From b2ab52009b764fe18f3d186553d4bfc1d8a964b3 Mon Sep 17 00:00:00 2001 From: Micah Johnson Date: Wed, 6 Jul 2022 14:07:51 -0600 Subject: [PATCH] Db mods (#73) * Converted over surveyors to observers * Moved utm_zone to integer * change connection string to utc default * change default timezone for testing * Fixes about half of the examples for #72 * Updated the docs to better reflect the database modification and splitting of the repos Co-authored-by: Micah Sandusky --- .github/workflows/main.yml | 4 +- docker-compose.yml | 4 +- docs/database_structure.rst | 7 +- .../compare_SSA_instruments_example.ipynb | 22 +-- .../compare_UAVSAR_to_depths_example.ipynb | 79 +++++----- docs/gallery/get_spiral_example.ipynb | 42 ++--- docs/gallery/getting_started_example.ipynb | 23 +-- docs/gallery/graupel_pits_example.ipynb | 37 ++--- docs/gallery/graupel_smp_example.ipynb | 43 ++---- docs/gallery/overview_example.ipynb | 83 ++++++---- docs/gallery/plot_raster_example.ipynb | 4 +- .../raster_union_and_more_example.ipynb | 4 +- docs/history.rst | 7 + docs/installation.rst | 144 ------------------ snowexsql/data.py | 9 +- snowexsql/db.py | 4 +- tests/test_db.py | 2 +- 17 files changed, 189 insertions(+), 329 deletions(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index f9a4978..ca80746 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -25,8 +25,8 @@ jobs: POSTGRES_PASSWORD: db_builder POSTGRES_USER: builder POSTGRES_DB: test - TZ: 'MST' - PGTZ: 'MST' + TZ: 'UTC' + PGTZ: 'UTC' POSTGIS_GDAL_ENABLED_DRIVERS: 'ENABLE_ALL' POSTGIS_ENABLE_OUTDB_RASTERS: 'True' ports: diff --git a/docker-compose.yml b/docker-compose.yml index 8ac313c..3789e21 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -10,8 +10,8 @@ services: POSTGRES_DB: 'test' POSTGIS_GDAL_ENABLED_DRIVERS: 'ENABLE_ALL' POSTGIS_ENABLE_OUTDB_RASTERS: 'True' - TZ: 'MST' - PGTZ: 'MST' + TZ: 'UTC' + PGTZ: 'UTC' ports: - 5432:5432 healthcheck: diff --git a/docs/database_structure.rst b/docs/database_structure.rst index c17208f..3330d16 100644 --- a/docs/database_structure.rst +++ b/docs/database_structure.rst @@ -53,7 +53,7 @@ This table has the following columns: * northing - Northing coordinate projected in UTM in meters * site_id - Unique identifier to pit location * site_name - Name describing the general survey area ( e.g. Grand Mesa) -* surveyors - Name of the people who acquired the data +* observers - Name of the people who acquired the data * time - Time (MST) that the data was collected * time_updated - Time this entry was last modified * type - Name of the data collected @@ -97,6 +97,7 @@ This table contains the following columns: * depth - Depth in centimeters in the snowpack that the data was collected * easting - UTM projected coordinate in the east direction in meters * elevation - Elevation at the site or acquisition in meters +* flags - data that was flagged typically just pits * geom - GIS software friendly version of the coordinates of where the data was collected in UTM. * id - Unique identifier that is automatically assigned when uploaded * instrument - Name of the instrument used to collect the data @@ -108,7 +109,7 @@ This table contains the following columns: * sample_c - 1 of potentially three samples that could have been taken for this measurement, e.g. density * site_id - Unique identifier to pit location * site_name - Name describing the general survey area ( e.g. Grand Mesa) -* surveyors - Names of the people performing the acquisition +* observers - Names of the people performing the acquisition * time - Time (MST) at the beginning of acquisition * time_created - Time this entry was uploaded * time_updated - Time this entry was last modified @@ -146,7 +147,7 @@ This table contains the following columns: * raster - Raster data in Well Known Binary Format (WKB) best generated using `raster2psql` in the command line * site_id - Unique identifier to pit location * site_name - Name describing the general survey area ( e.g. Grand Mesa) -* surveyors - Names of the people or organization that acquired the data +* observers - Names of the people or organization that acquired the data * time_created - Time this entry was uploaded * time_updated - Time this entry was last modified * type - Name of the data collected diff --git a/docs/gallery/compare_SSA_instruments_example.ipynb b/docs/gallery/compare_SSA_instruments_example.ipynb index 5ee23b6..fcf91df 100644 --- a/docs/gallery/compare_SSA_instruments_example.ipynb +++ b/docs/gallery/compare_SSA_instruments_example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -38,12 +38,13 @@ "\n", "# Connect to the database\n", "db_name = 'db.snowexdata.org/snowex'\n", + "\n", "engine, session = get_db(db_name, credentials='./credentials.json')\n", "\n", "# Grab all the equivalent diameter profiles\n", - "q = session.query(LayerData).filter(LayerData.type == 'specific_surface_area')\n", + "qry = session.query(LayerData).filter(LayerData.type == 'specific_surface_area')\n", "\n", - "df = query_to_geopandas(q, engine)\n", + "df = query_to_geopandas(qry, engine)\n", "\n", "# End our database session to avoid hanging transactions\n", "session.close()\n", @@ -61,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -93,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 6, "metadata": { "tags": [ "nbsphinx-thumbnail", @@ -103,7 +104,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -160,18 +161,11 @@ "plt.tight_layout()\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/compare_UAVSAR_to_depths_example.ipynb b/docs/gallery/compare_UAVSAR_to_depths_example.ipynb index 4561629..6391272 100644 --- a/docs/gallery/compare_UAVSAR_to_depths_example.ipynb +++ b/docs/gallery/compare_UAVSAR_to_depths_example.ipynb @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -60,22 +60,23 @@ "site_id = '5S31'\n", "\n", "# Distance around the pit to collect data in meters\n", - "buffer_dist = 500\n", + "buffer_dist = 50\n", "\n", "# Connect to the database\n", "db_name = 'db.snowexdata.org/snowex'\n", + "\n", "engine, session = get_db(db_name, credentials='./credentials.json')\n", "\n", "# Grab our pit location by provided site id from the site details table\n", - "q = session.query(SiteData.geom).filter(SiteData.site_id == site_id)\n", - "sites = q.all()\n", + "qry = session.query(SiteData.geom).filter(SiteData.site_id == site_id)\n", + "sites = qry.all()\n", "\n", "# There can be different dates at a single site, so we only grab one to retrieve the geometry object\n", "point = sites[0][0]\n", "\n", "# Create a polygon buffered by our distance centered on the pit\n", - "q = session.query(gfunc.ST_Buffer(point, buffer_dist))\n", - "buffered_pit = q.all()[0][0]" + "qry = session.query(gfunc.ST_Buffer(point, buffer_dist))\n", + "buffered_pit = qry.all()[0][0]" ] }, { @@ -87,21 +88,21 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "3925 Snow Depths found with 500m of 5S31\n" + "114 Snow Depths found with 50m of 5S31\n" ] } ], "source": [ "# Grab all the snow depths measured by a probe in the buffer\n", - "q = session.query(PointData).filter(gfunc.ST_Within(PointData.geom, buffered_pit))\n", - "points = q.filter(PointData.instrument.in_(['mesa','magnaprobe','pit ruler'])).all()\n", + "qry = session.query(PointData).filter(gfunc.ST_Within(PointData.geom, buffered_pit))\n", + "points = qry.filter(PointData.instrument.in_(['mesa','magnaprobe','pit ruler'])).all()\n", "\n", "# Convert the records received to geopandas\n", "df_points = points_to_geopandas(points)\n", @@ -117,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -132,22 +133,28 @@ " \n", " Return the records (which should be only one)\n", " '''\n", - " q = session.query(ImageData.id, \n", + " qry = session.query(ImageData.id, \n", " ImageData.type,\n", " func.ST_NearestValue(ImageData.raster, poi))\n", - " q = q.filter(ImageData.date == date(2020, 2, 12))\n", - " q = q.filter(ImageData.type.contains(name))\n", - " q = q.filter(ImageData.description.contains(polarization))\n", - " q = q.filter(ImageData.description.contains(dem))\n", - " q = q.filter(gfunc.ST_Within(poi, func.ST_Envelope(ImageData.raster)))\n", - " return q.all()\n", - "\n", - "\n", + " qry = qry.filter(ImageData.date == date(2020, 2, 12))\n", + " qry = qry.filter(ImageData.type.contains(name))\n", + " qry = qry.filter(ImageData.description.contains(polarization))\n", + " qry = qry.filter(ImageData.description.contains(dem))\n", + " qry = qry.filter(ImageData.site_name == 'Grand Mesa')\n", + " qry = qry.filter(gfunc.ST_Within(poi, func.ST_Envelope(ImageData.raster)))\n", + " return qry.all()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ "df = gpd.GeoDataFrame(columns=['geom','depth','img','real','phase'])\n", "\n", "# loop over all our snow depths\n", "for i, row in df_points.iterrows():\n", - " \n", " # Form a EWKT geom object to find values\n", " poi = from_shape(row['geom'], srid=26912).ST_AsEWKT()\n", " \n", @@ -162,12 +169,16 @@ " 'depth':row['value']}\n", "\n", " # Add it to our df\n", - " df = df.append(results, ignore_index=True)\n" + " df = df.append(results, ignore_index=True)\n", + "\n", + " \n", + "# Close the session to avoid hanging transactions\n", + "session.close()" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -177,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": { "tags": [ "nbsphinx-thumbnail", @@ -187,7 +198,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -206,27 +217,11 @@ "\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "session.close()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/get_spiral_example.ipynb b/docs/gallery/get_spiral_example.ipynb index 492c195..dde2eb6 100644 --- a/docs/gallery/get_spiral_example.ipynb +++ b/docs/gallery/get_spiral_example.ipynb @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ "import geoalchemy2.functions as gfunc\n", "import geopandas as gpd\n", "\n", - "# PIT Site Identifier\n", + "# Intense Observation Period Pit Site Identifier\n", "site_id = '5S31'\n", "\n", "# Distance around the pit to collect data in meters\n", @@ -44,6 +44,7 @@ "\n", "# Connect to the database we made.\n", "db_name = 'db.snowexdata.org/snowex'\n", + "\n", "engine, session = get_db(db_name, credentials='./credentials.json')\n", "\n", "# Grab our pit location by provided site id from the site details table\n", @@ -63,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -81,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -92,7 +93,10 @@ "qry = qry.filter(gfunc.ST_Within(PointData.geom.ST_AsText(), buffered_pit.ST_AsText()))\n", "\n", "# Execute the query\n", - "points = qry.all()\n" + "points = qry.all()\n", + "\n", + "# Close the session to avoid hanging transactions\n", + "session.close()" ] }, { @@ -104,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "metadata": { "tags": [ "nbsphinx-gallery", @@ -114,7 +118,17 @@ "outputs": [ { "data": { - "image/png": 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\n", + "text/plain": [ + "Text(68.6083306656794, 0.5, 'Northing [m]')" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", "text/plain": [ "
" ] @@ -138,23 +152,13 @@ "# Set the various plots x/y labels and title.\n", "ax.set_title('Grand Mesa Snow Depths w/in {}m of site {}'.format(buffer_dist, site_id))\n", "ax.set_xlabel('Easting [m]')\n", - "ax.set_ylabel('Northing [m]')\n", - "\n", - "# Close the session to avoid hanging transactions\n", - "session.close()" + "ax.set_ylabel('Northing [m]')" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/getting_started_example.ipynb b/docs/gallery/getting_started_example.ipynb index 729652b..c47ce1d 100644 --- a/docs/gallery/getting_started_example.ipynb +++ b/docs/gallery/getting_started_example.ipynb @@ -37,14 +37,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "5N15, 2S20, 2N13, 7S50, 7S23, 8N33, 9N30, 6S53, 6S32, 8N35, 9N39, 5N10, 8S41, 2N49, 6N17, TLSFL2A, 5N11, 2S45, 1C14, 8C26, 2C2, 2C9, 8S28, 9C28, 2C4, 1C7, 1C1, 4C30, 2C6, 6C24, 2N12, 8C22, 1C8, 2C3, 6C10, GML, 9C23, 8C31, 8C32, 5C27, 1S17, 6N16, 3N26, 1C1, 1S2, 2S16, 1N1, 9N28, 2S7, 2N8, 2S10, 8C18, 1N20, 8S18, 8C29, 6S22, 9C16, 8C11, 8N9, 8C36, 1S13, 6S15, 8C35, 2S4, 2S9, 8N54, 6S34, 5S49, 8N37, 9N47, 3S52, 8N52, 5S42, 9N42, 5S29, 8N51, 2S46, 2S27, 6S44, 7N40, 3S33, 9N43, 9N56, 6C37, 3S5, 6S19, 2S3, 1S1, 2S25, 5S43, 2S48, 2S36, 5S24, 9S51, 8S30, 3S47, FL1B, 5N24, 6S26, 2C12, 5N32, 2C13, 1C5, 9N29, 4N27, 8N34, 2C33, 9C17, 5C21, 8C25, 5S31, 2S35, 9C19, 6N36, 5C20, 6N31, 8N38, 7C15, 5N41, 9N44, 5N50, 3S14, 1S8, 5S21, 9S39, 2S37, 6N46, 8N45, 2N48, 6C34, 2S11, 3S38, 9S40, 1N3, 2N21, 2N14, 2S6, 1N7, 1N23, 1N5, 1S12, FL2A, 5N10, 2N4, 3N22, 5N19, 4N2, 7N57, 1N6, 3N53, 6N18, 8N55, 9N59, 8N25, 8N58\n", + "8C18, 1C1, Open 6, 2S4, 2S7, 6N36, Skyway Open, 6S22, 2S6, 9S40, 9N30, 1N1, 9N47, 1N3, 9N29, 8N45, 9N39, 8C35, 1C5, 6N31, 3S33, 5N24, 3N53, 1C7, 7N40, SNB 2, 8N55, County Line Open, 6N18, 5C20, 5N10, 8N52, 2N21, 1N5, 6S32, GML, 1S1, 2C3, 8S41, JPL 1, Forest 14, 6S53, C1, 8C11, Open, 2C13, Open Flat, Joe Wright, 8N54, 7S23, 6N16, 8C31, Open 2, 5S42, Mesa West Open, 8N34, Upper, 6C37, 5S49, 9S39, 1S17, 2S35, 1C8, BA Flux Tower, 8N9, FL2A, 5S31, 8N38, 6S26, Caples Lake, Open 4, 2S46, 8S28, 8C36, 5N15, 2C33, 6N46, 3S14, 6S15, 8N35, Skyway Tree, TLSFL2A, 2N13, 3N26, 1S8, Saddle, Banner Open, 3S47, 3S52, 4N2, 2S9, 9S51, Trench 13, 6C24, Panorama Dome, 5C27, Senator Beck, 2S25, Swamp Angel, FL1B, 9N42, 1N6, JPL 2, 2S11, 2N8, 9N59, 1N7, 8C25, 3S5, 8N58, 9C28, 2S10, 2S45, 5C21, 5S24, 7S50, 2N49, 8C22, Forest 13, 2N14, 9C17, 5N19, 2C9, 5N50, 2N4, Mores Creek Summit, LDP Tree, 1C14, 2C2, CUES, SNB 1, 8S18, Michigan River, 7C15, Irwin Barn, 2S20, 1S12, 6S44, 2S48, 9C19, 9N43, 9N56, 9N44, 8S30, 8C26, 7N57, 3S38, 9C16, 5N11, 6S34, 4N27, Forest 12, 5S21, 2C12, 2N12, 9C23, 1S2, 3N22, 2N48, 2S3, 5S29, 8N25, 2C4, Forest North, 2C6, Forest, 2S37, 2S16, HQ Met Station, 1S13, Alta Collins, 4C30, County Line Tree, Bogus Upper, 2S36, 6S19, 8N37, Forest Flat, Atwater, LDP Open, 9N28, 1N23, Gothic, 6N17, 8N51, 1N20, Forest South, 5N41, 8C32, 5S43, 8N33, 5N32, 6C10, Tower 4, Banner Snotel, 2S27, Mesa West Trees, 6C34, Aspen, 8C29\n", "\n" ] } @@ -54,7 +54,7 @@ "conn = engine.connect()\n", "\n", "# Form a typical SQL query and use python to populate the table name\n", - "qry = \"SELECT site_id FROM sites\"\n", + "qry = \"SELECT DISTINCT site_id FROM sites\"\n", "\n", "# Then we execute the sql command and collect the results\n", "results = conn.execute(qry)\n", @@ -82,14 +82,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "5N15, 2S20, 2N13, 7S50, 7S23, 8N33, 9N30, 6S53, 6S32, 8N35, 9N39, 5N10, 8S41, 2N49, 6N17, TLSFL2A, 5N11, 2S45, 1C14, 8C26, 2C2, 2C9, 8S28, 9C28, 2C4, 1C7, 1C1, 4C30, 2C6, 6C24, 2N12, 8C22, 1C8, 2C3, 6C10, GML, 9C23, 8C31, 8C32, 5C27, 1S17, 6N16, 3N26, 1C1, 1S2, 2S16, 1N1, 9N28, 2S7, 2N8, 2S10, 8C18, 1N20, 8S18, 8C29, 6S22, 9C16, 8C11, 8N9, 8C36, 1S13, 6S15, 8C35, 2S4, 2S9, 8N54, 6S34, 5S49, 8N37, 9N47, 3S52, 8N52, 5S42, 9N42, 5S29, 8N51, 2S46, 2S27, 6S44, 7N40, 3S33, 9N43, 9N56, 6C37, 3S5, 6S19, 2S3, 1S1, 2S25, 5S43, 2S48, 2S36, 5S24, 9S51, 8S30, 3S47, FL1B, 5N24, 6S26, 2C12, 5N32, 2C13, 1C5, 9N29, 4N27, 8N34, 2C33, 9C17, 5C21, 8C25, 5S31, 2S35, 9C19, 6N36, 5C20, 6N31, 8N38, 7C15, 5N41, 9N44, 5N50, 3S14, 1S8, 5S21, 9S39, 2S37, 6N46, 8N45, 2N48, 6C34, 2S11, 3S38, 9S40, 1N3, 2N21, 2N14, 2S6, 1N7, 1N23, 1N5, 1S12, FL2A, 5N10, 2N4, 3N22, 5N19, 4N2, 7N57, 1N6, 3N53, 6N18, 8N55, 9N59, 8N25, 8N58\n", + "8C18, 1C1, Open 6, 2S4, 2S7, 6N36, Skyway Open, 6S22, 2S6, 9S40, 9N30, 1N1, 9N47, 1N3, 9N29, 8N45, 9N39, 8C35, 1C5, 6N31, 3S33, 5N24, 3N53, 1C7, 7N40, SNB 2, 8N55, County Line Open, 6N18, 5C20, 5N10, 8N52, 2N21, 1N5, 6S32, GML, 1S1, 2C3, 8S41, JPL 1, Forest 14, 6S53, C1, 8C11, Open, 2C13, Open Flat, Joe Wright, 8N54, 7S23, 6N16, 8C31, Open 2, 5S42, Mesa West Open, 8N34, Upper, 6C37, 5S49, 9S39, 1S17, 2S35, 1C8, BA Flux Tower, 8N9, FL2A, 5S31, 8N38, 6S26, Caples Lake, Open 4, 2S46, 8S28, 8C36, 5N15, 2C33, 6N46, 3S14, 6S15, 8N35, Skyway Tree, TLSFL2A, 2N13, 3N26, 1S8, Saddle, Banner Open, 3S47, 3S52, 4N2, 2S9, 9S51, Trench 13, 6C24, Panorama Dome, 5C27, Senator Beck, 2S25, Swamp Angel, FL1B, 9N42, 1N6, JPL 2, 2S11, 2N8, 9N59, 1N7, 8C25, 3S5, 8N58, 9C28, 2S10, 2S45, 5C21, 5S24, 7S50, 2N49, 8C22, Forest 13, 2N14, 9C17, 5N19, 2C9, 5N50, 2N4, Mores Creek Summit, LDP Tree, 1C14, 2C2, CUES, SNB 1, 8S18, Michigan River, 7C15, Irwin Barn, 2S20, 1S12, 6S44, 2S48, 9C19, 9N43, 9N56, 9N44, 8S30, 8C26, 7N57, 3S38, 9C16, 5N11, 6S34, 4N27, Forest 12, 5S21, 2C12, 2N12, 9C23, 1S2, 3N22, 2N48, 2S3, 5S29, 8N25, 2C4, Forest North, 2C6, Forest, 2S37, 2S16, HQ Met Station, 1S13, Alta Collins, 4C30, County Line Tree, Bogus Upper, 2S36, 6S19, 8N37, Forest Flat, Atwater, LDP Open, 9N28, 1N23, Gothic, 6N17, 8N51, 1N20, Forest South, 5N41, 8C32, 5S43, 8N33, 5N32, 6C10, Tower 4, Banner Snotel, 2S27, Mesa West Trees, 6C34, Aspen, 8C29\n", "\n" ] } @@ -99,7 +99,7 @@ "from snowexsql.data import SiteData, PointData, LayerData, ImageData\n", "\n", "# Form the query to receive all the site_id from the sites table\n", - "qry = session.query(SiteData.site_id)\n", + "qry = session.query(SiteData.site_id).distinct()\n", "\n", "# Execute the query and collect the result\n", "results = qry.all()\n", @@ -113,25 +113,18 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Close your session to avoid hanging transactions\n", "session.close()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/graupel_pits_example.ipynb b/docs/gallery/graupel_pits_example.ipynb index ea6e39b..55e4793 100644 --- a/docs/gallery/graupel_pits_example.ipynb +++ b/docs/gallery/graupel_pits_example.ipynb @@ -26,14 +26,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Sites with Graupel: 8N38, 2S35\n" + "Sites with Graupel: 8S41, 8N38, 4C30, 1N7, 2N21, 2S35, 1S17, FL1B, 8N25, 5S21, 2S6, 1C7, 2C12, 1N3, 3S47, 2S11, County Line Open, 1N23, 6S32, County Line Open, County Line Tree, Mesa West Open, Mesa West Open, Mesa West Trees, Mesa West Trees, Skyway Open\n" ] } ], @@ -46,16 +46,17 @@ "\n", "# Connect to the database\n", "db_name = 'db.snowexdata.org/snowex'\n", + "\n", "engine, session = get_db(db_name, credentials='./credentials.json')\n", "\n", "# Build a query looking at hand hardness profiles, \n", - "q_base = session.query(LayerData).filter(LayerData.type == 'hand_hardness')\n", + "q_base = session.query(LayerData).filter(LayerData.type == 'hand_hardness').filter(LayerData.site_name == 'Grand Mesa')\n", "\n", "# add on to the query by filtering on comments containing graupel (case insensitive)\n", - "q = q_base.filter(LayerData.comments.contains('graupel'))\n", + "qry = q_base.filter(LayerData.comments.contains('graupel'))\n", "\n", "# Send query and convert records to a dataframe with the results\n", - "df_graupel = query_to_geopandas(q, engine)\n", + "df_graupel = query_to_geopandas(qry, engine)\n", "\n", "print('Sites with Graupel: {}'.format(', '.join(df_graupel['site_id'])))" ] @@ -69,18 +70,21 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Use the exact same query except use ~ to ask for the opposite (pits w/o graupel)\n", - "q = q_base.filter(~LayerData.comments.contains('graupel'))\n", + "qry= q_base.filter(~LayerData.comments.contains('graupel'))\n", "\n", "# There are multiple layers for a given site at different depths and dates. So insure we don't grab a site that on a given date had graupel\n", - "q = q.filter(~LayerData.date.in_(df_graupel['date']), ~LayerData.site_id.in_(df_graupel['site_id']))\n", + "qry = qry.filter(~LayerData.date.in_(df_graupel['date']), ~LayerData.site_id.in_(df_graupel['site_id']))\n", "\n", "# Send query and convert records to a dataframe with the results\n", - "df = query_to_geopandas(q, engine)" + "df = query_to_geopandas(qry, engine)\n", + "\n", + "# Close the database session to avoid hanging transactions\n", + "session.close()" ] }, { @@ -92,7 +96,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": { "tags": [ "nbsphinx-thumbnail", @@ -102,7 +106,7 @@ "outputs": [ { "data": { - "image/png": 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0z9hMq1at0tA7qUkbN25k/vz5rFu3Lt1dkRqQmZlJdnY2jRs3Tqm+AmQREZFq6Nwpm+mf/6vcAHn1iuXkdTswDb2SmjZ//nxatmxJTk4OZpbu7shOcHeWL1/O/Pnz6dy5c0ptdJOeiIhINWRlZdF6zyasXLXtXOSVq0povWcTsrIqnn4hu45169bRtm1bBccNgJnRtm3ban0boABZRESkmjp3ymb1iuXblK1esZzOnbLT1COpDQqOG47q/lkqQBYREamm5Cyysse7p02bNrFmzZoqt02bNu3Q8TMyMsjLy6N79+789Kc/pbS0lMLCQq699loAJk+ezD//+c+a/EgADBs2jPfeey/l+k8++SRHHHEEhx9+OLm5uVxxxRUprfZSWwYMGLDTz7BQgCwiIrID4llkZY93T5s3b2bhkuUsW1la4bZwyXI2b968Q8dv1qwZ06dP57PPPqNJkyaMHj2a/Px8HnjgAaD2AuSpU6fSp0+flOq+9tprjBo1iokTJzJz5kyKioo45phj+O6777aru6PjkA4KkEVERHZAIos8b+4cZY93U02bNqVF80waN2lCy1atttsaN2lCi+aZNG3adKfPVVBQQHFxMZMnT2bQoEHMnj2b0aNHM2rUKPLy8pgyZQrjxo2je/fu5Obm0r9//+2Occ011zBhwgQAzjzzTC677DIAHnvsMUaMGAHA559/ziGHHEJGRgbTp0+nT58+HHHEEZx55pl8//332x3zjjvuYOTIkXTs2BGIst6XXXYZXbt2BaInEt9444307NmTcePG8fDDD9OrVy9yc3M5++yzKS0tBWDo0KGMHz++7LgtWrQAol8C+vfvz6mnnkrXrl0ZNmwYW7ZsAeD111+nb9++9OzZk5/+9KesWbNmp8c5QQGyiIjIDurcKRs2lip7vBvbK6s160t/KHff+tIf2Cur9U6fY9OmTUycOJEePXqUleXk5DBs2DCuv/56pk+fTkFBAbfeeiuTJk1ixowZZYFwXEFBAVOmTAFgwYIFzJo1C4ApU6aUBdQTJ05k4MCBAFx88cXcddddfPLJJ/To0YPf//732x1z5syZ9OzZs9L+t23blqKiIoYMGcJZZ53FRx99xIwZM+jWrRuPPvpolZ//ww8/5MEHH2TWrFl88803PP/88yxbtozbb7+dN998k6KiIvLz87n33nurPFaqFCCLiIjsoKysLI7sfqiyx7uxzMxMMps22m6FhHXr1pHZtNFOPTBm7dq15OXlkZ+fT6dOnbj88ssrrd+vXz+GDh3Kww8/XO50hkSAPGvWLA477DDat2/PokWLeP/99znmmGMAmDRpEgMHDmTlypWUlJTwox/9CIBLLrmEf/zjH5We/9NPPyUvL4+DDjqIZ599tqz8vPPOK3v92WefUVBQQI8ePXjqqaeYOXNmleNw9NFHc+CBB5KRkcH555/Pu+++y9SpU5k1axb9+vUjLy+PsWPHMmfOnCqPlSqtgywiUksWL15crWWFMjMz2XfffWuxR1IbFBzLXlmtWfjd8m2C4fWlP9ChfdudOm5iDnKqRo8ezQcffMArr7zCUUcdxbRp02jbdmsfOnbsSElJCa+99hr9+/dnxYoVPPfcc7Ro0YKWLVtSWlpKSUkJHTp0YOXKlSmd8/DDD6eoqIjjjjuOHj16MH36dIYPH87atWvL6uy5555lr4cOHcqLL75Ibm4uY8aMYfLkyQA0atSobOrEli1b2LBhQ1mb5BUozAx358QTT+Tpp59OeXyqQwGyiEgtKC0tZf/9s2mxdxMaN636y7qN67fww/KNlJSspHnz5nXQQxGpKfEscmZmZo1kj1PRsmVLVq1aVfb+m2++oXfv3vTu3ZuJEycyb968bQJkgD59+nDffffx9ttvs3z5cs455xzOOeccAN555x2OO+44AFq3bk2bNm2YMmUKBQUF/PWvfy3LJsfdfPPN/OIXv+Cll14iOzuaahQPjpOtXr2a/fbbj40bN/LUU0+VzV3Oyclh2rRpnHvuuUyYMIGNGzeWtfnwww/59ttvOeCAA3j22We56qqr6NOnD9dccw3FxcV06dKFH374gQULFnDIIYfs4GhuSwGyiEgtaN68OeddeDYLOj3Psb+teomnKb/PYP955yg4FtlFxbPINZE9TsVpp53GOeecw0svvcSDDz7IqFGj+Prrr3F3fvzjH5Obm7tdm4KCAl5//XW6dOnCAQccwIoVKygoKACi+ceJYBlg7NixDBs2jNLSUg488EAef/zx7Y53yimnsHTpUk4++WQ2b95MVlYW3bt356STTiq3z7fddhu9e/emXbt29O7dm9WrVwNw5ZVXcvrpp5Obm8vAgQO3yTr36tWL4cOHU1xczHHHHceZZ57JHnvswZgxYzj//PNZv349ALfffnuNBcjm7jVyoApPYJYBFAIL3H2QmT0K5AMGfAUMdfc1ZnYDcAWwCVgKXObuc2LHaQXMAl509+Gh7ChgDNAMeBW4zt3dzPYCngVygNnAue7+vUU5+vuBU4DScO6iyvqfn5/vO7uWnojsnoqLizmqTw+u+nIdmZV8C7+uBB7qmknRB59x0EEH1V0HRaRCn3/+Od26datWm4WLv2Pthi00a7IHHfZtX0s9qz09e/bkgw8+oHHjxunuSpnJkyczcuRIXn755Z0+Vnl/pmY2zd3zk+vWxU161wGfx95f7+657n4EMBcYHso/BvJD+Xjg7qTj3AYkzw7/M3AlcHDYBobym4C33P1g4K3wHuDkWN2rQnsRkVrRpUsXTjttMIUPVP5l3Uf3ZzD4tNMVHIvs4vbKag1bNtbIyhXpUFRUVK+C43Sq1QDZzLKBU4FHEmXuvirsM6LMr4fyd9y9NFSbCmTHjnMU0B54PVa2H9DK3ad6lAZ/Ajgj7D4dGBtej00qf8IjU4GscBwRkVpxy4g7KPpjI9ZV8FCpdSXw8Z8ac8uv76jbjolIjcvMzKTjvvvU+tzj3cmAAQNqJHtcXbWdQb4P+BWwJV5oZo8Di4FDgQfLaXc5MDHU3QP4A/CLpDodgfmx9/NDGUB7d18UXi8mCq4TbeZV0EZEpMZVlUVW9likYVFw3DDUWoBsZoOAJe4+LXmfu18KdCCaenFeUrsLieYo3xOKfga86u7z2QEhu1ytidZmdpWZFZpZ4dKlS3fktCIiZSrKIit7LCJSP9XmKhb9gMFmdgqQCbQysyfd/UIAd99sZs8QZZgfBzCzE4ARwI/cfX04Tl+gwMx+BrQAmpjZGqKb7eKPLsoGFoTX35nZfu6+KEyhWBLKFwD7V9CmjLs/BDwE0U16OzMIIiJbs8jbrmih7LHIrkvrnDdstRYgu/vNwM0AZjaAaIrERWbWxd2LwxzkwcAXoc6RwF+Age6+JHacCxKvzWwo0Y18N4X3q8ysD/ABcDFbp2tMAC4B7gw/X4qVDw+BeW9gZWwqhohIrbllxB0c1WcC+dduIjNra/b40Q+UPRbZ1Wid84avrtdBNmBsWLLNgBnA1WHfPUQZ4nHhiSlz3X1wFcf7GVuXeZsYNogC4+fM7HJgDnBuKH+VaIm3YqJl3i7d+Y8kIlK15Cyyssciu666Wuc8IyODHj16sGnTJrp168bYsWOZNWsWTzzxBA888ACTJ0+mSZMmZY+JrinDhg3joosuol+/ftuUP/nkk9x9991s3ryZRo0a0atXL0aOHJm2p0kOGDCAkSNHkp+/3SptO61OAmR3nwxMDm/7VVDnhBSOM4YoIE68LwS6l1NvOfDjcsoduKbqHouI1LxEFrn7xZuUPRbZxSV/K1SRnfm2KP6o6QsuuIDRo0dzww03lAWEkydPpkWLFjUeIE+dOpU//vGP25S99tprjBo1iokTJ9KxY0c2b97M2LFj+e6777YLkDdv3kxGRkaN9qmu1cU6yCIiwtYs8pM/3kPZY5FdXF2vc15QUEBxcTGTJ09m0KBBzJ49m9GjRzNq1Cjy8vKYMmUK48aNo3v37uTm5tK/f//tjnHNNdcwYcIEAM4880wuu+wyAB577DFGjBgBRA/TOOSQQ7YLcO+44w5GjhxZ9mjojIwMLrvsMrp27QpEj4q+8cYb6dmzJ+PGjePhhx+mV69e5ObmcvbZZ1NaGq3kO3ToUMaPH1923BYtWgBRsN+/f39OPfVUunbtyrBhw9iyJVoE7fXXX6dv37707NmTn/70p6xZs2anxjIVCpBFROrQLSPuYPP3zbRyhUgDUFfrnG/atImJEyfSo0ePsrKcnByGDRvG9ddfz/Tp0ykoKODWW29l0qRJzJgxoywQjisoKGDKlCkALFiwgFmzZgEwZcqUsoB64sSJDBw4cLu2M2fOpGfPnpX2s23bthQVFTFkyBDOOussPvroI2bMmEG3bt149NFHq/ycH374IQ8++CCzZs3im2++4fnnn2fZsmXcfvvtvPnmmxQVFZGfn8+9995b5bF2lgJkEZE61KVLF5YuWa7ssUgDUNvrnK9du5a8vDzy8/Pp1KkTl19+eaX1+/Xrx9ChQ3n44YfZvHnzdvsTAfKsWbM47LDDaN++PYsWLeL9998vm6YxadKkcgPkuE8//ZS8vDwOOuggnn322bLy887bunLvZ599RkFBAT169OCpp55i5syZVX7eo48+mgMPPJCMjAzOP/983n33XaZOncqsWbPo168feXl5jB07ljlz5lR5rJ1V1zfpiYjs9po2bZruLohIDaloLnJNrFQTn4OcitGjR/PBBx/wyiuvcNRRRzFt2jTatm1btr9jx46UlJTw2muv0b9/f1asWMFzzz1HixYtaNmyJaWlpZSUlNChQ4ftjn344YdTVFTEcccdR48ePZg+fTrDhw9n7dq1ZXX23HPPstdDhw7lxRdfJDc3lzFjxjB58mQAGjVqVDZ1YsuWLWzYsKGsTVikYZv37s6JJ57I008/nfI41ARlkEVERER2UEVZ5LpYqaZly5asXr267P0333xD7969ufXWW2nXrh3z5s3brk2fPn2477776N+/PwUFBYwcOZKCggIA3nnnHY477rhyz3XzzTfzi1/8gvnztz63LR4cJ1u9ejX77bcfGzdu5Kmnniorz8nJYdq06BlyEyZMYOPGjWX7PvzwQ7799lu2bNnCs88+y7HHHkufPn147733KC4uBuCHH37gq6++SmV4dooCZBEREZGdkDwXua6eknnaaafxwgsvlN2k98tf/pIePXrQvXt3jjnmGHJzc7drU1BQwKZNm+jSpQs9e/ZkxYoVZQFyRfOPAU455RSuvfZaTj75ZA477DCOOeYYMjIyOOmkk8qtf9ttt9G7d2/69evHoYceWlZ+5ZVX8ve//53c3Fzef//9bbLOvXr1Yvjw4XTr1o3OnTtz5pln0q5dO8aMGcP555/PEUccQd++ffniiy92ZthSYtHKZ1KR/Px8LywsTHc3REREpA59/vnndOvWLeX6F156Xtm6yIl1j//6+DO12MOa17NnTz744AMaN25c5+eePHkyI0eO5OWXX661c5T3Z2pm09x9u4WUlUEWERER2UmJLHLJ7LrJHteGoqKitATH9ZECZBEREZGdpHXOd86AAQNqNXtcXQqQRURERGqA1jlvOLTMm4iIiEg53H27pccqk1jnXEs51j/VvedOGWQRERGRJJmZmSxfvrzagZWC4/rH3Vm+fDmZmZkpt1EGWURERCRJdnY28+fPZ+nSpenuitSAzMxMsrOzU66vAFlEREQkSePGjencuXO6uyFpUutTLMwsw8w+NrOXw/tHzWyGmX1iZuPNrEUov8HMZoXyt8zsgFB+gJkVmdl0M5tpZsNCectQltiWmdl9Yd9QM1sa23dFrD+XmNnXYbuktj+/iIiIiOxa6iKDfB3wOdAqvL/e3VcBmNm9wHDgTuBjIN/dS83sauBu4DxgEdDX3deHYPozM5vg7guBvMRJzGwa8HzsvM+6+/B4R8xsL+B3QD7gwLRwrO9r/FOLiIiIyC6pVjPIZpYNnAo8kiiLBccGNCMKVHH3d9y9NFSbCmSH8g3uvj6UNy2vz2Z2CLAPMKWKLp0EvOHuK0JQ/AZQ/jMVRURERGS3VNtTLO4DfgVsiRea2ePAYuBQ4MFy2l0OTIzV39/MPgHmAXeF7HHcEKDzXlsAACAASURBVKKMcfxW07Nj0zj2D2UdwzES5oeybZjZVWZWaGaFmpwvIiIisnuptQDZzAYBS9x9WvI+d78U6EA09eK8pHYXEk2BuCdWf567HwF0AS4xs/ZJhxwCPB17/zcgJ7R5Axhbnb67+0Punu/u+e3atatOUxERERHZxdVmBrkfMNjMZgPPAMeb2ZOJne6+OZSfnSgzsxOAEcDg2LQKYm0WAp8BBbE2uUCjeCDu7stj7R8BjgqvFwCJbDJE0zgW7MRnFBEREZEGptYCZHe/2d2z3T2HKMP7NnCRmXWBsjnIg4Evwvsjgb8QBcdLEscxs2wzaxZetwGOBb6Mnep8ts0eY2b7xd4OJspUA0wCfmJmbcKxfhLKRERERESAul8H2YCxZtYqvJ4BXB323QO0AMaFxzrOdffBQDfgD2bmoc1Id/80dsxzgVOSznOtmQ0GNgErgKEA7r7CzG4DPgr1bnX3FTX7EUVERERkV2bVfYTi7iY/P98LCwvT3Q0RERERqWFmNs3d85PLa/1BISIiIiIiuxIFyCIiIiIiMQqQRURERERiFCCLiIiIiMQoQBYRERERiVGALCIiIiISowBZRERERCSmwgeFmNlZKbRf5+6v1mB/RERERETSqrIn6T0MvET09LqK9AcUIIuIiIhIg1FZgDzR3S+rrLGZPVnD/RERERERSasK5yC7+4VVNU6ljoiIiIjIrqSyDDIAZpYBnArkxOu7+7211y0RERERkfSoMkAG/gasAz4FttRud0RERERE0iuVADnb3Y/Y0ROEDHQhsMDdB5nZo0A+0c1/XwFD3X2Nmd0AXAFsApYCl7n7HDM7AHiBaDpIY+BBdx8djj0Z2A9YG073E3dfYmZNgSeAo4DlwHnuPju0uRm4HNgMXOvuk3b0s4mIiIhIw5PKOsgTzewnO3GO64DPY++vd/fcEHTPBYaH8o+B/FA+Hrg7lC8C+rp7HtAbuMnMOsSOd4G754VtSSi7HPje3bsAo4C7AMzsMGAIcDgwEPhTCOBFRERERIDUAuSpwAtmttbMVpnZajNblcrBzSybaP7yI4kyd18V9hnQDPBQ/o67l8bOmR3KN7j7+lDeNMU+nw6MDa/HAz8O5zsdeMbd17v7t0AxcHQqn0VEREREdg+pBJv3An2B5u7eyt1bunurFI9/H/ArkuYum9njwGLgUODBctpdDkyM1d/fzD4B5gF3ufvCWN3HzWy6mf0mBMEAHUNd3H0TsBJoGy8P5ocyEREREREgtQB5HvCZu3t1Dmxmg4Al7j4teZ+7Xwp0IJp6cV5SuwuJ5ijfE6s/L0y96AJcYmbtw64L3L0HUBC2i6rTx0r6fpWZFZpZ4dKlS2vikCIiIiKyi0glQP4XMNnMbjazGxJbCu36AYPNbDbwDHB8/MEi7r45lJ+dKDOzE4ARwODYtApibRYCnxEFw7j7gvBzNfC/bJ0usQDYPxyzEdCa6Ga9svIgO5Qln+chd8939/x27dql8FFFREREpKFIJUD+FngLaAK0jG2Vcveb3T3b3XOIbox7G7jIzLpA2RzkwcAX4f2RwF+IguPEzXaYWbaZNQuv2wDHAl+aWSMz2zuUNwYGEQXPABOAS8Lrc4C3QwZ8AjDEzJqaWWfgYODDFMZARERERHYTVS7z5u6/r8HzGTDWzFqF1zOAq8O+e4AWwLgwlXiuuw8GugF/MDMPbUa6+6dmticwKQTHGcCbwMPhWI8CfzWzYmAFUYCOu880s+eAWUTLyV0TMtkiIiIiIgBYRVOLzewWd7+l0sYp1NnV5efne2FhYbq7ISIiIiI1zMymuXt+cnllGeQrqljOzYgys7fsZN9EREREROqNygLkh6l6rvHDVewXEREREdmlVBgg1/DcYxERERGRXUIqq1iIiIiIiOw2FCCLiIiIiMQoQBYRERERialyHWQze6Cc4pVAobu/VPNdEhERERFJn1QyyJlAHvB12I4gekTz5WZ2Xy32TURERESkzlWZQSYKiPslnjhnZn8GphA98vnTWuybiIiIiEidSyWD3IboEdAJewJ7hYB5fa30SkREREQkTVLJIN8NTDezyURPz+sP/JeZ7Qm8WYt9ExERERGpc1UGyO7+qJm9Chwdiv7T3ReG17+stZ6JiIiIiKRBqsu87QEsBb4HuphZ/9rrkoiIiIhI+qSyzNtdwHnATGBLKHbgH7XYLxERERGRtEglg3wG0NXdT3X308I2ONUTmFmGmX1sZi+H94+a2Qwz+8TMxptZi1B+g5nNCuVvmdkBofwAMysys+lmNtPMhoXy5mb2ipl9EcrvjJ1zqJktDW2mm9kVsX2XmNnXYbsk1c8hIiIiIruHVALkfwGNd+Ic1wGfx95f7+657n4EMBcYHso/BvJD+XiimwMBFgF93T0P6A3cZGYdwr6R7n4ocCTQz8xOjp3nWXfPC9sjAGa2F/C7cJyjgd+ZWZud+GwiIiIi0sCksopFKdEqFm8RW9bN3a+tqqGZZQOnAncAN4R2q8I+A5oRTdfA3d+JNZ0KXBjKN8TKmxKCencvBd5J1DGzIqIHmFTmJOANd18R+vAGMBB4uqrPIiIiIiK7h1QC5Alh2xH3Ab8CWsYLzexx4BRgFvDzctpdDkyM1d8feAXoAvwytopGYn8WcBpwf6z47HAz4VdEWet5QEdgXqzO/FC2DTO7CrgKoFOnTql8ThERERFpIFJZ5m3sjhzYzAYBS9x9mpkNSDrmpWaWATxIdAPg47F2FwL5wI9i9ecBR4SpFS+a2Xh3/y7Ub0SUAX7A3f8VmvwNeNrd15vZvwNjgeNT7bu7PwQ8BJCfn+/V++QiIiIisiurcA6ymT0Xfn4abpzbZkvh2P2AwWY2G3gGON7MnkzsDE/iewY4O3bOE4ARwGB33+4pfSFz/BlQECt+CPja3e+L1Vsea/8IcFR4vQDYP9Y2O5SJiIiIiACVZ5CvCz8H7ciB3f1m4GaAkEH+BXCRmXVx9+IwB3kw8EWocyTwF2Cguy9JHCfMY17u7mvDDXXHAqPCvtuB1kDZKhWhfD93XxTeDmbrTYKTiJ4CmLgx7yeJPoqIiIiIQCUBciLAdPc5NXg+A8aaWavwegZwddh3D9ACGBfFzswNy8l1A/5gZh7ajHT3T0PgPIIowC4Kbf4nrFhxrZkNBjYBK4Ch4bOsMLPbgI/COW9N3LAnIiIiIgJg7pVPsTWzs4C7gH2IAlQD3N1b1X730i8/P98LCwvT3Q0RERERqWFmNs3d85PLU1nF4m7gNHf/vMqaIiIiIiK7uFQeFPKdgmMRERER2V1UmEEOUysACs3sWeBFtn1QyPO13DcRERERkTpX2RSL02KvS4lWfEhwQAGyiIiIiDQ4la1icSmAmfVz9/fi+8ysX213TEREREQkHVKZg/xgimUiIiIiIru8yuYg9wWOAdqZ2Q2xXa2AjNrumIiIiIhIOlQ2B7kJ0YM7GgEtY+WrgHNqs1MiIiIiIulS2Rzkv5vZu8AR7v77OuyTiIiIiEjaVDoH2d03Ax3qqC8iIiIiImmXypP0ppvZBGAc8EOiUOsgi4iIiEhDlEqAnAksB46PlWkdZBERERFpkKoMkBPrIYuIiIiI7A6qXAfZzLLN7AUzWxK2/zOz7FRPYGYZZvaxmb0c3j9qZjPM7BMzG29mLUL5DWY2K5S/ZWYHhPIDzKzIzKab2UwzGxY79lFm9qmZFZvZA2ZmoXwvM3vDzL4OP9uEcgv1isN5elZvuERERESkoUvlQSGPAxOIbtbrAPwtlKXqOuDz2Pvr3T3X3Y8A5gLDQ/nHQH4oHw/cHcoXAX3dPQ/oDdxkZokbB/8MXAkcHLaBofwm4C13Pxh4K7wHODlW96rQXkRERESkTCoBcjt3f9zdN4VtDNAulYOHTPOpwCOJMndfFfYZ0IxoPjPu/o67l4ZqU4HsUL7B3deH8qaJPpvZfkArd5/q7g48AZwR6p0OjA2vxyaVP+GRqUBWOI6IiIiICJBagLzczC4MUyUyzOxCopv2UnEf8CtgS7zQzB4HFgOHUv5jqy8HJsbq729mnwDzgLvcfSHQEZgfazM/lAG0d/dF4fVioH143TEco7w2IiIiIiIpBciXAecSBZqLiJ6iV+WNe2Y2CFji7tOS94Ub/zoQTb04L6ndhUA+cE+s/rww9aILcImZtSdFIbvsqdYPfbjKzArNrHDp0qXVaSoiIiIiu7gqA2R3n+Pug929nbvv4+5nuPvcFI7dDxhsZrOBZ4DjzezJ2HE3h/KzE2VmdgIwAhgcm1YR78tC4DOgAFhAmIYRZIcygO8SUyfCzyWhfAGwfwVt4ud5yN3z3T2/XbuUZpOIiIiISANR4TJvZvbbStq5u99W2YHd/Wbg5nCsAcAvgIvMrIu7F4c5yIOBL0KdI4G/AAPdPRHQJuYxL3f3tWE1imOBUe6+yMxWmVkf4APgYrZO15gAXALcGX6+FCsfbmbPEN3wtzI2FUNEREREpNJ1kH8op2xPovnBbYFKA+QKGDDWzFqF1zOAq8O+e4AWwLiwWttcdx8MdAP+YGYe2ox0909Dm58BY4hu9pvI1nnLdwLPmdnlwByiKSIArwKnAMVAKSlMFRERERGR3YtFU3SrqGTWkmi5tsuB54A/xLO8DVl+fr4XFhamuxsiIiIiUsPMbJq75yeXV/okPTPbC7gBuIBoubSe7v597XRRRERERCT9KpuDfA9wFvAQ0MPd19RZr0RERERE0qSyVSx+TrQU26+BheGGuFVmttrMVtVN90RERERE6laFGWR3T2WNZBERERGRBkVBsIiIiIhIjAJkEREREZEYBcgiIiIiIjEKkEVEREREYhQgi4iIiIjEKEAWEREREYlRgCwiIiIiEqMAWUREREQkpsIHhYiISM1atmwZxcXFVdbr0qULe++9dx30SEREylPrAbKZZQCFwAJ3H2RmjwL5gAFfAUPdfY2Z3QBcAWwClgKXufscM8sD/gy0AjYDd7j7s+HYU4CW4VT7AB+6+xlmNgB4Cfg27Hve3W8NbQYC9wMZwCPufmftjoCISGTlypW88NZU9tq3U4V1Viyey1Xt2ilAFhFJo7rIIF8HfE4U4AJc7+6rAMzsXmA4cCfwMZDv7qVmdjVwN3AeUApc7O5fm1kHYJqZTXL3EncvSJzEzP6PKChOmOLug+IdCcH6H4ETgfnAR2Y2wd1n1fzHFhHZ1kEHHUTOvm2wNnuxX8cDttu/aMEcWrGagw46KA29ExGRhFqdg2xm2cCpwCOJslhwbEAzwEP5O+5eGqpNBbJD+Vfu/nV4vRBYArRLOk8r4HjgxSq6dDRQ7O7/cvcNwDPA6TvzGUVEquP4Y/uwaHb50ywWzS7m+GP71HGPREQkWW3fpHcf8CtgS7zQzB4HFgOHAg+W0+5yYGJyoZkdDTQBvknadQbwViL4Dvqa2Qwzm2hmh4eyjsC8WJ35oUxEpE507dqVfVs3ZtGCOduUL1owh31bN6Zr165p6pmIiCTUWoBsZoOAJe4+LXmfu18KdCCaenFeUrsLieYo35NUvh/wV+BSd98m4AbOB56OvS8CDnD3XKIAvKrMcnLfrzKzQjMrXLp0aXWaiohUqbwssrLHIiL1R21mkPsBg81sNtFUhuPN7MnETnffHMrPTpSZ2QnACGCwu6+PlbcCXgFGuPvU+EnMbG+iqROvxI69yt3XhNevAo1DvQXA/rHm2aFsG+7+kLvnu3t+u3btkneLiOyU5CyyssciIvVLrQXI7n6zu2e7ew4wBHgbuMjMukDZHOTBwBfh/ZHAX4iC4yWJ45hZE+AF4Al3H1/Oqc4BXnb3dbE2+4bjJ6Zl7AEsBz4CDjazzuG4Q4AJNfvJRUSqFs8iK3ssIlK/1PU6yAaMDRlhA2YAV4d99wAtgHEhtp3r7oOBc4H+QFszGxrqDnX36eH1EKJVMOLOAa42s03AWmCIuzuwycyGA5OIlnl7zN1n1vzHFBGpXNeuXdn33akUffS+ssciIvWMRXGjVCQ/P98LCwvT3Q0RaYC+/PJLnnz+VS486xQFyCIiaWBm09w9P7lcT9ITEUmTrl27cuFZKDgWEalnFCCn2fz585kxY0aV9XJzc8nOzq6DHolIXVJwLCJS/yhATrNly5bx1KtT2Du74idnLZv/DR07dlSALCIiIlIHFCCnWV5eHp3bv0pG233olHPwdvvnzv6alhuXkpeXl4beiYiIiOx+avtJepKCM04+kQXF5S+msaB4JmecfGId90hERERk96UAuR7o1asX+7aIssVxc2d/zb4tov0iIiIiUjcUINcT5WWRlT0WERERqXsKkOuJ5CyyssciIiIi6aEAuR6JZ5GVPRYRERFJDwXI9Ugiizz13TeVPRYRERFJEwXI9cwZJ5/IpuXzlD0WERERSROtg1zP9OrVi2tQ9lhEREQkXZRBrocUHIuIiIikjzLIIiIiIlKnSkpKmDt3bpX1OnXqRFZWVh30aFu1HiCbWQZQCCxw90Fm9iiQDxjwFTDU3deY2Q3AFcAmYClwmbvPMbM84M9AK2AzcIe7PxuOPQb4EbAynG6ou083MwPuB04BSkN5UWhzCfDrUP92dx9buyMgIiIiInFr1qxh4rvTaLNPxwrrfL9kARcM3qthBsjAdcDnRAEuwPXuvgrAzO4FhgN3Ah8D+e5eamZXA3cD5xEFuBe7+9dm1gGYZmaT3L0kHO+X7j4+6ZwnAweHrTdRgN3bzPYCfkcUoHs41gR3/75WPrmISJotXryYdevWpVw/MzOTfffdtxZ7JCIC2dnZHLBPG7xVFu337bDd/u8WL6QVpWRnZ6ehd7UcIJtZNnAqcAdwA0AsODagGVGgiru/E2s6FbgwlH+VKHT3hWa2BGgHlFCx04En3N2BqWaWZWb7AQOAN9x9RejDG8BA4Omd/rAiIvVMaWkp+++fTYu9m9C4adW3nGxcv4Uflm+kpGQlzZs3r4MeisjurE9+Hi+9/WG5AfKS+bM5/fij09CrSG1nkO8DfgW0jBea2eNE0x9mAT8vp93lwMTkQjM7GmgCfBMrvsPMfgu8Bdzk7uuBjsC8WJ35oayichGRBqd58+acd+HZLOj0PMf+dlOV9af8PoP9552j4FhE6kROTg7tW03nu8ULtwmSv1u8kPatmpCTk5O2vtXaKhZmNghY4u7Tkve5+6VAB6KpF+cltbuQaArEPUnl+wF/BS519y2h+GbgUKAXsBdwYw31/SozKzSzwqVLl9bEIUVE0uKWEXdQ9MdGrKvsOzdgXQl8/KfG3PLrO+qmYyIiRFnkJfNnb1O2ZP5s+uTnpadDQW0u89YPGGxms4FngOPN7MnETnffHMrPTpSZ2QnACGBwyAQnylsBrwAj3H1q7BiLPLIeeBxI5OIXAPvH+pIdyioq34a7P+Tu+e6e365dux357CIi9UKXLl047bTBFD5Q+ReGH92fweDTTueggw6qo56JiCSyyE34bvFCoH5kj6EWA2R3v9nds909BxgCvA1cZGZdoGwO8mDgi/D+SOAvRMHxksRxzKwJ8ALRnOJtbsYLWeXEsc4APgu7JgAXW6QPsNLdFwGTgJ+YWRszawP8JJSJiDRYVWWRlT0WkXSKZ5HrQ/YY6v5BIQaMNbNPgU+B/YBbw757gBbAODObbmYTQvm5QH9gaCifHpZ+A3gqdqy9gdtD+avAv4Bi4GHgZwDh5rzbgI/Cdmvihj0RkYaqqiyysscikk6JLPKnM4rqRfYYwKKFHqQi+fn5XlhYmO5uiEg9sG7dOkpKqpjMC2RlZZGZmVkHPUpdcXExR/XpwVVfriMztqTouhJ4qGsmRR98pgBZRNJm9uzZvPjaO5wx8Lg6DZDNbJq75yeX60l6IiIp2rBhA5989S17tqx40fofVpfQJ+/wehcgb80ib7uihbLHIlIf5OTk1HlwXBkFyCIiKWrVqhXtslqypWlzWrfaPkheuaqE5hmbadWqVTmt0++WEXdwVJ8J5F+7icysrXOPH/1Ac49FJP3qS3AMdT8HWURkl9a5UzarVywvd9/qFcvp3Ck9T31KRfJcZGWPRUTKpwBZRKQasrKyaL1nE1au2nYu8spVJbTeswlZWRVPv6gPEitalMzWyhUiIhVRgCwiUk3lZZHre/Y4IZFFfvLHeyh7LCJSAQXIIiLVlJxF3lWyxwm3jLiDzd83U/ZYRKQCCpBFRHZAPIu8q2SPE7p06cLSJcuVPRYRqYACZBGRHZDIIs+bO2eXyh4nNG3aNN1dEBGptxQgi4jsoM6dsmFj6S6VPRYRkaopQBYR2UFZWVkc2f3QXS57LCIilVOALCKyExQci4g0PAqQRURERERizN3T3Yd6zcyWAnPS3Y96am9gWbo7sRvQONcNjXPt0xjXDY1z3dA41766GOMD3L1dcqECZNlhZlbo7vnp7kdDp3GuGxrn2qcxrhsa57qhca596RxjTbEQEREREYlRgCwiIiIiEqMAWXbGQ+nuwG5C41w3NM61T2NcNzTOdUPjXPvSNsaagywiIiIiEqMMsoiIiIhIjALk3ZCZdTWz6bFtlZn9v9j+n5uZm9ne4f3pZvZJqFtoZsfG6l5iZl+H7ZJY+VFm9qmZFZvZA2ZmoXwvM3sj1H/DzNrU5WevS9Ud51h5LzPbZGbnxMo0zhXYget5gJmtjNX/bazuQDP7MoznTbHyzmb2QSh/1syahPKm4X1x2J9Td5+87uzItRzGebqZzTSzv8fKNcYV2IFr+Zexup+Z2WYz2yvs0zhXYAfGubWZ/c3MZoTr+dJYXf3bXI4dGOM2ZvaCRbHGh2bWPVY3Pdeyu2vbjTcgA1hMtA4gwP7AJKK1n/cOZS3YOh3nCOCL8Hov4F/hZ5vwuk3Y9yHQBzBgInByKL8buCm8vgm4K91jUF/GOVbvbeBV4ByNc61czwOAlyto+w1wINAEmAEcFvY9BwwJr0cDV4fXPwNGh9dDgGfTPQb1ZIyzgFlAp/B+H41xzY9zUv3TgLc1zrVyPf9n4t9QoB2wIoyr/m2uuTG+B/hdeH0o8FasbVquZWWQ5cfAN+6eeBjKKOBXQNnkdHdf4+FKA/aM7TsJeMPdV7j798AbwEAz2w9o5e5TQ7sngDNCm9OBseH12Fh5Q1flOAf/AfwfsCRWpnFOXarjXJ6jgWJ3/5e7bwCeAU4PmZ/jgfGhXnw84+M8HvhxIlPUgKUyxv8GPO/ucwHcPXE9a4xTV91r+Xzg6fBa45y6VMbZgZZhPFoQBcib0L/NqUpljA8jSg7h7l8AOWbWnjReywqQZQjhH1UzOx1Y4O4zkiuZ2Zlm9gXwCnBZKO4IzItVmx/KOobXyeUA7d19UXi9GGhfQ5+jvqtynM2sI3Am8Oekthrn1KV0PQN9w9elE83s8FBW0Ti3BUrcfVNS+TZtwv6VoX5DlsoYHwK0MbPJZjbNzC4O5Rrj1KV6LWNmzYGBRL9cg8a5OlIZ5/8BugELgU+B69x9C/q3OVWpjPEM4KxQ52jgACCbNF7LjarbQBqOMF9nMHBz+Af2P4GflFfX3V8AXjCz/sBtwAk7e353dzNr8MuoVGOc7wNudPctNZm40Thvp4joq741ZnYK8CJwcN31dNdVjTFuBBxFlDlqBrxvZlPrrKO7uOr82xycBrzn7ivqon8NRTXG+SRgOlHG8iDgDTObsrPn3x3+ba7GGN8J3G9m04l+CfkY2FxnHS2HMsi7t5OBInf/jugvfWdghpnNJvrNrcjM9o03cPd/AAeGifULiOYSJWSHsgXhdXI5wHfh6yfCz/hUgoYq1XHOB54J5ecAfzKzM9A4pyqlcXb3Ve6+BsDdXwUaV3E9LweyzKxRUjnxNmF/61C/oUr1Wp4PTHL3H9x9GfAPIBeNcaqq+29zWYYu0DinJtVxvpRoypC7ezHwLdE82f/f3r2FWlHFcRz//srKzNAsKILASxCZgogEmUJRTxb0Ij1FZBCIXSioFIKSXqQLRFER+WI3MAuVfKlQ6qHoYoGXk5RpHXwqKioUysBWD7NOzjkpnpNje5/4fmDYM2vWnpn9ZzGzzjprzfLefGJjuS8vK6XMA26l6ev9Db0sy111wnYZfwtNX55lx9k3yNHO85dydJDe/Fr4QjMw4VuawQnn1fVpNd/IAQpLavoTDB+g8Hiv49AvcR6Rvo7hg/SMc0dxBi5qlecrgQM1fhNobsgzODoY5Iqa7w2GDwZZUdfvZPhgkA29jkOfxPhyYFuN6SRgAJhjjLuNc92eQtMn9pxWmnHuMM403d5W1/ULaZ6BF3hv7jTGU4Ez6/odwMt1vWdluefBc+nNQjPY7idgynH2twvuSuALmn8xfQQsauW7HdhXl2Wt9AU0D8X9NP23hiok59M8OL8Gtg7dTP6vy1jiPCJ9HbWCbJw7L8931fK8E/gYWNjKtwTYW+P5UCt9Zn3g7as35bNq+sS6va/un9nrWPRDjOv2AzRvshgA7jXGpyzOtwHrj5HPOHcUZ+Bi4F2af/0PALe08nlv7ibGV9Xy+hWwkfo2kLqvJ2XZmfQkSZKkFvsgS5IkSS1WkCVJkqQWK8iSJElSixVkSZIkqcUKsiRJktRiBVmS+liSI0l2tJZV/+IY1yRZ2Npe3pr++WSvbzDJ7iQLxvCdWfW3HOriGiSpa77mTZL6WJJDpZTJJ3mM1cChUsqT3VzVsGMPAgtKM2PeWL970r9Nkk4FW5AlaRxK8nCS7UkGkryYJDX9niR7kuxKsj7JdGA5cF9ttV2cZHWS+2v+95M8luTTJHuTLK7pk5JsqMfalOST0bQS1xblNfVcnyWZn+SdJPuTLD91EZGk7kw4cRZJUg+dnWRHa3tNKeV14NlSyqMASV4BbgS20ExfO6OUcjjJ1FLKL0leoNWCnOS6EeeYUEq5MskS4BHgemAF8HMpZXaSOTQzaY7WgVLKvCRP0cwKeTXN7FYDNFPCSlJfs4IsSf3toUI12AAAAWBJREFUt1LKvGOkX5vkQWASMI1m+uwtwC7gtSSbgc2jPMfG+vk5ML2uLwKeBiilDCTZNYZrfqt+7gYml1IOAgeT/F1pH8OxJOk/ZxcLSRpnkkwEngeWllLmAmtpWmgBbgCeA+YD25OMpiHkcP08QjcNJ0PH+7O1PrRtw4ykvmcFWZLGn6HK8I9JJgNLAZKcBlxSSnkPWAlMASYDB4Fzx3iOD4Gb63FnA3M7uG5JGhf8S16S+tvIPshvl1JWJVlL06f3O2B73Xc68GqSKUCAZ2of5C3Am0luAu4e5XmfB15Ksgf4kqYLx68d/B5J6nu+5k2S9A9JTgfOKKX8nmQWsBW4rJTyx4h8g/iaN0n/M3axkCQdyyTggyQ7gU3AipGV4+oHYNu/mSgE+L6bS5WkbtmCLEmSJLXYgixJkiS1WEGWJEmSWqwgS5IkSS1WkCVJkqQWK8iSJElSixVkSZIkqeUvzVe5Gg/YyKcAAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -114,8 +118,6 @@ } ], "source": [ - "# Close the database session to avoid hanging transactions\n", - "session.close()\n", "\n", "# Plot the dataframe without graupel as grey and slightly transparent.\n", "ax = df.plot(color='steelblue', alpha=0.1, marker='v', markersize=80, edgecolor='black', label='Pits w/o Graupel', figsize=(10,8))\n", @@ -135,18 +137,11 @@ "# Ask matplotlib to try and avoid overlaying labels on each other\n", "plt.tight_layout()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/graupel_smp_example.ipynb b/docs/gallery/graupel_smp_example.ipynb index 11180af..47ec9c3 100644 --- a/docs/gallery/graupel_smp_example.ipynb +++ b/docs/gallery/graupel_smp_example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -42,10 +42,10 @@ "engine, session = get_db(db_name, credentials='./credentials.json')\n", "\n", "# Query the database looking at SMP profiles at our site\n", - "q = session.query(LayerData).filter(LayerData.type == 'force').filter(LayerData.site_id.contains(site))\n", + "qry = session.query(LayerData).filter(LayerData.type == 'force').filter(LayerData.site_id.contains(site))\n", "\n", "# Convert SMP profiles to geopandas dataframe\n", - "df = query_to_geopandas(q, engine)" + "df = query_to_geopandas(qry, engine)" ] }, { @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -72,15 +72,15 @@ ], "source": [ "# Grab hand hardness profiles at our site only\n", - "q = session.query(LayerData).filter(LayerData.type == 'hand_hardness')\n", - "q = q.filter(LayerData.site_id == site)\n", + "qry = session.query(LayerData).filter(LayerData.type == 'hand_hardness')\n", + "qry = qry.filter(LayerData.site_id == site)\n", "\n", "# Convert the results to a dataframe\n", - "hh = query_to_geopandas(q, engine)\n", + "hh = query_to_geopandas(qry, engine)\n", "\n", "# Find the word graupel in the comments\n", - "q = q.filter(LayerData.comments.contains('graupel'))\n", - "graupel = query_to_geopandas(q, engine).iloc[0]\n", + "qry = qry.filter(LayerData.comments.contains('graupel'))\n", + "graupel = query_to_geopandas(qry, engine).iloc[0]\n", "\n", "# Get the distance below surface to use with SMP data \n", "graupel['depth'] = graupel['depth'] - (hh['depth'].max())\n", @@ -106,12 +106,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -137,7 +137,6 @@ "# Avoid using Scientific notation for coords.\n", "ax.ticklabel_format(style='plain', useOffset=False)\n", "ax.legend()\n", - "# plt.tight_layout()\n", "plt.show()" ] }, @@ -150,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": { "tags": [ "nbsphinx-gallery", @@ -242,27 +241,11 @@ "fig.suptitle('SMP Profiles higlighting a graupel layer at Site {}\\n{}'.format(site, df['date'].max()).title(), fontsize=16)\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "session.close()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/overview_example.ipynb b/docs/gallery/overview_example.ipynb index f70abd7..f2c26ef 100644 --- a/docs/gallery/overview_example.ipynb +++ b/docs/gallery/overview_example.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -44,7 +44,7 @@ "\n", "# DEM data name and surveyor\n", "data_name = 'DEM'\n", - "surveyors = 'USGS'\n", + "observers = 'USGS'\n", "\n", "# Resolution to make our DEM/Hillshade\n", "res = 20\n", @@ -66,12 +66,12 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Define a function to reduce the same code used for getting the dem and hillshade\n", - "def filter_and_return(session, base, data_name, surveyors, extent):\n", + "def filter_and_return(session, base, data_name, observers, extent):\n", " '''\n", " Small function to apply redundent filters and raster making\n", " '''\n", @@ -80,7 +80,7 @@ " \n", " # Filter by data name and surveyor\n", " q = q.filter(ImageData.type == data_name)\n", - " q = q.filter(ImageData.surveyors == surveyors)\n", + " q = q.filter(ImageData.observers == observers)\n", " \n", " # Execute the query\n", " rasters = q.all()\n", @@ -92,20 +92,49 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "ProgrammingError", + "evalue": "(psycopg2.errors.UndefinedColumn) column images.observers does not exist\nLINE 3: WHERE public.images.type = 'DEM' AND public.images.observers...\n ^\n\n[SQL: SELECT ST_AsTIFF(ST_Clip(ST_Union(ST_Rescale(public.images.raster, %(ST_Rescale_1)s, %(ST_Rescale_2)s, %(ST_Rescale_3)s)), ST_AsEWKT(ST_GeomFromWKB(%(ST_GeomFromWKB_1)s, %(ST_GeomFromWKB_2)s)))) AS \"ST_AsTIFF_1\" \nFROM public.images \nWHERE public.images.type = %(type_1)s AND public.images.observers = %(observers_1)s]\n[parameters: {'ST_Rescale_1': 20, 'ST_Rescale_2': -20, 'ST_Rescale_3': 'blinear', 'ST_GeomFromWKB_1': , 'ST_GeomFromWKB_2': 26912, 'type_1': 'DEM', 'observers_1': 'USGS'}]\n(Background on this error at: http://sqlalche.me/e/14/f405)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mUndefinedColumn\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[0;34m(self, dialect, constructor, statement, parameters, execution_options, *args, **kw)\u001b[0m\n\u001b[1;32m 1705\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mevt_handled\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1706\u001b[0;31m self.dialect.do_execute(\n\u001b[0m\u001b[1;32m 1707\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/default.py\u001b[0m in \u001b[0;36mdo_execute\u001b[0;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[1;32m 716\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdo_execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 717\u001b[0;31m \u001b[0mcursor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 718\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mUndefinedColumn\u001b[0m: column images.observers does not exist\nLINE 3: WHERE public.images.type = 'DEM' AND public.images.observers...\n ^\n", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mProgrammingError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# Retrieve the dem, join all the tiles retrieved\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mbase\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mST_Union\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype_\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mRaster\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Is NOT EXECUTED until query is executed.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mdem\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfilter_and_return\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbase\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobservers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mextent_ewkt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# Merge all the tiles retrieved, then make the hillshade.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mfilter_and_return\u001b[0;34m(session, base, data_name, observers, extent)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;31m# Execute the query\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mrasters\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;31m# Convert the dataset from the DB to rasterio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/orm/query.py\u001b[0m in \u001b[0;36mall\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 2697\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0mref\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mfaq_query_deduplicating\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2698\u001b[0m \"\"\"\n\u001b[0;32m-> 2699\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2700\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2701\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0m_generative\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/orm/query.py\u001b[0m in \u001b[0;36m_iter\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 2832\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2833\u001b[0m \u001b[0mstatement\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_statement_20\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2834\u001b[0;31m result = self.session.execute(\n\u001b[0m\u001b[1;32m 2835\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2836\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/orm/session.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, statement, params, execution_options, bind_arguments, _parent_execute_state, _add_event, **kw)\u001b[0m\n\u001b[1;32m 1673\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1674\u001b[0m \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_connection_for_bind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclose_with_result\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1675\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute_20\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecution_options\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1676\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1677\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcompile_state_cls\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_20\u001b[0;34m(self, statement, parameters, execution_options)\u001b[0m\n\u001b[1;32m 1519\u001b[0m )\n\u001b[1;32m 1520\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1521\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs_10style\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs_10style\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecution_options\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1522\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1523\u001b[0m def exec_driver_sql(\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/sql/elements.py\u001b[0m in \u001b[0;36m_execute_on_connection\u001b[0;34m(self, connection, multiparams, params, execution_options, _force)\u001b[0m\n\u001b[1;32m 311\u001b[0m ):\n\u001b[1;32m 312\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0m_force\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupports_execution\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 313\u001b[0;31m return connection._execute_clauseelement(\n\u001b[0m\u001b[1;32m 314\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecution_options\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 315\u001b[0m )\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_clauseelement\u001b[0;34m(self, elem, multiparams, params, execution_options)\u001b[0m\n\u001b[1;32m 1388\u001b[0m \u001b[0mlinting\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdialect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompiler_linting\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mcompiler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mWARN_LINTING\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1389\u001b[0m )\n\u001b[0;32m-> 1390\u001b[0;31m ret = self._execute_context(\n\u001b[0m\u001b[1;32m 1391\u001b[0m \u001b[0mdialect\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1392\u001b[0m \u001b[0mdialect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecution_ctx_cls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_init_compiled\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/base.py\u001b[0m in 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"\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[0;34m(self, dialect, constructor, statement, parameters, execution_options, *args, **kw)\u001b[0m\n\u001b[1;32m 1704\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1705\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mevt_handled\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1706\u001b[0;31m self.dialect.do_execute(\n\u001b[0m\u001b[1;32m 1707\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1708\u001b[0m )\n", + "\u001b[0;32m~/projects/venv/snowexenv/lib/python3.8/site-packages/sqlalchemy/engine/default.py\u001b[0m in 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'blinear', 'ST_GeomFromWKB_1': , 'ST_GeomFromWKB_2': 26912, 'type_1': 'DEM', 'observers_1': 'USGS'}]\n(Background on this error at: http://sqlalche.me/e/14/f405)" + ] + } + ], "source": [ "# Create the base query to reduce code: Collect Rasters and rescale them to our resolution and use bilinear interpolation \n", "bq = func.ST_Rescale(ImageData.raster, res, -1 * res, 'blinear')\n", "\n", "# Retrieve the dem, join all the tiles retrieved\n", "base = gfunc.ST_Union(bq, type_=Raster) # Is NOT EXECUTED until query is executed.\n", - "dem = filter_and_return(session, base, data_name, surveyors, extent_ewkt) \n", + "dem = filter_and_return(session, base, data_name, observers, extent_ewkt) \n", "\n", "# Merge all the tiles retrieved, then make the hillshade.\n", "base = func.ST_Hillshade(gfunc.ST_Union(bq, type_=Raster)) # Is NOT EXECUTED until query is executed.\n", - "hillshade = filter_and_return(session, base, data_name, surveyors, extent_ewkt)" + "hillshade = filter_and_return(session, base, data_name, observers, extent_ewkt)" ] }, { @@ -208,16 +237,16 @@ "outputs": [], "source": [ "# Define a function to grab the center of each raster tile\n", - "def get_tile_centers(session, data_name, surveyors=None):\n", + "def get_tile_centers(session, data_name, observers=None):\n", " '''\n", " Simple function to grab the center of each tile given a data type and optionally a surveyor name\n", " '''\n", " # Use database to grab the centroid of each tile outline (envelope) filtering on type. Also return the surveyor.\n", " q = session.query(func.ST_Centroid(func.ST_Envelope(ImageData.raster))).filter(ImageData.type == data_name)\n", " \n", - " # If surveyors is provided, filter on that too\n", - " if surveyors != None:\n", - " q = q.filter(ImageData.surveyors == surveyors)\n", + " # If observers is provided, filter on that too\n", + " if observers != None:\n", + " q = q.filter(ImageData.observers == observers)\n", " \n", " centers = q.all()\n", " \n", @@ -251,11 +280,11 @@ "tiles = {}\n", "\n", "# Grab all the ASO DEM centers, assign color as blue and use squares for symbols\n", - "tiles['ASO Depths'] = (get_tile_centers(session, 'depth', surveyors='ASO Inc.'), 'steelblue', 's')\n", - "# tiles['ASO SWE'] = (get_tile_centers(session, 'swe', surveyors='ASO Inc.'), 'plum', 's')\n", + "tiles['ASO Depths'] = (get_tile_centers(session, 'depth', observers='ASO Inc.'), 'steelblue', 's')\n", + "# tiles['ASO SWE'] = (get_tile_centers(session, 'swe', observers='ASO Inc.'), 'plum', 's')\n", "\n", "# Grab all the USGS DEM centers, assign color as light red and use pentagons for symbols\n", - "tiles['USGS DEM'] = (get_tile_centers(session, 'DEM', surveyors='USGS'), 'plum','p')\n", + "tiles['USGS DEM'] = (get_tile_centers(session, 'DEM', observers='USGS'), 'plum','p')\n", "\n", "# Grab all the insar data centers, assign color as some shade of orange and use diamonds for symbols\n", "tiles['INSAR Amplitudes'] = (get_tile_centers(session, 'insar amplitude'), 'gold', 'D')\n", @@ -298,23 +327,23 @@ "\n", " metadata[k] = list(set(metadata[k]))\n", "\n", - "# Find all surveyors (Temporarily not working because surveyor upload is incorrect)\n", - "metadata['surveyors'] = []\n", + "# Find all observers (Temporarily not working because surveyor upload is incorrect)\n", + "metadata['observers'] = []\n", "\n", "for tbl in [PointData, LayerData, ImageData]:\n", - " print(f'Counting surveyors in {tbl.__name__}...')\n", + " print(f'Counting observers in {tbl.__name__}...')\n", " \n", " # Manage multiple names in the surveyor\n", - " surveyors = session.query(tbl.surveyors).filter(tbl.surveyors.isnot(None)).distinct().all()\n", - " for name in surveyors:\n", + " observers = session.query(tbl.observers).filter(tbl.observers.isnot(None)).distinct().all()\n", + " for name in observers:\n", " if ',' in name[0] and 'JPL' not in name[0]:\n", - " metadata['surveyors'] += name[0].split(',')\n", + " metadata['observers'] += name[0].split(',')\n", " elif '&' in name[0]:\n", - " metadata['surveyors'] += name[0].split('&')\n", + " metadata['observers'] += name[0].split('&')\n", " else:\n", - " metadata['surveyors'] += [name[0]]\n", + " metadata['observers'] += [name[0]]\n", "\n", - "metadata['surveyors'] = len(list(set(metadata['surveyors'])))\n", + "metadata['observers'] = len(list(set(metadata['observers'])))\n", "metadata['date'] = (min(metadata['date']).strftime('%Y-%m-%d'), max(metadata['date']).strftime('%Y-%m-%d'))\n", "metadata['instrument'] = len(metadata['instrument'])\n", "metadata['doi'] = len(metadata['doi'])\n" @@ -403,7 +432,7 @@ "# Add a block showing off details \n", "\n", "\n", - "textstr = '\\n'.join([f\"No. Surveyors: {metadata['surveyors']}\",\n", + "textstr = '\\n'.join([f\"No. observers: {metadata['observers']}\",\n", " f\"No. Instruments: {metadata['instrument']}\", \n", " f\"Temporal Extent: {metadata['date'][0]} - {metadata['date'][1]}\",\n", " f\"Published Datasets: {metadata['doi']}\"])\n", @@ -438,7 +467,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/plot_raster_example.ipynb b/docs/gallery/plot_raster_example.ipynb index cd8573a..4ff04d6 100644 --- a/docs/gallery/plot_raster_example.ipynb +++ b/docs/gallery/plot_raster_example.ipynb @@ -79,7 +79,7 @@ "print('Grabbing rasters that overlap on the point {}'.format(p_shp))\n", "\n", "# Grab the returned raster as a tiff\n", - "q = session.query(func.ST_AsTiff(ImageData.raster)).filter(ImageData.surveyors=='ASO Inc.')\n", + "q = session.query(func.ST_AsTiff(ImageData.raster)).filter(ImageData.observers=='ASO Inc.')\n", "q = q.filter(ImageData.type=='depth')\n", "\n", "# Filter rasters by where a tile intersects wihtour pit location\n", @@ -168,7 +168,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/gallery/raster_union_and_more_example.ipynb b/docs/gallery/raster_union_and_more_example.ipynb index 44c5c43..843a4d4 100644 --- a/docs/gallery/raster_union_and_more_example.ipynb +++ b/docs/gallery/raster_union_and_more_example.ipynb @@ -112,7 +112,7 @@ "q = session.query(func.ST_AsTiff(func.ST_Union(ImageData.raster, type_=Raster)))\n", "\n", "# Only grab rasters that are the bare earth DEM from USGS\n", - "q = q.filter(ImageData.type == 'DEM').filter(ImageData.surveyors=='USGS')\n", + "q = q.filter(ImageData.type == 'DEM').filter(ImageData.observers=='USGS')\n", "\n", "# And grab rasters touching the circle\n", "q = q.filter(gfunc.ST_Intersects(ImageData.raster, buffered_pit))\n", @@ -225,7 +225,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/docs/history.rst b/docs/history.rst index 9e7ff4f..73a6d91 100644 --- a/docs/history.rst +++ b/docs/history.rst @@ -22,3 +22,10 @@ Hack Week 2021 (2021-07-15) * snowex_db_ is now a repo containing all necessary assets to build db. .. _snowex_db: https://github.com/SnowEx/snowex_db + +0.3.0 (2022-07-6) +----------------------------- + +* New columns were added to the LayerData table for flags +* Converted surveyors to observers +* Changed utm zone to be an integer diff --git a/docs/installation.rst b/docs/installation.rst index 0a280d8..04533ab 100644 --- a/docs/installation.rst +++ b/docs/installation.rst @@ -23,105 +23,6 @@ Installation .. .. _pip: https://pip.pypa.io .. .. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/ -Mac OS ------- - -First ensure you have following prequisites: - -* Python3.5 + -* HomeBrew - -.. code-block:: bash - - cd scripts/install && sh install_mac.sh - - -Ubuntu ------- - -First ensure you have following prequisites: - -* Python3.5 + -* wget - -.. code-block:: bash - - cd scripts/install && sh install_ubuntu.sh - -Python ------- -Install the python package by: - -.. code-block:: bash - - python setup.py install - - -Installing the Database ------------------------ -The script under ./scripts/install will perform the following: - -1: Adds the following to the file /etc/postgresql/13/main/environment to enable rasters, for more info see `PostGIS installation`_ page under -*2.2. Configuring raster* - -.. code-block:: bash - - POSTGIS_ENABLE_OUTDB_RASTERS=1 - POSTGIS_GDAL_ENABLED_DRIVERS=ENABLE_ALL - -2. Then it will restart the PostGIS service using: - -.. code-block:: bash - - sudo service postgresql restart - - -.. _PostGIS installation: http://postgis.net/docs/postgis_installation.html#install_short_version -.. _PostGresSQL: https://www.postgresql.org/download/ - -3. Creates your tables, our main one called snowex, and another called test for -running small unittests on. - -.. code-block:: bash - - sudo -u psql -c "CREATE DATABASE snowex; CREATE DATABASE test;" - -4. Installs the post gis extensions via: - -.. code-block:: bash - - psql test -c "CREATE EXTENSION postgis; CREATE EXTENSION postgis_raster;" - psql snowex -c "CREATE EXTENSION postgis; CREATE EXTENSION postgis_raster;" - - -4. Create a users ubuntu and snow - -5. Make user snow a read only user - -6. Installs the python package snowexsql - -**Notes for Remote Access** - -* To allow access to your remote database modify '/etc/postgresql/13/main/postgresql.conf' - by uncommenting and setting the following: - -.. code-block:: console - - listen_addresses = '*' - -* Further to add remote access add the following to /etc/postgresql/13/main/postgresql.conf: - - 1. To add access from the unrestricted access to jupyter hub user add the line below: - - .. code-block:: console - - host snowex ubuntu trust - - 2. To add the read only user access from anywhere add the following: - - .. code-block:: console - - host snowex snow 0.0.0.0/0 md5 Install From Source ------------------- @@ -142,50 +43,5 @@ Once you have a copy of the source, you can install it with: Once you install the python package, you can populate the database. -Populating the Database ------------------------ -This is only required for the admin user setting up the database. Once the data is in the database any user will be able -to access it. - -1. Setup an earth login account at NSIDC_. -Then make the following file via: - -.. code-block:: console - - echo 'machine urs.earthdata.nasa.gov login password ' >> ~/.netrc - -2. Edit the file ~/.netrc and replace the above with your actual credentials to the earth login - -3. Protect that file via: - -.. code-block:: console - - chmod 0600 ~/.netrc - -4. Download the data by running all the shell scripts under `./scripts/download` - -5. In the `./scripts/upload` folder, there is a collection of scripts to upload data -to the database. Once the data is on the disk, a user can run the scripts individually -or all together. - -.. code-block:: bash - - cd scripts/upload - - # Run individually - python add_profiles.py - - # or all together... - python run.py - -**Note:** The `run.py` script has a few questions to ask for a couple inputs -that are required to run upload the data. Additionally, running the run.py file -can take a few hours. - -**Additional Note:** -Running the scripts individually does not consider whether the data is in the db. So running a script twice will result -in that data being uploaded twice! - .. _Github repo: https://github.com/SnowEx/snowexsql .. _tarball: https://github.com/SnowEx/snowexsql/tarball/master -.. _NSIDC: https://urs.earthdata.nasa.gov/profile \ No newline at end of file diff --git a/snowexsql/data.py b/snowexsql/data.py index 8b5a80b..cd31745 100644 --- a/snowexsql/data.py +++ b/snowexsql/data.py @@ -23,7 +23,6 @@ class SnowData(object): time_created = Column(DateTime(timezone=True), server_default=func.now()) time_updated = Column(DateTime(timezone=True), onupdate=func.now()) id = Column(Integer, primary_key=True) - site_id = Column(String(50)) doi = Column(String(50)) date_accessed = Column(Date) @@ -35,7 +34,7 @@ class Measurement(object): instrument = Column(String(50)) type = Column(String(50)) units = Column(String(50)) - surveyors = Column(String(100)) + observers = Column(String(100)) class SingleLocationData(SnowData): @@ -47,9 +46,10 @@ class SingleLocationData(SnowData): northing = Column(Float) easting = Column(Float) elevation = Column(Float) - utm_zone = Column(String(10)) + utm_zone = Column(Integer) geom = Column(Geometry("POINT")) time = Column(Time(timezone=True)) + site_id = Column(String(50)) class SiteData(SingleLocationData, Base): @@ -60,6 +60,7 @@ class SiteData(SingleLocationData, Base): __tablename__ = 'sites' __table_args__ = {"schema": "public"} + pit_id = Column(String(50)) slope_angle = Column(Float) aspect = Column(Float) air_temp = Column(Float) @@ -116,9 +117,11 @@ class LayerData(SingleLocationData, Measurement, Base): depth = Column(Float) site_id = Column(String(50)) + pit_id = Column(String(50)) bottom_depth = Column(Float) comments = Column(String(1000)) sample_a = Column(String(20)) sample_b = Column(String(20)) sample_c = Column(String(20)) value = Column(String(50)) + flags = Column(String(20)) diff --git a/snowexsql/db.py b/snowexsql/db.py index 65b6e16..607469d 100644 --- a/snowexsql/db.py +++ b/snowexsql/db.py @@ -54,10 +54,10 @@ def get_db(db_str, credentials=None, return_metadata=False): else: db = f"{prefix}{db_str}" - # Always create a Session in US/Mountain TZ + # Always create a Session in UTC time engine = create_engine( db, echo=False, connect_args={ - "options": "-c timezone=us/mountain"}) + "options": "-c timezone=UTC"}) Session = sessionmaker(bind=engine) metadata = MetaData(bind=engine) diff --git a/tests/test_db.py b/tests/test_db.py index d10c8d1..223b6b5 100644 --- a/tests/test_db.py +++ b/tests/test_db.py @@ -14,7 +14,7 @@ class TestDB(DBSetup): base_atts = ['site_name', 'date', 'site_id'] single_loc_atts = ['latitude', 'longitude', 'easting', 'elevation', 'utm_zone', 'geom', 'time'] - meas_atts = ['instrument', 'type', 'units', 'surveyors'] + meas_atts = ['instrument', 'type', 'units', 'observers'] site_atts = base_atts + single_loc_atts + \ ['slope_angle', 'aspect', 'air_temp', 'total_depth',