Add support for changing band combinations and colormaps interactively (

#46)

* Add support for changing band combinations and colormaps interactively

* Fix DESIS bug

* Add demo to docs

README.md

@@ -17,10 +17,15 @@
 -   Interactive visualization and analysis of hyperspectral data, such as [AVIRIS](https://aviris.jpl.nasa.gov), [DESIS](https://www.earthdata.nasa.gov/s3fs-public/imported/DESIS_TCloud_Mar0421.pdf), [EMIT](https://earth.jpl.nasa.gov/emit), [PACE](https://pace.gsfc.nasa.gov), [NEON AOP](https://data.neonscience.org/data-products/DP3.30006.001)
 -   Interactive visualization of NASA [ECOSTRESS](https://ecostress.jpl.nasa.gov) data
 -   Interactive extraction and visualization of spectral signatures
+-   Changing band combinations and colormaps interactively
 -   Saving spectral signatures as CSV files
 
 ## Demos
 
+-   Changing band combinations and colormaps interactively
+
+![colormap](https://i.imgur.com/jYItN4D.gif)
+
 -   Visualizing NASA [AVIRIS](https://aviris.jpl.nasa.gov) hyperspectral data interactively
 
 ![AVIRIS](https://i.imgur.com/RdegGqx.gif)

docs/examples/desis.ipynb

@@ -87,7 +87,7 @@
    "source": [
     "m = hypercoast.Map()\n",
     "m.add_basemap(\"Hybrid\")\n",
-    "m.add_desis(filepath, bands=[200], vmin=0, vmax=5000, nodata=0, colormap=\"jet\")\n",
+    "m.add_desis(filepath, wavelengths=[1000], vmin=0, vmax=5000, nodata=0, colormap=\"jet\")\n",
     "m.add_colormap(cmap=\"jet\", vmin=0, vmax=0.5, label=\"Reflectance\")\n",
     "m"
    ]
@@ -114,7 +114,7 @@
    "source": [
     "m = hypercoast.Map()\n",
     "m.add_basemap(\"Hybrid\")\n",
-    "m.add_desis(filepath, bands=[50, 100, 200], vmin=0, vmax=1000, nodata=0)\n",
+    "m.add_desis(filepath, wavelengths=[900, 600, 525], vmin=0, vmax=1000, nodata=0)\n",
     "m.add(\"spectral\")\n",
     "m"
    ]

docs/examples/ecostress.ipynb

@@ -169,6 +169,7 @@
     "m = hypercoast.Map()\n",
     "m.add_basemap(\"HYBRID\")\n",
     "m.add_raster(filepath, colormap=\"jet\", layer_name=\"LST\")\n",
+    "m.add(\"spectral\")\n",
     "m"
    ]
   },

docs/examples/emit.ipynb

@@ -86,7 +86,7 @@
    "source": [
     "m = hypercoast.Map()\n",
     "m.add_basemap(\"SATELLITE\")\n",
-    "m.add_emit(dataset, wavelengths=[500, 600, 1000], indexes=[3, 2, 1], layer_name=\"EMIT\")\n",
+    "m.add_emit(dataset, wavelengths=[1000, 600, 500], vmin=0, vmax=0.3, layer_name=\"EMIT\")\n",
     "m.add(\"spectral\")\n",
     "m"
    ]

docs/index.md

@@ -16,10 +16,15 @@
 -   Interactive visualization and analysis of hyperspectral data, such as [AVIRIS](https://aviris.jpl.nasa.gov), [DESIS](https://www.earthdata.nasa.gov/s3fs-public/imported/DESIS_TCloud_Mar0421.pdf), [EMIT](https://earth.jpl.nasa.gov/emit), [PACE](https://pace.gsfc.nasa.gov), [NEON AOP](https://data.neonscience.org/data-products/DP3.30006.001)
 -   Interactive visualization of NASA [ECOSTRESS](https://ecostress.jpl.nasa.gov) data
 -   Interactive extraction and visualization of spectral signatures
+-   Changing band combinations and colormaps interactively
 -   Saving spectral signatures as CSV files
 
 ## Demos
 
+-   Changing band combinations and colormaps interactively
+
+![colormap](https://i.imgur.com/jYItN4D.gif)
+
 -   Visualizing NASA [AVIRIS](https://aviris.jpl.nasa.gov) hyperspectral data interactively
 
 ![AVIRIS](https://i.imgur.com/RdegGqx.gif)

hypercoast/desis.py

@@ -9,15 +9,15 @@
 from .common import convert_coords
 
 
-def read_desis(filepath, bands=None, method="nearest", **kwargs):
+def read_desis(filepath, wavelengths=None, method="nearest", **kwargs):
     """
     Reads DESIS data from a given file and returns an xarray Dataset.
 
     Args:
         filepath (str): Path to the file to read.
-        bands (array-like, optional): Specific bands to select. If None, all
-            bands are selected.
-        method (str, optional): Method to use for selection when bands is not
+        wavelengths (array-like, optional): Specific wavelengths to select. If
+            None, all wavelengths are selected.
+        method (str, optional): Method to use for selection when wavelengths is not
             None. Defaults to "nearest".
         **kwargs: Additional keyword arguments to pass to the `sel` method when
             bands is not None.
@@ -26,30 +26,31 @@ def read_desis(filepath, bands=None, method="nearest", **kwargs):
         xr.Dataset: An xarray Dataset containing the DESIS data.
     """
 
+    url = "https://github.com/opengeos/datasets/releases/download/hypercoast/desis_wavelengths.csv"
+    df = pd.read_csv(url)
     dataset = xr.open_dataset(filepath)
+    dataset = dataset.rename(
+        {"band": "wavelength", "band_data": "reflectance"}
+    ).transpose("y", "x", "wavelength")
+    dataset["wavelength"] = df["wavelength"].tolist()
 
-    if bands is not None:
-        dataset = dataset.sel(band=bands, method=method, **kwargs)
+    if wavelengths is not None:
+        dataset = dataset.sel(wavelength=wavelengths, method=method, **kwargs)
 
-    dataset = dataset.rename({"band_data": "reflectance"})
-    url = "https://github.com/opengeos/datasets/releases/download/hypercoast/desis_wavelengths.csv"
-    df = pd.read_csv(url)
-    wavelengths = df["wavelength"].tolist()
-    dataset.attrs["wavelengths"] = wavelengths
     dataset.attrs["crs"] = dataset.rio.crs.to_string()
 
     return dataset
 
 
-def desis_to_image(dataset, bands=None, method="nearest", output=None, **kwargs):
+def desis_to_image(dataset, wavelengths=None, method="nearest", output=None, **kwargs):
     """
     Converts an DESIS dataset to an image.
 
     Args:
         dataset (xarray.Dataset or str): The dataset containing the DESIS data
             or the file path to the dataset.
-        bands (array-like, optional): The specific bands to select. If None, all
-            bands are selected. Defaults to None.
+        wavelengths (array-like, optional): The specific wavelengths to select.
+            If None, all wavelengths are selected. Defaults to None.
         method (str, optional): The method to use for data interpolation.
             Defaults to "nearest".
         output (str, optional): The file path where the image will be saved. If
@@ -67,10 +68,12 @@ def desis_to_image(dataset, bands=None, method="nearest", output=None, **kwargs)
     if isinstance(dataset, str):
         dataset = read_desis(dataset, method=method)
 
-    if bands is not None:
-        dataset = dataset.sel(band=bands, method=method)
+    if wavelengths is not None:
+        dataset = dataset.sel(wavelength=wavelengths, method=method)
 
-    return array_to_image(dataset["reflectance"], output=output, **kwargs)
+    return array_to_image(
+        dataset["reflectance"], output=output, transpose=False, **kwargs
+    )
 
 
 def extract_desis(ds, lat, lon):
@@ -93,7 +96,7 @@ def extract_desis(ds, lat, lon):
     values = ds.sel(x=x, y=y, method="nearest")["reflectance"].values / 10000
 
     da = xr.DataArray(
-        values, dims=["wavelength"], coords={"wavelength": ds.attrs["wavelengths"]}
+        values, dims=["wavelength"], coords={"wavelength": ds.coords["wavelength"]}
     )
 
     return da
@@ -143,8 +146,6 @@ def filter_desis(dataset, lat, lon, return_plot=False, **kwargs):
         print(x_min, y_min, x_max, y_max)
         da = dataset.sel(x=slice(x_min, x_max), y=slice(y_min, y_max))["reflectance"]
 
-    wavelengths = dataset.attrs["wavelengths"]
-
     if return_plot:
         rrs_stack = da.stack(
             {"pixel": ["latitude", "longitude"]},

hypercoast/emit.py

@@ -53,6 +53,7 @@ def read_emit(filepath, ortho=True, wavelengths=None, method="nearest", **kwargs
         if wavelengths is not None:
             ds = ds.sel(wavelengths=wavelengths, method=method)
 
+        ds = ds.rename({"wavelengths": "wavelength"})
         return ds
 
 
@@ -187,7 +188,7 @@ def viz_emit(
 
     if isinstance(ds, str):
         ds = read_emit(ds, ortho=ortho)
-    example = ds.sel(wavelengths=wavelengths, method=method)
+    example = ds.sel(wavelength=wavelengths, method=method)
 
     if title is None:
         title = f"Reflectance at {example.wavelengths.values:.3f} {example.wavelengths.units}"
@@ -248,7 +249,7 @@ def emit_to_image(data, wavelengths=None, method="nearest", output=None, **kwarg
     ds = data["reflectance"]
 
     if wavelengths is not None:
-        ds = ds.sel(wavelengths=wavelengths, method=method)
+        ds = ds.sel(wavelength=wavelengths, method=method)
     return array_to_image(ds, transpose=False, output=output, **kwargs)
 
 
@@ -354,6 +355,8 @@ def emit_xarray(
 
     if wavelengths is not None:
         out_xr = out_xr.sel(wavelengths=wavelengths, method=method)
+
+    out_xr = out_xr.rename({"wavelengths": "wavelength"})
     return out_xr
 
 

hypercoast/hypercoast.py

@@ -237,6 +237,7 @@ def add_emit(
 
         self.cog_layer_dict[layer_name]["xds"] = xds
         self.cog_layer_dict[layer_name]["hyper"] = "EMIT"
+        self._update_band_names(layer_name, wavelengths)
 
     def add_pace(
         self,
@@ -320,11 +321,12 @@ def add_pace(
 
         self.cog_layer_dict[layer_name]["xds"] = source
         self.cog_layer_dict[layer_name]["hyper"] = "PACE"
+        self._update_band_names(layer_name, wavelengths)
 
     def add_desis(
         self,
         source,
-        bands=[50, 100, 200],
+        wavelengths=[900, 650, 525],
         indexes=None,
         colormap="jet",
         vmin=None,
@@ -378,19 +380,19 @@ def add_desis(
 
             source = read_desis(source)
 
-        image = desis_to_image(source, bands=bands, method=method)
+        image = desis_to_image(source, wavelengths=wavelengths, method=method)
 
-        if isinstance(bands, list) and len(bands) > 1:
+        if isinstance(wavelengths, list) and len(wavelengths) > 1:
             colormap = None
 
-        if isinstance(bands, int):
-            bands = [bands]
+        if isinstance(wavelengths, int):
+            wavelengths = [wavelengths]
 
         if indexes is None:
-            if isinstance(bands, list) and len(bands) == 1:
+            if isinstance(wavelengths, list) and len(wavelengths) == 1:
                 indexes = [1]
             else:
-                indexes = [3, 2, 1]
+                indexes = [1, 2, 3]
 
         self.add_raster(
             image,
@@ -409,6 +411,7 @@ def add_desis(
 
         self.cog_layer_dict[layer_name]["xds"] = source
         self.cog_layer_dict[layer_name]["hyper"] = "DESIS"
+        self._update_band_names(layer_name, wavelengths)
 
     def add_neon(
         self,
@@ -491,6 +494,7 @@ def add_neon(
 
         self.cog_layer_dict[layer_name]["xds"] = xds
         self.cog_layer_dict[layer_name]["hyper"] = "NEON"
+        self._update_band_names(layer_name, wavelengths)
 
     def add_aviris(
         self,
@@ -574,6 +578,34 @@ def add_aviris(
         xds.attrs["bounds"] = self.cog_layer_dict[layer_name]["bounds"]
         self.cog_layer_dict[layer_name]["xds"] = xds
         self.cog_layer_dict[layer_name]["hyper"] = "AVIRIS"
+        self._update_band_names(layer_name, wavelengths)
+
+    def add_hyper(self, xds, type, wvl_indexes=None, **kwargs):
+        """Add a hyperspectral dataset to the map.
+
+        Args:
+            xds (str): The Xarray dataset containing the hyperspectral data.
+            type (str): The type of the hyperspectral dataset. Can be one of
+                "EMIT", "PACE", "DESIS", "NEON", "AVIRIS".
+            **kwargs: Additional keyword arguments to pass to the corresponding
+                add function.
+        """
+
+        if wvl_indexes is not None:
+            kwargs["wavelengths"] = (
+                xds.isel(wavelength=wvl_indexes).coords["wavelength"].values.tolist()
+            )
+
+        if type == "EMIT":
+            self.add_emit(xds, **kwargs)
+        elif type == "PACE":
+            self.add_pace(xds, **kwargs)
+        elif type == "DESIS":
+            self.add_desis(xds, **kwargs)
+        elif type == "NEON":
+            self.add_neon(xds, **kwargs)
+        elif type == "AVIRIS":
+            self.add_aviris(xds, **kwargs)
 
     def set_plot_options(
         self,
@@ -653,3 +685,45 @@ def spectral_to_csv(self, filename, index=True, **kwargs):
         df = self.spectral_to_df()
         df = df.rename_axis("band")
         df.to_csv(filename, index=index, **kwargs)
+
+    def _update_band_names(self, layer_name, wavelengths):
+
+        # Function to find the nearest indices
+        def find_nearest_indices(
+            dataarray, selected_wavelengths, dim_name="wavelength"
+        ):
+            indices = []
+            for wavelength in selected_wavelengths:
+                if dim_name == "band":
+                    nearest_wavelength = dataarray.sel(
+                        band=wavelength, method="nearest"
+                    )
+                else:
+                    nearest_wavelength = dataarray.sel(
+                        wavelength=wavelength, method="nearest"
+                    )
+                nearest_wavelength_index = nearest_wavelength[dim_name].item()
+                nearest_index = (
+                    dataarray[dim_name].values.tolist().index(nearest_wavelength_index)
+                )
+                indices.append(nearest_index + 1)
+            return indices
+
+        if "xds" in self.cog_layer_dict[layer_name]:
+            xds = self.cog_layer_dict[layer_name]["xds"]
+            dim_name = "wavelength"
+
+            if "band" in xds:
+                dim_name = "band"
+
+            band_count = xds.dims[dim_name]
+            band_names = ["b" + str(band) for band in range(1, band_count + 1)]
+            self.cog_layer_dict[layer_name]["band_names"] = band_names
+
+            try:
+                indexes = find_nearest_indices(xds, wavelengths, dim_name=dim_name)
+                vis_bands = ["b" + str(index) for index in indexes]
+                self.cog_layer_dict[layer_name]["indexes"] = indexes
+                self.cog_layer_dict[layer_name]["vis_bands"] = vis_bands
+            except Exception as e:
+                print(e)