Update pages/01_teste.py

pages/01_teste.py

@@ -1,139 +1,139 @@
-import ee
-import geemap
-import plotly.express as px
-import pandas as pd
-import solara
-import dataclasses
-from typing import Callable, cast
-
-df = pd.read_csv('CSVs\esa_stats_ucs_rj2.csv')
-columns = list(df.columns)
-#df = px.data.iris()
-
-@dataclasses.dataclass
-class ClickPoint:
-    row_index: int
-    x_column: str
-    y_column: str
-
-def find_row_index(fig, click_data):
-    # goes from trace index and point index to row index in a dataframe
-    # requires passing df.index as to custom_data
-    trace_index = click_data["points"]["trace_indexes"][0]
-    point_index = click_data["points"]["point_indexes"][0]
-    trace = fig.data[trace_index]
-    return trace.customdata[point_index][0]
-
-
-
-
-class Map(geemap.Map):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-        self.add_ee_data()
-        self.add("layer_manager")
-        self.add("inspector")
-
-    def add_ee_data(self):
-        # Add Earth Engine dataset
-
-        esa = ee.ImageCollection('ESA/WorldCover/v200').first()
-
-        ucs = ee.FeatureCollection("projects/ee-curso-gee-rhamon/assets/ucs_estaduais_rj")
-        rj = ee.FeatureCollection('FAO/GAUL/2015/level1').filter(ee.Filter.eq('ADM1_NAME', 'Rio De Janeiro'))
-
-       
-        esa = esa.clipToCollection(ucs)
-
-
-
-        # Set visualization parameters.
-
-        visualization = {
-             "bands": ['Map'],
-        }   
-
-
-        fc_vis_params = {
-            "color": "000000FF",
-            'lineType': 'solid',
-            "width": 1.5,
-            "fillColor": "00000000",
-        }
-
-        # Add Earth Engine layers to Map
-        
-        self.centerObject(ucs, zoom=8)
-        self.addLayer(ucs.style(**fc_vis_params), {}, "UCs Estaduais RJ")
-        self.addLayer(esa, visualization, "Uso de Solo ESA")
-        self.addLayer(rj.style(**fc_vis_params), {}, "Limite Estadual RJ")
-        self.add_legend(title="Land Cover Type", builtin_legend='ESA_WorldCover', position="bottomright")
-
-
-@solara.component
-def Page():
-    with solara.Column(style={"max-width": "100%",'margin': "10vw"}):
-        Map.element(
-            center=[40, -100],
-            zoom=4,
-            height="600px",
-        )
-        x = solara.use_state(x)
-        #fig = px.pie(df,values= x, names="Classes", title='Cobertura Florestal UCs Estaduais RJ')
-        #fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species")
-        #solara.FigurePlotly(fig)
-
-@solara.component
-def ClickScatter(df, y, click_row, on_click: Callable[[ClickPoint], None]):
-    
-    y, set_y = solara.use_state(y)
-    
-    #y, set_y = solara.use_state(y)
-    #fig = px.scatter(df, x, y, color=color, custom_data=[df.index])
-    fig = px.pie(df,values= y , names='Classes', title='Uso de Solo UCs Estaduais RJ')
-
-    def on_click_trace(click_data):
-        # sanity checks
-        assert click_data["event_type"] == "plotly_click"
-        row_index = find_row_index(fig, click_data)
-        on_click(ClickPoint(row_index, y))
-
-    if click_row:
-        click_y = df[y].values[click_row]
-        #fig.add_trace(px.scatter(x=, y=[click_y], text=["⭐️"]).data[0])
-        fig.add_trace(px.pie(values= [click_y], names='Classes', title='Uso de Solo UCs Estaduais RJ').data[0])
-    # make the figure a bit smaller
-    fig.update_layout(width=1500,height=800)
-    with solara.Column(style={"width": "100%",'margin': "10vw"}) as main:
-        solara.FigurePlotly(fig, on_click=on_click_trace)
-        solara.Select(label="Escolha aqui a Unidade de Conservação a ter o Uso de solo avaliado", value=y, values=columns, on_value=set_y)
-    return main
-
-@solara.component
-def Page():
-     with solara.Column(style={"min-width": "500px", "max-width": "100%",'margin': "10vw"}):
-        Map.element(
-            center=[-22, -43],
-            zoom=8,
-            height="600px",
-        )
-
-
-        click_point, set_click_point = solara.use_state(cast(ClickPoint, None))
-        if click_point:
-            clicked_row = click_point.row_index
-        else:
-            clicked_row = None
-
-            with solara.Row(justify="center", style={"flex-wrap": "wrap"}):
-                ClickScatter(df, 'nome', clicked_row, on_click=set_click_point)
-            if click_point is not None:
-                clicked_row = click_point.row_index
-                solara.Success(f"Clicked on row {clicked_row}. Which is highlighted in the both plots.")
-                solara.Markdown(
-                    f"""
-                ```python
-                row_data = {df.iloc[clicked_row].to_dict()}
-                ```"""
-                )
+import ee
+import geemap
+import plotly.express as px
+import pandas as pd
+import solara
+import dataclasses
+from typing import Callable, cast
+
+df = pd.read_csv('pages/esa_stats_ucs_rj2.csv')
+columns = list(df.columns)
+#df = px.data.iris()
+
+@dataclasses.dataclass
+class ClickPoint:
+    row_index: int
+    x_column: str
+    y_column: str
+
+def find_row_index(fig, click_data):
+    # goes from trace index and point index to row index in a dataframe
+    # requires passing df.index as to custom_data
+    trace_index = click_data["points"]["trace_indexes"][0]
+    point_index = click_data["points"]["point_indexes"][0]
+    trace = fig.data[trace_index]
+    return trace.customdata[point_index][0]
+
+
+
+
+class Map(geemap.Map):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.add_ee_data()
+        self.add("layer_manager")
+        self.add("inspector")
+
+    def add_ee_data(self):
+        # Add Earth Engine dataset
+
+        esa = ee.ImageCollection('ESA/WorldCover/v200').first()
+
+        ucs = ee.FeatureCollection("projects/ee-curso-gee-rhamon/assets/ucs_estaduais_rj")
+        rj = ee.FeatureCollection('FAO/GAUL/2015/level1').filter(ee.Filter.eq('ADM1_NAME', 'Rio De Janeiro'))
+
+       
+        esa = esa.clipToCollection(ucs)
+
+
+
+        # Set visualization parameters.
+
+        visualization = {
+             "bands": ['Map'],
+        }   
+
+
+        fc_vis_params = {
+            "color": "000000FF",
+            'lineType': 'solid',
+            "width": 1.5,
+            "fillColor": "00000000",
+        }
+
+        # Add Earth Engine layers to Map
+        
+        self.centerObject(ucs, zoom=8)
+        self.addLayer(ucs.style(**fc_vis_params), {}, "UCs Estaduais RJ")
+        self.addLayer(esa, visualization, "Uso de Solo ESA")
+        self.addLayer(rj.style(**fc_vis_params), {}, "Limite Estadual RJ")
+        self.add_legend(title="Land Cover Type", builtin_legend='ESA_WorldCover', position="bottomright")
+
+
+@solara.component
+def Page():
+    with solara.Column(style={"max-width": "100%",'margin': "10vw"}):
+        Map.element(
+            center=[40, -100],
+            zoom=4,
+            height="600px",
+        )
+        x = solara.use_state(x)
+        #fig = px.pie(df,values= x, names="Classes", title='Cobertura Florestal UCs Estaduais RJ')
+        #fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species")
+        #solara.FigurePlotly(fig)
+
+@solara.component
+def ClickScatter(df, y, click_row, on_click: Callable[[ClickPoint], None]):
+    
+    y, set_y = solara.use_state(y)
+    
+    #y, set_y = solara.use_state(y)
+    #fig = px.scatter(df, x, y, color=color, custom_data=[df.index])
+    fig = px.pie(df,values= y , names='Classes', title='Uso de Solo UCs Estaduais RJ')
+
+    def on_click_trace(click_data):
+        # sanity checks
+        assert click_data["event_type"] == "plotly_click"
+        row_index = find_row_index(fig, click_data)
+        on_click(ClickPoint(row_index, y))
+
+    if click_row:
+        click_y = df[y].values[click_row]
+        #fig.add_trace(px.scatter(x=, y=[click_y], text=["⭐️"]).data[0])
+        fig.add_trace(px.pie(values= [click_y], names='Classes', title='Uso de Solo UCs Estaduais RJ').data[0])
+    # make the figure a bit smaller
+    fig.update_layout(width=1500,height=800)
+    with solara.Column(style={"width": "100%",'margin': "10vw"}) as main:
+        solara.FigurePlotly(fig, on_click=on_click_trace)
+        solara.Select(label="Escolha aqui a Unidade de Conservação a ter o Uso de solo avaliado", value=y, values=columns, on_value=set_y)
+    return main
+
+@solara.component
+def Page():
+     with solara.Column(style={"min-width": "500px", "max-width": "100%",'margin': "10vw"}):
+        Map.element(
+            center=[-22, -43],
+            zoom=8,
+            height="600px",
+        )
+
+
+        click_point, set_click_point = solara.use_state(cast(ClickPoint, None))
+        if click_point:
+            clicked_row = click_point.row_index
+        else:
+            clicked_row = None
+
+            with solara.Row(justify="center", style={"flex-wrap": "wrap"}):
+                ClickScatter(df, 'nome', clicked_row, on_click=set_click_point)
+            if click_point is not None:
+                clicked_row = click_point.row_index
+                solara.Success(f"Clicked on row {clicked_row}. Which is highlighted in the both plots.")
+                solara.Markdown(
+                    f"""
+                ```python
+                row_data = {df.iloc[clicked_row].to_dict()}
+                ```"""
+                )