Update

app_lib/ckde.py

@@ -31,11 +31,10 @@ class cKDE:
     def _sample(self, z, cond_idx, m):
         sample_idx = list(set(range(len(z))) - set(cond_idx))
 
-        kde, _ = self.kde(z, cond_idx)
-
         sample_z = np.tile(z, (m, 1))
-        sample_z[:, sample_idx] = kde.resample(m).T
-
+        if len(sample_idx) > 0:
+            kde, _ = self.kde(z, cond_idx)
+            sample_z[:, sample_idx] = kde.resample(m).T
         return sample_z
 
     def kde(self, z, cond_idx):

app_lib/defaults.py

@@ -7,8 +7,8 @@ SIGNIFICANCE_LEVEL_STEP = 0.01
 TAU_MAX_VALUE = 200
 TAU_MAX_STEP = 50
 
-R_VALUE = 10
+R_VALUE = 20
 R_STEP = 5
 
-CARDINALITY_VALUE = lambda concepts: int(len(concepts) / 2)
+CARDINALITY_VALUE = 1
 CARDINALITY_STEP = 1

app_lib/main.py

@@ -16,6 +16,21 @@ def _disable():
     st.session_state.disabled = True
 
 
+def _toggle_sidebar(button):
+    if button:
+        st.session_state.sidebar_state = "expanded"
+        st.experimental_rerun()
+
+
+def _preload_results(image_name):
+    if image_name != st.session_state.image_name:
+        st.session_state.image_name = image_name
+        st.session_state.tested = False
+
+    if st.session_state.image_name is not None and not st.session_state.tested:
+        st.session_state.results = load_precomputed_results(image_name)
+
+
 def main(device=torch.device("cuda" if torch.cuda.is_available() else "cpu")):
     columns = st.columns([0.40, 0.60])
 
@@ -26,13 +41,6 @@ def main(device=torch.device("cuda" if torch.cuda.is_available() else "cpu")):
 
         with image_col:
             image_name, image = get_image()
-            if image_name != st.session_state.image_name:
-                st.session_state.image_name = image_name
-                st.session_state.tested = False
-
-            if image_name is not None and not st.session_state.tested:
-                st.session_state.results = load_precomputed_results(image_name)
-
             st.image(image, use_column_width=True)
 
             change_image_button = st.button(
@@ -40,9 +48,8 @@ def main(device=torch.device("cuda" if torch.cuda.is_available() else "cpu")):
                 use_container_width=False,
                 disabled=st.session_state.disabled,
             )
-            if change_image_button:
-                st.session_state.sidebar_state = "expanded"
-                st.experimental_rerun()
+            _toggle_sidebar(change_image_button)
+
         with concepts_col:
             model_name = get_model_name()
             class_name, class_ready, class_error = get_class_name(image_name)
@@ -74,13 +81,18 @@ def main(device=torch.device("cuda" if torch.cuda.is_available() else "cpu")):
                 disabled=st.session_state.disabled or not ready,
             )
 
-        if test_button:
-            st.session_state.results = None
+    if test_button:
+        st.session_state.results = None
 
-            testing_config = get_testing_config(
-                significance_level=significance_level, tau_max=tau_max, r=r
-            )
-            test(
+        with columns[1]:
+            viz_results()
+
+        testing_config = get_testing_config(
+            significance_level=significance_level, tau_max=tau_max, r=r
+        )
+
+        with columns[0]:
+            results = test(
                 testing_config,
                 image,
                 class_name,
@@ -91,8 +103,12 @@ def main(device=torch.device("cuda" if torch.cuda.is_available() else "cpu")):
                 device=device,
             )
 
-            st.session_state.tested = True
+        st.session_state.tested = True
+        st.session_state.results = results
+        st.session_state.disabled = False
+        st.experimental_rerun()
+    else:
+        _preload_results(image_name)
 
-    with columns[1]:
-        st.header("Results")
-        viz_results()
+        with columns[1]:
+            viz_results()

app_lib/test.py

@@ -255,9 +255,4 @@ def test(
         "wealth": wealth,
     }
 
-    if with_streamlit:
-        st.session_state.results = results
-        st.session_state.disabled = False
-        st.experimental_rerun()
-    else:
-        return results
+    return results

app_lib/user_input.py

@@ -86,11 +86,11 @@ def _get_cardinality(concepts, concepts_ready):
         "Size of conditioning set",
         help=(
             "The number of concepts to condition model predictions on. "
-            "Defaults to half of the number of concepts.",
+            "Defaults to {default}."
         ),
         min_value=1,
         max_value=max(2, len(concepts) - 1),
-        value=default(concepts),
+        value=default,
         step=step,
         disabled=st.session_state.disabled or not concepts_ready,
     )
@@ -132,7 +132,7 @@ def get_image():
         if uploaded_file is not None:
             return (None, Image.open(uploaded_file))
         else:
-            DEFAULT = IMAGE_NAMES.index("ace.jpg")
+            DEFAULT = IMAGE_NAMES.index("bowl_ace.jpg")
             image_idx = image_select(
                 label="or select one",
                 images=IMAGE_PATHS,
@@ -171,7 +171,7 @@ def get_concepts(image_name=None):
             "List of concepts to test the predictions of the model with. "
             "Write one concept per line. Maximum 10 concepts allowed."
         ),
-        height=160,
+        height=180,
         value=default,
         disabled=st.session_state.disabled,
         placeholder="Type one concept\nper line",

app_lib/viz.py

@@ -15,20 +15,37 @@ def _viz_rank(results):
     sorted_tau = tau_mu[sorted_idx]
     sorted_concepts = [concepts[idx] for idx in sorted_idx]
 
-    min_size, max_size = 14, 50
-
-    _, centercol, _ = st.columns(3)
-    with centercol:
-        with st.container():
-            for concept, tau in zip(sorted_concepts, sorted_tau):
-                style = (
-                    "text-align:center;"
-                    f"font-size:{max_size - tau * (max_size - min_size)}px"
-                )
-                st.write(
-                    f"<p style='{style}'>{concept}</p>",
-                    unsafe_allow_html=True,
-                )
+    sorted_width = 1 - sorted_tau
+    sorted_width /= sorted_width.max()
+    sorted_width *= 100
+
+    m = min(len(concepts), 7)
+    nrows = np.ceil(len(sorted_concepts) / m).astype(int)
+    with st.container():
+        for i in range(nrows):
+            cols = st.columns(m)
+            for j in range(m):
+                concept_idx = i * m + j
+                if concept_idx >= len(sorted_concepts):
+                    break
+                concept = sorted_concepts[concept_idx]
+                col = cols[j]
+                with col:
+                    circle_style = f"""
+                        background: #418FDE;
+                        border-radius: 50%;
+                        width: {sorted_width[concept_idx]}%;
+                        padding-bottom: {sorted_width[concept_idx]}%;
+                    """
+                    st.markdown(
+                        f"""
+                            <p id='concept'>
+                                <strong>{concept}</strong>
+                            </p>
+                            <div style='{circle_style}'></div>
+                        """,
+                        unsafe_allow_html=True,
+                    )
 
 
 def _viz_test(results):
@@ -125,46 +142,47 @@ def _viz_wealth(results):
         annotation_position="bottom right",
     )
     fig.update_yaxes(range=[0, 1.5 * 1 / significance_level])
+    fig.update_layout(margin=dict(l=20, r=20, t=20, b=20))
     st.plotly_chart(fig, use_container_width=True)
 
 
 def viz_results():
     results = st.session_state.results
 
-    if results is None:
-        st.info("Test concepts to show results", icon="ℹ️")
-    else:
-        rank_tab, test_tab, wealth_tab = st.tabs(
-            ["Rank of importance", "Testing results", "Wealth process"]
-        )
+    st.header("Results")
+    rank_tab, test_tab, wealth_tab = st.tabs(
+        ["Rank of importance", "Testing results", "Wealth process"]
+    )
 
-        with rank_tab:
-            st.subheader("Rank of Importance")
-            st.write(
-                """
+    with rank_tab:
+        st.subheader("Rank of Importance")
+        st.write(
+            """
                 This tab visually shows the rank of importance of the specified concepts 
                 for the prediction of the model on the input image. Larger font sizes indicate 
                 higher importance. See the other two tabs for more details.
-                """
-            )
+            """
+        )
 
-            if results is not None:
-                _viz_rank(results)
-                st.divider()
+        if results is not None:
+            _viz_rank(results)
+            st.divider()
+        else:
+            st.info("Waiting for results", icon="ℹ️")
 
-        with test_tab:
-            st.subheader("Testing Results")
-            st.write(
-                """
+    with test_tab:
+        st.subheader("Testing Results")
+        st.write(
+            """
                 Importance is measured by performing sequential tests of statistical independence. 
                 This tab shows the results of these tests and how the rank of importance is computed.
                 Concepts are sorted by increasing rejection time, where a shorter rejection time indicates 
                 higher importance.
+            """
+        )
+        with st.expander("Details"):
+            st.markdown(
                 """
-            )
-            with st.expander("Details"):
-                st.markdown(
-                    """
                     Results are averaged over multiple random draws of conditioning subsets of
                     concepts. The number of tests can be controlled under `Advanced settings`.
 
@@ -172,24 +190,28 @@ def viz_results():
                     - **Rejection time**: The (normalized) average number of steps before the test is 
                     rejected for a concept.
                     - **Significance level**: The level at which the test is rejected for a concept.
-                    """
-                )
+                """
+            )
 
-            if results is not None:
-                _viz_test(results)
-                st.divider()
+        if results is not None:
+            _viz_test(results)
+            st.divider()
+        else:
+            st.info("Waiting for results", icon="ℹ️")
 
-        with wealth_tab:
-            st.subheader("Wealth Process of Testing Procedures")
-            st.markdown(
-                """
+    with wealth_tab:
+        st.subheader("Wealth Process of Testing Procedures")
+        st.markdown(
+            """
                 Sequential tests instantiate a wealth process for each concept. Once the 
                 wealth reaches a value of 1/α, the test is rejected with Type I error control at
                 level α. This tab shows the average wealth process of the testing procedures for
                 each concept.
-                """
-            )
+            """
+        )
 
-            if results is not None:
-                _viz_wealth(results)
-                st.divider()
+        if results is not None:
+            _viz_wealth(results)
+            st.divider()
+        else:
+            st.info("Waiting for results", icon="ℹ️")

assets/image_presets.json

@@ -1,52 +1,50 @@
 {
-    "ace": {
+    "bowl_ace": {
         "class_name": "cat",
         "concepts": [
-            "piano",
-            "cute",
-            "whiskers",
-            "music",
-            "wild"
+            "sink",
+            "bathroom",
+            "paws",
+            "tabby",
+            "white",
+            "soap",
+            "mirror"
         ]
     },
-    "english_springer_1": {
-        "class_name": "English springer",
-        "concepts": [
-            "spaniel",
-            "sibling",
-            "fluffy",
-            "patch",
-            "portrait"
-        ]
-    },
-    "english_springer_2": {
-        "class_name": "English springer",
+    "gardener_ace": {
+        "class_name": "cat",
         "concepts": [
-            "spaniel",
-            "fetch",
-            "fishing",
-            "trumpet",
-            "cathedral"
+            "box",
+            "plant",
+            "floor",
+            "gardening",
+            "whiskers",
+            "fur",
+            "brown"
         ]
     },
-    "french_horn": {
-        "class_name": "French horn",
+    "gentleman_ace": {
+        "class_name": "cat",
         "concepts": [
-            "trumpet",
-            "band",
-            "instrument",
-            "major",
-            "naval"
+            "lamp",
+            "chair",
+            "blue",
+            "velvet",
+            "paw",
+            "pointy ears",
+            "wooden"
         ]
     },
-    "parachute": {
-        "class_name": "parachute",
+    "mathematician_ace": {
+        "class_name": "cat",
         "concepts": [
-            "flew",
-            "descending",
-            "tandem",
-            "instrument",
-            "band"
+            "desk",
+            "book",
+            "whiskers",
+            "green eyes",
+            "paws",
+            "math",
+            "play"
         ]
     }
 }

assets/results/{ace.npy → bowl_ace.npy}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c82df211515a7d8c565c6e350d4183ba7c877d23ab03e0d639319a3429d8850b
-size 81407
+oid sha256:7f7746293f59199f6872a9570757b2d9d827c2733935cedba2c161181a1cc19c
+size 226871

assets/results/{english_springer_1.npy → gardener_ace.npy}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:81c05c7f4cc612f2afefb06a67a970001605ccfe83ddc72e2eb46cafa27773dc
-size 81414
+oid sha256:9e3e4a87d960a3591c6c97e10cc40a9e0727048118cc1d5670770bdd74e457ce
+size 226873

assets/results/{english_springer_2.npy → gentleman_ace.npy}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c2ef386512d02796f4570464e88ffaf6df8829858ad6a23836eaa7f86c6a1302
-size 81416
+oid sha256:a319ecde9c2299323692edf385274b6939c15a9d6c296aa70629898d8798934f
+size 226874

assets/results/{french_horn.npy → mathematician_ace.npy}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:467bf67d0cbf873bb8c72b0bf68906e331573920cf019b78142245d37a9fafb9
-size 81412
+oid sha256:bf0f277e9f06b957f03c39620a11514a373754b72cf1b5e97088964d07ff7b4a
+size 226873

assets/results/parachute.npy

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:33b001c2390ecdd8975fc8a39b257813a0ff7a05fc65c6a52a981581693b6a42
-size 81415

precompute_results.py

@@ -26,7 +26,7 @@ for _image_name, _image_presets in image_presets.items():
     _image = Image.open(_image_path)
     _class_name = _image_presets["class_name"]
     _concepts = _image_presets["concepts"]
-    _cardinality = defaults.CARDINALITY_VALUE(_concepts)
+    _cardinality = defaults.CARDINALITY_VALUE
 
     _results = test(
         testing_config,

style.css

@@ -39,6 +39,14 @@ h1 {
     }
 }
 
+[data-testid="stMarkdownContainer"]:has(> #concept) {
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+
+    
+}
+
 .stSpinner>div {
     display: flex;
     justify-content: center;