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kuchaale/geoapps_vs_xcontour.ipynb

Created April 13, 2022 14:27
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Notebook documenting differences between GeoApps and xcontour calculation of effective diffusivity
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geoapps_vs_xcontour.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "2fe3e8d1-263f-47f6-8571-195ae5ee0006",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:16:28.963889Z",
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<xarray.Dataset>\n",
"Dimensions: (latitude: 241, level: 15, longitude: 480)\n",
"Coordinates:\n",
" * longitude (longitude) float32 0.0 0.75 1.5 2.25 ... 357.0 357.8 358.5 359.2\n",
" * latitude (latitude) float32 -90.0 -89.25 -88.5 -87.75 ... 88.5 89.25 90.0\n",
" * level (level) int32 265 275 285 300 315 330 ... 430 475 530 600 700 850\n",
" time datetime64[ns] ...\n",
"Data variables:\n",
" pv (level, latitude, longitude) float32 ...\n",
" grdSpv (level, latitude, longitude) float32 ...\n",
"Attributes:\n",
" units: K m**2 kg**-1 s**-1\n",
" long_name: Potential vorticity\n"
]
}
],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"import sys\n",
"#sys.path.append('../../')\n",
"from xcontour import Contour2D, latitude_lengths_at, add_latlon_metrics\n",
"\n",
"dset = xr.open_dataset('PV.nc')\n",
"\n",
"print(dset)\n",
"\n",
"# add metrics for xgcm.Grid\n",
"dset, grid = add_latlon_metrics(dset)\n",
"\n",
"# get PV as a tracer and its squared gradient\n",
"tracer = dset.pv\n",
"grdS = dset.grdSpv"
]
},
{
"cell_type": "markdown",
"id": "ddcdced2-4c1d-4db8-80f9-67a3a1b4653d",
"metadata": {},
"source": [
"# xcontour"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "23123bdc-0fbc-4588-a25f-a78fe46e5766",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:16:34.775077Z",
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<xarray.DataArray 'pv' (level: 15, contour: 121)>\n",
"array([[-4.34436952e-05, -4.15529321e-05, -3.96621690e-05, ...,\n",
" 1.79666269e-04, 1.81557029e-04, 1.83447788e-04],\n",
" [-3.12895281e-05, -2.95687532e-05, -2.78479802e-05, ...,\n",
" 1.71761829e-04, 1.73482593e-04, 1.75203371e-04],\n",
" [-1.68830156e-05, -1.58910643e-05, -1.48991139e-05, ...,\n",
" 1.00167170e-04, 1.01159116e-04, 1.02151069e-04],\n",
" ...,\n",
" [-8.51756777e-05, -8.26942050e-05, -8.02127397e-05, ...,\n",
" 2.07637800e-04, 2.10119280e-04, 2.12600746e-04],\n",
" [-1.42589153e-04, -1.37360956e-04, -1.32132773e-04, ...,\n",
" 4.74337576e-04, 4.79565788e-04, 4.84793971e-04],\n",
" [-3.23796354e-04, -3.09809897e-04, -2.95823411e-04, ...,\n",
" 1.32660719e-03, 1.34059368e-03, 1.35458005e-03]], dtype=float32)\n",
"Coordinates:\n",
" * level (level) int32 265 275 285 300 315 330 ... 430 475 530 600 700 850\n",
" time datetime64[ns] 2010-01-01\n",
" * contour (contour) float32 0.0 1.0 2.0 3.0 4.0 ... 117.0 118.0 119.0 120.0\n"
]
}
],
"source": [
"N = 121 # increase the contour number may get non-monotonic A(q) relation\n",
"increase = True # Y-index increases with latitude (sometimes not)\n",
"lt = True # northward of PV contours (larger than) is inside the contour\n",
" # change this should not change the result of Keff, but may alter\n",
" # the values at boundaries\n",
"dtype = np.float32 # use float32 to save memory\n",
"undef = -9.99e8 # for maskout topography if present\n",
"\n",
"# initialize a Contour2D analysis class using grid and tracer\n",
"analysis = Contour2D(grid, tracer,\n",
" dims={'X':'longitude','Y':'latitude'},\n",
" dimEq={'Y':'latitude'},\n",
" increase=increase,\n",
" lt=lt)\n",
"# evenly-spaced contours\n",
"ctr = analysis.cal_contours(N)\n",
"\n",
"# Mask for A(q) relation table.\n",
"# This can be done analytically in simple case, but we choose to do it\n",
"# numerically in case there are undefined values (topography) inside the domain.\n",
"mask = xr.where(tracer!=undef, 1, 0).astype(dtype)\n",
"\n",
"print(ctr)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "dc5881c2-5df7-48a7-8f48-8cd4cc27d206",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:16:45.153438Z",
"iopub.status.busy": "2022-04-13T14:16:45.152895Z",
"iopub.status.idle": "2022-04-13T14:17:41.704581Z",
"shell.execute_reply": "2022-04-13T14:17:41.703208Z",
"shell.execute_reply.started": "2022-04-13T14:16:45.153376Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"case 1: increase & lt\n"
]
}
],
"source": [
"# calculate related quantities for Keff\n",
"# First set of APIs\n",
"# xarray's conditional integration, memory consuming and not preferred, for test only\n",
"table = analysis.cal_area_eqCoord_table(mask) # A(Yeq) table\n",
"area = analysis.cal_integral_within_contours(ctr).rename('intArea')\n",
"intgrdS = analysis.cal_integral_within_contours(ctr, integrand=grdS).rename('intgrdS')\n",
"\n",
"# Second set of APIs\n",
"# xhistogram's box-counting, memory-friendly and preferred, but not here as contour bins vary with level\n",
"#table = analysis.cal_area_eqCoord_table_hist(mask) # A(Yeq) table\n",
"#area = analysis.cal_integral_within_contours_hist(ctr).rename('intArea')\n",
"#intgrdS = analysis.cal_integral_within_contours_hist(ctr, integrand=grdS).rename('intgrdS')\n",
"\n",
"latEq = table.lookup_coordinates(area).rename('latEq')\n",
"Lmin = latitude_lengths_at(latEq).rename('Lmin')\n",
"dintSdA = analysis.cal_gradient_wrt_area(intgrdS, area).rename('dintSdA')\n",
"dqdA = analysis.cal_gradient_wrt_area(ctr, area).rename('dqdA')\n",
"Leq2 = analysis.cal_sqared_equivalent_length(dintSdA, dqdA).rename('Leq2')\n",
"nkeff = analysis.cal_normalized_Keff(Leq2, Lmin).rename('nkeff')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "953bb939-769d-4086-9cd4-f11a5095052d",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:21:51.301506Z",
"iopub.status.busy": "2022-04-13T14:21:51.300980Z",
"iopub.status.idle": "2022-04-13T14:21:51.307511Z",
"shell.execute_reply": "2022-04-13T14:21:51.306638Z",
"shell.execute_reply.started": "2022-04-13T14:21:51.301467Z"
},
"tags": []
},
"outputs": [],
"source": [
"temp = nkeff.copy()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "036e71bc-f2f6-4051-8471-0438ed93748f",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:17:41.706398Z",
"iopub.status.busy": "2022-04-13T14:17:41.706196Z",
"iopub.status.idle": "2022-04-13T14:17:42.205669Z",
"shell.execute_reply": "2022-04-13T14:17:42.204825Z",
"shell.execute_reply.started": "2022-04-13T14:17:41.706371Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.contour.QuadContourSet at 0x7fb696281cd0>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"np.log(nkeff[8:]).plot.contourf(figsize=(12, 6), cmap='jet', levels=np.linspace(0, 4.6, 24))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "90b7792c-ad6c-48e5-90d9-ca84fdebff35",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:18:10.878221Z",
"iopub.status.busy": "2022-04-13T14:18:10.877575Z",
"iopub.status.idle": "2022-04-13T14:18:10.892840Z",
"shell.execute_reply": "2022-04-13T14:18:10.891009Z",
"shell.execute_reply.started": "2022-04-13T14:18:10.878141Z"
},
"tags": []
},
"outputs": [],
"source": [
"from GeoApps.ContourMethods import ContourAnalysisInLatLon\n",
"from GeoApps.DiagnosticMethods import Dynamics\n",
"from GeoApps.GridUtils import add_latlon_metrics"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "742165cb-25a9-44cc-8922-591b09b49293",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:18:41.740893Z",
"iopub.status.busy": "2022-04-13T14:18:41.740187Z",
"iopub.status.idle": "2022-04-13T14:18:41.843152Z",
"shell.execute_reply": "2022-04-13T14:18:41.842188Z",
"shell.execute_reply.started": "2022-04-13T14:18:41.740824Z"
},
"tags": []
},
"outputs": [],
"source": [
"dset, grid = add_latlon_metrics(dset)\n",
"tracer = dset.pv\n",
"grdS = Dynamics(dset, grid).cal_squared_gradient(tracer)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a3a64632-d2a7-45d1-977d-e31d50ab83cb",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:21:54.555364Z",
"iopub.status.busy": "2022-04-13T14:21:54.555041Z",
"iopub.status.idle": "2022-04-13T14:21:54.585483Z",
"shell.execute_reply": "2022-04-13T14:21:54.584698Z",
"shell.execute_reply.started": "2022-04-13T14:21:54.555330Z"
},
"tags": []
},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pv&#x27; (level: 15, contour: 121)&gt;\n",
"array([[-4.34436952e-05, -4.15529328e-05, -3.96621704e-05, ...,\n",
" 1.79666269e-04, 1.81557031e-04, 1.83447793e-04],\n",
" [-3.12895281e-05, -2.95687539e-05, -2.78479797e-05, ...,\n",
" 1.71761828e-04, 1.73482603e-04, 1.75203377e-04],\n",
" [-1.68830156e-05, -1.58910649e-05, -1.48991141e-05, ...,\n",
" 1.00167172e-04, 1.01159123e-04, 1.02151073e-04],\n",
" ...,\n",
" [-8.51756777e-05, -8.26942073e-05, -8.02127370e-05, ...,\n",
" 2.07637823e-04, 2.10119294e-04, 2.12600764e-04],\n",
" [-1.42589153e-04, -1.37360960e-04, -1.32132767e-04, ...,\n",
" 4.74337621e-04, 4.79565814e-04, 4.84794007e-04],\n",
" [-3.23796354e-04, -3.09809882e-04, -2.95823411e-04, ...,\n",
" 1.32660728e-03, 1.34059375e-03, 1.35458022e-03]])\n",
"Coordinates:\n",
" * level (level) int32 265 275 285 300 315 330 ... 430 475 530 600 700 850\n",
" time datetime64[ns] 2010-01-01\n",
" * contour (contour) float64 0.0 1.0 2.0 3.0 4.0 ... 117.0 118.0 119.0 120.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pv'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>level</span>: 15</li><li><span class='xr-has-index'>contour</span>: 121</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-48118a9e-a450-46d5-a872-8b458b0f545d' class='xr-array-in' type='checkbox' checked><label for='section-48118a9e-a450-46d5-a872-8b458b0f545d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-4.344e-05 -4.155e-05 -3.966e-05 ... 0.001327 0.001341 0.001355</span></div><div class='xr-array-data'><pre>array([[-4.34436952e-05, -4.15529328e-05, -3.96621704e-05, ...,\n",
" 1.79666269e-04, 1.81557031e-04, 1.83447793e-04],\n",
" [-3.12895281e-05, -2.95687539e-05, -2.78479797e-05, ...,\n",
" 1.71761828e-04, 1.73482603e-04, 1.75203377e-04],\n",
" [-1.68830156e-05, -1.58910649e-05, -1.48991141e-05, ...,\n",
" 1.00167172e-04, 1.01159123e-04, 1.02151073e-04],\n",
" ...,\n",
" [-8.51756777e-05, -8.26942073e-05, -8.02127370e-05, ...,\n",
" 2.07637823e-04, 2.10119294e-04, 2.12600764e-04],\n",
" [-1.42589153e-04, -1.37360960e-04, -1.32132767e-04, ...,\n",
" 4.74337621e-04, 4.79565814e-04, 4.84794007e-04],\n",
" [-3.23796354e-04, -3.09809882e-04, -2.95823411e-04, ...,\n",
" 1.32660728e-03, 1.34059375e-03, 1.35458022e-03]])</pre></div></div></li><li class='xr-section-item'><input id='section-8c2a69b4-cfd4-4aa0-b6b9-c2298d921d0d' class='xr-section-summary-in' type='checkbox' checked><label for='section-8c2a69b4-cfd4-4aa0-b6b9-c2298d921d0d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>265 275 285 300 ... 530 600 700 850</div><input id='attrs-fa9912af-2e01-4744-a153-6fee4a1efe22' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fa9912af-2e01-4744-a153-6fee4a1efe22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a527874-7d94-4b82-8155-f8a08ad292e9' class='xr-var-data-in' type='checkbox'><label for='data-1a527874-7d94-4b82-8155-f8a08ad292e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([265, 275, 285, 300, 315, 330, 350, 370, 395, 430, 475, 530, 600, 700,\n",
" 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-01-01</div><input id='attrs-e4c29ed8-3a7c-4758-81ba-cfceb10f514f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4c29ed8-3a7c-4758-81ba-cfceb10f514f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e3c7c81-4cf9-4739-bd8d-f58eb57c3b22' class='xr-var-data-in' type='checkbox'><label for='data-6e3c7c81-4cf9-4739-bd8d-f58eb57c3b22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;2010-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>contour</span></div><div class='xr-var-dims'>(contour)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 ... 118.0 119.0 120.0</div><input id='attrs-44a8feb3-4cc7-41c4-b311-458fcc54f810' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44a8feb3-4cc7-41c4-b311-458fcc54f810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a35338c-4351-4d8d-bc06-ad042fec2741' class='xr-var-data-in' type='checkbox'><label for='data-2a35338c-4351-4d8d-bc06-ad042fec2741' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11.,\n",
" 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23.,\n",
" 24., 25., 26., 27., 28., 29., 30., 31., 32., 33., 34., 35.,\n",
" 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
" 48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59.,\n",
" 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70., 71.,\n",
" 72., 73., 74., 75., 76., 77., 78., 79., 80., 81., 82., 83.,\n",
" 84., 85., 86., 87., 88., 89., 90., 91., 92., 93., 94., 95.,\n",
" 96., 97., 98., 99., 100., 101., 102., 103., 104., 105., 106., 107.,\n",
" 108., 109., 110., 111., 112., 113., 114., 115., 116., 117., 118., 119.,\n",
" 120.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-12e83cd1-7462-4dfd-a243-21da27176e65' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-12e83cd1-7462-4dfd-a243-21da27176e65' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'pv' (level: 15, contour: 121)>\n",
"array([[-4.34436952e-05, -4.15529328e-05, -3.96621704e-05, ...,\n",
" 1.79666269e-04, 1.81557031e-04, 1.83447793e-04],\n",
" [-3.12895281e-05, -2.95687539e-05, -2.78479797e-05, ...,\n",
" 1.71761828e-04, 1.73482603e-04, 1.75203377e-04],\n",
" [-1.68830156e-05, -1.58910649e-05, -1.48991141e-05, ...,\n",
" 1.00167172e-04, 1.01159123e-04, 1.02151073e-04],\n",
" ...,\n",
" [-8.51756777e-05, -8.26942073e-05, -8.02127370e-05, ...,\n",
" 2.07637823e-04, 2.10119294e-04, 2.12600764e-04],\n",
" [-1.42589153e-04, -1.37360960e-04, -1.32132767e-04, ...,\n",
" 4.74337621e-04, 4.79565814e-04, 4.84794007e-04],\n",
" [-3.23796354e-04, -3.09809882e-04, -2.95823411e-04, ...,\n",
" 1.32660728e-03, 1.34059375e-03, 1.35458022e-03]])\n",
"Coordinates:\n",
" * level (level) int32 265 275 285 300 315 330 ... 430 475 530 600 700 850\n",
" time datetime64[ns] 2010-01-01\n",
" * contour (contour) float64 0.0 1.0 2.0 3.0 4.0 ... 117.0 118.0 119.0 120.0"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Construct an analysis class using PV as the tracer\n",
"analysis = ContourAnalysisInLatLon(dset, tracer, grid)\n",
"\n",
"\n",
"# This should be called first to initialize contours from minimum value\n",
"# to maximum value (within lat/lon dims) using `N` contours.\n",
"N = 121\n",
"ctr = analysis.cal_contours(N, dims=['latitude', 'longitude'])#.metpy.dequantify()\n",
"ctr"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "68beb8b5-239d-404a-b8ac-b752f7439a54",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:22:11.365108Z",
"iopub.status.busy": "2022-04-13T14:22:11.364546Z",
"iopub.status.idle": "2022-04-13T14:22:15.497521Z",
"shell.execute_reply": "2022-04-13T14:22:15.496038Z",
"shell.execute_reply.started": "2022-04-13T14:22:11.365043Z"
},
"tags": []
},
"outputs": [],
"source": [
"# Calculate various diagnostics defined in contour-based coordinates\n",
"area = analysis.cal_integral_within_contours(ctr, out_name='intArea')\n",
"intgrdS = analysis.cal_integral_within_contours(ctr, grdS, out_name='intgrdS')\n",
"latEq = analysis.cal_equivalent_coords(area)\n",
"dgrdSdA = analysis.cal_gradient_wrt_area(intgrdS, area)\n",
"dqdA = analysis.cal_gradient_wrt_area(ctr, area)\n",
"Leq2 = analysis.cal_sqared_equivalent_length(dgrdSdA, dqdA)\n",
"Lmin = analysis.cal_minimum_possible_length(latEq)\n",
"nkeff = analysis.cal_normalized_Keff(Leq2, Lmin)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "ffc27dbc-fcba-42a3-8b5a-7d575ee12a35",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:22:23.968942Z",
"iopub.status.busy": "2022-04-13T14:22:23.968335Z",
"iopub.status.idle": "2022-04-13T14:22:24.256666Z",
"shell.execute_reply": "2022-04-13T14:22:24.255816Z",
"shell.execute_reply.started": "2022-04-13T14:22:23.968854Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.contour.QuadContourSet at 0x7fb6945bb880>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"np.log(nkeff[8:]).plot.contourf(figsize=(12, 6), cmap='jet', levels=np.linspace(0, 4.6, 24))"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "627cf9bf-402e-4c93-b682-00ff3207e277",
"metadata": {
"execution": {
"iopub.execute_input": "2022-04-13T14:26:02.303655Z",
"iopub.status.busy": "2022-04-13T14:26:02.302987Z",
"iopub.status.idle": "2022-04-13T14:26:02.575922Z",
"shell.execute_reply": "2022-04-13T14:26:02.575114Z",
"shell.execute_reply.started": "2022-04-13T14:26:02.303589Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.contour.QuadContourSet at 0x7fb693f377f0>"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"(nkeff[8:]-temp[8:]).plot.contourf(\n",
" figsize=(12, 6), \n",
" cmap='RdBu_r', \n",
" robust = True,\n",
" levels = 21\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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