Port to using GMT_DATA from qcore

pygmt_helper/examples/ds_sources.py

@@ -1,15 +1,13 @@
 from pathlib import Path
 
-import pygmt
-import pandas as pd
 import numpy as np
+import pandas as pd
+import pygmt
 
 from pygmt_helper import plotting
 
-
 # Config
 ds_ffp = Path(__file__).parent / "resources" / "NZ_DSmodel_2015.txt"
-map_data_ffp = Path("path to qcore/qcore/data")
 output_dir = Path("path to the output directory")
 
 
@@ -26,7 +24,7 @@
 ds_df["lon"] = split_ids[:, 1]
 
 # Plotting data
-map_data = plotting.NZMapData.load(map_data_ffp) if map_data_ffp is not None else None
+map_data = plotting.NZMapData.load()
 
 if incl_rec_prob:
     sum_df = (

pygmt_helper/examples/event_stations.py

@@ -22,14 +22,11 @@
 inset_region = [172.60, 172.69, -43.545, -43.495]
 # Output file name
 output_ffp = Path("path to the output file")
-# Path to the map data
-# Is part of the qcore package, once installed it
-# can be found under qcore/qcore/data
-# Set to None for lower quality map, but much faster plotting time
-map_data_ffp = None
+# If true, then use New Zealand specific map data
+use_map_data = True
 # If true, then use the high resolution topography
 # This will further increase plot time, and only has an
-# effect if map_data_ffp is set
+# effect if use_map_data is set
 use_high_res_topo = True
 # List of events to highlight
 events_to_highlight = None
@@ -66,11 +63,7 @@
 
 
 # Load map data
-map_data = (
-    None
-    if map_data_ffp is None
-    else plotting.NZMapData.load(map_data_ffp, high_res_topo=use_high_res_topo)
-)
+map_data = plotting.NZMapData.load(high_res_topo=use_high_res_topo) if use_map_data else None
 
 # Generate the figure
 fig = plotting.gen_region_fig(

pygmt_helper/examples/fault_traces.py

@@ -1,15 +1,13 @@
 from pathlib import Path
 
-import pandas as pd
 import numpy as np
-
+import pandas as pd
 from qcore import nhm
-from pygmt_helper import plots
-from pygmt_helper import plotting
+
+from pygmt_helper import plots, plotting
 
 # Config
 nhm_ffp = Path("path to nhm file")
-map_data_ffp = Path("path to qcore/qcore/data")
 output_dir = Path("path to the output directory")
 
 # If true, then for each CS fault
@@ -20,7 +18,7 @@
 nhm_data = nhm.load_nhm(str(nhm_ffp))
 
 # Load plotting data
-map_data = plotting.NZMapData.load(map_data_ffp)
+map_data = plotting.NZMapData.load()
 
 # Load the source information
 cybershake_df = pd.read_csv(

pygmt_helper/examples/ratio.py

@@ -2,16 +2,14 @@
 
 from pathlib import Path
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 from pygmt_helper import plotting
 
 site_ffp = Path(__file__).parent / "resources"
 
 # Config
-# map_data_ffp = Path("path to qcore/qcore/data")
-map_data_ffp = Path("/Users/claudy/dev/work/code/qcore/qcore/data")
 site_locations = (
     Path(__file__).parent
     / "resources"
@@ -30,7 +28,7 @@
 )
 
 # Load plotting data
-map_data = plotting.NZMapData.load(map_data_ffp)
+map_data = plotting.NZMapData.load()
 
 # Add some fake data
 df["ratio"] = np.random.uniform(-0.5, 0.5, df.shape[0])

pygmt_helper/examples/srf.py

@@ -7,11 +7,10 @@
 
 import numpy as np
 import pandas as pd
+from qcore import srf
 
 from pygmt_helper import plotting
-from qcore import srf
 
-map_data_ffp = Path("/path/to/qcore/qcore/data")
 output_dir = Path("/path/to/output_dir")
 
 srf_ffp = Path(__file__).parent / "resources" / "Akatarawa.srf"
@@ -23,7 +22,7 @@
 slip_values = srf.srf2llv_py(str(srf_ffp), value="slip")
 
 # Set map_data to None for faster plotting without topography
-map_data = plotting.NZMapData.load(map_data_ffp, high_res_topo=False)
+map_data = plotting.NZMapData.load(high_res_topo=False)
 # map_data = None
 
 # Compute colormap limits

pygmt_helper/plots.py

@@ -212,7 +212,7 @@ def im_plots(
     output_dir: Path,
     rel_name: Optional[str] = None,
     nhm_ffp: Optional[Path] = None,
-    qcore_data_dir: Optional[Path] = None,
+    nz_map_data: Optional[plotting.NZMapData] = None,
     cb_limits_dict: Optional[dict[str, tuple[float, float]]] = None,
     n_procs: int = 1,
 ) -> None:
@@ -233,8 +233,8 @@ def im_plots(
         If provided, the function will generate plots for a specific realization (run) identified by this name.
     nhm_ffp : Path, optional
         Path to the NHM file, which can provide fault trace information.
-    qcore_data_dir : Path, optional
-        Path to the directory containing QCore data used for NZ map generation.
+    nz_map_data: Optional[NZMapData], default=None
+        The NZMapData object to supply topographic data.
     cb_limits_dict : dict, optional
         A dictionary specifying the color bar limits for each intensity measure (IM). If None, limits will be automatically computed.
     n_procs : int, optional
@@ -245,9 +245,6 @@ def im_plots(
     None
         This function saves the generated plots to the specified output directory and does not return any values.
     """
-    nz_map_data = (
-        None if qcore_data_dir is None else plotting.NZMapData.load(qcore_data_dir)
-    )
 
     # Load the trace if possible
     fault_trace = (

pygmt_helper/plotting.py

@@ -10,6 +10,7 @@
 import pandas as pd
 import pygmt
 import xarray as xr
+from qcore import gmt
 from scipy import interpolate
 from shapely import geometry
 
@@ -25,13 +26,11 @@ class NZMapData(NamedTuple):
     topo_shading_grid: xr.DataArray = None
 
     @classmethod
-    def load(cls, qcore_data_dir: Path, high_res_topo: bool = False) -> Self:
+    def load(cls, high_res_topo: bool = False) -> Self:
         """Load NZMapData from qcore resources.
 
         Parameters
         ----------
-        qcore_data_dir : Path
-            Path to qcore data directory.
         high_res_topo : bool
             If True, load high resolution topographic data.
 
@@ -40,17 +39,17 @@ def load(cls, qcore_data_dir: Path, high_res_topo: bool = False) -> Self:
         NZMapData
             A map data object containing the paths to the map data.
         """
-        road_ffp = qcore_data_dir / "Paths/road/NZ.gmt"
-        highway_ffp = qcore_data_dir / "Paths/highway/NZ.gmt"
-        coastline_ffp = qcore_data_dir / "Paths/coastline/NZ.gmt"
-        water_ffp = qcore_data_dir / "Paths/water/NZ.gmt"
+        road_ffp = gmt.GMT_DATA.fetch("data/Paths/road/NZ.gmt")
+        highway_ffp = gmt.GMT_DATA.fetch("data/Paths/highway/NZ.gmt")
+        coastline_ffp = gmt.GMT_DATA.fetch("data/Paths/coastline/NZ.gmt")
+        water_ffp = gmt.GMT_DATA.fetch("data/Paths/water/NZ.gmt")
 
         if high_res_topo:
-            topo_ffp = qcore_data_dir / "Topo/srtm_NZ_1s.grd"
-            topo_shading_ffp = qcore_data_dir / "Topo/srtm_NZ_1s_i5.grd"
+            topo_ffp = gmt.GMT_DATA.fetch("data/Topo/srtm_NZ_1s.grd")
+            topo_shading_ffp = gmt.GMT_DATA.fetch("data/Topo/srtm_NZ_1s_i5.grd")
         else:
-            topo_ffp = qcore_data_dir / "Topo/srtm_NZ.grd"
-            topo_shading_ffp = qcore_data_dir / "Topo/srtm_NZ_i5.grd"
+            topo_ffp = gmt.GMT_DATA.fetch("data/Topo/srtm_NZ.grd")
+            topo_shading_ffp = gmt.GMT_DATA.fetch("data/Topo/srtm_NZ_i5.grd")
 
         return cls(
             road_df=geopandas.read_file(road_ffp),
@@ -372,7 +371,7 @@ def plot_grid(
         phase = f"+{cmap_limits[0]}" if cmap_limits[0] > 0 else f"+{cmap_limits[1]}"
         cb_frame = [f"a+{cmap_limits[2] * 2}{phase}f+{cmap_limits[2]}"]
         if cb_label is not None:
-            cb_frame.append(f'x+l"{cb_label}"')
+            cb_frame.append(f"x+l{cb_label.replace(' ', r'\040')}")
         fig.colorbar(
             cmap=cpt_ffp,
             frame=cb_frame,