Upgrade onecodex to 1.1.0

requirements.txt

@@ -1,11 +1,13 @@
+# jupyter_contrib_nbextensions imports pkg_resources, which setuptools removed
+# in v81; the python:3.13-slim base image no longer ships setuptools at all.
+setuptools<81
 awscli
 biopython
 ipywidgets
 jupyter_contrib_nbextensions
 nbconvert==6.5.0
-openpyxl
 xlrd
 statsmodels
-onecodex[all,reports]==0.19.3
+onecodex[all,reports]==1.1.0
 taxonomy
 widgetsnbextension

test/notebooks/example.ipynb

@@ -34,6 +34,10 @@
     "\n",
     "import warnings\n",
     "\n",
+    "# filter warnings because the timestamp shows up in diff-pdf\n",
+    "warnings.filterwarnings(\"ignore\", message=\".*SampleCollection contains multiple.*\")\n",
+    "warnings.filterwarnings(\"ignore\", message=\".*is deprecated.*\")\n",
+    "\n",
     "from IPython.display import display\n",
     "\n",
     "project = ocx.Projects.get(\"d53ad03b010542e3\")  # get DIABIMMUNE project by ID\n",
@@ -50,7 +54,7 @@
     "    \"wheat\",\n",
     "    \"rice\",\n",
     "]]\n",
-    "    \n",
+    "\n",
     "display(md_table)"
    ]
   },
@@ -69,14 +73,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# filter warning because timestamp shows up in diff-pdf\n",
-    "with warnings.catch_warnings():\n",
-    "    warnings.filterwarnings(\"ignore\", message=\".*SampleCollection contains multiple.*\")\n",
-    "    warnings.filterwarnings(\"ignore\", message=\".*is deprecated.*\")\n",
-    "    \n",
-    "    observed_taxa = samples.plot_metadata(vaxis=\"observed_taxa\", haxis=\"geo_loc_name\", return_chart=True)\n",
-    "    simpson = samples.plot_metadata(vaxis=\"simpson\", haxis=\"geo_loc_name\", return_chart=True)\n",
-    "    shannon = samples.plot_metadata(vaxis=\"shannon\", haxis=\"geo_loc_name\", return_chart=True)\n",
+    "observed_taxa = samples.plot_metadata(vaxis=\"observed_taxa\", haxis=\"geo_loc_name\", return_chart=True)\n",
+    "simpson = samples.plot_metadata(vaxis=\"simpson\", haxis=\"geo_loc_name\", return_chart=True)\n",
+    "shannon = samples.plot_metadata(vaxis=\"shannon\", haxis=\"geo_loc_name\", return_chart=True)\n",
     "\n",
     "observed_taxa | simpson | shannon"
    ]
@@ -128,18 +127,12 @@
    "outputs": [],
    "source": [
     "# generate a dataframe containing relative abundances\n",
-    "df_rel = samples.to_df(rank=\"genus\")\n",
-    "\n",
     "# fetch all samples for subject P014839\n",
-    "subject_metadata = samples.metadata.loc[samples.metadata[\"host_subject_id\"] == \"P014839\"]\n",
-    "subject_df = df_rel.loc[subject_metadata.index]\n",
+    "subject_df = samples.filter(lambda s: s.metadata.custom[\"host_subject_id\"] == \"P014839\")\n",
     "\n",
-    "# put them in order of sample date\n",
-    "subject_df = subject_df.loc[subject_metadata[\"host_age\"].sort_values().index]\n",
-    "\n",
-    "# you can access our library using the ocx accessor on pandas dataframes!\n",
-    "subject_df.ocx.plot_bargraph(\n",
+    "subject_df.plot_bargraph(\n",
     "    rank=\"genus\",\n",
+    "    metric=\"normalized_readcount_w_children\",\n",
     "    label=lambda metadata: str(metadata[\"host_age\"]),\n",
     "    title=\"Subject P014839 Over Time\",\n",
     "    xlabel=\"Host Age at Sampling Time (days)\",\n",
@@ -161,7 +154,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_rel[:30].ocx.plot_heatmap(legend=\"Relative Abundance\", tooltip=\"geo_loc_name\")"
+    "samples[:30].plot_heatmap(legend=\"Relative Abundance\", tooltip=\"geo_loc_name\", rank='genus', metric='normalized_readcount_w_children')"
    ]
   },
   {
@@ -179,10 +172,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# generate a dataframe containing read counts\n",
-    "df_abs = samples.to_df()\n",
-    "\n",
-    "df_abs[:30].ocx.plot_distance(metric=\"weighted_unifrac\")"
+    "samples[:30].plot_distance(diversity_metric=\"weighted_unifrac\", metric='normalized_readcount_w_children')"
    ]
   },
   {
@@ -215,7 +205,11 @@
    "outputs": [],
    "source": [
     "samples.plot_mds(\n",
-    "    metric=\"weighted_unifrac\", method=\"pcoa\", color=\"geo_loc_name\", title=\"My PCoA Plot\"\n",
+    "    metric='abundance_w_children',\n",
+    "    diversity_metric=\"weighted_unifrac\",\n",
+    "    method=\"pcoa\",\n",
+    "    color=\"geo_loc_name\",\n",
+    "    title=\"My PCoA Plot\"\n",
     ")"
    ]
   },