saburq commited on
Commit
62a6171
Β·
1 Parent(s): 93f7649

add labels

Browse files
Files changed (1) hide show
  1. app.py +40 -41
app.py CHANGED
@@ -23,30 +23,32 @@ LEVELS = [1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 50]
23
  SOIL_LEVELS = [1, 2]
24
  DEFAULT_DATE = OpendataClient().latest()
25
 
26
- # First define the variable descriptions
27
- VARIABLE_DESCRIPTIONS = {
28
- # Surface variables (10m)
29
- "10u": "10m U Wind Component",
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- "10v": "10m V Wind Component",
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- "2d": "2m Dewpoint Temperature",
32
- "2t": "2m Temperature",
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- "msl": "Mean Sea Level Pressure",
34
- "skt": "Skin Temperature",
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- "sp": "Surface Pressure",
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- "tcw": "Total Column Water",
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- "lsm": "Land-Sea Mask",
38
- "z": "Surface Geopotential",
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- "slor": "Slope of Sub-gridscale Orography",
40
- "sdor": "Standard Deviation of Orography",
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-
42
- # Soil variables
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- "stl1": "Soil Temperature Level 1",
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- "stl2": "Soil Temperature Level 2",
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- "swvl1": "Soil Water Volume Level 1",
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- "swvl2": "Soil Water Volume Level 2",
 
 
47
  }
48
 
49
- # Add pressure level variable descriptions dynamically
50
  for var in ["t", "u", "v", "w", "q", "z"]:
51
  var_name = {
52
  "t": "Temperature",
@@ -58,7 +60,8 @@ for var in ["t", "u", "v", "w", "q", "z"]:
58
  }[var]
59
 
60
  for level in LEVELS:
61
- VARIABLE_DESCRIPTIONS[f"{var}_{level}"] = f"{var_name} at {level}hPa"
 
62
 
63
  def get_open_data(param, levelist=[]):
64
  fields = {}
@@ -118,27 +121,23 @@ def plot_forecast(state, selected_variable):
118
  ax.coastlines()
119
  ax.add_feature(cfeature.BORDERS, linestyle=":")
120
  triangulation = tri.Triangulation(longitudes, latitudes)
121
- contour = ax.tricontourf(triangulation, values, levels=20, transform=ccrs.PlateCarree(), cmap="RdBu")
 
 
 
 
122
  plt.title(f"{selected_variable} at {state['date']}")
123
  plt.colorbar(contour)
124
  return fig
125
 
126
- # Then create the available variables list
127
- AVAILABLE_VARIABLES = (
128
- # Surface variables
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- ["10u", "10v", "2d", "2t", "msl", "skt", "sp", "tcw", "lsm", "z", "slor", "sdor"] +
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- # Soil variables
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- ["stl1", "stl2", "swvl1", "swvl2"] +
132
- # Pressure level variables (adding level suffix)
133
- [f"{var}_{level}" for var in ["t", "u", "v", "w", "q", "z"]
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- for level in LEVELS]
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- )
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-
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- # Finally create the dropdown choices
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- DROPDOWN_CHOICES = [
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- (f"{VARIABLE_DESCRIPTIONS[var_id]} ({var_id})", var_id)
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- for var_id in sorted(AVAILABLE_VARIABLES)
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- ]
142
 
143
  def gradio_interface(date_str, lead_time, device, selected_variable):
144
  try:
@@ -156,7 +155,7 @@ demo = gr.Interface(
156
  gr.Radio(choices=["cuda", "cpu"], value="cuda", label="Compute Device"),
157
  gr.Dropdown(
158
  choices=DROPDOWN_CHOICES,
159
- value="t_850", # This should be the variable ID
160
  label="Select Variable to Plot",
161
  info="Choose a meteorological variable to visualize"
162
  )
 
23
  SOIL_LEVELS = [1, 2]
24
  DEFAULT_DATE = OpendataClient().latest()
25
 
26
+ # First organize variables into categories
27
+ VARIABLE_GROUPS = {
28
+ "Surface Variables": {
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+ "10u": "10m U Wind Component",
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+ "10v": "10m V Wind Component",
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+ "2d": "2m Dewpoint Temperature",
32
+ "2t": "2m Temperature",
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+ "msl": "Mean Sea Level Pressure",
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+ "skt": "Skin Temperature",
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+ "sp": "Surface Pressure",
36
+ "tcw": "Total Column Water",
37
+ "lsm": "Land-Sea Mask",
38
+ "z": "Surface Geopotential",
39
+ "slor": "Slope of Sub-gridscale Orography",
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+ "sdor": "Standard Deviation of Orography",
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+ },
42
+ "Soil Variables": {
43
+ "stl1": "Soil Temperature Level 1",
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+ "stl2": "Soil Temperature Level 2",
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+ "swvl1": "Soil Water Volume Level 1",
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+ "swvl2": "Soil Water Volume Level 2",
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+ },
48
+ "Pressure Level Variables": {} # Will fill this dynamically
49
  }
50
 
51
+ # Add pressure level variables dynamically
52
  for var in ["t", "u", "v", "w", "q", "z"]:
53
  var_name = {
54
  "t": "Temperature",
 
60
  }[var]
61
 
62
  for level in LEVELS:
63
+ var_id = f"{var}_{level}"
64
+ VARIABLE_GROUPS["Pressure Level Variables"][var_id] = f"{var_name} at {level}hPa"
65
 
66
  def get_open_data(param, levelist=[]):
67
  fields = {}
 
121
  ax.coastlines()
122
  ax.add_feature(cfeature.BORDERS, linestyle=":")
123
  triangulation = tri.Triangulation(longitudes, latitudes)
124
+
125
+ # Use 'RdBu_r' instead of 'RdBu' to reverse the color scheme
126
+ contour = ax.tricontourf(triangulation, values, levels=20,
127
+ transform=ccrs.PlateCarree(),
128
+ cmap='RdBu_r')
129
  plt.title(f"{selected_variable} at {state['date']}")
130
  plt.colorbar(contour)
131
  return fig
132
 
133
+ # Create dropdown choices with groups
134
+ DROPDOWN_CHOICES = []
135
+ for group_name, variables in VARIABLE_GROUPS.items():
136
+ # Add group separator
137
+ DROPDOWN_CHOICES.append((f"── {group_name} ──", None))
138
+ # Add variables in this group
139
+ for var_id, desc in sorted(variables.items()):
140
+ DROPDOWN_CHOICES.append((f"{desc} ({var_id})", var_id))
 
 
 
 
 
 
 
 
141
 
142
  def gradio_interface(date_str, lead_time, device, selected_variable):
143
  try:
 
155
  gr.Radio(choices=["cuda", "cpu"], value="cuda", label="Compute Device"),
156
  gr.Dropdown(
157
  choices=DROPDOWN_CHOICES,
158
+ value="2t", # Default to 2m temperature
159
  label="Select Variable to Plot",
160
  info="Choose a meteorological variable to visualize"
161
  )