docs

Author: leonfoks

docs/_downloads/08bdc8e848fcac58fd5281891c5579e4/plot_csv_loupe.zip

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Magnetic Survey\n\nThese magnetic data channels were pulled from the Wisconsin Skytem example in this repository\n\nDataset Reference:\nMinsley, B.J, Bloss, B.R., Hart, D.J., Fitzpatrick, W., Muldoon, M.A., Stewart, E.K., Hunt, R.J., James, S.R., Foks, N.L., and Komiskey, M.J., 2022, Airborne electromagnetic and magnetic survey data, northeast Wisconsin (ver. 1.1, June 2022): U.S. Geological Survey data release, https://doi.org/10.5066/P93SY9LI.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\nfrom os.path import join\nimport numpy as np\nimport gspy\nfrom gspy import Survey\nimport xarray as xr\nfrom pprint import pprint"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Convert the magnetic csv data to NetCDF\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Initialize the Survey\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "# Path to example files\ndata_path = '..//..//..//..//example_material//mag_example'\n\n# Survey metadata file\nmetadata = join(data_path, \"WI_Magnetics_survey_md.yml\")\n\n# Establish the Survey\nsurvey = Survey.from_dict(metadata)\n\ndata_container = survey.gs.add_container('data', **dict(content = \"raw and gridded data\",\n                                                        comment = \"This is a test\"))"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "1 - Raw Data -\nImport raw mag data from CSV-format.\nDefine input data file and associated metadata file\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "d_data1 = join(data_path, 'WI_Magnetics.csv')\nd_supp1 = join(data_path, 'WI_Magnetics_raw_data_md.yml')\n\n# Add the raw AEM data as a tabular dataset\ndata_container.gs.add(key='raw_data', data_filename=d_data1, metadata_file=d_supp1)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "1 - Gridded Data -\nImport a tif of gridded mag data.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "d_supp1 = join(data_path, 'WI_Magnetics_grids_md.yml')\n\n# Add the raw AEM data as a tabular dataset\ndata_container.gs.add(key='grids', metadata_file=d_supp1)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Save to NetCDF file\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "d_out = join(data_path, 'WI_Magnetics.nc')\nsurvey.gs.to_netcdf(d_out)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Reading back in\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "new_survey = gspy.open_datatree(d_out)['survey']\n\nprint(new_survey)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Plotting\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "plt.figure()\nnew_survey['data/raw_data']['height'].plot()\nplt.tight_layout()\n\npd = new_survey['data/raw_data']['tmi']\nplt.figure()\npd.plot()\nplt.tight_layout()\n\nm = new_survey['data/grids/magnetic_tmi']\nplt.figure()\nm.plot(cmap='jet')\nplt.tight_layout()\n\nplt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "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": "3.12.11"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

docs/_downloads/0baab6385002cc5642dc64c790489dc8/plot_xarray_methods.zip

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+"""
+Magnetic Survey
+---------------
+
+These magnetic data channels were pulled from the Wisconsin Skytem example in this repository
+
+Dataset Reference:
+Minsley, B.J, Bloss, B.R., Hart, D.J., Fitzpatrick, W., Muldoon, M.A., Stewart, E.K., Hunt, R.J., James, S.R., Foks, N.L., and Komiskey, M.J., 2022, Airborne electromagnetic and magnetic survey data, northeast Wisconsin (ver. 1.1, June 2022): U.S. Geological Survey data release, https://doi.org/10.5066/P93SY9LI.
+"""
+#%%
+import matplotlib.pyplot as plt
+from os.path import join
+import numpy as np
+import gspy
+from gspy import Survey
+import xarray as xr
+from pprint import pprint
+
+
+#%%
+# Convert the magnetic csv data to NetCDF
+# +++++++++++++++++++++++++++++++++++++++
+
+#%%
+# Initialize the Survey
+
+# Path to example files
+data_path = '..//..//..//..//example_material//mag_example'
+
+# Survey metadata file
+metadata = join(data_path, "WI_Magnetics_survey_md.yml")
+
+# Establish the Survey
+survey = Survey.from_dict(metadata)
+
+data_container = survey.gs.add_container('data', **dict(content = "raw and gridded data",
+                                                        comment = "This is a test"))
+
+#%%
+# 1 - Raw Data -
+# Import raw mag data from CSV-format.
+# Define input data file and associated metadata file
+d_data1 = join(data_path, 'WI_Magnetics.csv')
+d_supp1 = join(data_path, 'WI_Magnetics_raw_data_md.yml')
+
+# Add the raw AEM data as a tabular dataset
+data_container.gs.add(key='raw_data', data_filename=d_data1, metadata_file=d_supp1)
+
+#%%
+# 1 - Gridded Data -
+# Import a tif of gridded mag data.
+d_supp1 = join(data_path, 'WI_Magnetics_grids_md.yml')
+
+# Add the raw AEM data as a tabular dataset
+data_container.gs.add(key='grids', metadata_file=d_supp1)
+
+#%%
+# Save to NetCDF file
+d_out = join(data_path, 'WI_Magnetics.nc')
+survey.gs.to_netcdf(d_out)
+
+#%%
+# Reading back in
+new_survey = gspy.open_datatree(d_out)['survey']
+
+print(new_survey)
+
+#%%
+# Plotting
+plt.figure()
+new_survey['data/raw_data']['height'].plot()
+plt.tight_layout()
+
+pd = new_survey['data/raw_data']['tmi']
+plt.figure()
+pd.plot()
+plt.tight_layout()
+
+m = new_survey['data/grids/magnetic_tmi']
+plt.figure()
+m.plot(cmap='jet')
+plt.tight_layout()
+
+plt.show()
+
+
+