我想在我的类“ DeviceClass”中使用openlayers库,所以我这样做:
#!/usr/bin/python
# call with: python3 cgl.py 10 500 1 1
import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
ON = 255
OFF = 0
def update(frameNum, img, grid, gridsize):
"""Updates the grid every time it is refreshed"""
newgrid = grid.copy()
for i in range(gridsize):
for j in range(gridsize):
# this formula considers the edge/boundary conditions that appear
# every cell has to have 8 neighbouring cells
# to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
# we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
grid[(i - 1) % gridsize, (j - 1) % gridsize] +
grid[(i - 1) % gridsize, (j + 1) % gridsize] +
grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
(i + 1) % gridsize, (j + 1) % gridsize]) / 255)
# apply conway's basic rules of the game of life for each cell
if grid[i, j] == ON:
if (total < 2) or (total > 3):
newgrid[i, j] = OFF
else:
if total == 3:
newgrid[i, j] = ON
# update data
grid[:] = newgrid[:]
img.set_data(newgrid)
return img,
def add_glider(i, j, grid):
"""adds a glider with top-left cell at (i, j)"""
glider = np.array([[0, 0, 255],
[255, 0, 255],
[0, 255, 255]])
grid[i:i+3, j:j+3] = glider
def main():
parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
parser.add_argument('gridsize', type=int, help='Dimension of grid.')
parser.add_argument('interval', type=int, help='Interval.')
parser.add_argument('formationflag', type=bool, help='Predefined formation.')
parser.add_argument('frame', type=int, help='How many frames to animate.')
# get arguments from input function
arguments = parser.parse_args()
# set the arguments
frame = int(arguments.frame)
gridsize = int(arguments.gridsize)
interval = int(arguments.interval)
formation = arguments.formationflag
# if you want to start with a formation:
if formation:
grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
add_glider(1, 1, grid)
# else display a randopm grid
else:
grid = randomgrid(gridsize)
fig, ax = plt.subplots()
# colormap: black -> alive, white -> dead
img = ax.imshow(grid, cmap='binary', interpolation='nearest')
# # this will be used to save the animation in a later version
ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
frames=frame,
interval=interval,
save_count=50)
# remove x and y - axis labels, numbers and ticks
ax.axes.xaxis.set_ticklabels([])
ax.axes.yaxis.set_ticklabels([])
plt.xticks([])
plt.yticks([])
# plot the animated output
plt.show()
if __name__ == '__main__':
main()
print("DONE")
现在我得到了一个错误
没有给出与所需形式相对应的参数 参数c#类openlayers
并且是
设备类底层
。有人可以帮忙吗?
完整代码为:
public class DeviceClass : OpenLayers.DeviceCollection.Device
{
}