n-dimensional
raster that should be selected in order to form a close
approximation to a straight line between two points.
"""
points = []
is_steep = abs(y1 - y0) > abs(x1 - x0)
if is_steep:
x0, y0 = y0, x0
x1, y1 = y1, x1
swapped = False
if x0 > x1:
x0, x1 = x1, x0
y0, y1 = y1, y0
swapped = True
dx = x1 - x0
dy = y1 - y0
error = int(dx / 2.0)
y_step = 1 if y0 < y1 else -1
y = y0
for x in range(x0, x1 + 1):
coord = (y, x) if is_steep else (x, y)
points.append(coord)
error -= abs(dy)
if error < 0:
y += y_step
error += dx
if swapped:
points.reverse()
return points
if __name__ == '__main__':
evauation=Evaluation()