Update publication codes and figures

.github/workflows/deploy_streamlit.yaml

@@ -0,0 +1,33 @@
+name: Deploy streamlit docker to Azure
+on: [] # [push, pull_request]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Login to Azure
+        uses: azure/login@v1
+        with:
+          creds: ${{ secrets.AZURE_CREDENTIALS }}
+      - name: Build and push
+        uses: azure/docker-login@v1
+        with:
+          login-server: ${{ secrets.REGISTRY_LOGIN_SERVER }}
+          username: ${{ secrets.REGISTRY_USERNAME }}
+          password: ${{ secrets.REGISTRY_PASSWORD }}
+      - run: |
+          docker build . -t ${{ secrets.REGISTRY_LOGIN_SERVER }}/marsilea:${{ github.sha }}
+          docker push ${{ secrets.REGISTRY_LOGIN_SERVER }}/marsilea:${{ github.sha }}
+
+      - name: Deploy to Azure Web App
+        uses: azure/webapps-deploy@v2
+        with:
+          resource-group: ${{ secrets.RESOURCE_GROUP }}
+          dns-name-label: ${{ secrets.RESOURCE_GROUP }}${{ github.run_number }}
+          image: ${{ secrets.REGISTRY_LOGIN_SERVER }}/marsilea:${{ github.sha }}
+          registry-login-server: ${{ secrets.REGISTRY_LOGIN_SERVER }}
+          registry-username: ${{ secrets.REGISTRY_USERNAME }}
+          registry-password: ${{ secrets.REGISTRY_PASSWORD }}
+          name: marsilea
+          location: 'west us'

examples/plot_available_plotters.py

@@ -15,37 +15,63 @@
 
 from marsilea.layers import Rect, RightTri, FrameRect, FracRect
 
+# sphinx_gallery_start_ignore
+import mpl_fontkit as fk
+
+fk.install("Lato", verbose=False)
+
+# sphinx_gallery_end_ignore
+
+def label_ax(ax, text):
+    ax.text(1.05, .5, text, transform=ax.transAxes,
+            ha="left", va="center")
+
+
+# sphinx_gallery_start_ignore
+from pathlib import Path
+
+save_path = Path(__file__).parent / "imgs"
+plt.rcParams['svg.fonttype'] = 'none'
+# sphinx_gallery_end_ignore
+
+
 # %%
 # Mesh plotters
 plt.ion()
 rng = np.random.default_rng(0)
 data = np.arange(5)
 data2d = np.arange(5).reshape(1, 5)
 pieces = {
-    0: FrameRect(color="g", label="2"),
-    1: Rect(color="g", label="2"),
-    2: RightTri(color="g", label="3"),
-    3: FracRect(color="b", label="3"),
-    4: RightTri(color="b", label="3", right_angle="upper right"),
+    0: FrameRect(color="#7E2E84", width=2),
+    1: Rect(color="#D14081"),
+    2: RightTri(color="#EF798A"),
+    3: FracRect(color="#F9F5E3", frac=(.5, .5)),
+    4: RightTri(color="#CCF5AC", right_angle="upper right"),
 }
 
 plotters = {
     "Color Mesh": mp.ColorMesh(data2d, cmap="Blues"),
-    "Sized Mesh": mp.SizedMesh(data2d, sizes=(100, 500), cmap="Greens"),
-    "Marker Mesh": mp.MarkerMesh(data2d >= 2, size=300, marker="*", color="red"),
+    "Sized Mesh": mp.SizedMesh(data2d, sizes=(100, 500), color="#A05F96"),
+    "Marker Mesh": mp.MarkerMesh(data2d > 0, size=300, marker="x", color="#AAD9BB"),
     "Layers Mesh": ma.layers.LayersMesh(data2d, pieces=pieces),
 }
 
 canvas = ma.Heatmap(data2d, width=5, height=0, cmap="Oranges", label="Color Mesh")
 for title, plotter in plotters.items():
-    plotter.set_label(title, "right")
-    canvas.add_bottom(plotter)
+    canvas.add_bottom(plotter, name=title)
 
-canvas.add_dendrogram("bottom", method="ward", colors="#FFDD95")
+canvas.add_dendrogram("bottom", method="ward", colors="#1D2B53", name="Dendrogram")
 canvas.render()
 
-for ax in canvas.figure.get_axes():
+for title in list(plotters.keys()) + ["Dendrogram"]:
+    ax = canvas.get_ax(title)
     ax.set_axis_off()
+    label_ax(ax, title)
+
+# sphinx_gallery_start_ignore
+if '__file__' in globals():
+    plt.savefig(save_path / "all_plotters_mesh.svg", bbox_inches="tight")
+# sphinx_gallery_end_ignore
 
 # %%
 # Label plotters
@@ -64,35 +90,44 @@
         text_color.append(".1")
 matrix = rng.standard_normal((1, 100))
 canvas2 = ma.Heatmap(matrix, width=5, height=.1)
-canvas2.add_top(mp.Labels(text, text_props={'color': text_color}, rotation=0, label="Labels"))
-canvas2.add_bottom(mp.AnnoLabels(labels, mark=[3, 4, 5, 96, 97, 98], rotation=0))
+canvas2.add_top(mp.Labels(text, text_props={'color': text_color}, rotation=0), name="Labels")
+canvas2.add_bottom(mp.AnnoLabels(labels, mark=[3, 4, 5, 96, 97, 98], rotation=0), name="AnnoLabels")
 canvas2.render()
 
+for title in ["Labels", "AnnoLabels"]:
+    ax = canvas2.get_ax(title)
+    label_ax(ax, title)
+
+# sphinx_gallery_start_ignore
+if '__file__' in globals():
+    plt.savefig(save_path / "all_plotters_label.svg", bbox_inches="tight")
+# sphinx_gallery_end_ignore
 
 # %%
 # Statistics plotters
 
 data1d = np.arange(1, 6)
 data2d = rng.integers(1, 10, size=(10, 5))
-bar_width = .6
+bar_width = .5
 
 plotters = {
     "Simple Bar": mp.Numbers(data1d, color="#756AB6", width=bar_width),
     "Bar": mp.Bar(data2d, color="#5F8670", width=bar_width),
     "Boxen": mp.Boxen(data2d, color="#FFB534", width=bar_width),
     "Violin": mp.Violin(rng.standard_normal((20, 5)), color="#65B741"),
-    "Point": mp.Point(data2d, color="#4CB9E7"),
-    "Strip": mp.Strip(data2d, color="#FF004D"),
-    "Swarm": mp.Swarm(data2d, color="#647D87"),
+    "Point": mp.Point(data2d, color="#656176"),
+    "Strip": mp.Strip(rng.standard_normal((50, 5)), color="#FF004D"),
+    "Swarm": mp.Swarm(rng.standard_normal((50, 5)), color="#647D87"),
     "Stacked Bar": mp.StackBar(rng.integers(1, 10, (5, 5)), items="abcde", width=bar_width),
     "Center Bar": mp.CenterBar(rng.integers(1, 10, (5, 2)), colors=["#EE7214", "#527853"], width=bar_width),
 }
 
 canvas3 = ma.Heatmap(rng.standard_normal((10, 5)), width=4, height=0)
 for title, plotter in plotters.items():
-    plotter.allow_labeling = True
-    plotter.set_label(title, "right")
-    canvas3.add_bottom(plotter, pad=.3, size=2, name=title)
+    size = 1
+    if title in ["Violin", "Strip", "Swarm"]:
+        size = 1.5
+    canvas3.add_bottom(plotter, pad=.1, size=size, name=title)
 
 canvas3.vsplit(cut=[2])
 canvas3.add_bottom(mp.Chunk(["Lower", "Upper"], ["#FFDD95", "#FFB000"], padding=10))
@@ -104,19 +139,35 @@
         ax.spines[dir].set_visible(False)
     ax.tick_params(left=False, labelleft=False)
 
-# for title in plotters.keys():
-#     ax = canvas3.get_ax(title)[0]
-#     ax.text(-.1, .5, title, transform=ax.transAxes, fontsize=14, ha="right", va="center")
+for title in plotters.keys():
+    ax = canvas3.get_ax(title)[-1]
+    label_ax(ax, title)
+
+# sphinx_gallery_start_ignore
+if '__file__' in globals():
+    plt.savefig(save_path / "all_plotters_stat.svg", bbox_inches="tight")
+# sphinx_gallery_end_ignore
 
 
 # %%
 # Other plotters
 matrix = pd.DataFrame(data=rng.integers(1, 10, (4, 5)), index=list("ACGT"))
-colors = {"A": "r", "C": "b", "G": "g", "T": "black"}
+colors = {"A": "#D81159", "C": "#218380", "G": "#FBB13C", "T": "#73D2DE"}
+weights = rng.integers(1, 10, 4)
 seqlogo = mp.SeqLogo(matrix, color_encode=colors)
-arc = mp.Arc([1, 2, 3, 4, 5], [(1, 5), (2, 3), (1, 2), (4, 5)], width=1, colors="#FF004D")
+arc = mp.Arc([1, 2, 3, 4, 5], [(1, 5), (2, 3), (1, 2), (4, 5)],
+             weights=weights, width=(2, 5), colors="#534D56")
 
 canvas4 = ma.Heatmap(rng.standard_normal((10, 5)), width=4, height=0)
-canvas4.add_top(seqlogo, size=2)
-canvas4.add_top(arc, size=1, pad=.2)
+canvas4.add_top(seqlogo, size=2, name="Sequence Logo")
+canvas4.add_top(arc, size=1, pad=.2, name="Arc Diagram")
 canvas4.render()
+
+for title in ["Sequence Logo", "Arc Diagram"]:
+    ax = canvas4.get_ax(title)
+    label_ax(ax, title)
+
+# sphinx_gallery_start_ignore
+if '__file__' in globals():
+    plt.savefig(save_path / "all_plotters_other.svg", bbox_inches="tight")
+# sphinx_gallery_end_ignore

examples/plot_mouse_embryo.py

@@ -17,7 +17,98 @@
 
 # sphinx_gallery_start_ignore
 import mpl_fontkit as fk
+
 fk.install("Lato", verbose=False)
+
+
+class Transforms:
+    """
+    Holds transformation matrices.
+    All the details for transformation matrices can be found at: https://arxiv.org/pdf/1711.10662.pdf.
+    """
+
+    @staticmethod
+    def rgb_to_lms():
+        """
+        Matrix for RGB color-space to LMS color-space transformation.
+        """
+        return np.array([[17.8824, 43.5161, 4.11935],
+                         [3.45565, 27.1554, 3.86714],
+                         [0.0299566, 0.184309, 1.46709]]).T
+
+    @staticmethod
+    def lms_to_rgb() -> np.ndarray:
+        """
+        Matrix for LMS colorspace to RGB colorspace transformation.
+        """
+        return np.array([[0.0809, -0.1305, 0.1167],
+                         [-0.0102, 0.0540, -0.1136],
+                         [-0.0004, -0.0041, 0.6935]]).T
+
+    @staticmethod
+    def lms_protanopia_sim(degree: float = 1.0) -> np.ndarray:
+        """
+        Matrix for Simulating Protanopia colorblindness from LMS color-space.
+        :param degree: Protanopia degree.
+        """
+        return np.array([[1 - degree, 2.02344 * degree, -2.52581 * degree],
+                         [0, 1, 0],
+                         [0, 0, 1]]).T
+
+    @staticmethod
+    def lms_deutranopia_sim(degree: float = 1.0) -> np.ndarray:
+        """
+        Matrix for Simulating Deutranopia colorblindness from LMS color-space.
+        :param degree: Deutranopia degree.
+        """
+        return np.array([[1, 0, 0],
+                         [0.494207 * degree, 1 - degree, 1.24827 * degree],
+                         [0, 0, 1]]).T
+
+    @staticmethod
+    def lms_tritanopia_sim(degree: float = 1.0) -> np.ndarray:
+        """
+        Matrix for Simulating Tritanopia colorblindness from LMS color-space.
+        :param degree: Tritanopia degree.
+        """
+        return np.array([[1, 0, 0],
+                         [0, 1, 0],
+                         [-0.395913 * degree, 0.801109 * degree, 1 - degree]]).T
+
+    @staticmethod
+    def hybrid_protanomaly_deuteranomaly_sim(degree_p: float = 1.0, degree_d: float = 1.0) -> np.ndarray:
+        """
+        Matrix for Simulating Hybrid Colorblindness (protanomaly + deuteranomaly) from LMS color-space.
+        :param degree_p: protanomaly degree.
+        :param degree_d: deuteranomaly degree.
+        """
+        return np.array([[1 - degree_p, 2.02344 * degree_p, -2.52581 * degree_p],
+                         [0.494207 * degree_d, 1 - degree_d, 1.24827 * degree_d],
+                         [0, 0, 1]]).T
+
+
+def simulate_colorblind(
+        image_rgb: np.ndarray,
+        sim_type='protan',
+        degree: float | tuple = 1.0
+) -> np.ndarray:
+    img_lms = np.dot(image_rgb[:, :, :3], Transforms.rgb_to_lms())
+
+    if sim_type == 'protan':
+        transform = Transforms.lms_protanopia_sim(degree)
+    elif sim_type == 'deutan':
+        transform = Transforms.lms_deutranopia_sim(degree)
+    elif sim_type == 'tritan':
+        transform = Transforms.lms_tritanopia_sim(degree)
+    else:
+        transform = Transforms.hybrid_protanomaly_deuteranomaly_sim(degree, degree)
+
+    img_lms_sim = np.dot(img_lms, transform)
+    img_rgb_sim = np.uint8(np.dot(img_lms_sim, Transforms.lms_to_rgb()) * 255)
+
+    return img_rgb_sim
+
+
 # sphinx_gallery_end_ignore
 
 embryo = ma.load_data('mouse_embryo')
@@ -83,7 +174,8 @@ def get_xy_hist(ct):
 
 # Draw cell
 ax = b.get_main_ax()
-ax.scatter(embryo['cell_x'], embryo['cell_y'], s=1, c=embryo['colors'])
+points = ax.scatter(embryo['cell_x'], embryo['cell_y'], s=1, c=embryo['colors'])
+points.set_rasterized(True)
 ax.set_xlim(xstart, xend)
 ax.set_ylim(ystart, yend)
 ax.set_title("Mouse Embryo E12.5")
@@ -106,12 +198,15 @@ def get_xy_hist(ct):
     y_ax.set_axis_off()
     y_ax.text(0.5, 0, n, va="top", ha="center", rotation=90, transform=y_ax.transAxes)
 
+
+#%%
 # sphinx_gallery_start_ignore
 if '__file__' in globals():
     from pathlib import Path
     import matplotlib.pyplot as plt
 
+    plt.rcParams['svg.fonttype'] = 'none'
     save_path = Path(__file__).parent / "imgs"
     plt.savefig(save_path / "mouse_embryo.svg", bbox_inches="tight")
+    plt.savefig(save_path / "mouse_embryo.png", dpi=300, bbox_inches="tight")
 # sphinx_gallery_end_ignore
-

examples/plot_oil_well.py

@@ -80,6 +80,7 @@
     from pathlib import Path
     import matplotlib.pyplot as plt
 
+    plt.rcParams['svg.fonttype'] = 'none'
     save_path = Path(__file__).parent / "imgs"
     plt.savefig(save_path / "oil_well.svg", bbox_inches="tight")
 # sphinx_gallery_end_ignore

examples/plot_oncoprint.py

@@ -102,6 +102,7 @@
 if '__file__' in globals():
     from pathlib import Path
     import matplotlib.pyplot as plt
+    plt.rcParams['svg.fonttype'] = 'none'
     save_path = Path(__file__).parent / "imgs"
     plt.savefig(save_path / "oncoprint.svg", bbox_inches="tight")
 # sphinx_gallery_end_ignore