ENH: invert data list + some simplifications

display_api.py

@@ -5,6 +5,7 @@ Some functions for Jupyter displaying
 """
 
 import os
+import datetime
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -110,7 +111,7 @@ def rasters_on_map(rasters_list, out_dir, overlay_names_list, geojson_data=None)
     # - plot quicklook
     for raster, overlay_name in zip(rasters_list, overlay_names_list):
         bounds = transform_bounds(raster.crs, epsg4326, *raster.bounds)
-        quicklook_url = os.path.join(out_dir, os.path.splitext(overlay_name.replace("/", "_"))[0] + "_PREVIEW.JPG")
+        quicklook_url = os.path.join(out_dir, "PREVIEW_{}.JPG".format(datetime.datetime.now()))
         write_quicklook(raster, quicklook_url)
         quicklook = ImageOverlay(
             url=quicklook_url,

otb_workshop.ipynb

@@ -51,7 +51,7 @@
     "\n",
     "# Date list\n",
     "date_buttons = ipywidgets.ToggleButtons(\n",
-    "    options=[\"20180706\", \"20180621\", \"20180701\", \"20180711\"],\n",
+    "    options=[\"20180711\", \"20180706\", \"20180701\", \"20180621\"],\n",
     "    description=\"Dates:\")\n",
     "\n",
     "date_buttons"

step1_compute_radiometric_indices.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "<img style=\"float: left; margin:0px 15px 15px 0px; width:120px\" src=\"https://www.orfeo-toolbox.org/wp-content/uploads/2016/03/logo-orfeo-toolbox.png\">\n",
     "\n",
-    "# OTB Guided Tour - JURSE 2019 Vannes France - May 21th\n",
+    "# OTB Guided Tour - FOSS4G 2019 Bucharest\n",
     "## Yannick TANGUY and David YOUSSEFI (CNES, French Space Agency)\n",
     "\n",
     "<br>\n",
@@ -26,13 +26,6 @@
     "\\end{equation}"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Given example: compute ndvi"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -40,11 +33,8 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "import otbApplication\n",
-    "import rasterio\n",
-    "\n",
-    "import display_api\n",
-    "import utils\n",
+    "from glob import glob\n",
+    "import ipywidgets\n",
     "\n",
     "# Data directory\n",
     "DATA_DIR = \"data\"\n",
@@ -52,43 +42,30 @@
     "# Output directory\n",
     "OUTPUT_DIR = \"output\"\n",
     "\n",
-    "print(utils.list_images(DATA_DIR,\"_RVBPIR.tif\"))\n",
-    "\n",
-    "def compute_ndvi(images, out_dir):\n",
-    "    \"\"\"\n",
-    "    Compute NDVI from images with Red, Green, Blue and NIR bands\n",
-    "    :param images: list of images. Their filenames match the pattern [...]_RVBPIR.tif\n",
-    "    :param out_dir: path to the output directory\n",
-    "    \"\"\"\n",
-    "    out_list = []\n",
-    "    for im in images:\n",
-    "        out = os.path.join(out_dir, os.path.basename(im.replace(\"_RVBPIR.tif\",\"_NDVI.tif\")))\n",
-    "        # Here we create an application\n",
-    "        app = otbApplication.Registry.CreateApplication(\"BandMath\")\n",
-    "        # BandMath takes a list of images as input,\n",
-    "        # so we have to give a Python list [ image ], or [ image1, image2, .., imageN]\n",
-    "        app.SetParameterStringList(\"il\",[im])\n",
-    "        app.SetParameterString(\"out\", out)\n",
-    "        # the main parameter is the mathematical expression\n",
-    "        # here, we compute NDVI : (nir - red) / (nir + red)\n",
-    "        # The corresponding bands for NIR and Red are respectively the 4th and the 3rd bands (b4, b3)\n",
-    "        # of the first image (im1)\n",
-    "        app.SetParameterString(\"exp\",\"(im1b4-im1b1)/(im1b4+im1b1)\")\n",
-    "        app.ExecuteAndWriteOutput()\n",
-    "        out_list.append(out)\n",
-    "        \n",
-    "    return out_list"
+    "# Date list\n",
+    "date_buttons = ipywidgets.ToggleButtons(\n",
+    "    options=[\"20180711\", \"20180706\", \"20180701\", \"20180621\"],\n",
+    "    description=\"Dates:\")\n",
+    "\n",
+    "date_buttons"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# Compute radiometric indices (NDVI & NDWI2) on a stack of images\n",
-    "ndvi_filenames_list = compute_ndvi(utils.list_images(DATA_DIR,\"_RVBPIR.tif\"), OUTPUT_DIR)\n",
-    "print (ndvi_filenames_list)"
+    "### Given example: compute ndvi\n",
+    "\n",
+    "Here we create an application with ```otbApplication.Registry.CreateApplication(\"BandMath\")```\n",
+    "\n",
+    "BandMath takes a list of images as input, so we have to give a Python list with ```\"il\"``` parameter : [image], or [image1, image2, .., imageN] and the main parameter is the mathematical expression ```\"exp\"```.\n",
+    "\n",
+    "Here, we compute NDVI :\n",
+    "\\begin{equation}\n",
+    "\\mbox{NDVI}=\\frac{(Xnir - Xred)}{(Xnir + Xred)}\n",
+    "\\end{equation}\n",
+    "\n",
+    "The corresponding bands for NIR and Red are respectively the 4th and the 1st bands (b4, b1) of the first image (im1)"
    ]
   },
   {
@@ -97,34 +74,48 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Display on a map\n",
-    "rasters = list(map(rasterio.open, ndvi_filenames_list))\n",
-    "overnames = list(map(os.path.basename, ndvi_filenames_list))\n",
-    "m, dc = display_api.rasters_on_map(rasters, OUTPUT_DIR, overnames)\n",
-    "m"
+    "import otbApplication\n",
+    "\n",
+    "# input / output files\n",
+    "DATE = date_buttons.value\n",
+    "im = glob(os.path.join(DATA_DIR, \"*{}*.tif\".format(DATE)))[0]\n",
+    "out = os.path.join(OUTPUT_DIR, \"NDVI.tif\")\n",
+    "\n",
+    "# Given example\n",
+    "def compute_ndvi():\n",
+    "    app = otbApplication.Registry.CreateApplication(\"BandMath\")\n",
+    "    app.SetParameterStringList(\"il\",[im])\n",
+    "    app.SetParameterString(\"out\", out)\n",
+    "    app.SetParameterString(\"exp\", \"(im1b4-im1b1)/(im1b4+im1b1)\")\n",
+    "    exit_code = app.ExecuteAndWriteOutput()\n",
+    "\n",
+    "compute_ndvi()"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "### Compute ndwi : <b> Fill the <span style=\"color:black;background:yellow\">compute_ndwi</span> function </b> "
+    "import rasterio\n",
+    "import display_api\n",
+    "raster = rasterio.open(out)\n",
+    "m, dc = display_api.rasters_on_map([raster], OUTPUT_DIR, [DATE+\"_NDVI\"])\n",
+    "m"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "def compute_ndwi(images, out_dir):\n",
-    "    \"\"\"\n",
-    "    Compute NDWI2 from images with Red, Green, Blue and NIR bands\n",
-    "    :param images: list of images. Their filenames match the pattern [...]_RVBPIR.tif\n",
-    "    :param out_dir: path to the output directory\n",
-    "    \"\"\"\n",
-    "    # TODO: fill the compute_ndwi_function\n",
-    "    return None"
+    "### Compute ndwi : <b> Fill the <span style=\"color:black;background:yellow\">compute_ndwi</span> function </b> \n",
+    "\n",
+    "**Reminder** : NDWI2 is computed from green and nir bands (defined by McFeeters, 1996):\n",
+    "\n",
+    "\\begin{equation}\n",
+    "\\mbox{NDWI2}=\\frac{(Xgreen - Xnir)}{(Xgreen + Xnir)}\n",
+    "\\end{equation}"
    ]
   },
   {
@@ -133,12 +124,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Compute radiometric indices (NDVI & NDWI2) on a stack of images\n",
-    "ndwi_filenames_list = compute_ndwi(utils.list_images(DATA_DIR,\"_RVBPIR.tif\"), OUTPUT_DIR)\n",
-    "if ndwi_filenames_list is not None:\n",
-    "    print (ndwi_filenames_list)http://localhost:8888/notebooks/step1_compute_radiometric_indices.ipynb#\n",
-    "else:\n",
-    "    print (\"TODO: fill the compute_ndwi_function\")"
+    "import otbApplication\n",
+    "\n",
+    "# input / output files\n",
+    "DATE = date_buttons.value\n",
+    "im = glob(os.path.join(DATA_DIR, \"*{}*.tif\".format(DATE)))[0]\n",
+    "out = os.path.join(OUTPUT_DIR, \"NDWI.tif\")\n",
+    "\n",
+    "def compute_ndwi():\n",
+    "    # Fill the compute_ndwi function\n",
+    "    pass\n",
+    "    \n",
+    "compute_ndwi()"
    ]
   },
   {
@@ -147,10 +144,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Display on a map\n",
-    "rasters = list(map(rasterio.open, ndwi_filenames_list))\n",
-    "overnames = list(map(os.path.basename, ndwi_filenames_list))\n",
-    "m, dc = display_api.rasters_on_map(rasters, OUTPUT_DIR, overnames)\n",
+    "import rasterio\n",
+    "import display_api\n",
+    "raster = rasterio.open(out)\n",
+    "m, dc = display_api.rasters_on_map([raster], OUTPUT_DIR, [DATE+\"_NDWI\"])\n",
     "m"
    ]
   },