Merge ssh://192.168.66.221/~vitor/Yap/yap-6.3

packages/python/yap_kernel/#install.py#

@@ -0,0 +1,44 @@
+import json
+import os
+import sys
+
+try:
+    from jupyter_client.kernelspec import install_kernel_spec
+except ImportError:
+    from IPython.kernel.kernelspec import install_kernel_spec
+from IPython.utils.tempdir import TemporaryDirectory
+
+
+kernel_json = {
+    "argv": [sys.executable,
+             "-m", "yap_kernel",
+             "-f", "{connection_file}"],
+    "display_name": "yap",
+    "mimetype": "text/x-prolog",
+    "language": "prolog",
+    "name": "yap",
+}
+
+def install_my_kernel_spec(user=False):
+    with TemporaryDirectory() as td:
+        os.chmod(td, 0o755) # Starts off as 700, not user readable
+        with open(os.path.join(td, 'kernel.json'), 'w') as f:
+            json.dump(kernel_json, f, sort_keys=True)
+        # TODO: Copy resources once they're specified
+
+        print('Installing IPython kernel spec')
+        install_kernel_spec(td, 'yap', user=False, replace=True)
+
+def _is_root():
+    return True
+    try:
+        return os.geteuid() == 0
+    except AttributeError:
+        return False # assume not an admin on non-Unix platforms
+
+def main(argv=[]):
+    user = '--user' in argv or not _is_root()
+    install_my_kernel_spec(user=user)
+
+if __name__ == '__main__':
+    main(argv=sys.argv)

packages/python/yap_kernel/clause.py

@@ -0,0 +1,30 @@
+"""
+Paired Density and Scatterplot Matrix
+=====================================
+
+_thumb: .5, .5
+"""
+import seaborn as sns
+import matplotlib.pyplot as plt
+sns.set(style="white")
+
+df = sns.load_dataset("iris")
+
+g = sns.PairGrid(df, diag_sharey=False)
+g.map_lower(sns.kdeplot, cmap="Blues_d")
+g.map_upper(plt.scatter)
+g.map_diag(sns.kdeplot, lw=3)
+
+"""
+Grouped barplots
+================
+
+_thumb: .45, .5
+"""
+sns.set(style="whitegrid")
+
+# Draw a nested barplot to show survival for class and sex
+g = sns.factorplot(x="class", y="survived", hue="sex", data=[15,30,5],
+                   size=3, kind="bar", palette="muted")
+g.despine(left=True)
+g.set_ylabels("survival probability")