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Added extensive Readable Comments #59

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36 changes: 28 additions & 8 deletions geoplot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,8 @@
from string import Template
from agent_torch.core.helpers import get_by_path

# HTML/JS template string is being used here to render cesium-based 3D visualisation.
# Populated with actual data, timestamps, etc.
geoplot_template = """
<!doctype html>
<html lang="en">
Expand Down Expand Up @@ -214,10 +216,20 @@


def read_var(state, var):
'''
Helper function to get access to nested fields in the state using '/'

'''
return get_by_path(state, re.split("/", var))


class GeoPlot:
'''
init function for initializing the geoplot visualizer.
Args:
config: dictionary containing simulation metadata like num_episodes, num_steps...etc.
options: dictionary containing with required config like cesium_token, feature, type of visualization,..etc.
'''
def __init__(self, config, options):
self.config = config
(
Expand All @@ -235,19 +247,25 @@ def __init__(self, config, options):
)

def render(self, state_trajectory):
'''
Converts simulation trajectory into GeoJSON and HTML visualization.
Args:
state_trajectory: A 2D list representing simulation states across episodes & steps.
'''
coords, values = [], []
name = self.config["simulation_metadata"]["name"]
geodata_path, geoplot_path = f"{name}.geojson", f"{name}.html"
name = self.config["simulation_metadata"]["name"] # Extracting output file names from simulation metadata
geodata_path, geoplot_path = f"{name}.geojson", f"{name}.html"

# Extracting the final state of each episode and read coordinates and property values
for i in range(0, len(state_trajectory) - 1):
final_state = state_trajectory[i][-1]

coords = np.array(read_var(final_state, self.entity_position)).tolist()
coords = np.array(read_var(final_state, self.entity_position)).tolist() # coordinates of each entity
values.append(
np.array(read_var(final_state, self.entity_property)).flatten().tolist()
)

start_time = pd.Timestamp.utcnow()
start_time = pd.Timestamp.utcnow() # Creating timestamp for each simulation step
timestamps = [
start_time + pd.Timedelta(seconds=i * self.step_time)
for i in range(
Expand All @@ -256,7 +274,8 @@ def render(self, state_trajectory):
)
]

geojsons = []
# Creating GeoJSON time-series data for each entity
geojsons = []
for i, coord in enumerate(coords):
features = []
for time, value_list in zip(timestamps, values):
Expand All @@ -265,19 +284,20 @@ def render(self, state_trajectory):
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [coord[1], coord[0]],
"coordinates": [coord[1], coord[0]], # [longitude, latitude]
},
"properties": {
"value": value_list[i],
"value": value_list[i], # value of the property at this timestamp
"time": time.isoformat(),
},
}
)
geojsons.append({"type": "FeatureCollection", "features": features})

with open(geodata_path, "w", encoding="utf-8") as f:
json.dump(geojsons, f, ensure_ascii=False, indent=2)
json.dump(geojsons, f, ensure_ascii=False, indent=2) # writing GeoJSON data to disk

# Filling the HTML/JS Template with actual data
tmpl = Template(geoplot_template)
with open(geoplot_path, "w", encoding="utf-8") as f:
f.write(
Expand Down