Spaces:
Sleeping
Sleeping
File size: 6,612 Bytes
5a1ff44 aea4fce 5a1ff44 a4feeb2 5a1ff44 760889f 5a1ff44 aea4fce 5a1ff44 006a8c3 5a1ff44 9ea8ec2 5a1ff44 aea4fce a4feeb2 aea4fce a4feeb2 aea4fce b611df6 aea4fce 5a1ff44 fc0c6a0 f16b7aa 2dc2135 5a1ff44 2dc2135 5a1ff44 2dc2135 5a1ff44 a4feeb2 5a1ff44 59f8e2c 5a1ff44 fc0c6a0 f16b7aa 5a1ff44 aea4fce a4feeb2 5a1ff44 9ea8ec2 a4feeb2 5a1ff44 a4feeb2 5a1ff44 60fd94d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 |
import os
import zipfile
import gradio as gr
import pandas as pd
import plotly.graph_objects as go
from geo_tools import (
shapefile_to_latlong,
mask_shapefile_to_grid_indices,
points_to_shapefile,
get_cached_grid_indices,
)
DATA_DIR = "data/"
MASK_PATH = os.path.join(DATA_DIR, "serp.shp")
HOSP_PATH = os.path.join(DATA_DIR, "hospitals.shp")
POLICE_PATH = os.path.join(DATA_DIR, "police.shp")
OUT_DIR = "out/"
def gr_generate_map(
side_len: str,
show_hospitals: bool = True,
show_police: bool = True,
region: str = "None",
):
token = "pk.eyJ1IjoiZGlsaXRoIiwiYSI6ImNsaTZ3b3I4MjF6MmczZG80cXBmeTgyaGsifQ.JmrU3qbp2jlK_9Yl2il8pw"
side_len = float(side_len)
show_mask = False
scattermaps = []
grid_path = MASK_PATH[: -len(".shp")] + f"-gap={side_len}.shp"
prefix = ".".join(grid_path.split(".")[:-1])
if not os.path.exists(grid_path):
indices, labels = mask_shapefile_to_grid_indices(MASK_PATH, side_len)
points_to_shapefile(indices, labels, grid_path)
file_list = [prefix + ext for ext in (".shp", ".shx", ".prj", ".dbf", ".cpg")]
with zipfile.ZipFile(prefix + ".zip", "w") as fp:
for file in file_list:
fp.write(file, compress_type=zipfile.ZIP_DEFLATED)
grid_point_df = pd.DataFrame(
data=[
[labels[i], f"{indices[i][1]}, {indices[i][0]}"]
for i in range(len(indices))
],
columns=["Name", "Coordinates"],
)
grid_point_df.to_csv(prefix + ".csv", index=False)
else:
indices, labels = get_cached_grid_indices(grid_path)
grid_point_df = pd.read_csv(prefix + ".csv")
box = go.Scattermapbox(
lat=indices[:, 1],
lon=indices[:, 0],
mode="markers+text",
text=labels,
marker=go.scattermapbox.Marker(size=6),
)
box.name = "Grids"
box.textfont.update({"color": "White"})
scattermaps.append(box)
if show_mask:
contours = shapefile_to_latlong(MASK_PATH)
for contour in contours:
lons = contour[:, 0]
lats = contour[:, 1]
scattermaps.append(
go.Scattermapbox(
fill="toself",
lat=lats,
lon=lons,
mode="markers",
marker=go.scattermapbox.Marker(size=6),
)
)
if show_hospitals:
indices, labels = get_cached_grid_indices(HOSP_PATH)
box = go.Scattermapbox(
lat=indices[:, 1],
lon=indices[:, 0],
mode="markers+text",
text=labels,
marker=go.scattermapbox.Marker(size=10),
)
box.name = "Hospitals"
box.textfont.update({"color": "White"})
scattermaps.append(box)
if show_police:
indices, labels = get_cached_grid_indices(POLICE_PATH)
box = go.Scattermapbox(
lat=indices[:, 1],
lon=indices[:, 0],
mode="markers+text",
text=labels,
marker=go.scattermapbox.Marker(size=10),
)
box.name = "Police Stations"
box.textfont.update({"color": "White"})
scattermaps.append(box)
fig = go.Figure(scattermaps)
center = (7.753769, 80.691730)
if region == "Ussangoda":
center = (6.0994295, 80.9860763)
elif region == "Indikolapelessa":
center = (6.3602253, 80.9371957)
elif region == "Ginigalpelessa":
center = (6.3846744, 80.8868755)
elif region == "Yudhaganawa":
center = (7.665643, 80.9529867)
elif region == "Seruwila":
center = (8.335057, 81.320460)
elif region == "Rupaha":
center = (7.0401336625287, 80.89709495963253)
modebar_icons = [
"lasso",
"select",
"pan",
"zoomin",
"zoomout",
"toImage",
"resetview",
]
if token:
fig.update_layout(
mapbox=dict(
style="satellite-streets",
accesstoken=token,
center=go.layout.mapbox.Center(lat=center[0], lon=center[1]),
pitch=0,
zoom=6 if region == "None" else 13,
),
mapbox_layers=[
{
# "below": "traces",
"sourcetype": "raster",
"sourceattribution": "United States Geological Survey",
"source": [
"https://basemap.nationalmap.gov/arcgis/rest/services/USGSImageryOnly/MapServer/tile/{z}/{y}/{x}"
],
}
],
modebar_remove=modebar_icons,
)
else:
fig.update_layout(
mapbox_style="open-street-map",
hovermode="closest",
mapbox=dict(
bearing=0,
center=go.layout.mapbox.Center(lat=center[0], lon=center[1]),
pitch=0,
zoom=6 if region == "None" else 13,
),
modebar_remove=modebar_icons,
)
return fig, prefix + ".zip", prefix + ".csv", grid_point_df
with gr.Blocks() as demo:
gr.Markdown("""# Serpentinite Sampling Grid Generator""")
with gr.Tab("Sampling"):
grid_side_len = gr.Textbox(value="100", label="Sampling Gap (m)")
grid_show_hosp = gr.Checkbox(True, label="Show Hospitals")
grid_show_police = gr.Checkbox(True, label="Show Police Stations")
grid_button = gr.Button("Generate Grid")
grid_map = gr.Plot(label="Plot")
grid_region = gr.Radio(
label="Zoom to Region",
choices=[
"None",
"Ussangoda",
"Indikolapelessa",
"Ginigalpelessa",
"Yudhaganawa",
"Seruwila",
"Rupaha",
],
)
grid_shapefile = gr.File(label="Grid Shapefile")
grid_point_info = gr.File(label="Grid Point Info")
grid_point_table = gr.Dataframe(label="Grid Point Info Table")
grid_button.click(
gr_generate_map,
inputs=[grid_side_len],
outputs=[grid_map, grid_shapefile, grid_point_info, grid_point_table],
)
grid_region.change(
gr_generate_map,
inputs=[
grid_side_len,
grid_show_hosp,
grid_show_police,
grid_region,
],
outputs=[grid_map, grid_shapefile, grid_point_info, grid_point_table],
)
demo.queue(concurrency_count=10).launch(debug=True)
|