Detect incidents

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# Log in
import geoanalytics
geoanalytics.auth(username="myusername", password="mypassword")

# Imports
from geoanalytics.tools import DetectIncidents
from geoanalytics.sql import functions as ST
from pyspark.sql import functions as F

# Path to the Atlantic hurricanes data
data_path = r"https://sampleserver6.arcgisonline.com/arcgis/rest/services/" \
            "Hurricanes/MapServer/0"

# Create an Atlantic hurricanes DataFrame
df = spark.read.format("feature-service").load(data_path) \
                    .st.set_time_fields("Date_Time")

# Run Detect Incidents to find where the windspeed of a hurricane is greater than
# or equal to 70 nautical miles per hour (knots)
result = DetectIncidents() \
   .setTrackFields("EVENTID") \
   .setStartConditionExpression(start_condition_expression="$feature.WINDSPEED >= 70") \
   .setOutputMode("Incidents") \
   .run(dataframe=df)

# Convert IncidentDuration from milliseconds to hours
result = result.withColumn("IncidentDuration_hours",
                           F.col("IncidentDuration") / (60 * 60 * 1000))

# Show the first 5 rows of the result DataFrame
result.filter(result["EVENTID"] == 'Alberto') \
      .filter(result["IncidentStatus"] == 'OnGoing') \
      .select("EVENTID", "IncidentStatus", "IncidentDuration","IncidentDuration_hours",
             F.date_format("Date_Time", "yyyy-MM-dd").alias("Date_Time")) \
      .sort("IncidentDuration_hours", "Date_Time", ascending=False).show(5, truncate=False)

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+-------+--------------+----------------+----------------------+----------+
|EVENTID|IncidentStatus|IncidentDuration|IncidentDuration_hours|Date_Time |
+-------+--------------+----------------+----------------------+----------+
|Alberto|OnGoing       |302400000       |84.0                  |2000-08-22|
|Alberto|OnGoing       |280800000       |78.0                  |2000-08-22|
|Alberto|OnGoing       |259200000       |72.0                  |2000-08-22|
|Alberto|OnGoing       |237600000       |66.0                  |2000-08-21|
|Alberto|OnGoing       |237600000       |66.0                  |2000-08-13|
+-------+--------------+----------------+----------------------+----------+
only showing top 5 rows

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# Create a world continents DataFrame for plotting
continents_path = "https://services.arcgis.com/P3ePLMYs2RVChkJx/ArcGIS/rest/services/" \
                "World_Continents/FeatureServer/0"
continents_subset_df = spark.read.format("feature-service").load(continents_path) \
                    .where("""CONTINENT = 'North America' or CONTINENT = 'South America' or
                              CONTINENT = 'Africa' or CONTINENT = 'Europe'""")

# Plot the resulting incidents for hurricane Alberto with the USA continents data
continents_subset_plot = continents_subset_df.st.plot(facecolor="lightgreen",
                                                      edgecolors="black",
                                                      alpha=0.3,
                                                      figsize=(20,10),
                                                      basemap="light")
alberto_tracks_plot = df.where("EVENTID = 'Alberto'").st.plot(color="lightgrey",
                                                              edgecolors="darkgrey",
                                                              ax=continents_subset_plot)
result_plot = result.where("EVENTID = 'Alberto'").st.plot(cmap_values="IncidentStatus",
                                                          cmap="tab10",
                                                          is_categorical=True,
                                                          legend=True,
                                                          legend_kwds={"title": "Incident status",
                                                                       "loc" : "upper left"},
                                                          ax=alberto_tracks_plot)
result_plot.set_title("Detected incidents for hurricane Alberto where windspeed was greater\n"
 "than or equal to 70 nautical miles per hour (knots)", {'fontsize': 12})
result_plot.set_xlabel("X (Meters)")
result_plot.set_xlim(left=-20000000, right=8000000)
result_plot.set_ylabel("X (Meters)")
result_plot.set_ylim(bottom=-8000000, top=20000000);