Python wrappers

Examples/Notebooks/PyPCalc_EX01.ipynb

@@ -0,0 +1,166 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7da98c8c",
+   "metadata": {},
+   "source": [
+    "## Example 01"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "485d2c22",
+   "metadata": {},
+   "source": [
+    "This notebook is designed to replicate example 1 from the PCalc user's manual"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cba5c210",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.insert(0, \"../../python\")\n",
+    "\n",
+    "\n",
+    "jarfile = '../../target/salsa3d-software-1.2022.5-jar-with-dependencies.jar'\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "from PyPCalc import PCalc\n",
+    "PCalc.print_example01_info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d96db269",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# PCalc objects are best initialized after setting your desired configuration and properties.\n",
+    "# configuration refers to how the python wrapper class interacts with the base pcalc jar file\n",
+    "# properties define the pcalc propeties that are used when the jar is executed\n",
+    "\n",
+    "config = PCalc.initialize_configuration(captureOutput=True, use_slbm=False, \n",
+    "                                        returnObject='points',\n",
+    "                                        jarFile = jarfile)\n",
+    "\n",
+    "props = PCalc.initialize_properties(\n",
+    "    application = 'model_query',\n",
+    "    workDir = '.',\n",
+    "    geotessModel=\"../data/AK135.geotess\",\n",
+    "    inputType = 'file',\n",
+    "    inputFile = \"../data/example_coords.xyz\",\n",
+    "    inputAttributes = 'latitude longitude depth',\n",
+    "    batchSize = 10,\n",
+    "    outputFile = \"<property:workDir>/pcalc_query_file_output.dat\",\n",
+    "    logFile = \"<property:workDir>/pcalc_log.txt\",\n",
+    "    terminalOutput = True,\n",
+    "    separator = 'space',\n",
+    "    outputAttributes = 'pslowness')\n",
+    "\n",
+    "# Creates the PCalc object using the define properties and configuration dictionaries.\n",
+    "calc = PCalc(config = config, properties = props)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c7b81a21",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set properties and configuration aspects can be viewed:\n",
+    "print(\"PCalc properties:\")\n",
+    "calc.viewSetProperties()\n",
+    "print(\"++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\")\n",
+    "print(\"PyPCalc Configuration:\")\n",
+    "calc.viewSetConfiguration()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0ff14c62",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# In order to actually run pcalc, first write the properties file and then execute\n",
+    "calc.writePropertiesFile()\n",
+    "r, data = calc.execute()\n",
+    "# The execute method calls the PCalc jar file and returns the terminal output as the first value (r)\n",
+    "# and the data file that is generated as output is read in to Python as the second value (data)\n",
+    "\n",
+    "print(r.stdout)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1ab4f0ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# For this case, we've set the 'returnObject' in the configuration to points\n",
+    "# This creates a list of values from the class PointMeasurement that just contains the data contained \n",
+    "# the output file. Alternatives include 'dataFrame' to get the raw pandas dataFrame object\n",
+    "# or 'array' to get a numpy array\n",
+    "#data[0].toString()\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0a0f88ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# If you want to create your own input file rather than the included ../data/example_coords.xyz, you can use the write \n",
+    "# method of the PointMeasurement object as:\n",
+    "fp = open(\"tmp.dat\", \"w\")\n",
+    "for pt in data:\n",
+    "    pt.write(fp, mode='longitude latitude depth', separator = 'tab')\n",
+    "fp.close()\n",
+    "!head tmp.dat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6ec04f1a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Examples/Notebooks/PyPCalc_EX02.ipynb

@@ -0,0 +1,141 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c60ce11d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.insert(0, \"../../python\")\n",
+    "\n",
+    "\n",
+    "jarfile = '../../target/salsa3d-software-1.2022.5-jar-with-dependencies.jar'\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "from PyPCalc import PCalc\n",
+    "PCalc.print_example02_info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f081092b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "config = PCalc.initialize_configuration(captureOutput=True, use_slbm=False, returnObject='dataFrame',\n",
+    "                jarFile = jarfile)\n",
+    "\n",
+    "props = PCalc.initialize_properties(\n",
+    "    application = 'model_query',\n",
+    "    workDir = '.',\n",
+    "    geotessModel=\"../data/AK135.geotess\",\n",
+    "    inputType = 'greatcircle',\n",
+    "    gcStart = \"0 0\",\n",
+    "    gcDistance = 180,\n",
+    "    gcAzimuth = 0,\n",
+    "    gcSpacing = 10,\n",
+    "    gcPositionParameters = 'x, y, distance, depth',\n",
+    "    depthSpecificationMethod = 'maxDepthSpacing',\n",
+    "    maxDepthSpacing = 100,\n",
+    "    maxDepth = 'top of m660',\n",
+    "    outputFile = \"<property:workDir>/pcalc_query_greatcircle_output.dat\",\n",
+    "    logFile = \"<property:workDir>/pcalc_log.txt\",\n",
+    "    terminalOutput = True,\n",
+    "    outputHeader = True,\n",
+    "    separator = 'tab',\n",
+    "    outputAttributes = 'pslowness')\n",
+    "\n",
+    "calc = PCalc(config = config, properties = props)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ff120d98",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set properties and configuration aspects can be viewed:\n",
+    "print(\"PCalc properties:\")\n",
+    "calc.viewSetProperties()\n",
+    "print(\"++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\")\n",
+    "print(\"PyPCalc Configuration:\")\n",
+    "calc.viewSetConfiguration()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64db4ce4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# In order to actually run pcalc, first write the properties file and then execute\n",
+    "calc.writePropertiesFile()\n",
+    "r, data = calc.execute()\n",
+    "# The execute method calls the PCalc jar file and returns the terminal output as the first value (r)\n",
+    "# and the data file that is generated as output is read in to Python as the second value (data)\n",
+    "\n",
+    "print(r.stdout)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0a4f5417",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This time, the configuration set the returnObject to dataFrame.\n",
+    "# This is a structure from the Pandas library that organizes tables nicely\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "86657193",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.boxplot()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4c5957a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}