Allow merging of config sets in dmap.

1 files changed, 43 insertions, 8 deletions

diff --git a/test/sca/test_tree.py b/test/sca/test_tree.py
index 7964173..6ef83a8 100644
--- a/test/sca/test_tree.py
+++ b/test/sca/test_tree.py
@@ -1,18 +1,37 @@
+import random
+import time
+
 from pyecsca.sca.re.tree import Tree, Map
 import pandas as pd
 
 
+def test_map():
+    cfgs = {"a", "b"}
+    binary_sets = {"a": {1, 2, 3}, "b": {2, 4}}
+    dmap = Map.from_sets(cfgs, binary_sets)
+    assert dmap.domain == [1, 2, 3, 4]
+    assert dmap.codomain == {True, False}
+    assert dmap.mapping.index.tolist() == [0, 1]
+    assert set(dmap.cfg_map.index) == cfgs
+
+    io_map = {"a": {1: 5, 2: 7}, "b": {1: 3}}
+    dmap = Map.from_io_maps(cfgs, io_map)
+    assert dmap.domain == [1, 2]
+    assert dmap.codomain == {5, 3, 7, None}
+
+
 def test_build_tree():
     cfgs = ["a", "b", "c"]
+    cfg_map = pd.DataFrame([0, 1, 2], index=cfgs, columns=["vals"])
     inputs1 = [1, 2, 3, 4]
     codomain1 = {0, 1, 3, 4, 5}
-    mapping1 = pd.DataFrame([(0, 4, 5, 0), (0, 3, 0, 0), (1, 4, 0, 0)], index=cfgs)
-    dmap1 = Map(mapping1, inputs1, codomain1)
+    mapping1 = pd.DataFrame([(0, 4, 5, 0), (0, 3, 0, 0), (1, 4, 0, 0)])
+    dmap1 = Map(mapping1, cfg_map, inputs1, codomain1)
 
     inputs2 = ["f", "e", "d"]
     codomain2 = {0, 1, 2, 3}
-    mapping2 = pd.DataFrame([(1, 0, 0), (2, 0, 0), (3, 0, 0)], index=cfgs)
-    dmap2 = Map(mapping2, inputs2, codomain2)
+    mapping2 = pd.DataFrame([(1, 0, 0), (2, 0, 0), (3, 0, 0)])
+    dmap2 = Map(mapping2, cfg_map, inputs2, codomain2)
     tree = Tree.build(set(cfgs), dmap1, dmap2)
     tree.render()
     tree.describe()
@@ -20,15 +39,31 @@ def test_build_tree():
 
 def test_expand_tree():
     cfgs = ["a", "b", "c"]
+    cfg_map = pd.DataFrame([0, 1, 2], index=cfgs, columns=["vals"])
     inputs1 = [1, 2]
     codomain1 = {0, 3, 4}
-    mapping1 = pd.DataFrame([(0, 4), (0, 3), (0, 4)], index=cfgs)
-    dmap1 = Map(mapping1, inputs1, codomain1)
+    mapping1 = pd.DataFrame([(0, 4), (0, 3), (0, 4)])
+    dmap1 = Map(mapping1, cfg_map, inputs1, codomain1)
 
     inputs2 = ["f", "e", "d"]
     codomain2 = {0, 1, 2, 3}
-    mapping2 = pd.DataFrame([(1, 0, 0), (2, 0, 0), (3, 0, 0)], index=cfgs)
-    dmap2 = Map(mapping2, inputs2, codomain2)
+    mapping2 = pd.DataFrame([(1, 0, 0), (2, 0, 0), (3, 0, 0)])
+    dmap2 = Map(mapping2, cfg_map, inputs2, codomain2)
     tree = Tree.build(set(cfgs), dmap1)
     res = tree.expand(dmap2)
     assert res.height > tree.height
+
+
+def test_df():
+    nrows = 12_000_000
+    ncols = 5
+    index = list(range(nrows))
+    df = pd.DataFrame(
+        [random.choices((True, False), k=ncols) for _ in index], index=index
+    )
+    print(df.memory_usage().sum())
+    start = time.perf_counter()
+    for row, data in df.groupby(df.columns.tolist(), as_index=False):
+        pass
+    end = time.perf_counter()
+    print(end - start)