def angle_heapmaps(description, zextractor):
configuration_names = Configuration.names()
configurations = [Configuration.create_specific(name, 11, 4.5, "topology") for name in Configuration.names()]
#Get rid of configurations that aren't grids
configurations = filter(lambda c: isinstance(c.topology, Grid), configurations)
# Get rid of configurations that do not have 2 sources
configurations = filter(lambda c: len(c.source_ids) == 2, configurations)
grapher = configuration_heatmap.Grapher("results/Configurations", description, zextractor)
grapher.nokey = True
grapher.xaxis_label = "X Coordinate"
grapher.yaxis_label = "Y Coordinate"
grapher.cb_label = "Source Angle"
grapher.dgrid3d_dimensions = "11,11"
grapher.cbrange = (0, 180)
grapher.create(configurations)
summary_grapher = summary.GraphSummary(
os.path.join("results/Configurations", description),
'{}-{}'.format("results/Configurations", description)
)
summary_grapher.width_factor = None
summary_grapher.height = "7cm"
summary_grapher.run()
parser.add_argument(
"-d",
"--distance",
type=ArgumentsCommon.type_positive_float,
default=4.5,
help=
"The distance between nodes. How this is used depends on the configuration specified."
),
parser.add_argument(
"-nido",
"--node-id-order",
choices=("topology", "randomised"),
default="topology",
help=
"With 'topology' node id orders are the same as the topology defines. 'randomised' causes the node ids to be randomised."
),
parser.add_argument("--show", default=False, action="store_true")
args = parser.parse_args()
configuration = Configuration.create_specific(args.configuration,
args.network_size,
args.distance,
args.node_id_order,
seed=args.seed)
main(configuration, show=args.show)
from simulator.Topology import Grid
from data.graph import summary, configuration_heatmap
parser = argparse.ArgumentParser(description="Misc. Grapher", add_help=True)
parser.add_argument("--min-source-distance-heatmap", action='store_true', default=False)
parser.add_argument("--source-angle-estimate-heatmap", action='store_true', default=False)
parser.add_argument("--source-angle-meters-heatmap", action='store_true', default=False)
parser.add_argument("--source-angle-actual-heatmap", action='store_true', default=False)
parser.add_argument("--source-angle-det-heatmap", action='store_true', default=False)
parser.add_argument("--source-angle-tan-heatmap", action='store_true', default=False)
args = parser.parse_args(sys.argv[1:])
if args.min_source_distance_heatmap:
configuration_names = Configuration.names()
configurations = [Configuration.create_specific(name, 11, 4.5, "topology") for name in Configuration.names()]
#Get rid of configurations that aren't grids
configurations = filter(lambda c: isinstance(c.topology, Grid), configurations)
def zextractor(configuration, nid):
return min(configuration.node_source_distance(nid, src_id) for src_id in configuration.source_ids)
grapher = configuration_heatmap.Grapher("results/Configurations", "min-src-distance", zextractor)
grapher.nokey = True
grapher.xaxis_label = "X Coordinate"
grapher.yaxis_label = "Y Coordinate"
grapher.cb_label = "Minimum Source Distance (m)"
grapher.create(configurations)
def _create_plot(self, global_params, src_period, params, results):
def chunks(l, n):
""" Yield successive n-sized chunks from l."""
for i in range(0, len(l), n):
yield l[i:i + n]
global_parameter_names = self._key_names_base
# Pop the source period off the end of the parameters
global_params_dict = dict(
zip(global_parameter_names[:-1], global_params))
config = global_params_dict["configuration"]
size = int(global_params_dict["network size"])
distance = float(global_params_dict["distance"])
nido = global_params_dict["node id order"]
dat = results[self.result_index]
# The dat is a (mean, var) pair, so take the mean
if isinstance(dat, np.ndarray):
dat = dat[0]
if not isinstance(dat, dict):
raise RuntimeError(
"The data is not a dict. It is a {} with value {}".format(
type(dat), dat))
dir_name = os.path.join(
self.output_directory, self.result_name,
*(global_params + (str(src_period), ) + tuple(map(str, params))))
print(dir_name)
# Ensure that the dir we want to put the files in actually exists
data.util.create_dirtree(dir_name)
configuration = Configuration.create_specific(config, size, distance,
nido)
(minx, miny) = configuration.minxy_coordinates()
(maxx, maxy) = configuration.maxxy_coordinates()
self._write_plot_data(dir_name, configuration, dat)
with open(os.path.join(dir_name, 'graph.gp'), 'w') as graph_p:
graph_p.write('#!/usr/bin/gnuplot\n')
graph_p.write('set terminal pdf enhanced\n')
graph_p.write('set output "graph.pdf" \n')
if self.palette is not None:
graph_p.write('set palette {}\n'.format(self.palette))
#graph_p.write('set title "Heat Map of Messages Sent"\n')
graph_p.write('unset key\n')
#graph_p.write('set size ratio 0.5\n')
#graph_p.write('set tic scale 0\n')
graph_p.write('set xlabel "X Coordinate"\n')
graph_p.write('set ylabel "Y Coordinate"\n')
graph_p.write('set size square\n')
# To top left to be (0, 0)
graph_p.write('set xrange [{}:{}]\n'.format(minx, maxx))
graph_p.write('set xtics auto\n')
#graph_p.write('set yrange [{}:{}] reverse\n'.format(maxy, miny))
graph_p.write('set yrange [:] reverse\n')
graph_p.write('set ytics auto\n')
graph_p.write('set cbrange [:]\n')
graph_p.write('set cblabel "{}"\n'.format(
self.result_name.title()))
graph_p.write('set dgrid3d {0},{0}\n'.format(size))
graph_p.write('set pm3d map interpolate 3,3\n')
graph_p.write('splot "graph.dat" using 1:2:3 with pm3d\n')
with open(os.path.join(dir_name, 'graph.caption'),
'w') as graph_caption:
graph_caption.write('Parameters:\\newline\n')
for (name, value) in global_params_dict.items():
graph_caption.write('{}: {}\\newline\n'.format(
latex.escape(name.title()), latex.escape(value)))
for (name, value) in zip(self.results.parameter_names, params):
graph_caption.write('{}: {}\\newline\n'.format(
latex.escape(str(name)), latex.escape(str(value))))