Added local hazard visualization

[ywkim312]

Added local hazard visualization for earthquake, flood, hurricane, and tsunami. To test this, install the PR branch first, then create a test notebook file using the following code and run the notebook with attached zip file after unzip it.
data.zip

import os
import json

from pyincore import Hurricane, Flood, Earthquake, Tsunami

from pyincore_viz.geoutil import GeoUtil as viz
from pyincore_viz.plotutil import PlotUtil as plot

# create local hurricane and visualize
workspace = 'data/hurricane'

with open(os.path.join(workspace, "hurricane-dataset.json"), 'r') as file:
    hurricane_dataset_json = file.read()
    print(json.dumps(json.loads(hurricane_dataset_json), indent=4))

# create the hurricane object
hurricane = Hurricane.from_json_file((os.path.join(workspace, "hurricane-dataset.json")))

# attach datasets from local files
hurricane.hazardDatasets[0].from_file((os.path.join(workspace, "Wave_Raster.tif")),
                                      data_type="ncsa:deterministicHurricaneRaster")
hurricane.hazardDatasets[1].from_file(os.path.join(workspace, "Surge_Raster.tif"),
                                      data_type="ncsa:deterministicHurricaneRaster")
hurricane.hazardDatasets[2].from_file(os.path.join(workspace, "Inundation_Raster.tif"),
                                      data_type="ncsa:deterministicHurricaneRaster")

# display the hurricane
for hurricane in hurricane.hazardDatasets:
    # visualize
    viz.plot_local_hurricane(hurricane)
    
# create local earthquake and visualize
workspace = os.path.join("data", "earthquake")
eq = Earthquake.from_json_file(os.path.join(workspace, "eq-dataset.json"))

# attach datasets from local files
eq.hazardDatasets[0].from_file((os.path.join(workspace, "eq-dataset-SA.tif")),
                               data_type="ergo:probabilisticEarthquakeRaster")
eq.hazardDatasets[1].from_file((os.path.join(workspace, "eq-dataset-PGA.tif")),
                               data_type="ergo:probabilisticEarthquakeRaster")

# display the earthquake
for earthquake in eq.hazardDatasets:
    # visualize
    viz.plot_local_earthquake(earthquake)

# create local tsunami and visualize
workspace = 'data/tsunami'

with open(os.path.join(workspace, "tsunami.json"), 'r') as file:
    tsunami_dataset_json = file.read()
    print(json.dumps(json.loads(tsunami_dataset_json), indent=4))

# create the tsunami object
tsunami = Tsunami.from_json_file(os.path.join(workspace, "tsunami.json"))

# attach datasets from local files
tsunami.hazardDatasets[0].from_file((os.path.join(workspace, "Tsu_100yr_Vmax.tif")),
                                    data_type="ncsa:probabilisticTsunamiRaster")
tsunami.hazardDatasets[1].from_file((os.path.join(workspace, "Tsu_100yr_Mmax.tif")),
                                    data_type="ncsa:probabilisticTsunamiRaster")
tsunami.hazardDatasets[2].from_file((os.path.join(workspace, "Tsu_100yr_Hmax.tif")),
                                    data_type="ncsa:probabilisticTsunamiRaster")

for tsunami in tsunami.hazardDatasets:
    viz.plot_local_tsunami(tsunami)

# create local flood and visualize
workspace = 'data/flood'

with open(os.path.join(workspace, "flood-dataset.json"), 'r') as file:
    flood_dataset_json = file.read()
    print(json.dumps(json.loads(flood_dataset_json), indent=4))

# create the flood object
flood = Flood.from_json_file(os.path.join(workspace, "flood-dataset.json"))

# attach datasets from local files
flood.hazardDatasets[0].from_file((os.path.join(workspace, "flood-inundationDepth-50ft.tif")),
                                  data_type="ncsa:probabilisticFloodRaster")
flood.hazardDatasets[1].from_file(os.path.join(workspace, "flood-WSE-50ft.tif"),
                                  data_type="ncsa:probabilisticFloodRaster")

for flood in flood.hazardDatasets:
    viz.plot_local_flood(flood)

# create local tornado
workspace = os.path.join('data', 'tornado')

with open(os.path.join(workspace, "tornado_dataset.json"), 'r') as file:
    tornado_dataset_json = file.read()
    print(json.dumps(json.loads(tornado_dataset_json), indent=4))

# create the tornado object
tornado = Tornado.from_json_file(os.path.join(workspace, "tornado_dataset.json"))

# attach dataset from local file
tornado.hazardDatasets[0].from_file((os.path.join(workspace, "joplin_path_wgs84.shp")),
                                    data_type="incore:tornadoWindfield")

# visualize the tornado
outmap = viz.plot_local_tornado(tornado)
outmap

[longshuicy]

Just curious, is tornado (shapefile) not possible yet?

[ywkim312]

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

[longshuicy]

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

[ywkim312]

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

I am not very sure if it is worthwhile because it might

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

We've been started using gdf.explore() for the shapefile visualization and it can't be wrapped. So maybe we can just add an example of showing tornado using gdf.explore() instead of creating the method, like we did in workshop session 2.

[ywkim312]

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

I am not very sure if it is worthwhile because it might

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

We've been started using gdf.explore() for the shapefile visualization and it can't be wrapped. So maybe we can just add an example of showing tornado using gdf.explore() instead of creating the method, like we did in workshop session 2.

I can create a wrapper for using our existing ones but that wouldn't be any better than using gdf.explore()

[ywkim312]

Just curious, is tornado (shapefile) not possible yet?

Tornado is not included in here since it is a shapefile. So just use the local shapefile dataset visualization and it should work

For consistency of the API maybe it is worthwhile to add a similar method even though it's just wrap around the visualize local dataset?

Anyway, I added the local visualization of tornado using the existing method of pyincore-viz. I also updated the description part to include the local tornado visualization. However, still, using gdf.explore() will be better way.

[longshuicy]

Code looks good. You might want to include tornado example in the data.zip for easy testing.

[ywkim312]

Code looks good. You might want to include tornado example in the data.zip for easy testing.

Updated data.zip

[Vismayak]

Just an aesthetic suggestion, not necessary... but we can use .title() instead of .upper() for the title so the resulting title is not all in uppercase?

[Vismayak]

Code looks good and testing worked. Just left a small comment about aesthetic but not important