tutorials keep me busy

dinsar/agregado.py

@@ -335,7 +335,7 @@ def set_estacion(self, estacion=None, bd=None, way='nearest', orden=1,
         self._info_estaciones = {'estacion':_estacion, 'bd':bd_object}
 
         if not _silent:
-            print(f"Fijada la estación: {self.estacion.name}"
+            print(f"Fijada la estación: {self.estacion.name} "
                   f"según el método '{way}'.")
 
         return self

examples/Adding other database to the model.ipynb

@@ -0,0 +1,57 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8159acc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from shapely.geometry import Point\n",
+    "import random\n",
+    "\n",
+    "x1, y1, x2, y2 = Doñana.get('Asc').gdf.total_bounds\n",
+    "\n",
+    "random_point = lambda x1, y1, x2, y2 : Point(random.uniform(x1, x2), random.uniform(y1, y2))\n",
+    "\n",
+    "# Definición de la base de datos (pandas.DataFrame):\n",
+    "columns, values = [i for i in 'ABCDE'], [np.random.random(60) for i in range(5)]\n",
+    "df_table = {i:j for i,j in zip(columns, values)}\n",
+    "df = pd.DataFrame(df_table, index=pd.date_range(start='2015', end='2020', freq='M'))\n",
+    "df = df.melt(var_name='Nombre', value_name='Valores', ignore_index=False)\n",
+    "df.index.name = 'Fechas'\n",
+    "df.reset_index(inplace=True)\n",
+    "\n",
+    "# Definición de un archivo espacial\n",
+    "table = {'Nombre':[i for i in 'ABCDE'],\n",
+    "         'geometry':[random_point(x1, y1, x2, y2) for i in range(5)]}\n",
+    "gdf = gpd.GeoDataFrame(table, crs=25830)\n",
+    "\n",
+    "gps = dinsar.DataBase(df, name='gps', units='cm', color='black')\n",
+    "gps.append_geometry(gdf)\n",
+    "Doñana.append(gps)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/Creating a dinsar model.ipynb

@@ -15,6 +15,8 @@
     "\n",
     "---------------------------------------------------------------------------------------------------------------------------\n",
     "\n",
+    "<h1><center>Creating a dinsar Model</center></h1>\n",
+    "\n",
     "## 1. Creation of a Model\n",
     "The dinsar package design holds a data **model** as the main object around which all of the program functionalities spin around. This model will include all the DInSAR datasets and databases that are consulted in the study area and is created through the `Model` class. Since the simplest way of analyzing DInSAR deformation points (also called persistent or permanent scatterers; PS) is through their **aggregation into polygons**, the initialization of this class requieres a polygonal spatial file, that should be introduced as a relative path to its ubication. This way, each of these polygons will define the different analysis areas of the model -analogous to [ADA's](https://open.igme.es/xmlui/bitstream/handle/20.500.12468/708/fast_detection_ground_2017.pdf?sequence=1) (Active Deformation Areas), called in the code as **agregados** and hereinafter as *aggregates*.\n",
     "\n",
@@ -280,7 +282,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "836305ca",
+   "id": "2b334d20",
    "metadata": {},
    "source": [
     "## 5. Main functions of Model object:\n",
@@ -293,7 +295,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "da3c0596",
+   "id": "dd519337",
    "metadata": {},
    "outputs": [
     {

examples/Visualizing with plot and mapa methods..ipynb

@@ -0,0 +1,39 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0604ed54",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import dinsar\n",
+    "\n",
+    "# Para centrar las gráficas salientes en un notebook de Jupyter.\n",
+    "from IPython.core.display import HTML\n",
+    "HTML(\"\"\"<style>.output_png {display: table-cell; text-align: center; vertical-align: middle;}</style>\"\"\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/Working with model parts.ipynb

@@ -0,0 +1,49 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "37fef053",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " # Cojo los cinco primeros PS del Dataset 'Ascending' (dessde fuera del modelo ) y calculo su deformación promedio\n",
+    "ps = Asc.ps[0:5] \n",
+    "Asc.subset(ps).plot(plot_average=True)\n",
+    "\n",
+    "# Cojo el primer piezómetro de la base de datos de piezometría y ploteo su serie temporal\n",
+    "piezo = bbdd.piezos[0]\n",
+    "bbdd.plot(piezo)\n",
+    "\n",
+    "# A través del método 'take' accedo al array con su serie tempral: --> bbdd.take(piezo)\n",
+    "\n",
+    "# Selecciono la estación de Almonte y ploteo su serie temporal según su desviación acumulada\n",
+    "# Puedo ver qué estaciones hay en la base de datos así: --> precipi.estaciones\n",
+    "precipi.plot('Almonte', values='dsv')\n",
+    "\n",
+    "precipi.estaciones"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}