logic for symmetric matrices and calculating fingerprints

for latter, if fingerprints are not already calculated

src/matbench_genmetrics/core.py

@@ -6,7 +6,6 @@
 from typing import List, Optional
 
 import numpy as np
-import pystow
 from mp_time_split.core import MPTimeSplit
 from pymatgen.core.structure import Structure
 from pystow import ensure_csv
@@ -56,10 +55,10 @@ def fib(n):
 
 IN_COLAB = "google.colab" in sys.modules
 
-FULL_COMP_SNAPSHOT_NAME = "comp_fingerprints.csv"
-DUMMY_COMP_SNAPSHOT_NAME = "dummy_comp_fingerprints.csv"
-FULL_STRUCT_SNAPSHOT_NAME = "struct_fingerprints.csv"
-DUMMY_STRUCT_SNAPSHOT_NAME = "dummy_struct_fingerprints.csv"
+FULL_COMP_NAME = "comp_fingerprints.csv"
+DUMMY_COMP_NAME = "dummy_comp_fingerprints.csv"
+FULL_STRUCT_NAME = "struct_fingerprints.csv"
+DUMMY_STRUCT_NAME = "dummy_struct_fingerprints.csv"
 
 FULL_COMP_CHECKSUM_FROZEN = "0d714081a8f0bc53af84b0ce96d3536f"
 DUMMY_COMP_CHECKSUM_FROZEN = "5630a3bfc7cbeac0cb3d7897b02aae9f"
@@ -72,7 +71,7 @@ def fib(n):
 DUMMY_STRUCT_URL = "https://figshare.com/ndownloader/files/36582177"
 
 
-MBGM_HOME = pystow.join("matbench-genmetrics")
+DATA_HOME = "matbench-genmetrics"
 
 
 class GenMatcher(object):
@@ -98,21 +97,34 @@ def __init__(
         self.match_type = match_type
         self.match_kwargs = match_kwargs
 
-        if test_structures and (gen_structures is None):
+        if gen_structures is None:
             self.gen_structures = test_structures
             self.symmetric = True
-        elif test_structures and gen_structures:
+        else:
             self.gen_structures = gen_structures
             self.symmetric = False
-        elif test_comp_fingerprints and (gen_comp_fingerprints is None):
-            self.gen_comp_fingerprints = test_comp_fingerprints
-            self.gen_struct_fingerprints = test_struct_fingerprints
-            self.symmetric = True
-        elif test_comp_fingerprints and gen_comp_fingerprints:
-            assert gen_comp_fingerprints is not None
-            self.gen_comp_fingerprints = gen_comp_fingerprints
-            self.gen_struct_fingerprints = gen_struct_fingerprints
-            self.symmetric = False
+
+        # featurize test and/or gen structures if features not provided
+        if self.match_type == "cdvae_coverage":
+            if test_comp_fingerprints is None or test_struct_fingerprints is None:
+                (
+                    self.test_comp_fingerprints,
+                    self.test_struct_fingerprints,
+                ) = featurize_comp_struct(self.test_structures)
+
+            if self.symmetric:
+                self.gen_comp_fingerprints, self.gen_struct_fingerprints = (
+                    self.test_comp_fingerprints,
+                    self.test_struct_fingerprints,
+                )
+            elif gen_comp_fingerprints is None or gen_struct_fingerprints is None:
+                (
+                    self.gen_comp_fingerprints,
+                    self.gen_struct_fingerprints,
+                ) = featurize_comp_struct(self.gen_structures)
+            else:
+                self.gen_comp_fingerprints = gen_comp_fingerprints
+                self.gen_struct_fingerprints = gen_struct_fingerprints
 
         self.num_test = len(self.test_structures)
         self.num_gen = len(self.gen_structures)
@@ -345,14 +357,24 @@ def load_fingerprints(self, dummy=False):
 
         comp_url = DUMMY_COMP_URL if dummy else FULL_COMP_URL
         struct_url = DUMMY_STRUCT_URL if dummy else FULL_STRUCT_URL
+        comp_name = DUMMY_COMP_NAME if dummy else FULL_COMP_NAME
+        struct_name = DUMMY_STRUCT_NAME if dummy else FULL_STRUCT_NAME
+
+        read_csv_kwargs = dict(index_col="material_id", sep=",")
+        self.comp_fingerprints_df = ensure_csv(
+            DATA_HOME,
+            name=comp_name,
+            url=comp_url,
+            read_csv_kwargs=read_csv_kwargs,
+        )
+        self.struct_fingerprints_df = ensure_csv(
+            DATA_HOME,
+            name=struct_name,
+            url=struct_url,
+            read_csv_kwargs=read_csv_kwargs,
+        )
 
-        self.comp_fps_df = ensure_csv(MBGM_HOME, url=comp_url)
-        self.struct_fps_df = ensure_csv(MBGM_HOME, url=struct_url)
-
-        self.comp_fingerprints = self.comp_fps_df.drop("material_id", axis=1).values
-        self.struct_fingerprints = self.struct_fps_df.drop("material_id", axis=1).values
-
-        return self.comp_fingerprints, self.struct_fingerprints
+        return self.comp_fingerprints_df, self.struct_fingerprints_df
 
     def get_train_and_val_data(self, fold, include_val=False):
 
@@ -369,11 +391,11 @@ def get_train_and_val_data(self, fold, include_val=False):
             comp_fps, struct_fps = self.load_fingerprints()
 
             self.train_comp_fingerprints, self.val_comp_fingerprints = [
-                comp_fps.iloc[tvs] for tvs in self.mpt.trainval_splits[fold]
+                comp_fps.iloc[tvs].values for tvs in self.mpt.trainval_splits[fold]
             ]
 
             self.train_struct_fingerprints, self.val_struct_fingerprints = [
-                struct_fps.iloc[tvs] for tvs in self.mpt.trainval_splits[fold]
+                struct_fps.iloc[tvs].values for tvs in self.mpt.trainval_splits[fold]
             ]
         elif self.match_type == "StructureMatcher":
             self.train_comp_fingerprints = None
@@ -596,3 +618,13 @@ def run():
 #     IN_COLAB = True
 # except ImportError:
 #     IN_COLAB = False
+
+# elif test_comp_fingerprints and (gen_comp_fingerprints is None):
+#     self.gen_comp_fingerprints = test_comp_fingerprints
+#     self.gen_struct_fingerprints = test_struct_fingerprints
+#     self.symmetric = True
+# elif test_comp_fingerprints and gen_comp_fingerprints:
+#     assert gen_comp_fingerprints is not None
+#     self.gen_comp_fingerprints = gen_comp_fingerprints
+#     self.gen_struct_fingerprints = gen_struct_fingerprints
+#     self.symmetric = False