time  = 0

# This will store the randomly generated data points, to be plotted as a
# histogram.
sampled_time_to_fire = []

# How long the time series will be.
time_to_run = 50000.0

# Helper iterator.
i = 0

# Loop to generate time series
while time <= time_to_run:
    # Generate event
    new_event = FG.generate_fire_recurrence()

    # Adjust the time so it fits in with our time series.
    time_elapsed = new_event + fire_events[i]

    # Append our new events to the fire time series.
    fire_events.append(time_elapsed)

    # Append our sampled time to fire to create a historgram.
    sampled_time_to_fire.append(new_event)
    i+= 1
    time = time_elapsed



# Plotting the histogram to show the distribution.
Exemple #2
0
time = 0

# This will store the randomly generated data points, to be plotted as a
# histogram.
sampled_time_to_fire = []

# How long the time series will be.
time_to_run = 50000.0

# Helper iterator.
i = 0

# Loop to generate time series
while time <= time_to_run:
    # Generate event
    new_event = FG.generate_fire_recurrence()

    # Adjust the time so it fits in with our time series.
    time_elapsed = new_event + fire_events[i]

    # Append our new events to the fire time series.
    fire_events.append(time_elapsed)

    # Append our sampled time to fire to create a historgram.
    sampled_time_to_fire.append(new_event)
    i += 1
    time = time_elapsed

# Plotting the histogram to show the distribution.
plt.figure(1)
plt.hist(sampled_time_to_fire)