Merge branch 'fix-open-dataset-respecting-method'

Author: eeholmes

examples/docs_1_l3_examples.ipynb examples/docs_1_pace_l3.ipynbexamples/docs_1_l3_examples.ipynb renamed to examples/docs_1_pace_l3.ipynb

@@ -5,11 +5,10 @@
    "id": "556f084f-684f-41e4-b004-4fde273a8217",
    "metadata": {},
    "source": [
-    "# Level 3 matchups with PACE data\n",
+    "# PACE Level 3\n",
+    "<br>\n",
     "\n",
-    "```\n",
-    "import point_collocation as pc\n",
-    "```\n",
+    "**Steps:**\n",
     "\n",
     "* Create a plan for files to use `pc.plan()`\n",
     "* Print the plan to check it `print(plan.summary())`\n",
@@ -260,7 +259,6 @@
    ],
    "source": [
     "%%time\n",
-    "# orig / new 2 second\n",
     "res = pc.matchup(plan, variables=[\"Rrs\"])\n",
     "res"
    ]
@@ -356,7 +354,6 @@
    ],
    "source": [
     "%%time\n",
-    "# old 1.5 s / new 1.2 sseems to vary\n",
     "import point_collocation as pc\n",
     "plan = pc.plan(\n",
     "    df,\n",
@@ -653,7 +650,6 @@
    ],
    "source": [
     "%%time\n",
-    "# 4-5 s\n",
     "import earthaccess\n",
     "import point_collocation as pc\n",
     "\n",
@@ -715,7 +711,6 @@
    ],
    "source": [
     "%%time\n",
-    "# 8.3 s / 20.6s, later 8.6, 14, 11, 10 !!\n",
     "res = pc.matchup(plan, variables = [\"avw\"])"
    ]
   },

examples/docs_2_l2_examples.ipynb examples/docs_2_pace_l2.ipynbexamples/docs_2_l2_examples.ipynb renamed to examples/docs_2_pace_l2.ipynb

@@ -5,11 +5,14 @@
    "id": "556f084f-684f-41e4-b004-4fde273a8217",
    "metadata": {},
    "source": [
-    "# Level 2 matchups with PACE data\n",
+    "# PACE Level 2\n",
+    "<br>\n",
+    "\n",
+    "**Steps:**\n",
     "\n",
     "* Create a plan for files to use `pc.plan()`\n",
     "* Print the plan to check it `print(plan.summary())`\n",
-    "* Do the plan and get matchups `pc.matchup(plan, open_method=\"datatree-merge\", spatial_method=\"xoak\")`\n",
+    "* Do the plan and get matchups `pc.matchup(plan, spatial_method=\"xoak\")`\n",
     "\n",
     "## Prerequisite -- Login to EarthData\n",
     "\n",
@@ -207,7 +210,6 @@
    ],
    "source": [
     "%%time\n",
-    "# time 11 s / 5 s\n",
     "import point_collocation as pc\n",
     "plan = pc.plan(\n",
     "    df_points[0:50], \t\n",
@@ -339,7 +341,6 @@
    ],
    "source": [
     "%%time\n",
-    "# 1 min /\n",
     "res = pc.matchup(plan, spatial_method=\"xoak\", variables=[\"Rrs\"])"
    ]
   },

examples/docs_3_many_points.ipynb

@@ -5,7 +5,8 @@
    "id": "c46b9f0e-346f-47fb-8f14-98d35b827626",
    "metadata": {},
    "source": [
-    "# Large number of point matchups\n",
+    "# 1000s of points\n",
+    "<br>\n",
     "\n",
     "When we have 10s of thousands of points for matchups, we need to be careful with memory. `point-collocation` will try to minimize memory accummulation, but you may still need to use a machine with more RAM to handle the task. 5Gb RAM is needed for the example with 15k+ points here. The amount of memory needed depends a bit on how your points are distributed across the grid and how they match up with the underlying netcdf chunking. The user doesn't have to worry abou that however. The package is designed to take care of using memory efficient approaches.\n",
     "\n",
@@ -277,4 +278,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}