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< li class = "toctree-l2 current" > < a class = "current reference internal" href = "#" > Precip Accumulation Region of Interest< / a > < ul >
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< li class = "toctree-l4" > < a class = "reference internal" href = "#function-calculate-accumulated-precip" > 3 Function: calculate_accumulated_precip()< / a > < / li >
< li class = "toctree-l4" > < a class = "reference internal" href = "#fuction-make-map" > 4 Fuction: make_map()< / a > < / li >
< li class = "toctree-l4" > < a class = "reference internal" href = "#get-the-data" > 5 Get the Data!< / a > < / li >
< li class = "toctree-l4" > < a class = "reference internal" href = "#plot-the-data" > 6 Plot the Data!< / a > < / li >
< li class = "toctree-l4" > < a class = "reference internal" href = "#high-resolution-roi" > 7 High Resolution ROI< / a > < / li >
< li class = "toctree-l4" > < a class = "reference internal" href = "#see-also" > 8 See Also< / a > < / li >
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< section id = "precip-accumulation-region-of-interest" >
< h1 > Precip Accumulation Region of Interest< a class = "headerlink" href = "#precip-accumulation-region-of-interest" title = "Permalink to this heading" > < / a > < / h1 >
< p > < a class = "reference external" href = "http://nbviewer.ipython.org/github/Unidata/python-awips/blob/master/examples/notebooks/Precip_Accumulation_Region_of_Interest.ipynb" > Notebook< / a >
Python-AWIPS Tutorial Notebook< / p >
< hr class = "docutils" / >
< section id = "objectives" >
< h2 > Objectives< a class = "headerlink" href = "#objectives" title = "Permalink to this heading" > < / a > < / h2 >
< ul class = "simple" >
< li > < p > Access the model data from an EDEX server and limit the data returned
by using model specific parameters< / p > < / li >
< li > < p > Calculate the total precipitation over several model runs< / p > < / li >
< li > < p > Create a colorized plot for the continental US of the accumulated
precipitation data< / p > < / li >
< li > < p > Calculate and identify area of highest of precipitation< / p > < / li >
< li > < p > Use higher resolution data to draw region of interest< / p > < / li >
< / ul >
< hr class = "docutils" / >
< section id = "table-of-contents" >
< h3 > Table of Contents< a class = "headerlink" href = "#table-of-contents" title = "Permalink to this heading" > < / a > < / h3 >
< div class = "line-block" >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#imports" > 1
Imports< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#initial-setup" > 2 Initial
Setup< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#geographic-filter" > 2.1 Geographic
Filter< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#edex-connection" > 2.2 EDEX
Connnection< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#refine-the-request" > 2.3 Refine the
Request< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#get-times" > 2.4 Get
Times< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#function-calculate-accumulated-precip" > 3 Function:
calculate_accumulated_precip()< / a > < / div >
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< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.htmlt#function-make-map" > 4 Function:
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make_map()< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#get-the-data" > 5 Get the
Data!< / a > < / div >
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< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#plot-the-data" > 6 Plot the
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Data!< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#create-conus-image" > 6.1 Create CONUS
Image< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#create-region-of-interest-image" > 6.2 Create Region of Interest
Image< / a > < / div >
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< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#high-resolution-roi" > 7 High Resolution
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ROI< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#new-data-request" > 7.1 New Data
Request< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#calculate-data" > 7.2 Calculate
Data< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#plot-roi" > 7.3 Plot
ROI< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest#see-also" > 8 See
Also< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#related-notebooks" > 8.1 Related
Notebooks< / a > < / div >
< div class = "line" > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html#additional-documentation" > 8.2 Additional
Documentation< / a > < / div >
< / div >
< / section >
< section id = "imports" >
< h3 > 1 Imports< a class = "headerlink" href = "#imports" title = "Permalink to this heading" > < / a > < / h3 >
< p > The imports below are used throughout the notebook. Note the first
import is coming directly from python-awips and allows us to connect to
an EDEX server. The subsequent imports are for data manipulation and
visualization.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "kn" > from< / span > < span class = "nn" > awips.dataaccess< / span > < span class = "kn" > import< / span > < span class = "n" > DataAccessLayer< / span >
< span class = "kn" > import< / span > < span class = "nn" > cartopy.crs< / span > < span class = "k" > as< / span > < span class = "nn" > ccrs< / span >
< span class = "kn" > import< / span > < span class = "nn" > matplotlib.pyplot< / span > < span class = "k" > as< / span > < span class = "nn" > plt< / span >
< span class = "kn" > from< / span > < span class = "nn" > metpy.units< / span > < span class = "kn" > import< / span > < span class = "n" > units< / span >
< span class = "kn" > import< / span > < span class = "nn" > numpy< / span > < span class = "k" > as< / span > < span class = "nn" > np< / span >
< span class = "kn" > from< / span > < span class = "nn" > shapely.geometry< / span > < span class = "kn" > import< / span > < span class = "n" > Point< / span > < span class = "p" > ,< / span > < span class = "n" > Polygon< / span >
< / pre > < / div >
< / div >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< hr class = "docutils" / >
< section id = "initial-setup" >
< h3 > 2 Initial Setup< a class = "headerlink" href = "#initial-setup" title = "Permalink to this heading" > < / a > < / h3 >
< section id = "geographic-filter" >
< h4 > 2.1 Geographic Filter< a class = "headerlink" href = "#geographic-filter" title = "Permalink to this heading" > < / a > < / h4 >
< p > By defining a bounding box for the Continental US (CONUS), we’
optimize the data request sent to the EDEX server.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > conus< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "mi" > 125< / span > < span class = "p" > ,< / span > < span class = "o" > -< / span > < span class = "mi" > 65< / span > < span class = "p" > ,< / span > < span class = "mi" > 25< / span > < span class = "p" > ,< / span > < span class = "mi" > 55< / span > < span class = "p" > ]< / span >
< span class = "n" > conus_envelope< / span > < span class = "o" > =< / span > < span class = "n" > Polygon< / span > < span class = "p" > ([(< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ]),(< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 3< / span > < span class = "p" > ]),< / span >
< span class = "p" > (< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 3< / span > < span class = "p" > ]),(< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ]),< / span >
< span class = "p" > (< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > conus< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ])])< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "edex-connection" >
< h4 > 2.2 EDEX Connection< a class = "headerlink" href = "#edex-connection" title = "Permalink to this heading" > < / a > < / h4 >
< p > First we establish a connection to Unidata’
that connection made, we can create a < a class = "reference external" href = "http://unidata.github.io/python-awips/api/IDataRequest.html" > new data request
object< / a >
and set the data type to < strong > grid< / strong > , and use the geographic envelope we
just created.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > changeEDEXHost< / span > < span class = "p" > (< / span > < span class = "s2" > " edex-cloud.unidata.ucar.edu" < / span > < span class = "p" > )< / span >
< span class = "n" > request< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > newDataRequest< / span > < span class = "p" > (< / span > < span class = "s2" > " grid" < / span > < span class = "p" > ,< / span > < span class = "n" > envelope< / span > < span class = "o" > =< / span > < span class = "n" > conus_envelope< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "refine-the-request" >
< h4 > 2.3 Refine the Request< a class = "headerlink" href = "#refine-the-request" title = "Permalink to this heading" > < / a > < / h4 >
< p > Here we specify which model we’
< em > LocationNames< / em > , and the specific data we’
the < em > Levels< / em > and < em > Parameters< / em > .< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > request< / span > < span class = "o" > .< / span > < span class = "n" > setLocationNames< / span > < span class = "p" > (< / span > < span class = "s2" > " GFS1p0" < / span > < span class = "p" > )< / span >
< span class = "n" > request< / span > < span class = "o" > .< / span > < span class = "n" > setLevels< / span > < span class = "p" > (< / span > < span class = "s2" > " 0.0SFC" < / span > < span class = "p" > )< / span >
< span class = "n" > request< / span > < span class = "o" > .< / span > < span class = "n" > setParameters< / span > < span class = "p" > (< / span > < span class = "s2" > " TP" < / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "get-times" >
< h4 > 2.4 Get Times< a class = "headerlink" href = "#get-times" title = "Permalink to this heading" > < / a > < / h4 >
< p > We need to get the available times and cycles for our model data< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > cycles< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getAvailableTimes< / span > < span class = "p" > (< / span > < span class = "n" > request< / span > < span class = "p" > ,< / span > < span class = "kc" > True< / span > < span class = "p" > )< / span >
< span class = "n" > times< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getAvailableTimes< / span > < span class = "p" > (< / span > < span class = "n" > request< / span > < span class = "p" > )< / span >
< span class = "n" > fcstRun< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getForecastRun< / span > < span class = "p" > (< / span > < span class = "n" > cycles< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > times< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< / section >
< hr class = "docutils" / >
< section id = "function-calculate-accumulated-precip" >
< h3 > 3 Function: calculate_accumulated_precip()< a class = "headerlink" href = "#function-calculate-accumulated-precip" title = "Permalink to this heading" > < / a > < / h3 >
< p > Since we’
more than once, it makes sense to create a function that we can call
instead of duplicating the logic.< / p >
< p > This function cycles through all the grid data responses and adds up all
of the rainfall to produce a numpy array with the total ammount of
rainfall for the given data request. It also finds the maximum rainfall
point in x and y coordinates.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "k" > def< / span > < span class = "nf" > calculate_accumulated_precip< / span > < span class = "p" > (< / span > < span class = "n" > dataRequest< / span > < span class = "p" > ,< / span > < span class = "n" > forecastRun< / span > < span class = "p" > ):< / span >
< span class = "k" > for< / span > < span class = "n" > i< / span > < span class = "p" > ,< / span > < span class = "n" > tt< / span > < span class = "ow" > in< / span > < span class = "nb" > enumerate< / span > < span class = "p" > (< / span > < span class = "n" > forecastRun< / span > < span class = "p" > ):< / span >
< span class = "n" > response< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getGridData< / span > < span class = "p" > (< / span > < span class = "n" > dataRequest< / span > < span class = "p" > ,< / span > < span class = "p" > [< / span > < span class = "n" > tt< / span > < span class = "p" > ])< / span >
< span class = "n" > grid< / span > < span class = "o" > =< / span > < span class = "n" > response< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "k" > if< / span > < span class = "n" > i< / span > < span class = "o" > > < / span > < span class = "mi" > 0< / span > < span class = "p" > :< / span >
< span class = "n" > data< / span > < span class = "o" > +=< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getRawData< / span > < span class = "p" > ()< / span >
< span class = "k" > else< / span > < span class = "p" > :< / span >
< span class = "n" > data< / span > < span class = "o" > =< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getRawData< / span > < span class = "p" > ()< / span >
< span class = "n" > data< / span > < span class = "p" > [< / span > < span class = "n" > data< / span > < span class = "o" > < =< / span > < span class = "o" > -< / span > < span class = "mi" > 9999< / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (),< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > (),< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getDataTime< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > getFcstTime< / span > < span class = "p" > ()< / span > < span class = "o" > /< / span > < span class = "mi" > 3600< / span > < span class = "p" > )< / span >
< span class = "c1" > # Convert from mm to inches< / span >
2023-11-08 20:24:28 +00:00
< span class = "n" > result< / span > < span class = "o" > =< / span > < span class = "p" > (< / span > < span class = "n" > data< / span > < span class = "o" > *< / span > < span class = "n" > units< / span > < span class = "o" > .< / span > < span class = "n" > mm< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "n" > to< / span > < span class = "p" > (< / span > < span class = "n" > units< / span > < span class = "o" > .< / span > < span class = "n" > inch< / span > < span class = "p" > )< / span >
2023-10-30 23:10:38 +00:00
< span class = "n" > ii< / span > < span class = "p" > ,< / span > < span class = "n" > jj< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > where< / span > < span class = "p" > (< / span > < span class = "n" > result< / span > < span class = "o" > ==< / span > < span class = "n" > result< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > ())< / span >
< span class = "n" > i< / span > < span class = "o" > =< / span > < span class = "n" > ii< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "n" > j< / span > < span class = "o" > =< / span > < span class = "n" > jj< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "k" > return< / span > < span class = "n" > result< / span > < span class = "p" > ,< / span > < span class = "n" > i< / span > < span class = "p" > ,< / span > < span class = "n" > j< / span >
< / pre > < / div >
< / div >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< hr class = "docutils" / >
< section id = "fuction-make-map" >
< h3 > 4 Fuction: make_map()< a class = "headerlink" href = "#fuction-make-map" title = "Permalink to this heading" > < / a > < / h3 >
< p > This function creates the basics of the map we’
on. It takes in a bounding box to determine the extent and then adds
coastlines for easy frame of reference.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "k" > def< / span > < span class = "nf" > make_map< / span > < span class = "p" > (< / span > < span class = "n" > bbox< / span > < span class = "p" > ,< / span > < span class = "n" > projection< / span > < span class = "o" > =< / span > < span class = "n" > ccrs< / span > < span class = "o" > .< / span > < span class = "n" > PlateCarree< / span > < span class = "p" > ()):< / span >
< span class = "n" > fig< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > subplots< / span > < span class = "p" > (< / span > < span class = "n" > figsize< / span > < span class = "o" > =< / span > < span class = "p" > (< / span > < span class = "mi" > 20< / span > < span class = "p" > ,< / span > < span class = "mi" > 14< / span > < span class = "p" > ),< / span >
< span class = "n" > subplot_kw< / span > < span class = "o" > =< / span > < span class = "nb" > dict< / span > < span class = "p" > (< / span > < span class = "n" > projection< / span > < span class = "o" > =< / span > < span class = "n" > projection< / span > < span class = "p" > ))< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > set_extent< / span > < span class = "p" > (< / span > < span class = "n" > bbox< / span > < span class = "p" > )< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > coastlines< / span > < span class = "p" > (< / span > < span class = "n" > resolution< / span > < span class = "o" > =< / span > < span class = "s1" > ' 50m' < / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > fig< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span >
< / pre > < / div >
< / div >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< hr class = "docutils" / >
< section id = "get-the-data" >
< h3 > 5 Get the Data!< a class = "headerlink" href = "#get-the-data" title = "Permalink to this heading" > < / a > < / h3 >
< p > Access the data from the DataAccessLayer interface using the
< em > getGridData< / em > function. Use that data to calculate the accumulated
rainfall, the maximum rainfall point, and the region of interest
bounding box.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "c1" > ## get the grid response from edex< / span >
< span class = "n" > response< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getGridData< / span > < span class = "p" > (< / span > < span class = "n" > request< / span > < span class = "p" > ,< / span > < span class = "p" > [< / span > < span class = "n" > fcstRun< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ]])< / span >
< span class = "c1" > ## take the first result to get the location information from< / span >
< span class = "n" > grid< / span > < span class = "o" > =< / span > < span class = "n" > response< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "c1" > ## get the location coordinates and create a bounding box for our map< / span >
< span class = "n" > lons< / span > < span class = "p" > ,< / span > < span class = "n" > lats< / span > < span class = "o" > =< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getLatLonCoords< / span > < span class = "p" > ()< / span >
< span class = "n" > bbox< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > lons< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (),< / span > < span class = "n" > lons< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > (),< / span > < span class = "n" > lats< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (),< / span > < span class = "n" > lats< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > ()]< / span >
< span class = "n" > fcstHr< / span > < span class = "o" > =< / span > < span class = "nb" > int< / span > < span class = "p" > (< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getDataTime< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > getFcstTime< / span > < span class = "p" > ()< / span > < span class = "o" > /< / span > < span class = "mi" > 3600< / span > < span class = "p" > )< / span >
< span class = "c1" > ## calculate the total precipitation< / span >
< span class = "n" > tp_inch< / span > < span class = "p" > ,< / span > < span class = "n" > i< / span > < span class = "p" > ,< / span > < span class = "n" > j< / span > < span class = "o" > =< / span > < span class = "n" > calculate_accumulated_precip< / span > < span class = "p" > (< / span > < span class = "n" > request< / span > < span class = "p" > ,< / span > < span class = "n" > fcstRun< / span > < span class = "p" > )< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > tp_inch< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (),< / span > < span class = "n" > tp_inch< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > ())< / span >
< span class = "c1" > ## use the max points coordinates to get the max point in lat/lon coords< / span >
< span class = "n" > maxPoint< / span > < span class = "o" > =< / span > < span class = "n" > Point< / span > < span class = "p" > (< / span > < span class = "n" > lons< / span > < span class = "p" > [< / span > < span class = "n" > i< / span > < span class = "p" > ][< / span > < span class = "n" > j< / span > < span class = "p" > ],< / span > < span class = "n" > lats< / span > < span class = "p" > [< / span > < span class = "n" > i< / span > < span class = "p" > ][< / span > < span class = "n" > j< / span > < span class = "p" > ])< / span >
< span class = "n" > inc< / span > < span class = "o" > =< / span > < span class = "mf" > 3.5< / span >
< span class = "c1" > ## create a region of interest bounding box< / span >
< span class = "n" > roi_box< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > x< / span > < span class = "o" > -< / span > < span class = "n" > inc< / span > < span class = "p" > ,< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > x< / span > < span class = "o" > +< / span > < span class = "n" > inc< / span > < span class = "p" > ,< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > y< / span > < span class = "o" > -< / span > < span class = "n" > inc< / span > < span class = "p" > ,< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > y< / span > < span class = "o" > +< / span > < span class = "n" > inc< / span > < span class = "p" > ]< / span >
< span class = "n" > roi_polygon< / span > < span class = "o" > =< / span > < span class = "n" > Polygon< / span > < span class = "p" > ([(< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ]),(< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 3< / span > < span class = "p" > ]),< / span >
< span class = "p" > (< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 3< / span > < span class = "p" > ]),(< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ]),(< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > roi_box< / span > < span class = "p" > [< / span > < span class = "mi" > 2< / span > < span class = "p" > ])])< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > maxPoint< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "mf" > 0.0< / span > < span class = "mf" > 10.0625< / span > < span class = "mf" > 6.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 21.75< / span > < span class = "mf" > 12.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 35.1875< / span > < span class = "mf" > 18.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 43.5< / span > < span class = "mf" > 24.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 45.5625< / span > < span class = "mf" > 42.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 47.9375< / span > < span class = "mf" > 48.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 52.0625< / span > < span class = "mf" > 54.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 56.375< / span > < span class = "mf" > 60.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 86.625< / span > < span class = "mf" > 66.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 92.4375< / span > < span class = "mf" > 72.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 94.375< / span > < span class = "mf" > 78.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 95.375< / span > < span class = "mf" > 84.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 98.3125< / span > < span class = "mf" > 90.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 100.125< / span > < span class = "mf" > 96.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 101.6875< / span > < span class = "mf" > 102.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 104.0< / span > < span class = "mf" > 108.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 107.1875< / span > < span class = "mf" > 114.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 115.25< / span > < span class = "mf" > 120.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 129.0< / span > < span class = "mf" > 126.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 136.375< / span > < span class = "mf" > 132.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 141.125< / span > < span class = "mf" > 138.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 145.25< / span > < span class = "mf" > 144.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 147.375< / span > < span class = "mf" > 150.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 5.802169< / span >
< span class = "n" > POINT< / span > < span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mi" > 124< / span > < span class = "mi" > 42< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< hr class = "docutils" / >
< section id = "plot-the-data" >
< h3 > 6 Plot the Data!< a class = "headerlink" href = "#plot-the-data" title = "Permalink to this heading" > < / a > < / h3 >
< section id = "create-conus-image" >
< h4 > 6.1 Create CONUS Image< a class = "headerlink" href = "#create-conus-image" title = "Permalink to this heading" > < / a > < / h4 >
< p > Plot our data on our CONUS map.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > cmap< / span > < span class = "o" > =< / span > < span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > get_cmap< / span > < span class = "p" > (< / span > < span class = "s1" > ' rainbow' < / span > < span class = "p" > )< / span >
< span class = "n" > fig< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > make_map< / span > < span class = "p" > (< / span > < span class = "n" > bbox< / span > < span class = "o" > =< / span > < span class = "n" > bbox< / span > < span class = "p" > )< / span >
< span class = "n" > cs< / span > < span class = "o" > =< / span > < span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > pcolormesh< / span > < span class = "p" > (< / span > < span class = "n" > lons< / span > < span class = "p" > ,< / span > < span class = "n" > lats< / span > < span class = "p" > ,< / span > < span class = "n" > tp_inch< / span > < span class = "p" > ,< / span > < span class = "n" > cmap< / span > < span class = "o" > =< / span > < span class = "n" > cmap< / span > < span class = "p" > )< / span >
< span class = "n" > cbar< / span > < span class = "o" > =< / span > < span class = "n" > fig< / span > < span class = "o" > .< / span > < span class = "n" > colorbar< / span > < span class = "p" > (< / span > < span class = "n" > cs< / span > < span class = "p" > ,< / span > < span class = "n" > shrink< / span > < span class = "o" > =< / span > < span class = "mf" > 0.7< / span > < span class = "p" > ,< / span > < span class = "n" > orientation< / span > < span class = "o" > =< / span > < span class = "s1" > ' horizontal' < / span > < span class = "p" > )< / span >
2023-11-08 20:24:28 +00:00
< span class = "n" > cbar< / span > < span class = "o" > .< / span > < span class = "n" > set_label< / span > < span class = "p" > (< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getLocationName< / span > < span class = "p" > ()< / span > < span class = "o" > +< / span > < span class = "s2" > " Total accumulated precipitation in inches, " < / span > \
2023-10-30 23:10:38 +00:00
< span class = "o" > +< / span > < span class = "nb" > str< / span > < span class = "p" > (< / span > < span class = "n" > fcstHr< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "s2" > " -hr fcst valid " < / span > < span class = "o" > +< / span > < span class = "nb" > str< / span > < span class = "p" > (< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getDataTime< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > getRefTime< / span > < span class = "p" > ()))< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > scatter< / span > < span class = "p" > (< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > x< / span > < span class = "p" > ,< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > y< / span > < span class = "p" > ,< / span > < span class = "n" > s< / span > < span class = "o" > =< / span > < span class = "mi" > 300< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "n" > ccrs< / span > < span class = "o" > .< / span > < span class = "n" > PlateCarree< / span > < span class = "p" > (),< / span > < span class = "n" > marker< / span > < span class = "o" > =< / span > < span class = "s2" > " +" < / span > < span class = "p" > ,< / span > < span class = "n" > facecolor< / span > < span class = "o" > =< / span > < span class = "s1" > ' black' < / span > < span class = "p" > )< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > add_geometries< / span > < span class = "p" > ([< / span > < span class = "n" > roi_polygon< / span > < span class = "p" > ],< / span > < span class = "n" > ccrs< / span > < span class = "o" > .< / span > < span class = "n" > PlateCarree< / span > < span class = "p" > (),< / span > < span class = "n" > facecolor< / span > < span class = "o" > =< / span > < span class = "s1" > ' none' < / span > < span class = "p" > ,< / span > < span class = "n" > edgecolor< / span > < span class = "o" > =< / span > < span class = "s1" > ' white' < / span > < span class = "p" > ,< / span > < span class = "n" > linewidth< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "o" > < < / span > < span class = "n" > cartopy< / span > < span class = "o" > .< / span > < span class = "n" > mpl< / span > < span class = "o" > .< / span > < span class = "n" > feature_artist< / span > < span class = "o" > .< / span > < span class = "n" > FeatureArtist< / span > < span class = "n" > at< / span > < span class = "mh" > 0x13eb32340< / span > < span class = "o" > > < / span >
< / pre > < / div >
< / div >
< img alt = "../../_images/Precip_Accumulation_Region_of_Interest_27_1.png" src = "../../_images/Precip_Accumulation_Region_of_Interest_27_1.png" / >
< / section >
< section id = "create-region-of-interest-image" >
< h4 > 6.2 Create Region of Interest Image< a class = "headerlink" href = "#create-region-of-interest-image" title = "Permalink to this heading" > < / a > < / h4 >
< p > Now crop the data and zoom in on the region of interest (ROI) to create
a new plot.< / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "c1" > # cmap = plt.get_cmap(' rainbow' )< / span >
< span class = "n" > fig< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > make_map< / span > < span class = "p" > (< / span > < span class = "n" > bbox< / span > < span class = "o" > =< / span > < span class = "n" > roi_box< / span > < span class = "p" > )< / span >
< span class = "n" > cs< / span > < span class = "o" > =< / span > < span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > pcolormesh< / span > < span class = "p" > (< / span > < span class = "n" > lons< / span > < span class = "p" > ,< / span > < span class = "n" > lats< / span > < span class = "p" > ,< / span > < span class = "n" > tp_inch< / span > < span class = "p" > ,< / span > < span class = "n" > cmap< / span > < span class = "o" > =< / span > < span class = "n" > cmap< / span > < span class = "p" > )< / span >
< span class = "n" > cbar< / span > < span class = "o" > =< / span > < span class = "n" > fig< / span > < span class = "o" > .< / span > < span class = "n" > colorbar< / span > < span class = "p" > (< / span > < span class = "n" > cs< / span > < span class = "p" > ,< / span > < span class = "n" > shrink< / span > < span class = "o" > =< / span > < span class = "mf" > 0.7< / span > < span class = "p" > ,< / span > < span class = "n" > orientation< / span > < span class = "o" > =< / span > < span class = "s1" > ' horizontal' < / span > < span class = "p" > )< / span >
2023-11-08 20:24:28 +00:00
< span class = "n" > cbar< / span > < span class = "o" > .< / span > < span class = "n" > set_label< / span > < span class = "p" > (< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getLocationName< / span > < span class = "p" > ()< / span > < span class = "o" > +< / span > < span class = "s2" > " Total accumulated precipitation in inches, " < / span > \
2023-10-30 23:10:38 +00:00
< span class = "o" > +< / span > < span class = "nb" > str< / span > < span class = "p" > (< / span > < span class = "n" > fcstHr< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "s2" > " -hr fcst valid " < / span > < span class = "o" > +< / span > < span class = "nb" > str< / span > < span class = "p" > (< / span > < span class = "n" > grid< / span > < span class = "o" > .< / span > < span class = "n" > getDataTime< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > getRefTime< / span > < span class = "p" > ()))< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > scatter< / span > < span class = "p" > (< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > x< / span > < span class = "p" > ,< / span > < span class = "n" > maxPoint< / span > < span class = "o" > .< / span > < span class = "n" > y< / span > < span class = "p" > ,< / span > < span class = "n" > s< / span > < span class = "o" > =< / span > < span class = "mi" > 300< / span > < span class = "p" > ,< / span >
< span class = "n" > transform< / span > < span class = "o" > =< / span > < span class = "n" > ccrs< / span > < span class = "o" > .< / span > < span class = "n" > PlateCarree< / span > < span class = "p" > (),< / span > < span class = "n" > marker< / span > < span class = "o" > =< / span > < span class = "s2" > " +" < / span > < span class = "p" > ,< / span > < span class = "n" > facecolor< / span > < span class = "o" > =< / span > < span class = "s1" > ' black' < / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "o" > < < / span > < span class = "n" > matplotlib< / span > < span class = "o" > .< / span > < span class = "n" > collections< / span > < span class = "o" > .< / span > < span class = "n" > PathCollection< / span > < span class = "n" > at< / span > < span class = "mh" > 0x13ed521c0< / span > < span class = "o" > > < / span >
< / pre > < / div >
< / div >
< img alt = "../../_images/Precip_Accumulation_Region_of_Interest_29_1.png" src = "../../_images/Precip_Accumulation_Region_of_Interest_29_1.png" / >
< p > < a class = "reference external" href = "https://unidata.github.io/python-awips/examples/generated/Precip_Accumulation_Region_of_Interest.html" > Top< / a > < / p >
< / section >
< / section >
< hr class = "docutils" / >
< section id = "high-resolution-roi" >
< h3 > 7 High Resolution ROI< a class = "headerlink" href = "#high-resolution-roi" title = "Permalink to this heading" > < / a > < / h3 >
< section id = "new-data-request" >
< h4 > 7.1 New Data Request< a class = "headerlink" href = "#new-data-request" title = "Permalink to this heading" > < / a > < / h4 >
< p > To see the region of interest more clearly, we can redo the process with
a higher resolution model (GFS20 vs. < / p >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > roiRequest< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > newDataRequest< / span > < span class = "p" > (< / span > < span class = "s2" > " grid" < / span > < span class = "p" > ,< / span > < span class = "n" > envelope< / span > < span class = "o" > =< / span > < span class = "n" > conus_envelope< / span > < span class = "p" > )< / span >
< span class = "n" > roiRequest< / span > < span class = "o" > .< / span > < span class = "n" > setLocationNames< / span > < span class = "p" > (< / span > < span class = "s2" > " GFS20" < / span > < span class = "p" > )< / span >
< span class = "n" > roiRequest< / span > < span class = "o" > .< / span > < span class = "n" > setLevels< / span > < span class = "p" > (< / span > < span class = "s2" > " 0.0SFC" < / span > < span class = "p" > )< / span >
< span class = "n" > roiRequest< / span > < span class = "o" > .< / span > < span class = "n" > setParameters< / span > < span class = "p" > (< / span > < span class = "s2" > " TP" < / span > < span class = "p" > )< / span >
< span class = "n" > roiCycles< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getAvailableTimes< / span > < span class = "p" > (< / span > < span class = "n" > roiRequest< / span > < span class = "p" > ,< / span > < span class = "kc" > True< / span > < span class = "p" > )< / span >
< span class = "n" > roiTimes< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getAvailableTimes< / span > < span class = "p" > (< / span > < span class = "n" > roiRequest< / span > < span class = "p" > )< / span >
< span class = "n" > roiFcstRun< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getForecastRun< / span > < span class = "p" > (< / span > < span class = "n" > roiCycles< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > roiTimes< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "calculate-data" >
< h4 > 7.2 Calculate Data< a class = "headerlink" href = "#calculate-data" title = "Permalink to this heading" > < / a > < / h4 >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > roiResponse< / span > < span class = "o" > =< / span > < span class = "n" > DataAccessLayer< / span > < span class = "o" > .< / span > < span class = "n" > getGridData< / span > < span class = "p" > (< / span > < span class = "n" > roiRequest< / span > < span class = "p" > ,< / span > < span class = "p" > [< / span > < span class = "n" > roiFcstRun< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ]])< / span >
< span class = "nb" > print< / span > < span class = "p" > (< / span > < span class = "n" > roiResponse< / span > < span class = "p" > )< / span >
< span class = "n" > roiGrid< / span > < span class = "o" > =< / span > < span class = "n" > roiResponse< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "n" > roiLons< / span > < span class = "p" > ,< / span > < span class = "n" > roiLats< / span > < span class = "o" > =< / span > < span class = "n" > roiGrid< / span > < span class = "o" > .< / span > < span class = "n" > getLatLonCoords< / span > < span class = "p" > ()< / span >
< span class = "n" > roi_data< / span > < span class = "p" > ,< / span > < span class = "n" > i< / span > < span class = "p" > ,< / span > < span class = "n" > j< / span > < span class = "o" > =< / span > < span class = "n" > calculate_accumulated_precip< / span > < span class = "p" > (< / span > < span class = "n" > roiRequest< / span > < span class = "p" > ,< / span > < span class = "n" > roiFcstRun< / span > < span class = "p" > )< / span >
< span class = "n" > roiFcstHr< / span > < span class = "o" > =< / span > < span class = "nb" > int< / span > < span class = "p" > (< / span > < span class = "n" > roiGrid< / span > < span class = "o" > .< / span > < span class = "n" > getDataTime< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > getFcstTime< / span > < span class = "p" > ()< / span > < span class = "o" > /< / span > < span class = "mi" > 3600< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< div class = "highlight-default notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "p" > [< / span > < span class = "o" > < < / span > < span class = "n" > awips< / span > < span class = "o" > .< / span > < span class = "n" > dataaccess< / span > < span class = "o" > .< / span > < span class = "n" > PyGridData< / span > < span class = "o" > .< / span > < span class = "n" > PyGridData< / span > < span class = "nb" > object< / span > < span class = "n" > at< / span > < span class = "mh" > 0x13ecb4eb0< / span > < span class = "o" > > < / span > < span class = "p" > ]< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 22.5625< / span > < span class = "mf" > 3.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 35.375< / span > < span class = "mf" > 6.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 38.375< / span > < span class = "mf" > 9.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 38.375< / span > < span class = "mf" > 12.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 41.375< / span > < span class = "mf" > 15.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 48.625< / span > < span class = "mf" > 18.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 73.0625< / span > < span class = "mf" > 30.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 94.9375< / span > < span class = "mf" > 33.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 96.125< / span > < span class = "mf" > 36.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 97.0< / span > < span class = "mf" > 39.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 99.375< / span > < span class = "mf" > 45.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 100.0625< / span > < span class = "mf" > 48.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 100.25< / span > < span class = "mf" > 51.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 100.4375< / span > < span class = "mf" > 57.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 100.4375< / span > < span class = "mf" > 63.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 118.25< / span > < span class = "mf" > 66.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 127.625< / span > < span class = "mf" > 69.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 131.125< / span > < span class = "mf" > 75.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 131.375< / span > < span class = "mf" > 78.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 131.5< / span > < span class = "mf" > 81.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 131.875< / span > < span class = "mf" > 84.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 132.875< / span > < span class = "mf" > 90.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 133.375< / span > < span class = "mf" > 96.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 139.1875< / span > < span class = "mf" > 102.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 141.625< / span > < span class = "mf" > 120.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 141.75< / span > < span class = "mf" > 126.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 142.1875< / span > < span class = "mf" > 132.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 143.375< / span > < span class = "mf" > 138.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 148.6875< / span > < span class = "mf" > 144.0< / span >
< span class = "mf" > 0.0< / span > < span class = "mf" > 156.25< / span > < span class = "mf" > 150.0< / span >
< / pre > < / div >
< / div >
< / section >
< section id = "plot-roi" >
< h4 > 7.3 Plot ROI< a class = "headerlink" href = "#plot-roi" title = "Permalink to this heading" > < / a > < / h4 >
< div class = "highlight-ipython3 notranslate" > < div class = "highlight" > < pre > < span > < / span > < span class = "c1" > # cmap = plt.get_cmap(' rainbow' )< / span >
< span class = "n" > fig< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > make_map< / span > < span class = "p" > (< / span > < span class = "n" > bbox< / span > < span class = "o" > =< / span > < span class = "n" > roi_box< / span > < span class = "p" > )< / span >
< span class = "n" > cs< / span > < span class = "o" > =< / span > < span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > pcolormesh< / span > < span class = "p" > (< / span > < span class = "n" > roiLons< / span > < span class = "p" > ,< / span > < span class = "n" > roiLats< / span > < span class = "p" > ,< / span > < span class = "n" > roi_data< / span > < span class = "p" > ,< / span > < span class = "n" > cmap< / span > < span class = "o" > =< / span > < span class = "n" > cmap< / span > < span class = "p" > )< / span >
< span class = "n" > cbar< / span > < span class = "o" > =< / span > < span class = "n" > fig< / span > < span class = "o" > .< / span > < span class = "n" > colorbar< / span > < span class = "p" > (< / span > < span class = "n" > cs< / span > < span class = "p" > ,< / span > < span class = "n" > shrink< / span > < span class = "o" > =< / span > < span class = "mf" > 0.7< / span > < span class = "p" > ,< / span > < span class = "n" > orientation< / span > < span class = "o" > =< / span > < span class = "s1" > ' horizontal' < / span > < span class = "p" > )< / span >
2023-11-08 20:24:28 +00:00
< span class = "n" > cbar< / span > < span class = "o" > .< / span > < span class = "n" > set_label< / span > < span class = "p" > (< / span > < span class = "n" > roiGrid< / span > < span class = "o" > .< / span > < span class = "n" > getLocationName< / span > < span class = "p" > ()< / span > < span class = "o" > +< / span > < span class = "s2" > " Total accumulated precipitation in inches, " < / span > \
2023-10-30 23:10:38 +00:00
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