def saveMap(self, fileName):
"""Save a map to file"""
md = MapData(self._g, self._keys, self._gates, self._m, self._n, self._endNode,
self._ordering, self._startNode, self._weightedNeutral,
self._h_mapping, self._v_mapping)
with open(fileName, "wb") as pFile:
pickle.dump(md, pFile, protocol=pickle.HIGHEST_PROTOCOL)
async def gamma(ctx, author, args):
whitelisted_twitch_users = config.get_list('whitelist_twitchusers')
if USE_WHITELIST and author not in whitelisted_twitch_users and not ctx.author.is_mod:
await ctx.channel.send(
f"{author}, you do not have the correct permissions to use this command."
f"If you wanna be whitelisted to use such a command, please contact neyo#0382 on discord."
)
return
value = float(args[0])
if 0.5 <= (value) <= 1.6:
logging.info("i did it..")
api.exec_command(f"r_gamma {value}")
MapData.save(serverstate.STATE.mapname, 'gamma', value)
else:
await ctx.channel.send(
f"{author}, the allowed values for gamma are 1.0-1.6")
def main(filename_coord, filename_anc, column, shapefile, boundry_lines):
"""
"""
# set up plot
lllon = -120
lllat = -70
urlon = -20
urlat = 40
display = MainDisplay(lllon, lllat, urlon, urlat, files_shape=shapefile)
# TODO calculate this on the mapdata module
level_min, level_max = -1.0, 70.2
# load ancestry and location data
for country, anc, boundry_rect in zip(shapefile, filename_anc,
boundry_lines):
map_data = MapData(filename_coord, anc, columns)
map_data.get_coordinates()
#map_data.get_ancestry_average_by_coordinates(columns[1])
map_data.project_coordinates(
display.anc_map, boundry_rect) # pass the rect of the country
xi, yi, zi, x, y, z = map_data.interpolate(columns[1])
shape_clip = process_shapefile(country, display.anc_map, display.ax)
display.draw(xi, yi, zi, x, y, z, map_data.coordinates,
map_data.df[columns[1]], shape_clip, level_min, level_max)
display.add_colorbar()
plt.title("Mean Anc {}".format(column[1]))
#plt.savefig("native_{}.png".format(column[1]), format="png", dpi=300, transparent=True)
plt.show()
async def picmip(ctx, author, args):
whitelisted_twitch_users = config.get_list('whitelist_twitchusers')
if USE_WHITELIST and author not in whitelisted_twitch_users and not ctx.author.is_mod:
await ctx.channel.send(
f"{author}, you do not have the correct permissions to use this command."
f"If you wanna be whitelisted to use such a command, please contact neyo#0382 on discord."
)
return
value = args[0]
if value.isdigit() and (0 <= int(value) <= 6):
logging.info("vid_restarting..")
serverstate.VID_RESTARTING = True
serverstate.PAUSE_STATE = True
api.exec_command(f"r_picmip {value};vid_restart")
MapData.save(serverstate.STATE.mapname, 'picmip', value)
else:
await ctx.channel.send(
f"{author}, the allowed values for picmip are 0-5.")
def main(filename_coord, filename_anc, column, shapefile, boundry_lines):
"""
"""
# set up plot
lllon = -120
lllat = -70
urlon = -20
urlat = 40
display = MainDisplay(lllon, lllat, urlon, urlat, files_shape=shapefile)
# TODO calculate this on the mapdata module
level_min, level_max = -1.0, 70.2
# load ancestry and location data
for country, anc, boundry_rect in zip(shapefile, filename_anc, boundry_lines):
map_data = MapData(filename_coord, anc, columns)
map_data.get_coordinates()
#map_data.get_ancestry_average_by_coordinates(columns[1])
map_data.project_coordinates(display.anc_map, boundry_rect) # pass the rect of the country
xi, yi, zi, x, y, z = map_data.interpolate(columns[1])
shape_clip = process_shapefile(country, display.anc_map, display.ax)
display.draw(xi, yi, zi, x, y, z, map_data.coordinates, map_data.df[columns[1]], shape_clip, level_min, level_max)
display.add_colorbar()
plt.title("Mean Anc {}".format(column[1]))
#plt.savefig("native_{}.png".format(column[1]), format="png", dpi=300, transparent=True)
plt.show()
def saveMap(self, fileName):
"""Save a map to file"""
md = MapData(self._g, self._keys, self._gates, self._m, self._n, self._endNode,
self._ordering, self._startNode, self._weightedNeutral,
self._h_mapping, self._v_mapping)
for wall in self._walls: wall.makePickleSafe()
for platform in self._platforms: platform.makePickleSafe()
for key in self._backupKeys: key.makePickleSafe()
self._finish.makePickleSafe()
gm = GeneratedMap(md, self._finish, self._walls, self._platforms,
self._backupKeys, self._playerStart,
(self._roomWidth,self._roomHeight))
with open(fileName, "wb") as pFile:
pickle.dump(gm, pFile, protocol=pickle.HIGHEST_PROTOCOL)
self._finish.undoPickleSafe()
for wall in self._walls: wall.undoPickleSafe()
for plat in self._platforms: plat.undoPickleSafe()
for key in self._backupKeys: key.undoPickleSafe()
async def drawgun(ctx, author, args):
api.exec_command(
f"toggle cg_drawgun 1 2;cg_centertime 3;displaymessage 140 10 ^3{author} ^7has changed: ^3Gun movement"
)
MapData.toggle(serverstate.STATE.mapname, 'drawgun', 2, 1)
async def angles(ctx, author, args):
api.exec_command(
f"toggle df_chs1_Info6 0 40;cg_centertime 3;displaymessage 140 10 ^3{author} ^7has changed: ^3Weapon angles"
)
MapData.toggle(serverstate.STATE.mapname, 'angles', 40, 0)
async def nodraw(ctx, author, args):
api.exec_command(
f"toggle df_mp_NoDrawRadius 100 100000;cg_centertime 3;displaymessage 140 10 ^3{author} ^7has changed: ^3Players visibility"
)
MapData.toggle(serverstate.STATE.mapname, 'nodraw', 100000, 100)
def create_schedule():
"""Creates a schedule based on the current game map."""
map_data = MapData(game, Scheduler.ghost)
scheduler = Scheduler(game, map_data)
return scheduler.get_schedule()
ps = pstats.Stats(pr, stream=s).sort_stats('cumulative')
ps.print_stats()
logging.info(s.getvalue())
s.close()
# Initialize the game.
game = Game()
load_parameters(game)
logging.info(param)
# Define some globals for convenience.
me = game.me
game_map = game.game_map
MapData(game, None)
while(time.time() - bot_start < 9.7 and DistanceCalculator.needs_precompute()):
DistanceCalculator.precompute()
# Play the game.
game.ready("TeamSchildpad")
while True:
game.update_frame()
start = time.time()
command_queue = generate_commands()
# time_taken = time.time() - start
# logging.info(time_taken)
# if time_taken > 1.4:
# log_profiling()
while(time.time() - start < 1.7 and DistanceCalculator.needs_precompute()):
def make_sample(outfile, noise=0.0, pixsize=1.0):
'''Create a sample data file for mpi-mapmaker-test/
Creates a small rectangular map of a circular Gaussian and scans
row of detectors across the map in two orientations.
Optionally add noise.
'''
# create a fake map (from a Gaussian)
nx = 32
ny = 16
gaussfwhm = 4
xx = (np.arange(nx)-nx/2)**2
yy = (np.arange(ny)-ny/2)**2
rr = xx[:,np.newaxis] + yy
gausssig = gaussfwhm / 2.354
image = np.exp(-rr/2.0/gausssig**2)
# scan once horizontally and twice vertically
ndet = 16
nsamp = 64
# allocate arrays
det_x = np.zeros([ndet, nsamp], dtype=np.int32)
det_y = np.zeros_like(det_x)
det_s = np.zeros_like(det_x, dtype=np.float64)
# horizontal scan
offs = 0
for i in range(nx):
for j in range(ndet):
det_x[j,offs+i] = i
det_y[j,offs+i] = j
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# first half vertical
offs += nx
for i in range(ny):
for j in range(ndet):
det_x[j,offs+i] = j
det_y[j,offs+i] = i
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# second half vertical
offs += ny
for i in range(ny):
for j in range(ndet):
det_x[j,offs+i] = nx/2+j
det_y[j,offs+i] = i
det_s[j,offs+i] = image[det_x[j,offs+i],det_y[j,offs+i]]
# add noise
det_s += np.random.randn(ndet, nsamp) * noise
# create data file
# initialize data class
out_data = MapData(outfile, ndet, nsamp)
# write attributes
out_data.set_nx(nx)
out_data.set_ny(ny)
out_data.set_pixsize(pixsize)
# set data arrays
out_data.x[...] = det_x
out_data.y[...] = det_y
out_data.s[...] = det_s
out_data.q[...] = np.zeros([ndet,nsamp], dtype=np.uint32)
# done
out_data.close()
def convert_data(infile, outfile, pixsize, verbose=False):
'''convert data file for use by mpi_makemap
Convert input data file, as created by Jack Sayer's simulator, to
format used as input to mpi_makemap. Calculates tangent-plane
projection and saves pixel position for each sample.
Arguments:
input: name of input file (as created from Jack Sayer's simulator)
output: name of output file
pixsize: size of pixels (in degrees)
verbose: print progress messages [False]
'''
# get data from file
f = h5py.File(infile)
det_ra = f[det_ra_name].value
det_dec = f[det_dec_name].value
tel_ra = f[tel_ra_name].value
tel_dec = f[tel_dec_name].value
scannum = f[scannum_name].value
# check that coordinate system is supported
coordsys = f[det_ra_name].attrs["coordinate_system"][0]
if coordsys != "radec":
sys.stderr.write("error: coordinate system must be 'radec'")
sys.exit()
# get data lengths
nsamp,ndet = f[signal_name].shape
# use mean telescope pointing as tangent point
tan_ra = tel_ra.mean()
tan_dec = tel_dec.mean()
# WCS for coordinate transformations
w = wcs.WCS(naxis=2)
w.wcs.crpix = [0, 0]
w.wcs.cdelt = np.array([-pixsize, pixsize])
w.wcs.crval = [tan_ra, tan_dec]
w.wcs.ctype = ["RA---TAN", "DEC--TAN"]
# initialize min/max collectors
minx = np.infty
maxx = -np.infty
miny = np.infty
maxy = -np.infty
if verbose:
print "Calculating map extent:"
# loop over detectors and calculate pixel position to get map range
for d in range(ndet):
if verbose:
print "\tdetector {} of {}".format(d, ndet)
# project into tangent plane
x,y = w.wcs_world2pix(tel_ra-det_ra[d]/np.cos(tel_dec*np.pi/180),
tel_dec+det_dec[d], 0)
# convert to integers
x = np.floor(x)
y = np.floor(y)
minx = min(x.min(), minx)
maxx = max(x.max(), maxx)
miny = min(y.min(), miny)
maxy = max(y.max(), maxy)
# determine map range
nx = maxx - minx + 1
ny = maxy - miny + 1
if verbose:
print "opening output file '{}'".format(outfile)
# set up output data file
out_data = MapData(outfile, ndet, nsamp)
out_data.set_nx(nx)
out_data.set_ny(ny)
out_data.set_pixsize(pixsize)
if verbose:
print "writing data to file:"
# figure out block dimensions (powers of two, assuming blocksize is
# power of two)
ndata_block = blocksize / out_data.s.dtype.itemsize
blocksize_sqrt = np.sqrt(ndata_block)
ndet_block = np.int(np.exp2(np.floor(np.log2(blocksize_sqrt))))
ndet_block = min(ndet_block, ndet)
nsamp_block = np.int(ndata_block / ndet_block)
nsamp_block = min(nsamp_block, nsamp)
# loop over data set and write to output
this_det0 = 0
while this_det0 < ndet:
# number of detectors in this block
this_ndet = min(ndet_block, ndet-this_det0)
this_det1 = this_det0 + this_ndet
if verbose:
print "Read/write block: det {}-{} of {}".format(
this_det0, this_det1, ndet)
this_samp0 = 0
while this_samp0 < nsamp:
# number of samples in this block
this_nsamp = min(nsamp_block, nsamp-this_samp0)
this_samp1 = this_samp0 + this_nsamp
# create ra/det blocks
ra_block = tel_ra[this_samp0:this_samp1] - \
det_ra[this_det0:this_det1,np.newaxis] / \
np.cos(tel_dec[this_samp0:this_samp1]*np.pi/180)
dec_block = tel_dec[this_samp0:this_samp1] + \
det_dec[this_det0:this_det1,np.newaxis]
x,y = w.wcs_world2pix(ra_block,dec_block, 0)
x = np.floor(x) - minx
y = np.floor(y) - miny
# write to file
out_data.x[this_det0:this_det1,this_samp0:this_samp1] = x
out_data.y[this_det0:this_det1,this_samp0:this_samp1] = y
out_data.s[this_det0:this_det1,this_samp0:this_samp1] = \
np.transpose(f[signal_name][this_samp0:this_samp1,
this_det0:this_det1])
# quality (0 -> good when scannum >= 0)
thisqual = (scannum[this_samp0:this_samp1] < 0).astype(np.uint32)
out_data.q[this_det0:this_det1,this_samp0:this_samp1] = thisqual
# increment samp pointer
this_samp0 = this_samp1
# increment det pointer
this_det0 = this_det1
if verbose:
print "closing files"
# done
f.close()
out_data.close()