diff --git a/docs/source/notebooks/dap_subset.ipynb b/docs/source/notebooks/dap_subset.ipynb index 8bd3fd29..54247918 100644 --- a/docs/source/notebooks/dap_subset.ipynb +++ b/docs/source/notebooks/dap_subset.ipynb @@ -17,10 +17,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:06.622100Z", - "iopub.status.busy": "2021-09-07T20:26:06.621700Z", - "iopub.status.idle": "2021-09-07T20:26:08.031803Z", - "shell.execute_reply": "2021-09-07T20:26:08.031377Z" + "iopub.execute_input": "2021-09-21T19:41:40.215964Z", + "iopub.status.busy": "2021-09-21T19:41:40.214196Z", + "iopub.status.idle": "2021-09-21T19:41:43.080778Z", + "shell.execute_reply": "2021-09-21T19:41:43.080116Z" } }, "outputs": [], @@ -43,10 +43,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:08.034681Z", - "iopub.status.busy": "2021-09-07T20:26:08.034065Z", - "iopub.status.idle": "2021-09-07T20:26:09.732966Z", - "shell.execute_reply": "2021-09-07T20:26:09.732597Z" + "iopub.execute_input": "2021-09-21T19:41:43.084662Z", + "iopub.status.busy": "2021-09-21T19:41:43.084117Z", + "iopub.status.idle": "2021-09-21T19:41:44.739277Z", + "shell.execute_reply": "2021-09-21T19:41:44.739727Z" } }, "outputs": [ @@ -429,35 +429,38 @@ " Conventions: CF-1.0\n", " id: pcmdi.ipcc4.miub_echo_g.sresa2.run1.atm.da\n", " history: Mon Aug 1 11:42:37 2011: ncks -4 -L 7 -d lat,42.0,64.0 -...\n", - " NCO: 4.0.9" ], "text/plain": [ @@ -506,10 +509,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:09.744979Z", - "iopub.status.busy": "2021-09-07T20:26:09.744599Z", - "iopub.status.idle": "2021-09-07T20:26:09.747025Z", - "shell.execute_reply": "2021-09-07T20:26:09.746659Z" + "iopub.execute_input": "2021-09-21T19:41:44.759354Z", + "iopub.status.busy": "2021-09-21T19:41:44.758788Z", + "iopub.status.idle": "2021-09-21T19:41:44.761205Z", + "shell.execute_reply": "2021-09-21T19:41:44.761682Z" } }, "outputs": [ @@ -557,10 +560,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:10.131528Z", - "iopub.status.busy": "2021-09-07T20:26:10.129889Z", - "iopub.status.idle": "2021-09-07T20:26:10.285852Z", - "shell.execute_reply": "2021-09-07T20:26:10.284401Z" + "iopub.execute_input": "2021-09-21T19:41:45.291209Z", + "iopub.status.busy": "2021-09-21T19:41:45.290650Z", + "iopub.status.idle": "2021-09-21T19:41:45.440996Z", + "shell.execute_reply": "2021-09-21T19:41:45.441428Z" } }, "outputs": [ @@ -936,7 +939,7 @@ " Conventions: CF-1.0\n", " id: pcmdi.ipcc4.miub_echo_g.sresa2.run1.atm.da\n", " history: Mon Aug 1 11:42:37 2011: ncks -4 -L 7 -d lat,42.0,64.0 -...\n", - " NCO: 4.0.9" ], "text/plain": [ @@ -994,10 +997,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:10.681170Z", - "iopub.status.busy": "2021-09-07T20:26:10.679327Z", - "iopub.status.idle": "2021-09-07T20:26:11.076934Z", - "shell.execute_reply": "2021-09-07T20:26:11.078211Z" + "iopub.execute_input": "2021-09-21T19:41:45.929122Z", + "iopub.status.busy": "2021-09-21T19:41:45.928426Z", + "iopub.status.idle": "2021-09-21T19:41:46.424965Z", + "shell.execute_reply": "2021-09-21T19:41:46.425387Z" } }, "outputs": [ @@ -1376,7 +1379,8 @@ " Conventions: CF-1.0\n", " id: pcmdi.ipcc4.miub_echo_g.sresa2.run1.atm.da\n", " history: Mon Aug 1 11:42:37 2011: ncks -4 -L 7 -d lat,42.0,64.0 -...\n", - " NCO: 4.0.9" ], "text/plain": [ @@ -1437,10 +1441,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:11.473605Z", - "iopub.status.busy": "2021-09-07T20:26:11.472006Z", - "iopub.status.idle": "2021-09-07T20:26:12.235921Z", - "shell.execute_reply": "2021-09-07T20:26:12.234751Z" + "iopub.execute_input": "2021-09-21T19:41:46.943045Z", + "iopub.status.busy": "2021-09-21T19:41:46.942484Z", + "iopub.status.idle": "2021-09-21T19:41:47.685981Z", + "shell.execute_reply": "2021-09-21T19:41:47.686539Z" } }, "outputs": [ @@ -1820,12 +1824,14 @@ " Conventions: CF-1.0\n", " id: pcmdi.ipcc4.miub_echo_g.sresa2.run1.atm.da\n", " history: Mon Aug 1 11:42:37 2011: ncks -4 -L 7 -d lat,42.0,64.0 -...\n", - " NCO: 4.0.9" ], "text/plain": [ @@ -1877,10 +1883,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:12.246146Z", - "iopub.status.busy": "2021-09-07T20:26:12.244616Z", - "iopub.status.idle": "2021-09-07T20:26:12.252155Z", - "shell.execute_reply": "2021-09-07T20:26:12.250726Z" + "iopub.execute_input": "2021-09-21T19:41:47.692408Z", + "iopub.status.busy": "2021-09-21T19:41:47.691703Z", + "iopub.status.idle": "2021-09-21T19:41:47.695158Z", + "shell.execute_reply": "2021-09-21T19:41:47.695713Z" } }, "outputs": [ @@ -1904,10 +1910,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:12.270634Z", - "iopub.status.busy": "2021-09-07T20:26:12.268594Z", - "iopub.status.idle": "2021-09-07T20:26:12.275500Z", - "shell.execute_reply": "2021-09-07T20:26:12.274467Z" + "iopub.execute_input": "2021-09-21T19:41:47.705883Z", + "iopub.status.busy": "2021-09-21T19:41:47.705155Z", + "iopub.status.idle": "2021-09-21T19:41:47.708670Z", + "shell.execute_reply": "2021-09-21T19:41:47.709226Z" } }, "outputs": [ @@ -1949,10 +1955,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:12.673355Z", - "iopub.status.busy": "2021-09-07T20:26:12.671759Z", - "iopub.status.idle": "2021-09-07T20:26:13.149406Z", - "shell.execute_reply": "2021-09-07T20:26:13.150535Z" + "iopub.execute_input": "2021-09-21T19:41:48.231202Z", + "iopub.status.busy": "2021-09-21T19:41:48.230264Z", + "iopub.status.idle": "2021-09-21T19:41:49.019918Z", + "shell.execute_reply": "2021-09-21T19:41:49.019316Z" } }, "outputs": [ @@ -2331,12 +2337,14 @@ " Conventions: CF-1.0\n", " id: pcmdi.ipcc4.miub_echo_g.sresa2.run1.atm.da\n", " history: Mon Aug 1 11:42:37 2011: ncks -4 -L 7 -d lat,42.0,64.0 -...\n", - " NCO: 4.0.9" ], "text/plain": [ @@ -2396,19 +2404,19 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:13.163835Z", - "iopub.status.busy": "2021-09-07T20:26:13.159729Z", - "iopub.status.idle": "2021-09-07T20:26:15.547432Z", - "shell.execute_reply": "2021-09-07T20:26:15.547781Z" + "iopub.execute_input": "2021-09-21T19:41:49.032571Z", + "iopub.status.busy": "2021-09-21T19:41:49.025111Z", + "iopub.status.idle": "2021-09-21T19:41:52.503916Z", + "shell.execute_reply": "2021-09-21T19:41:52.503274Z" } }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmpc2yih62c/sdii_SRES-A2-experiment_20600101-20640101.nc.\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { @@ -2782,10 +2790,10 @@ "Attributes:\n", " units: mm/day\n", " cell_methods: time: mean (interval: 30 minutes)\n", - " xclim_history: pr=max(0,pr) applied to raw data;\\n[2021-09-07 16:26:14] ...\n", + " xclim_history: pr=max(0,pr) applied to raw data;\\n[2021-09-21 15:41:50] ...\n", " standard_name: lwe_thickness_of_precipitation_amount\n", " long_name: Average precipitation during wet days (sdii)\n", - " description: Annual simple daily intensity index (sdii) : annual avera...
  • units :
    mm/day
    cell_methods :
    time: mean (interval: 30 minutes)
    xclim_history :
    pr=max(0,pr) applied to raw data;\n", + "[2021-09-21 15:41:50] sdii: SDII(pr=<array>, thresh='1 mm/day', freq='YS') - xclim version: 0.27.0.
    standard_name :
    lwe_thickness_of_precipitation_amount
    long_name :
    Average precipitation during wet days (sdii)
    description :
    Annual simple daily intensity index (sdii) : annual average precipitation for days with daily precipitation over 1 mm/day. this indicator is also known as the 'simple daily intensity index' (sdii).
    • " ], "text/plain": [ "\n", @@ -2818,7 +2827,7 @@ "Attributes:\n", " units: mm/day\n", " cell_methods: time: mean (interval: 30 minutes)\n", - " xclim_history: pr=max(0,pr) applied to raw data;\\n[2021-09-07 16:26:14] ...\n", + " xclim_history: pr=max(0,pr) applied to raw data;\\n[2021-09-21 15:41:50] ...\n", " standard_name: lwe_thickness_of_precipitation_amount\n", " long_name: Average precipitation during wet days (sdii)\n", " description: Annual simple daily intensity index (sdii) : annual avera..." @@ -2853,7 +2862,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/finch-usage.ipynb b/docs/source/notebooks/finch-usage.ipynb index cd2f9907..150eb88b 100644 --- a/docs/source/notebooks/finch-usage.ipynb +++ b/docs/source/notebooks/finch-usage.ipynb @@ -14,10 +14,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:17.427431Z", - "iopub.status.busy": "2021-09-07T20:26:17.427012Z", - "iopub.status.idle": "2021-09-07T20:26:18.801663Z", - "shell.execute_reply": "2021-09-07T20:26:18.801272Z" + "iopub.execute_input": "2021-09-21T19:41:55.713447Z", + "iopub.status.busy": "2021-09-21T19:41:55.710552Z", + "iopub.status.idle": "2021-09-21T19:41:58.489436Z", + "shell.execute_reply": "2021-09-21T19:41:58.488709Z" } }, "outputs": [], @@ -45,10 +45,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:18.804809Z", - "iopub.status.busy": "2021-09-07T20:26:18.804425Z", - "iopub.status.idle": "2021-09-07T20:26:18.807473Z", - "shell.execute_reply": "2021-09-07T20:26:18.806425Z" + "iopub.execute_input": "2021-09-21T19:41:58.494504Z", + "iopub.status.busy": "2021-09-21T19:41:58.493944Z", + "iopub.status.idle": "2021-09-21T19:41:58.496859Z", + "shell.execute_reply": "2021-09-21T19:41:58.497312Z" } }, "outputs": [ @@ -58,7 +58,7 @@ "text": [ "Help on method frost_days in module birdy.client.base:\n", "\n", - "frost_days(tasmin=None, check_missing='any', cf_compliance='warn', data_validation='raise', thresh='0 degC', freq='YS', missing_options=None, variable=None) method of birdy.client.base.WPSClient instance\n", + "frost_days(tasmin=None, thresh='0 degC', freq='YS', check_missing='any', missing_options=None, cf_compliance='warn', data_validation='raise', variable=None) method of birdy.client.base.WPSClient instance\n", " Number of days where daily minimum temperatures are below 0.\n", " \n", " Parameters\n", @@ -112,10 +112,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:18.812825Z", - "iopub.status.busy": "2021-09-07T20:26:18.811376Z", - "iopub.status.idle": "2021-09-07T20:26:22.948414Z", - "shell.execute_reply": "2021-09-07T20:26:22.949279Z" + "iopub.execute_input": "2021-09-21T19:41:58.501513Z", + "iopub.status.busy": "2021-09-21T19:41:58.500960Z", + "iopub.status.idle": "2021-09-21T19:42:03.053671Z", + "shell.execute_reply": "2021-09-21T19:42:03.052981Z" } }, "outputs": [], @@ -129,10 +129,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:22.957296Z", - "iopub.status.busy": "2021-09-07T20:26:22.956233Z", - "iopub.status.idle": "2021-09-07T20:26:22.963447Z", - "shell.execute_reply": "2021-09-07T20:26:22.962489Z" + "iopub.execute_input": "2021-09-21T19:42:03.060784Z", + "iopub.status.busy": "2021-09-21T19:42:03.059756Z", + "iopub.status.idle": "2021-09-21T19:42:03.062986Z", + "shell.execute_reply": "2021-09-21T19:42:03.063594Z" } }, "outputs": [ @@ -141,7 +141,7 @@ "output_type": "stream", "text": [ "Process status: ProcessSucceeded\n", - "Link to process output: https://pavics.ouranos.ca/wpsoutputs/dbb7dbb0-1019-11ec-9959-a44cc85b43bf/frost-days_SRES-A2-experiment_20460101-20650101.nc\n" + "Link to process output: https://pavics.ouranos.ca/wpsoutputs/fbdf3143-1b13-11ec-9dcd-28d24417f566/frost-days_SRES-A2-experiment_20460101-20650101.nc\n" ] } ], @@ -163,10 +163,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:22.975884Z", - "iopub.status.busy": "2021-09-07T20:26:22.974848Z", - "iopub.status.idle": "2021-09-07T20:26:23.023263Z", - "shell.execute_reply": "2021-09-07T20:26:23.022935Z" + "iopub.execute_input": "2021-09-21T19:42:03.072562Z", + "iopub.status.busy": "2021-09-21T19:42:03.071859Z", + "iopub.status.idle": "2021-09-21T19:42:03.202664Z", + "shell.execute_reply": "2021-09-21T19:42:03.203271Z" } }, "outputs": [ @@ -561,7 +561,7 @@ " xclim_history: tas=max(195,tas) applied to raw data; min of 194.73 detec...\n", " standard_name: days_with_air_temperature_below_threshold\n", " long_name: Number of frost days (tmin < 0c)\n", - " description: Annual number of days with minimum daily temperature belo...
    • height
      ()
      float64
      ...
      units :
      m
      positive :
      up
      standard_name :
      height
      axis :
      Z
      long_name :
      height
      array(2.)
    • time
      (time)
      object
      2046-01-01 00:00:00 ... 2065-01-...
      array([cftime.Datetime360Day(2046, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2047, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2048, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2049, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2050, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2051, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2052, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2053, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2054, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2055, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2056, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2057, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2058, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2059, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2060, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2061, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2062, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2063, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2064, 1, 1, 0, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.Datetime360Day(2065, 1, 1, 0, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)
    • lat
      (lat)
      float64
      42.68 46.39 50.1 53.81 57.52 61.23
      units :
      degrees_north
      long_name :
      latitude
      standard_name :
      latitude
      bounds :
      lat_bnds
      axis :
      Y
      _ChunkSizes :
      6
      array([42.677605, 46.388557, 50.099453, 53.810272, 57.520992, 61.231571])
    • lon
      (lon)
      float64
      281.2 285.0 288.8 ... 300.0 303.8
      units :
      degrees_east
      long_name :
      longitude
      standard_name :
      longitude
      bounds :
      lon_bnds
      axis :
      X
      _ChunkSizes :
      7
      array([281.25, 285.  , 288.75, 292.5 , 296.25, 300.  , 303.75])
  • units :
    days
    cell_methods :
    time: minimum (interval: 30 minutes) time: minimum within days time: sum over days
    xclim_history :
    tas=max(195,tas) applied to raw data; min of 194.73 detected;\n", + "[2021-09-21 15:42:00] frost_days: FROST_DAYS(tasmin=<array>, thresh='0 degC', freq='YS') - xclim version: 0.27.0.
    standard_name :
    days_with_air_temperature_below_threshold
    long_name :
    Number of frost days (tmin < 0c)
    description :
    Annual number of days with minimum daily temperature below 0℃.
    • " ], "text/plain": [ "\n", @@ -673,19 +674,19 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:23.029796Z", - "iopub.status.busy": "2021-09-07T20:26:23.029173Z", - "iopub.status.idle": "2021-09-07T20:26:23.076977Z", - "shell.execute_reply": "2021-09-07T20:26:23.076530Z" + "iopub.execute_input": "2021-09-21T19:42:03.215357Z", + "iopub.status.busy": "2021-09-21T19:42:03.214613Z", + "iopub.status.idle": "2021-09-21T19:42:03.478103Z", + "shell.execute_reply": "2021-09-21T19:42:03.478706Z" } }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmpwmm9fh88/frost-days_SRES-A2-experiment_20460101-20650101.nc.\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { @@ -1064,27 +1065,28 @@ " NCO: 4.0.9\n", " climateindex_package_id: https://github.com/Ouranosinc/xclim\n", " product: derived climate index\n", - " institute_id: CCCS" ], "text/plain": [ @@ -1181,7 +1183,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.7" } }, "nbformat": 4, diff --git a/docs/source/notebooks/subset.ipynb b/docs/source/notebooks/subset.ipynb index da65607e..531e5c5d 100644 --- a/docs/source/notebooks/subset.ipynb +++ b/docs/source/notebooks/subset.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "id": "66b3223f", "metadata": {}, "source": [ "# Spatial subsets and averages\n", @@ -14,12 +15,13 @@ { "cell_type": "code", "execution_count": 1, + "id": "8f4fd0c3", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:25.095696Z", - "iopub.status.busy": "2021-09-07T20:26:25.095264Z", - "iopub.status.idle": "2021-09-07T20:26:25.729035Z", - "shell.execute_reply": "2021-09-07T20:26:25.728590Z" + "iopub.execute_input": "2021-09-21T19:42:07.010140Z", + "iopub.status.busy": "2021-09-21T19:42:07.009291Z", + "iopub.status.idle": "2021-09-21T19:42:08.320388Z", + "shell.execute_reply": "2021-09-21T19:42:08.320881Z" } }, "outputs": [], @@ -32,12 +34,13 @@ { "cell_type": "code", "execution_count": 2, + "id": "500631a5", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:25.763691Z", - "iopub.status.busy": "2021-09-07T20:26:25.762429Z", - "iopub.status.idle": "2021-09-07T20:26:26.481489Z", - "shell.execute_reply": "2021-09-07T20:26:26.481144Z" + "iopub.execute_input": "2021-09-21T19:42:08.329315Z", + "iopub.status.busy": "2021-09-21T19:42:08.328736Z", + "iopub.status.idle": "2021-09-21T19:42:10.564246Z", + "shell.execute_reply": "2021-09-21T19:42:10.563667Z" } }, "outputs": [], @@ -50,6 +53,7 @@ }, { "cell_type": "markdown", + "id": "81f66ddd", "metadata": {}, "source": [ "For the examples in this notebook, we are using a year of daily data, minimum temperature over southern Québec." @@ -58,12 +62,13 @@ { "cell_type": "code", "execution_count": 3, + "id": "f7a203aa", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:26.483950Z", - "iopub.status.busy": "2021-09-07T20:26:26.483591Z", - "iopub.status.idle": "2021-09-07T20:26:26.485662Z", - "shell.execute_reply": "2021-09-07T20:26:26.485241Z" + "iopub.execute_input": "2021-09-21T19:42:10.568479Z", + "iopub.status.busy": "2021-09-21T19:42:10.567753Z", + "iopub.status.idle": "2021-09-21T19:42:10.570286Z", + "shell.execute_reply": "2021-09-21T19:42:10.569796Z" } }, "outputs": [], @@ -74,6 +79,7 @@ }, { "cell_type": "markdown", + "id": "1322a378", "metadata": {}, "source": [ "## Bounding box subsetting\n", @@ -86,12 +92,13 @@ { "cell_type": "code", "execution_count": 4, + "id": "eee118da", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:26.489906Z", - "iopub.status.busy": "2021-09-07T20:26:26.489193Z", - "iopub.status.idle": "2021-09-07T20:26:28.149515Z", - "shell.execute_reply": "2021-09-07T20:26:28.150031Z" + "iopub.execute_input": "2021-09-21T19:42:10.574817Z", + "iopub.status.busy": "2021-09-21T19:42:10.574267Z", + "iopub.status.idle": "2021-09-21T19:42:12.325887Z", + "shell.execute_reply": "2021-09-21T19:42:12.325310Z" } }, "outputs": [], @@ -103,36 +110,27 @@ { "cell_type": "code", "execution_count": 5, + "id": "961b3e52", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:28.155263Z", - "iopub.status.busy": "2021-09-07T20:26:28.154645Z", - "iopub.status.idle": "2021-09-07T20:26:28.527366Z", - "shell.execute_reply": "2021-09-07T20:26:28.527001Z" + "iopub.execute_input": "2021-09-21T19:42:12.330932Z", + "iopub.status.busy": "2021-09-21T19:42:12.330388Z", + "iopub.status.idle": "2021-09-21T19:42:13.058002Z", + "shell.execute_reply": "2021-09-21T19:42:13.058405Z" } }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmp2r9rzw1z/nrcan_canada_daily_tasmin_1990_sub.nc.\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/home/david/.conda/envs/finch/lib/python3.8/site-packages/xarray/plot/plot.py:1451: FutureWarning: Conversion of the second argument of issubdtype from `str` to `str` is deprecated. In future, it will be treated as `np.str_ == np.dtype(str).type`.\n", - " and not np.issubdtype(x.dtype, str)\n", - "/home/david/.conda/envs/finch/lib/python3.8/site-packages/xarray/plot/plot.py:1466: FutureWarning: Conversion of the second argument of issubdtype from `str` to `str` is deprecated. In future, it will be treated as `np.str_ == np.dtype(str).type`.\n", - " and not np.issubdtype(y.dtype, str)\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
    " ] @@ -151,6 +149,7 @@ }, { "cell_type": "markdown", + "id": "3d7d0f71", "metadata": {}, "source": [ "## Polygon subsetting\n", @@ -167,12 +166,13 @@ { "cell_type": "code", "execution_count": 6, + "id": "e2bc916c", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:28.530621Z", - "iopub.status.busy": "2021-09-07T20:26:28.530205Z", - "iopub.status.idle": "2021-09-07T20:26:29.145337Z", - "shell.execute_reply": "2021-09-07T20:26:29.144371Z" + "iopub.execute_input": "2021-09-21T19:42:13.062987Z", + "iopub.status.busy": "2021-09-21T19:42:13.062434Z", + "iopub.status.idle": "2021-09-21T19:42:13.723666Z", + "shell.execute_reply": "2021-09-21T19:42:13.724080Z" } }, "outputs": [], @@ -189,6 +189,7 @@ }, { "cell_type": "markdown", + "id": "57fa6bbb", "metadata": {}, "source": [ "#### Downloading and handling polygons locally\n", @@ -199,12 +200,13 @@ { "cell_type": "code", "execution_count": 7, + "id": "288f4067", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:29.156645Z", - "iopub.status.busy": "2021-09-07T20:26:29.155815Z", - "iopub.status.idle": "2021-09-07T20:26:32.305824Z", - "shell.execute_reply": "2021-09-07T20:26:32.305447Z" + "iopub.execute_input": "2021-09-21T19:42:13.732499Z", + "iopub.status.busy": "2021-09-21T19:42:13.731753Z", + "iopub.status.idle": "2021-09-21T19:42:16.874990Z", + "shell.execute_reply": "2021-09-21T19:42:16.875421Z" } }, "outputs": [ @@ -405,12 +407,13 @@ { "cell_type": "code", "execution_count": 8, + "id": "22746b90", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:32.312299Z", - "iopub.status.busy": "2021-09-07T20:26:32.311942Z", - "iopub.status.idle": "2021-09-07T20:26:32.332558Z", - "shell.execute_reply": "2021-09-07T20:26:32.332191Z" + "iopub.execute_input": "2021-09-21T19:42:16.884810Z", + "iopub.status.busy": "2021-09-21T19:42:16.884198Z", + "iopub.status.idle": "2021-09-21T19:42:16.916222Z", + "shell.execute_reply": "2021-09-21T19:42:16.915778Z" } }, "outputs": [ @@ -481,12 +484,13 @@ { "cell_type": "code", "execution_count": 9, + "id": "da924370", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:32.363881Z", - "iopub.status.busy": "2021-09-07T20:26:32.359823Z", - "iopub.status.idle": "2021-09-07T20:26:32.365895Z", - "shell.execute_reply": "2021-09-07T20:26:32.365531Z" + "iopub.execute_input": "2021-09-21T19:42:16.925306Z", + "iopub.status.busy": "2021-09-21T19:42:16.924736Z", + "iopub.status.idle": "2021-09-21T19:42:16.963524Z", + "shell.execute_reply": "2021-09-21T19:42:16.963965Z" } }, "outputs": [], @@ -498,6 +502,7 @@ }, { "cell_type": "markdown", + "id": "cf042c5b", "metadata": {}, "source": [ "Now that we have a (multipart) polygon, we can call the WPS subset process. When passing a local file, birdy requires the path to be absolute, our use of a `Path` object makes this easy. Before subsetting, the three polygons of our GeoJSON will be merged as one." @@ -506,12 +511,13 @@ { "cell_type": "code", "execution_count": 10, + "id": "b9f968d5", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:32.370238Z", - "iopub.status.busy": "2021-09-07T20:26:32.369869Z", - "iopub.status.idle": "2021-09-07T20:26:33.780111Z", - "shell.execute_reply": "2021-09-07T20:26:33.779694Z" + "iopub.execute_input": "2021-09-21T19:42:16.971199Z", + "iopub.status.busy": "2021-09-21T19:42:16.970643Z", + "iopub.status.idle": "2021-09-21T19:42:18.261104Z", + "shell.execute_reply": "2021-09-21T19:42:18.261579Z" } }, "outputs": [], @@ -523,36 +529,27 @@ { "cell_type": "code", "execution_count": 11, + "id": "ea7a2700", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:33.788198Z", - "iopub.status.busy": "2021-09-07T20:26:33.787784Z", - "iopub.status.idle": "2021-09-07T20:26:33.951386Z", - "shell.execute_reply": "2021-09-07T20:26:33.951089Z" + "iopub.execute_input": "2021-09-21T19:42:18.271377Z", + "iopub.status.busy": "2021-09-21T19:42:18.270802Z", + "iopub.status.idle": "2021-09-21T19:42:18.708635Z", + "shell.execute_reply": "2021-09-21T19:42:18.708119Z" } }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmpa6wlg76t/nrcan_canada_daily_tasmin_1990_sub.nc.\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/home/david/.conda/envs/finch/lib/python3.8/site-packages/xarray/plot/plot.py:1451: FutureWarning: Conversion of the second argument of issubdtype from `str` to `str` is deprecated. In future, it will be treated as `np.str_ == np.dtype(str).type`.\n", - " and not np.issubdtype(x.dtype, str)\n", - "/home/david/.conda/envs/finch/lib/python3.8/site-packages/xarray/plot/plot.py:1466: FutureWarning: Conversion of the second argument of issubdtype from `str` to `str` is deprecated. In future, it will be treated as `np.str_ == np.dtype(str).type`.\n", - " and not np.issubdtype(y.dtype, str)\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
    " ] @@ -571,6 +568,7 @@ }, { "cell_type": "markdown", + "id": "502eff39", "metadata": {}, "source": [ "## Averaging over polygons\n", @@ -586,12 +584,13 @@ { "cell_type": "code", "execution_count": 12, + "id": "2955da6e", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:33.955389Z", - "iopub.status.busy": "2021-09-07T20:26:33.954168Z", - "iopub.status.idle": "2021-09-07T20:26:35.970287Z", - "shell.execute_reply": "2021-09-07T20:26:35.969731Z" + "iopub.execute_input": "2021-09-21T19:42:18.716047Z", + "iopub.status.busy": "2021-09-21T19:42:18.712938Z", + "iopub.status.idle": "2021-09-21T19:42:20.688354Z", + "shell.execute_reply": "2021-09-21T19:42:20.687766Z" } }, "outputs": [], @@ -604,26 +603,27 @@ { "cell_type": "code", "execution_count": 13, + "id": "6fec7d59", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:35.981420Z", - "iopub.status.busy": "2021-09-07T20:26:35.980693Z", - "iopub.status.idle": "2021-09-07T20:26:36.143257Z", - "shell.execute_reply": "2021-09-07T20:26:36.142963Z" + "iopub.execute_input": "2021-09-21T19:42:20.697548Z", + "iopub.status.busy": "2021-09-21T19:42:20.690487Z", + "iopub.status.idle": "2021-09-21T19:42:21.114388Z", + "shell.execute_reply": "2021-09-21T19:42:21.114833Z" } }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmpe5c25po1/nrcan_canada_daily_tasmin_1990_avg.nc.\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
    " ] @@ -643,12 +643,13 @@ { "cell_type": "code", "execution_count": 14, + "id": "88713a7e", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:36.149322Z", - "iopub.status.busy": "2021-09-07T20:26:36.148966Z", - "iopub.status.idle": "2021-09-07T20:26:36.158850Z", - "shell.execute_reply": "2021-09-07T20:26:36.158469Z" + "iopub.execute_input": "2021-09-21T19:42:21.123606Z", + "iopub.status.busy": "2021-09-21T19:42:21.122331Z", + "iopub.status.idle": "2021-09-21T19:42:21.136283Z", + "shell.execute_reply": "2021-09-21T19:42:21.136798Z" } }, "outputs": [ @@ -1017,18 +1018,18 @@ "Data variables:\n", " tasmin (time, geom) float64 264.7 nan 265.6 260.9 ... 266.3 nan 268.2\n", "Attributes:\n", - " regrid_method: conservative
  • regrid_method :
    conservative
    • " ], "text/plain": [ "\n", @@ -1057,6 +1058,7 @@ }, { "cell_type": "markdown", + "id": "8b406a18", "metadata": {}, "source": [ "### High-resolution polygons\n", @@ -1067,12 +1069,13 @@ { "cell_type": "code", "execution_count": 15, + "id": "d4f67c8c", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:36.163216Z", - "iopub.status.busy": "2021-09-07T20:26:36.162884Z", - "iopub.status.idle": "2021-09-07T20:26:43.271004Z", - "shell.execute_reply": "2021-09-07T20:26:43.270635Z" + "iopub.execute_input": "2021-09-21T19:42:21.144055Z", + "iopub.status.busy": "2021-09-21T19:42:21.143485Z", + "iopub.status.idle": "2021-09-21T19:42:29.541949Z", + "shell.execute_reply": "2021-09-21T19:42:29.542535Z" } }, "outputs": [ @@ -1164,12 +1167,13 @@ { "cell_type": "code", "execution_count": 16, + "id": "a9dde0db", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:43.274428Z", - "iopub.status.busy": "2021-09-07T20:26:43.274080Z", - "iopub.status.idle": "2021-09-07T20:26:44.639116Z", - "shell.execute_reply": "2021-09-07T20:26:44.638767Z" + "iopub.execute_input": "2021-09-21T19:42:29.549159Z", + "iopub.status.busy": "2021-09-21T19:42:29.548419Z", + "iopub.status.idle": "2021-09-21T19:42:31.135878Z", + "shell.execute_reply": "2021-09-21T19:42:31.136323Z" } }, "outputs": [], @@ -1182,12 +1186,13 @@ { "cell_type": "code", "execution_count": 17, + "id": "08e3483f", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:44.645250Z", - "iopub.status.busy": "2021-09-07T20:26:44.644889Z", - "iopub.status.idle": "2021-09-07T20:26:49.382256Z", - "shell.execute_reply": "2021-09-07T20:26:49.381868Z" + "iopub.execute_input": "2021-09-21T19:42:31.148745Z", + "iopub.status.busy": "2021-09-21T19:42:31.148194Z", + "iopub.status.idle": "2021-09-21T19:42:38.095539Z", + "shell.execute_reply": "2021-09-21T19:42:38.096018Z" } }, "outputs": [], @@ -1203,12 +1208,13 @@ { "cell_type": "code", "execution_count": 18, + "id": "17ef4147", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:49.387203Z", - "iopub.status.busy": "2021-09-07T20:26:49.386835Z", - "iopub.status.idle": "2021-09-07T20:26:49.509081Z", - "shell.execute_reply": "2021-09-07T20:26:49.507929Z" + "iopub.execute_input": "2021-09-21T19:42:38.104112Z", + "iopub.status.busy": "2021-09-21T19:42:38.103523Z", + "iopub.status.idle": "2021-09-21T19:42:38.479639Z", + "shell.execute_reply": "2021-09-21T19:42:38.479047Z" } }, "outputs": [ @@ -1233,12 +1239,13 @@ { "cell_type": "code", "execution_count": 19, + "id": "db34519a", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:49.519853Z", - "iopub.status.busy": "2021-09-07T20:26:49.518783Z", - "iopub.status.idle": "2021-09-07T20:26:58.237679Z", - "shell.execute_reply": "2021-09-07T20:26:58.237260Z" + "iopub.execute_input": "2021-09-21T19:42:38.485922Z", + "iopub.status.busy": "2021-09-21T19:42:38.485362Z", + "iopub.status.idle": "2021-09-21T19:42:48.696926Z", + "shell.execute_reply": "2021-09-21T19:42:48.696329Z" } }, "outputs": [], @@ -1255,21 +1262,22 @@ { "cell_type": "code", "execution_count": 20, + "id": "46026a4b", "metadata": { "execution": { - "iopub.execute_input": "2021-09-07T20:26:58.245406Z", - "iopub.status.busy": "2021-09-07T20:26:58.244921Z", - "iopub.status.idle": "2021-09-07T20:26:58.294820Z", - "shell.execute_reply": "2021-09-07T20:26:58.293955Z" + "iopub.execute_input": "2021-09-21T19:42:48.707264Z", + "iopub.status.busy": "2021-09-21T19:42:48.706699Z", + "iopub.status.idle": "2021-09-21T19:42:48.869141Z", + "shell.execute_reply": "2021-09-21T19:42:48.868585Z" } }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Metalink content-type detected.\n", - "Downloading to /tmp/tmpndxd4bnr/nrcan_canada_daily_tasmin_1990_avg.nc.\n" + "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n", + "context: service \n" ] }, { @@ -1642,18 +1650,18 @@ "Data variables:\n", " tasmin (time, geom) float64 nan 262.2 nan 259.7 ... nan 255.9 nan 265.9\n", "Attributes:\n", - " regrid_method: conservative
    • tasmin
      (time, geom)
      float64
      ...
      array([[       nan, 262.163031],\n",
+       "       [       nan, 259.651348],\n",
+       "       [       nan, 266.146687],\n",
+       "       [       nan, 271.360387],\n",
+       "       [       nan, 262.576608],\n",
+       "       [       nan, 260.14709 ],\n",
+       "       [       nan, 255.935185],\n",
+       "       [       nan, 265.850208]])
  • regrid_method :
    conservative
    • " ], "text/plain": [ "\n", @@ -1703,7 +1711,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.7" } }, "nbformat": 4, diff --git a/environment.yml b/environment.yml index 41da5dd7..6ae21732 100644 --- a/environment.yml +++ b/environment.yml @@ -2,25 +2,25 @@ name: finch channels: - conda-forge dependencies: - - python>=3.7 + - python >=3.7 - pip - jinja2 - click - psutil - netcdf4 - unidecode - - dask>=2.9 + - dask >=2.9 - distributed - - xarray>=0.18.2 + - xarray >=0.18.2 - pandas - sentry-sdk - siphon # remember to match xclim version in environment-docs.yml as well - - xclim==0.27 - - clisops>=0.6.4 - - pywps==4.4.5 + - xclim ==0.27 + - clisops >=0.6.4 + - pywps ==4.4.5 - parse - pandoc # for building docs on Travis-CI, version on Pypi too old - - xesmf>=0.5.3 - - + - xesmf >=0.5.3 + - nbconvert >6.0 # see: https://github.com/jupyter/jupyter_client/issues/637 + - jupyter_client >7.0 # see: https://github.com/jupyter/jupyter_client/issues/637 diff --git a/requirements_dev.txt b/requirements_dev.txt index f12995df..0e36d482 100644 --- a/requirements_dev.txt +++ b/requirements_dev.txt @@ -12,8 +12,6 @@ bumpversion twine cruft # Changing dependencies above this comment will create merge conflicts when updating the cookiecutter template with cruft. Add extra requirements below this line. -nbval -nbconvert birdhouse-birdy geojson matplotlib