Hackathon

CP5/active_plugins/DumpIt.py

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+import cellprofiler_core.module
+from cellprofiler_core.setting.subscriber import ImageSubscriber
+from cellprofiler_core.setting.text import ImageName
+from cellprofiler_core.setting.text import Text
+from cellprofiler_core.setting import Binary
+from cellprofiler_core.setting import Color
+
+__doc__ = """\
+DumpIt
+======
+
+**DumpIt** does nothing of interest yet.
+
+
+I am a module
+look at me,
+about as simple
+as could be.
+
+|
+
+============ ============ ===============
+Supports 2D? Supports 3D? Respects masks?
+============ ============ ===============
+YES          NO            YES
+============ ============ ===============
+
+"""
+
+class DumpIt(cellprofiler_core.module.ImageProcessing):
+    module_name = "DumpIt"
+
+    variable_revision_number = 1
+
+    def create_settings(self):
+        self.x_name = ImageSubscriber(
+            "Select the input image", doc="Select the image you want to use."
+        )
+
+        self.y_name = ImageName(
+            "Name the output image",
+            self.__class__.__name__,
+            doc="Enter the name you want to call the image produced by this module.",
+        )
+        self.overlay_text = Text("Some Text", "Hello World!", doc="The text you would like to be overlayed on top of the image.")
+
+        self.binary = Binary("Some binary", True)
+        self.color = Color("Some color choice", "red")
+
+    def settings(self):
+        return [self.x_name, self.y_name, self.overlay_text, self.binary,
+                self.color]
+
+    def visible_settings(self):
+        return self.settings()
+
+    def run(self, workspace):
+        self.function = lambda x_data, args: ...
+        super().run(workspace)

CP5/active_plugins/HelloWorld.py

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+import matplotlib.pyplot as plt
+from matplotlib import patheffects
+import numpy as np
+
+import cellprofiler_core.module
+import cellprofiler_core.setting.text
+
+__doc__ = """\
+HelloWorld
+============
+
+**HelloWorld** takes an image, and overlays "Hello World!" on top of it, by default.
+
+
+I am a module
+look at me,
+about as simple
+as could be.
+
+|
+
+============ ============ ===============
+Supports 2D? Supports 3D? Respects masks?
+============ ============ ===============
+YES          NO            YES
+============ ============ ===============
+
+"""
+
+class HelloWorld(cellprofiler_core.module.ImageProcessing):
+    module_name = "HelloWorld"
+
+    variable_revision_number = 1
+
+    def create_settings(self):
+        super().create_settings()
+        self.y_name.set_value("OverlayImage")
+        self.overlay_text = cellprofiler_core.setting.text.Text("Overlay Text", "Hello World!", doc="The text you would like to be overlayed on top of the image.")
+
+    def settings(self):
+        return super().settings() + [self.overlay_text]
+
+    # normally unnecessary, but ImageProcessing defines this so we have to too
+    def visible_settings(self):
+        return self.settings()
+
+    def run(self, workspace):
+        self.function = self.place_text_on_image
+        super().run(workspace)
+
+    def place_text_on_image(self,
+                            img,
+                            text,
+                            x_pos = 0, 
+                            y_pos = 0.99, 
+                            color = "white", 
+                            weight = "bold", 
+                            ha = "left", 
+                            va = "top", 
+                            outline_color = "black", 
+                            outline_width = 3):
+        fig = plt.figure()
+        fig.figimage(img, resize=True)
+
+        fontsize = 34/400*img.shape[0]
+
+        # Main text
+        txt = fig.text(x_pos, y_pos, text, fontsize=fontsize, color=color, weight=weight, 
+                    horizontalalignment=ha, verticalalignment=va)
+
+        # Apply white outline using path_effects
+        outline_effect = patheffects.withStroke(linewidth=outline_width, foreground=outline_color)
+        txt.set_path_effects([outline_effect])
+
+        fig.canvas.draw()
+        annotated_img = np.asarray(fig.canvas.renderer.buffer_rgba())
+        plt.close(fig)
+        return annotated_img

active_plugins/dumbmodule.py

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+#################################
+#
+# Imports from useful Python libraries
+#
+#################################
+
+import locale
+import sys
+
+#################################
+#
+# Imports from CellProfiler
+#
+##################################
+
+import cellprofiler_core.module
+import cellprofiler_core.setting.text
+
+__doc__ = """\
+DumbModule
+============
+
+**DumbModule** does nothing of importance.
+
+
+I am a module
+look at me,
+about as simple
+as could be.
+
+|
+
+============ ============ ===============
+Supports 2D? Supports 3D? Respects masks?
+============ ============ ===============
+NO           NO            NO
+============ ============ ===============
+
+"""
+
+#raise NotImplementedError("DumbModule does nothing")
+
+class DumbModule(cellprofiler_core.module.Module):
+    module_name = "DumbModule"
+    category = "Info"
+
+    variable_revision_number = 1
+
+    def create_settings(self):
+        self.some_setting = cellprofiler_core.setting.text.Text("dumb setting", "i am a setting", doc="I do nothing at all")
+
+    def settings(self):
+        return [self.some_setting]
+
+    def visible_settings(self):
+        return [self.some_setting]
+
+    def run(self, workspace):
+        f = open("/Users/ngogober/Desktop/log.txt", "wt")
+        f_repr = repr(f)
+        f.close()
+
+        labels = ["func name", "value"]
+        encoding_info_table = [
+            ["locale.getdefaultlocale:", repr(locale.getdefaultlocale())],
+            ["locale.getlocale", repr(locale.getlocale())],
+            ["locale.getpreferredencoding (do not set)", repr(locale.getpreferredencoding(False))],
+            ["locale.getpreferredencoding", repr(locale.getpreferredencoding())],
+            ["sys.getfilesystemencoding", repr(sys.getfilesystemencoding())],
+            ["filestream", f_repr],
+        ]
+
+        if self.show_window:
+            workspace.display_data.statistics = encoding_info_table
+            workspace.display_data.labels = labels
+        else:
+            print(encoding_info_table)
+
+    def display(self, workspace, figure):
+        statistics = workspace.display_data.statistics
+        labels = workspace.display_data.labels
+        figure.set_subplots((1, 1))
+        figure.subplot_table(0, 0, statistics, labels)