Merge pull request #2 from noahbenson/nyu-rebase

Nyu rebase

Author: noahbenson

Dockerfile

@@ -10,7 +10,7 @@
 # Configuration ################################################################
 
 # Start with the python 3.10 Jupyter scipy-notebook docker-image.
-FROM jupyter/scipy-notebook:python-3.10
+FROM jupyter/scipy-notebook:x86_64-python-3.10
 # Note the Maintainer.
 MAINTAINER Noah C. Benson <nben@uw.edu>
 
@@ -78,19 +78,19 @@ RUN curl -L -o /data/required_subjects/fsaverage_sym.tar.gz \
 USER $NB_USER
 # Install some stuff we are likely to need, including neuropythy.
 
-# The following line that installs jupyter_contrib_nbextensions is a
-# bug workaround; it should be replaced by just this line once the
-# bug is fixed:
-#  && conda install -y -cconda-forge ipywidgets pip jupyter_contrib_nbextensions
-RUN conda update -y -n base conda \
- && conda install -y nibabel s3fs \
- && conda install -y -cconda-forge ipywidgets pip 'jupyter_contrib_nbextensions < 0.7' 'traitlets = 5.9.0' \
- && pip install --upgrade setuptools \
- && pip install ipycanvas pyyaml neuropythy
+RUN mamba update -y -n base mamba
+RUN mamba update --all -y
+#RUN mamba install -y -cconda-forge nibabel s3fs
+RUN mamba install -y -cconda-forge \
+          ipywidgets pip traitlets webcolors jsonschema-with-format-nongpl
+RUN pip install --upgrade setuptools
+RUN pip install ipycanvas pyyaml neuropythy nibabel s3fs
+RUN pip install diplib
 # Install collapsible cell extensions...
-RUN jupyter contrib nbextension install --user \
- && jupyter nbextension enable collapsible_headings/main \
- && jupyter nbextension enable select_keymap/main
+#RUN mamba install -cconda-forge jupyter_contrib_nbextensions \
+# && jupyter contrib nbextension install --user \
+# && jupyter nbextension enable collapsible_headings/main \
+# && jupyter nbextension enable select_keymap/main
 RUN mkdir -p /home/$NB_USER/.jupyter/custom
 # Copy the config directory's requirements over and install them.
 COPY config/requirements.txt /build/

config/config.yaml

@@ -112,11 +112,12 @@ targets:
   # from the sections above.
   cortex: |
     # Extract the subject object and the hsmisphere name.
+    sid = target['Subject ID']
     sub = target['subject']
     h = target['Hemisphere'].lower()
     # Load retinotopic mapping data from the label directory, where these data
     # are stored on the NSD repository.
-    label_path = nsd_path.subpath('freesurfer', sub, 'label')
+    label_path = nsd_path.subpath('freesurfer', sid, 'label')
     props = {
         k: ny.load(label_path.subpath(f'{h}.{filename}'))
         for (k,filename) in nsd_prf_files.items()}
@@ -284,3 +285,65 @@ figures:
                    cmap='hot', vmin=0, vmax=100)
   curvature: |
     ny.cortex_plot(target['flatmap'], axes=axes)
+
+review: |
+  #from annotate import watershed_contours
+  #im = watershed_contours(annotations.values(), max_depth=1)
+  #axes.imshow(im, cmap='hsv', vmin=0, vmax=1.5*np.max(im))
+  import numpy as np
+  # V1:
+  v1uvm = annotations['V1 UVM (ventral)']
+  v1lvm = annotations['V1 LVM (dorsal)']
+  v1per = annotations['V1 Periphery']
+  v1pol = np.vstack([v1uvm, v1per, np.flipud(v1lvm)])
+  # V2:
+  v2uvm = annotations['V2 UVM (ventral)']
+  v2lvm = annotations['V2 LVM (dorsal)']
+  v2pev = annotations['V2 Ventral Periphery']
+  v2ped = annotations['V2 Dorsal Periphery']
+  v2pol = np.vstack(
+      [v2uvm, v2pev, np.flipud(v1uvm), v1lvm, np.flipud(v2ped), np.flipud(v2lvm)])
+  # V3:
+  v3uvm = annotations['V3 UVM (ventral)']
+  v3lvm = annotations['V3 LVM (dorsal)']
+  v3pev = annotations['V3 Ventral Periphery']
+  v3ped = annotations['V3 Dorsal Periphery']
+  v3pol = np.vstack(
+      [v3uvm, v3pev, np.flipud(v2uvm), v2lvm, np.flipud(v3ped), np.flipud(v3lvm)])
+  # Turn these into traces:
+  fmap = target['flatmap']
+  v1_trace = ny.path_trace(fmap, v1pol.T, closed=True)
+  v2_trace = ny.path_trace(fmap, v2pol.T, closed=True)
+  v3_trace = ny.path_trace(fmap, v3pol.T, closed=True)
+  # Convert the path traces into paths then into labels:
+  cortex = target['cortex']
+  v1_path = v1_trace.to_path(cortex)
+  v2_path = v2_trace.to_path(cortex)
+  v3_path = v3_trace.to_path(cortex)
+  v1 = v1_path.label > 0.5
+  v2 = v2_path.label > 0.5
+  v3 = v3_path.label > 0.5
+  if np.sum(v1) > np.sum(~v1):
+    v1 = ~v1
+  if np.sum(v2) > np.sum(~v2):
+    v2 = ~v2
+  if np.sum(v3) > np.sum(~v3):
+    v3 = ~v3
+  labels = np.zeros(cortex.vertex_count, dtype=int)
+  labels[v1] = 1
+  labels[v2] = 2
+  labels[v3] = 3
+  fmap_labels = labels[fmap.labels]
+  # If the user saves the contours, we want to save these labels.
+  save_hooks['v123-labels.mgz'] = lambda filename: ny.save(filename, labels)
+  # Plot the results:
+  ny.cortex_plot(
+      fmap,
+      color=fmap_labels,
+      cmap='rainbow',
+      mask=(fmap_labels > 0),
+      axes=axes,
+      alpha=0.5)
+  axes.axis('equal')
+  axes.axis('off')
+

src/annotate/__init__.py

@@ -18,7 +18,7 @@
 
 # Imports ######################################################################
 
-from ._util import (delay, ldict)
+from ._util import (delay, ldict, watershed_contours)
 from ._core import AnnotationTool
 
 

src/annotate/_config.py

@@ -511,6 +511,50 @@ def __init__(self, yaml, init, all_figures):
                                                       init)
         # Same these into the dictionary.
         self.update(res)
+class ReviewConfig:
+    """An object that stores the configuration of the review panel.
+
+    The `ReviewConfig` type stores information from the `review` section of the
+    `config.yaml` file for the `cortex-annotate` project. This section stores
+    only a function that generates the figure to plot in the `Review` tab of the
+    display panel. The review function requires the arguments `target`,
+    `annotations`, `figure`, and `axes`, and it must draw the desired graphics
+    on the given matplotlib axes. The `annotations` argument is a dictionary
+    whose keys are the annotation names and whose values are the drawn
+    annotation. Annotations may be missing if the user opens the review tab
+    before completing the annotations. If an error is raised from this function,
+    then the error message is printed to the display.
+    """
+    __slots__ = ('code', 'function', 'figsize', 'dpi')
+    @staticmethod
+    def _compile(code, initcfg):
+        return _compile_fn(
+            "target, annotations, figure, axes, save_hooks",
+            f"{code}\n",
+            initcfg)
+    def __init__(self, yaml, init):
+        if yaml is None:
+            self.code = None
+            self.function = None
+            self.figsize = None
+            self.dpi = None
+            return
+        elif isinstance(yaml, str):
+            yaml = {'function': yaml}
+        elif not isinstance(yaml, dict):
+            raise ConfigError(
+                "review",
+                "review section must contain a Python code string or a dict",
+                yaml)
+        self.code = yaml.get('function')
+        if self.code is None:
+            raise ConfigError(
+                "review",
+                "review section must contain the key function",
+                yaml)
+        self.figsize = yaml.get('figsize', (3,3))
+        self.dpi = yaml.get('dpi', 256)
+        self.function = ReviewConfig._compile(self.code, init)
 class Config:
     """The configuration object for the `cortex-annotate` project.
 
@@ -521,8 +565,9 @@ class Config:
     not recognized by `Config` are not parsed, but they are available in the
     `Config.yaml` member variable.
     """
-    __slots__ = ('config_path', 'yaml', 'display', 'init', 'targets', 'figures',
-                 'annotations', 'builtin_annotations', 'annotation_types')
+    __slots__ = (
+        'config_path', 'yaml', 'display', 'init', 'targets', 'figures',
+        'annotations', 'builtin_annotations', 'review', 'annotation_types')
     def __init__(self, config_path='/config/config.yaml'):
         self.config_path = config_path
         with open(config_path, 'rt') as f:
@@ -534,15 +579,20 @@ def __init__(self, config_path='/config/config.yaml'):
         # Parse the targets section.
         self.targets = TargetsConfig(self.yaml.get('targets', None), self.init)
         # Parse the annotations section.
-        self.annotations = AnnotationsConfig(self.yaml.get('annotations', None),
-                                             self.init)
+        self.annotations = AnnotationsConfig(
+            self.yaml.get('annotations', None),
+            self.init)
         # Parse the builtin_annotations section.
         self.builtin_annotations = BuiltinAnnotationsConfig(
             self.yaml.get('builtin_annotations', None),
             self.init)
         # Parse the figures section.
-        self.figures = FiguresConfig(self.yaml.get('figures', None), self.init,
-                                     self.annotations.all_figures)
+        self.figures = FiguresConfig(
+            self.yaml.get('figures', None),
+            self.init,
+            self.annotations.all_figures)
+        # Parse the review section.
+        self.review = ReviewConfig(self.yaml.get('review', None), self.init)
         # Make the annotation types dictionary.
         d = self.annotations.types.copy()
         d.update(self.builtin_annotations.types)

src/annotate/_control.py

@@ -333,11 +333,31 @@ def __init__(self, state,
         self.imagesize_slider = self._make_imagesize_slider(imagesize)
         self.selection_panel = SelectionPanel(state)
         self.style_panel = StylePanel(state)
+        self.review_button = ipw.Button(
+            description='Review',
+            button_style='',
+            tooltip='Review the annotations.')
         self.save_button = ipw.Button(
             description='Save',
             button_style='',
-            tooltip='Save all annotations and preferences.',
-            layout={'margin':"3% 33% 3% 33%", "width": "34%"})
+            tooltip='Save all annotations and preferences.')
+        self.edit_button = ipw.Button(
+            description='Edit',
+            button_style='',
+            tooltip='Continue editing annotation.')
+        if state.config.review.function is not None:
+            buttons = [self.review_button, self.save_button, self.edit_button]
+            self.review_button.disabled = False
+            self.save_button.disabled = True
+            self.edit_button.disabled = True
+            layout = {'margin':"3% 3% 3% 3%", "width": "94%"}
+        else:
+            buttons = [self.save_button]
+            self.review_button.disabled = True
+            self.save_button.disabled = False
+            self.edit_button.disabled = True
+            layout = {'margin':"3% 33% 3% 33%", "width": "34%"}
+        self.button_box = ipw.HBox(buttons, layout=layout)
         self.info_message = self._make_infomsg()
         hline = self._make_hline()
         self.vbox_children = [
@@ -348,7 +368,7 @@ def __init__(self, state,
             hline,
             self.style_panel,
             hline,
-            self.save_button,
+            self.button_box,
             hline,
             self.info_message]
         vbox_layout = {'width': '250px'}
@@ -433,10 +453,24 @@ def observe_imagesize(self, fn):
     def observe_save(self, fn):
         """Registers the argument to be called when the save button is clicked.
         
-        The function is called with a single argument, which is the save buttom
+        The function is called with a single argument, which is the save button
         instance.
         """
         self.save_button.on_click(fn)
+    def observe_review(self, fn):
+        """Registers the argument to be called when the save button is clicked.
+        
+        The function is called with a single argument, which is the review
+        button instance.
+        """
+        self.review_button.on_click(fn)
+    def observe_edit(self, fn):
+        """Registers the argument to be called when the edit button is clicked.
+        
+        The function is called with a single argument, which is the edit button
+        instance.
+        """
+        self.edit_button.on_click(fn)
     @property
     def target(self):
         """Compute the current target selection."""