#197 fix zenodo downloads + es points + csv

src/coastseg/common.py

@@ -24,6 +24,7 @@
 from ipywidgets import ToggleButton, HBox, VBox, Layout, HTML
 from requests.exceptions import SSLError
 from shapely.geometry import Polygon
+from shapely.geometry import MultiPoint, LineString
 
 # Specific classes/functions from modules
 from typing import Callable, List, Optional, Union, Dict, Set
@@ -1207,21 +1208,24 @@ def download_url(url: str, save_path: str, filename: str = None, chunk_size: int
         content_length = r.headers.get("Content-Length")
         if content_length:
             total_length = int(content_length)
-            with open(save_path, "wb") as fd:
-                with tqdm(
-                    total=total_length,
-                    unit="B",
-                    unit_scale=True,
-                    unit_divisor=1024,
-                    desc=f"Downloading {filename}",
-                    initial=0,
-                    ascii=True,
-                ) as pbar:
-                    for chunk in r.iter_content(chunk_size=chunk_size):
-                        fd.write(chunk)
-                        pbar.update(len(chunk))
         else:
-            logger.warning("Content length not found in response headers")
+            print(
+                "Content length not found in response headers. Downloading without progress bar."
+            )
+            total_length = None
+        with open(save_path, "wb") as fd:
+            with tqdm(
+                total=total_length,
+                unit="B",
+                unit_scale=True,
+                unit_divisor=1024,
+                desc=f"Downloading {filename}",
+                initial=0,
+                ascii=True,
+            ) as pbar:
+                for chunk in r.iter_content(chunk_size=chunk_size):
+                    fd.write(chunk)
+                    pbar.update(len(chunk))
 
 
 def get_center_point(coords: list) -> tuple:
@@ -1593,6 +1597,33 @@ def save_extracted_shoreline_figures(
         )
 
 
+def convert_linestrings_to_multipoints(gdf: gpd.GeoDataFrame) -> gpd.GeoDataFrame:
+    """
+    Convert LineString geometries in a GeoDataFrame to MultiPoint geometries.
+
+    Args:
+    - gdf (gpd.GeoDataFrame): The input GeoDataFrame.
+
+    Returns:
+    - gpd.GeoDataFrame: A new GeoDataFrame with MultiPoint geometries. If the input GeoDataFrame
+                        already contains MultiPoints, the original GeoDataFrame is returned.
+    """
+
+    # Check if the gdf already contains MultiPoints
+    if any(gdf.geometry.type == "MultiPoint"):
+        return gdf
+
+    def linestring_to_multipoint(linestring):
+        if isinstance(linestring, LineString):
+            return MultiPoint(linestring.coords)
+        return linestring
+
+    # Convert each LineString to a MultiPoint
+    gdf["geometry"] = gdf["geometry"].apply(linestring_to_multipoint)
+
+    return gdf
+
+
 def save_extracted_shorelines(
     extracted_shorelines: "Extracted_Shoreline", save_path: str
 ):
@@ -1619,9 +1650,11 @@ def save_extracted_shorelines(
         save_path, "extracted_shorelines_lines.geojson", extracted_shorelines_gdf_lines
     )
 
+    points_gdf = convert_linestrings_to_multipoints(extracted_shorelines.gdf)
+    projected_gdf = stringify_datetime_columns(points_gdf)
     # Save extracted shorelines as a GeoJSON file
     extracted_shorelines.to_file(
-        save_path, "extracted_shorelines_points.geojson", extracted_shorelines.gdf
+        save_path, "extracted_shorelines_points.geojson", projected_gdf
     )
 
     # Save shoreline settings as a JSON file

src/coastseg/tide_correction.py

@@ -49,7 +49,7 @@ def compute_tidal_corrections(
 def save_csv_per_id(
     df: pd.DataFrame,
     save_location: str,
-    filename: str = "timeseries_tidally_corrected",
+    filename: str = "timeseries_tidally_corrected.csv",
     id_column_name: str = "transect_id",
 ):
     new_df = pd.DataFrame()
@@ -220,7 +220,7 @@ def correct_tides(
         save_csv_per_id(
             tide_corrected_timeseries_df,
             session_path,
-            filename="timeseries_tidally_corrected",
+            filename="timeseries_tidally_corrected.csv",
         )
         update(f"{roi_id} was tidally corrected")
     return tide_corrected_timeseries_df

src/coastseg/zoo_model.py

@@ -107,7 +107,7 @@ def get_files_to_download(
         response = next((f for f in available_files if f["filename"] == filename), None)
         if response is None:
             raise ValueError(f"Cannot find {filename} at {model_id}")
-        link = response["links"]["self"]
+        link = response["links"]["download"]
         file_path = os.path.join(model_path, filename)
         url_dict[file_path] = link
     return url_dict
@@ -798,6 +798,7 @@ def extract_shorelines_with_unet(
 
         # save extracted shorelines, detection jpgs, configs, model settings files to the session directory
         common.save_extracted_shorelines(extracted_shorelines, new_session_path)
+
         # common.save_extracted_shoreline_figures(extracted_shorelines, new_session_path)
         print(f"Saved extracted shorelines to {new_session_path}")
 
@@ -1320,7 +1321,7 @@ def download_best(
         # if best BEST_MODEL.txt file not exist then download it
         if not os.path.isfile(BEST_MODEL_txt_path):
             common.download_url(
-                best_model_json["links"]["self"],
+                best_model_json["links"]["download"],
                 BEST_MODEL_txt_path,
                 "Downloading best_model.txt",
             )
@@ -1405,7 +1406,7 @@ def download_ensemble(
         logger.info(f"all_json_reponses : {all_json_reponses }")
         for response in all_models_reponses + all_json_reponses:
             # get the link of the best model
-            link = response["links"]["self"]
+            link = response["links"]["download"]
             filename = response["key"]
             filepath = os.path.join(model_path, filename)
             download_dict[filepath] = link