Change method name to get demo data, to be explicit

Author: AntSimi

examples/01_general_things/pet_storage.py

@@ -17,7 +17,7 @@
 
 import py_eddy_tracker_sample
 
-from py_eddy_tracker.data import get_path, get_remote_sample
+from py_eddy_tracker.data import get_demo_path, get_remote_demo_sample
 from py_eddy_tracker.observations.network import NetworkObservations
 from py_eddy_tracker.observations.observation import EddiesObservations, Table
 from py_eddy_tracker.observations.tracking import TrackEddiesObservations
@@ -33,7 +33,7 @@
 
 # %%
 # Eddies files (zarr or netcdf) could be loaded with ```load_file``` method:
-eddies_collections = EddiesObservations.load_file(get_path("Cyclonic_20160515.nc"))
+eddies_collections = EddiesObservations.load_file(get_demo_path("Cyclonic_20160515.nc"))
 eddies_collections.field_table()
 # offset and scale_factor are used only when data is stored in zarr or netCDF4
 
@@ -69,7 +69,7 @@
 # - **observation_number** : Eddy temporal index in a trajectory, days starting at the eddy first detection
 # - **cost_association** : result of the cost function to associate the eddy with the next observation
 eddies_tracks = TrackEddiesObservations.load_file(
-    py_eddy_tracker_sample.get_path("eddies_med_adt_allsat_dt2018/Cyclonic.zarr")
+    py_eddy_tracker_sample.get_demo_path("eddies_med_adt_allsat_dt2018/Cyclonic.zarr")
 )
 # In this example some fields are removed (effective_contour_longitude,...) in order to save time for doc building
 eddies_tracks.field_table()
@@ -87,7 +87,7 @@
 # - previous_cost : Result of the cost function (1 is a good association, 0 is bad) with previous observation
 # - next_cost : Result of the cost function (1 is a good association, 0 is bad) with next observation
 eddies_network = NetworkObservations.load_file(
-    get_remote_sample(
+    get_remote_demo_sample(
         "eddies_med_adt_allsat_dt2018_err70_filt500_order1/Anticyclonic_network.nc"
     )
 )

examples/02_eddy_identification/pet_contour_circle.py

@@ -11,7 +11,7 @@
 
 # %%
 # Load detection files
-a = EddiesObservations.load_file(data.get_path("Anticyclonic_20190223.nc"))
+a = EddiesObservations.load_file(data.get_demo_path("Anticyclonic_20190223.nc"))
 
 # %%
 # Plot the speed and effective (dashed) contours

examples/02_eddy_identification/pet_display_id.py

@@ -11,8 +11,8 @@
 
 # %%
 # Load detection files
-a = EddiesObservations.load_file(data.get_path("Anticyclonic_20190223.nc"))
-c = EddiesObservations.load_file(data.get_path("Cyclonic_20190223.nc"))
+a = EddiesObservations.load_file(data.get_demo_path("Anticyclonic_20190223.nc"))
+c = EddiesObservations.load_file(data.get_demo_path("Cyclonic_20190223.nc"))
 
 # %%
 # Fill effective contour with amplitude

examples/02_eddy_identification/pet_eddy_detection.py

@@ -35,7 +35,9 @@ def update_axes(ax, mappable=None):
 # %%
 # Load Input grid, ADT is used to detect eddies
 g = RegularGridDataset(
-    data.get_path("dt_med_allsat_phy_l4_20160515_20190101.nc"), "longitude", "latitude"
+    data.get_demo_path("dt_med_allsat_phy_l4_20160515_20190101.nc"),
+    "longitude",
+    "latitude",
 )
 
 ax = start_axes("ADT (m)")

examples/02_eddy_identification/pet_eddy_detection_ACC.py

@@ -60,7 +60,7 @@ def set_fancy_labels(fig, ticklabelsize=14, labelsize=14, labelweight="semibold"
 margin = 30
 
 kw_data = dict(
-    filename=data.get_path("nrt_global_allsat_phy_l4_20190223_20190226.nc"),
+    filename=data.get_demo_path("nrt_global_allsat_phy_l4_20190223_20190226.nc"),
     x_name="longitude",
     y_name="latitude",
     # Manual area subset

examples/02_eddy_identification/pet_eddy_detection_gulf_stream.py

@@ -37,7 +37,7 @@ def update_axes(ax, mappable=None):
 # Load Input grid, ADT is used to detect eddies
 margin = 30
 g = RegularGridDataset(
-    data.get_path("nrt_global_allsat_phy_l4_20190223_20190226.nc"),
+    data.get_demo_path("nrt_global_allsat_phy_l4_20190223_20190226.nc"),
     "longitude",
     "latitude",
     # Manual area subset

examples/02_eddy_identification/pet_filter_and_detection.py

@@ -33,7 +33,9 @@ def update_axes(ax, mappable=None):
 # Add a new filed to store the high-pass filtered ADT
 
 g = RegularGridDataset(
-    data.get_path("dt_med_allsat_phy_l4_20160515_20190101.nc"), "longitude", "latitude"
+    data.get_demo_path("dt_med_allsat_phy_l4_20160515_20190101.nc"),
+    "longitude",
+    "latitude",
 )
 g.add_uv("adt")
 g.copy("adt", "adt_high")

examples/02_eddy_identification/pet_interp_grid_on_dataset.py

@@ -30,11 +30,13 @@ def update_axes(ax, mappable=None):
 
 # %%
 # Load detection files and data to interp
-a = EddiesObservations.load_file(data.get_path("Anticyclonic_20160515.nc"))
-c = EddiesObservations.load_file(data.get_path("Cyclonic_20160515.nc"))
+a = EddiesObservations.load_file(data.get_demo_path("Anticyclonic_20160515.nc"))
+c = EddiesObservations.load_file(data.get_demo_path("Cyclonic_20160515.nc"))
 
 aviso_map = RegularGridDataset(
-    data.get_path("dt_med_allsat_phy_l4_20160515_20190101.nc"), "longitude", "latitude"
+    data.get_demo_path("dt_med_allsat_phy_l4_20160515_20190101.nc"),
+    "longitude",
+    "latitude",
 )
 aviso_map.add_uv("adt")
 

examples/02_eddy_identification/pet_radius_vs_area.py

@@ -13,7 +13,7 @@
 
 # %%
 # Load detection files
-a = EddiesObservations.load_file(data.get_path("Anticyclonic_20190223.nc"))
+a = EddiesObservations.load_file(data.get_demo_path("Anticyclonic_20190223.nc"))
 areas = list()
 # For each contour area will be compute in local reference
 for i in a:

examples/02_eddy_identification/pet_shape_gallery.py

@@ -25,7 +25,9 @@ def build_circle(x0, y0, r):
 # %%
 # We iterate over closed contours and sort with regards of shape error
 g = RegularGridDataset(
-    data.get_path("dt_med_allsat_phy_l4_20160515_20190101.nc"), "longitude", "latitude"
+    data.get_demo_path("dt_med_allsat_phy_l4_20160515_20190101.nc"),
+    "longitude",
+    "latitude",
 )
 c = Contours(g.x_c, g.y_c, g.grid("adt") * 100, arange(-50, 50, 0.2))
 contours = dict()