Branched from: https://community.esri.com/thread/199323-re-trend-analysis-through-time-series-of-raster-data Hi Xander Bakker, Some modification I want to do in correlation script. I Would like to calculate the P value as a raster in addition to correlation raster. Using scipy library, I just ran one script to obtain the correlation and P value. Script is attached below import numpy as np from scipy . stats import pearsonr x = np . array ( [ 58295.62187335 , 45420.95483714 , 3398.64920064 , 977.22166306 , 5515.32801851 , 14184.57621022 , 16027.2803392 , 15313.01865824 , 6443.2448182 ] ) y = np . array ( [ 143547.79123381 , 22996.69597427 , 2591.56411049 , 661.93115277 , 8826.96549102 , 17735.13549851 , 11629.13003263 , 14438.33177173 , 6997.89334741 ] ) r , p = pearsonr ( x , y ) print "r" , r print "p" , p Output Returns:r : 0.831087956392 Pearson’s correlation coefficient p-value : 0.00550539621039 2-tailed p-value So instead of Numpy, can we use here Numpy and Scipy both library to get the addition p value or in the existing script can we add this function to obtain the p Value as a raster Thanks & regards Shouvik Jha

Hi shouvik jha , I branched this question to give it more visibility and to avoid letting the post grow too much and contain multiple questions. Basically, what I would do is define a second numpy that will hold the pearson value. This is what it would look like: * line 11 defined the pearson output raster path and name * line 35 creates the pearson numpy array * line 57 and 58 will call the pearson function and store the result in the numpy array * line 76 to 80 will store the output pearson raster * line 103 to 112 contains the function that calculated the pearson value def main ( ) : print "load modules..." import arcpy arcpy . env . overwriteOutput = True import numpy as np template1 = r 'C:\GeoNet\Correlation\Parameter1\r{0}_NPP.TIF' template2 = r 'C:\GeoNet\Correlation\Parameter2\r{0}_WUE.TIF' nodata = - 3.4028235e+38 out_ras_corr = r 'C:\GeoNet\Correlation\Pearson\correlation.TIF' out_ras_pear = r 'C:\GeoNet\Correlation\Pearson\pearson.TIF' print "create nested numpy array list..." lst_np_ras = [ ] for i in range ( 1 , 14 ) : ras_path1 = template1 . format ( "%03d" % ( i , ) ) print " - " , ras_path1 ras_np1 = arcpy . RasterToNumPyArray ( ras_path1 ) ras_path2 = template2 . format ( "%03d" % ( i , ) ) print " - " , ras_path2 ras_np2 = arcpy . RasterToNumPyArray ( ras_path2 ) lst_np_ras . append ( [ ras_np1 , ras_np2 ] ) print "read props numpy raster..." ras_np = lst_np_ras [ 0 ] [ 0 ] # take first numpy array from list rows = ras_np . shape [ 0 ] cols = ras_np . shape [ 1 ] print " - rows:" , rows print " - cols:" , cols print "create output numpy array..." ras_path = template1 . format ( "%03d" % ( 1 , ) ) raster = arcpy . Raster ( ras_path ) ras_np_res_corr = np . ndarray ( ( rows , cols ) ) ras_np_res_pear = np . ndarray ( ( rows , cols ) ) print " - out rows:" , ras_np_res_corr . shape [ 0 ] print " - out cols:" , ras_np_res_corr . shape [ 1 ] print "loop through pixels..." pix_cnt = 0 for row in range ( rows ) : for col in range ( cols ) : pix_cnt += 1 if pix_cnt % 5000 == 0 : print " - row:" , row , " col:" , col , " pixel:" , pix_cnt lst_vals1 = [ ] lst_vals2 = [ ] try : for lst_pars in lst_np_ras : lst_vals1 . append ( lst_pars [ 0 ] [ row , col ] ) lst_vals2 . append ( lst_pars [ 1 ] [ row , col ] ) lst_vals1 = ReplaceNoData ( lst_vals1 , nodata ) lst_vals2 = ReplaceNoData ( lst_vals2 , nodata ) # perform calculation on list correlation = CalculateCorrelation ( lst_vals1 , lst_vals2 , nodata ) ras_np_res_corr [ row , col ] = correlation pearson = CalculatePearsons ( lst_vals1 , lst_vals2 , nodata ) ras_np_res_pear [ row , col ] = pearson except Exception as e : print "ERR:" , e print " - row:" , row , " col:" , col , " pixel:" , pix_cnt print " - lst_vals1:" , lst_vals1 print " - lst_vals2:" , lst_vals2 pnt = arcpy . Point ( raster . extent . XMin , raster . extent . YMin ) # - raster.meanCellHeight xcellsize = raster . meanCellWidth ycellsize = raster . meanCellHeight print "Write output rasters..." print " - " , out_ras_corr ras_res_corr = arcpy . NumPyArrayToRaster ( ras_np_res_corr , lower_left_corner = pnt , x_cell_size = xcellsize , y_cell_size = ycellsize , value_to_nodata = nodata ) ras_res_corr . save ( out_ras_corr ) arcpy . DefineProjection_management ( in_dataset = out_ras_corr , coor_system = "GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]" ) print " - " , out_ras_pear ras_res_pear = arcpy . NumPyArrayToRaster ( ras_np_res_pear , lower_left_corner = pnt , x_cell_size = xcellsize , y_cell_size = ycellsize , value_to_nodata = nodata ) ras_res_pear . save ( out_ras_pear ) arcpy . DefineProjection_management ( in_dataset = out_ras_pear , coor_system = "GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]" ) def CalculateCorrelation ( a , b , nodata ) : import numpy try : coef = numpy . corrcoef ( a , b ) return coef [ 0 ] [ 1 ] except : return nodata def ReplaceNoData ( lst , nodata ) : res = [ ] for a in lst : if a nodata / 2.0 : res . append ( None ) else : res . append ( a ) return res def CalculatePearsons ( a , b , nodata ) : import numpy from scipy . stats import pearsonr try : x = np . array ( a ) y = np . array ( b ) r , p = pearsonr ( a , y ) return p except : return nodata if __name__ == '__main__' : main ( ) At this moment I am getting a "RuntimeError: ERROR 999998: Unexpected Error" on line 73 when saving the output correlation raster. I will look into that and see what the problem is. You could try and run the code to see if it works on your system.

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Calculate Correlation and Pearson between two sets of rasters

ShouvikJha

Branched from: https://community.esri.com/thread/199323-re-trend-analysis-through-time-series-of-raster-data

Hi Xander Bakker‌, Some modification I want to do in correlation script.

I Would like to calculate the P value as a raster in addition to correlation raster.

Using scipy library, I just ran one script to obtain the correlation and P value. Script is attached below

<SPAN class="keyword token">import</SPAN> numpy <SPAN class="keyword token">as</SPAN> np
<SPAN class="keyword token">from</SPAN> scipy<SPAN class="punctuation token">.</SPAN>stats <SPAN class="keyword token">import</SPAN> pearsonr
x <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN> <SPAN class="number token">58295.62187335</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp; <SPAN class="number token">45420.95483714</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp; <SPAN class="number token">3398.64920064</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp;&nbsp; <SPAN class="number token">977.22166306</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">5515.32801851</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp; <SPAN class="number token">14184.57621022</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp; <SPAN class="number token">16027.2803392</SPAN> <SPAN class="punctuation token">,</SPAN>&nbsp; <SPAN class="number token">15313.01865824</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">6443.2448182</SPAN> <SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
y <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN> <SPAN class="number token">143547.79123381</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp; <SPAN class="number token">22996.69597427</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp;&nbsp; <SPAN class="number token">2591.56411049</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">661.93115277</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp;&nbsp; <SPAN class="number token">8826.96549102</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp; <SPAN class="number token">17735.13549851</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">11629.13003263</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp; <SPAN class="number token">14438.33177173</SPAN><SPAN class="punctuation token">,</SPAN>&nbsp;&nbsp;&nbsp; <SPAN class="number token">6997.89334741</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>

r<SPAN class="punctuation token">,</SPAN>p <SPAN class="operator token">=</SPAN> pearsonr<SPAN class="punctuation token">(</SPAN>x<SPAN class="punctuation token">,</SPAN>y<SPAN class="punctuation token">)</SPAN>

<SPAN class="keyword token">print</SPAN> <SPAN class="string token">"r"</SPAN><SPAN class="punctuation token">,</SPAN> r

<SPAN class="keyword token">print</SPAN> <SPAN class="string token">"p"</SPAN><SPAN class="punctuation token">,</SPAN> p

‍‍‍‍‍‍‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Output

Returns:

r : 0.831087956392

Pearson’s correlation coefficient

p-value : 0.00550539621039

2-tailed p-value

So instead of Numpy, can we use here Numpy and Scipy both library to get the addition p value or in the existing script can we add this function to obtain the p Value as a raster

Thanks & regards

Shouvik Jha

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Accepted answers

XanderBakker

Hi shouvik jha , I branched this question to give it more visibility and to avoid letting the post grow too much and contain multiple questions.

Basically, what I would do is define a second numpy that will hold the pearson value. This is what it would look like:

line 11 defined the pearson output raster path and name
line 35 creates the pearson numpy array
line 57 and 58 will call the pearson function and store the result in the numpy array
line 76 to 80 will store the output pearson raster
line 103 to 112 contains the function that calculated the pearson value

<SPAN class="keyword token">def</SPAN> <SPAN class="token function">main</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"load modules..."</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> arcpy
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>env<SPAN class="punctuation token">.</SPAN>overwriteOutput <SPAN class="operator token">=</SPAN> <SPAN class="token boolean">True</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy <SPAN class="keyword token">as</SPAN> np
&nbsp;&nbsp;&nbsp; template1 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Parameter1\r{0}_NPP.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; template2 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Parameter2\r{0}_WUE.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; nodata <SPAN class="operator token">=</SPAN> <SPAN class="operator token">-</SPAN><SPAN class="number token">3.4028235e+38</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_corr <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Pearson\correlation.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_pear <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Pearson\pearson.TIF'</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"create nested numpy array list..."</SPAN>
&nbsp;&nbsp;&nbsp; lst_np_ras <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> i <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">14</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_path1 <SPAN class="operator token">=</SPAN> template1<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN>i<SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> ras_path1
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np1 <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>ras_path1<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_path2 <SPAN class="operator token">=</SPAN> template2<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN>i<SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> ras_path2
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np2 <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>ras_path2<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_np_ras<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN>ras_np1<SPAN class="punctuation token">,</SPAN> ras_np2<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"read props numpy raster..."</SPAN>
&nbsp;&nbsp;&nbsp; ras_np <SPAN class="operator token">=</SPAN> lst_np_ras<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>&nbsp; <SPAN class="comment token"># take first numpy array from list</SPAN>
&nbsp;&nbsp;&nbsp; rows <SPAN class="operator token">=</SPAN> ras_np<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; cols <SPAN class="operator token">=</SPAN> ras_np<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - rows:"</SPAN><SPAN class="punctuation token">,</SPAN> rows
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - cols:"</SPAN><SPAN class="punctuation token">,</SPAN> cols

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"create output numpy array..."</SPAN>
&nbsp;&nbsp;&nbsp; ras_path <SPAN class="operator token">=</SPAN> template1<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; raster <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>Raster<SPAN class="punctuation token">(</SPAN>ras_path<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_np_res_corr <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>ndarray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">,</SPAN> cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_np_res_pear <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>ndarray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">,</SPAN> cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - out rows:"</SPAN><SPAN class="punctuation token">,</SPAN> ras_np_res_corr<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - out cols:"</SPAN><SPAN class="punctuation token">,</SPAN> ras_np_res_corr<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"loop through pixels..."</SPAN>
&nbsp;&nbsp;&nbsp; pix_cnt <SPAN class="operator token">=</SPAN> <SPAN class="number token">0</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> row <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> col <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN>cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; pix_cnt <SPAN class="operator token">+=</SPAN> <SPAN class="number token">1</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">if</SPAN> pix_cnt <SPAN class="operator token">%</SPAN> <SPAN class="number token">5000</SPAN> <SPAN class="operator token">==</SPAN> <SPAN class="number token">0</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - row:"</SPAN><SPAN class="punctuation token">,</SPAN> row<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; col:"</SPAN><SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; pixel:"</SPAN><SPAN class="punctuation token">,</SPAN> pix_cnt
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1 <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2 <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> lst_pars <SPAN class="keyword token">in</SPAN> lst_np_ras<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>lst_pars<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>lst_pars<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1 <SPAN class="operator token">=</SPAN> ReplaceNoData<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2 <SPAN class="operator token">=</SPAN> ReplaceNoData<SPAN class="punctuation token">(</SPAN>lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="comment token"># perform calculation on list</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; correlation <SPAN class="operator token">=</SPAN> CalculateCorrelation<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np_res_corr<SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> correlation
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; pearson <SPAN class="operator token">=</SPAN> CalculatePearsons<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np_res_pear<SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> pearson
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN> Exception <SPAN class="keyword token">as</SPAN> e<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"ERR:"</SPAN><SPAN class="punctuation token">,</SPAN> e
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - row:"</SPAN><SPAN class="punctuation token">,</SPAN> row<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; col:"</SPAN><SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; pixel:"</SPAN><SPAN class="punctuation token">,</SPAN> pix_cnt
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - lst_vals1:"</SPAN><SPAN class="punctuation token">,</SPAN> lst_vals1
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - lst_vals2:"</SPAN><SPAN class="punctuation token">,</SPAN> lst_vals2

&nbsp;&nbsp;&nbsp; pnt <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>Point<SPAN class="punctuation token">(</SPAN>raster<SPAN class="punctuation token">.</SPAN>extent<SPAN class="punctuation token">.</SPAN>XMin<SPAN class="punctuation token">,</SPAN> raster<SPAN class="punctuation token">.</SPAN>extent<SPAN class="punctuation token">.</SPAN>YMin<SPAN class="punctuation token">)</SPAN> <SPAN class="comment token">#&nbsp; - raster.meanCellHeight</SPAN>
&nbsp;&nbsp;&nbsp; xcellsize <SPAN class="operator token">=</SPAN> raster<SPAN class="punctuation token">.</SPAN>meanCellWidth
&nbsp;&nbsp;&nbsp; ycellsize <SPAN class="operator token">=</SPAN> raster<SPAN class="punctuation token">.</SPAN>meanCellHeight

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"Write output rasters..."</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> out_ras_corr
&nbsp;&nbsp;&nbsp; ras_res_corr <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>NumPyArrayToRaster<SPAN class="punctuation token">(</SPAN>ras_np_res_corr<SPAN class="punctuation token">,</SPAN> lower_left_corner<SPAN class="operator token">=</SPAN>pnt<SPAN class="punctuation token">,</SPAN> x_cell_size<SPAN class="operator token">=</SPAN>xcellsize<SPAN class="punctuation token">,</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y_cell_size<SPAN class="operator token">=</SPAN>ycellsize<SPAN class="punctuation token">,</SPAN> value_to_nodata<SPAN class="operator token">=</SPAN>nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_res_corr<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_ras_corr<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>DefineProjection_management<SPAN class="punctuation token">(</SPAN>in_dataset<SPAN class="operator token">=</SPAN>out_ras_corr<SPAN class="punctuation token">,</SPAN> coor_system<SPAN class="operator token">=</SPAN><SPAN class="string token">"GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]"</SPAN><SPAN class="punctuation token">)</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> out_ras_pear
&nbsp;&nbsp;&nbsp; ras_res_pear <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>NumPyArrayToRaster<SPAN class="punctuation token">(</SPAN>ras_np_res_pear<SPAN class="punctuation token">,</SPAN> lower_left_corner<SPAN class="operator token">=</SPAN>pnt<SPAN class="punctuation token">,</SPAN> x_cell_size<SPAN class="operator token">=</SPAN>xcellsize<SPAN class="punctuation token">,</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y_cell_size<SPAN class="operator token">=</SPAN>ycellsize<SPAN class="punctuation token">,</SPAN> value_to_nodata<SPAN class="operator token">=</SPAN>nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_res_pear<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_ras_pear<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>DefineProjection_management<SPAN class="punctuation token">(</SPAN>in_dataset<SPAN class="operator token">=</SPAN>out_ras_pear<SPAN class="punctuation token">,</SPAN> coor_system<SPAN class="operator token">=</SPAN><SPAN class="string token">"GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]"</SPAN><SPAN class="punctuation token">)</SPAN>



<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculateCorrelation</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; coef <SPAN class="operator token">=</SPAN> numpy<SPAN class="punctuation token">.</SPAN>corrcoef<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> coef<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata


<SPAN class="keyword token">def</SPAN> <SPAN class="token function">ReplaceNoData</SPAN><SPAN class="punctuation token">(</SPAN>lst<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; res <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> a <SPAN class="keyword token">in</SPAN> lst<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">if</SPAN> a <SPAN class="operator token"><</SPAN> nodata <SPAN class="operator token">/</SPAN> <SPAN class="number token">2.0</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; res<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>None<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">else</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; res<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> res


<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculatePearsons</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">from</SPAN> scipy<SPAN class="punctuation token">.</SPAN>stats <SPAN class="keyword token">import</SPAN> pearsonr
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; x <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; r<SPAN class="punctuation token">,</SPAN> p <SPAN class="operator token">=</SPAN> pearsonr<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> y<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> p
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata


<SPAN class="keyword token">if</SPAN> __name__ <SPAN class="operator token">==</SPAN> <SPAN class="string token">'__main__'</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; main<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

At this moment I am getting a "RuntimeError: ERROR 999998: Unexpected Error" on line 73 when saving the output correlation raster. I will look into that and see what the problem is. You could try and run the code to see if it works on your system.

All comments

XanderBakker

Hi shouvik jha , just like the original code has the function CalculateCorrelation:

<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculateCorrelation</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; coef <SPAN class="operator token">=</SPAN> numpy<SPAN class="punctuation token">.</SPAN>corrcoef<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> coef<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

... you could implement one that calculates p:

<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculatePearsons</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">from</SPAN> scipy<SPAN class="punctuation token">.</SPAN>stats <SPAN class="keyword token">import</SPAN> pearsonr
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; x <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; r<SPAN class="punctuation token">,</SPAN> p <SPAN class="operator token">=</SPAN> pearsonr<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> y<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> p
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Include the function and on line 62 change:

correlation <SPAN class="operator token">=</SPAN> CalculateCorrelation<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN></SPAN>

by (although the "correlation" will be the p value) :

correlation <SPAN class="operator token">=</SPAN> CalculatePearsons<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN></SPAN>

I did not try the code though.

PaoloGull_sow_3-1607187126467.png

ShouvikJha

Hi Xander Bakker‌, Thank you for the suggestion.

I trying to modify the code as you suggested but i don't understand, where I have to call the p Value raster.

From our earlier script, We got the output only Correlation raster, but this time I want Correlation raster as well as P value raster.

Snap from our earlier script on Input and output:

<SPAN class="keyword token">import</SPAN> numpy <SPAN class="keyword token">as</SPAN> np
&nbsp;&nbsp;&nbsp; template1 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'D:\Correlation\Parameter1\r{0}_NPP.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; template2 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'D:\Correlation\Parameter2\r{0}_WUE.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; nodata <SPAN class="operator token">=</SPAN> <SPAN class="operator token">-</SPAN><SPAN class="number token">3.4028235e+38</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_Corr <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'D:\Correlation\correlation.TIF'</SPAN> <SPAN class="comment token"># Already exist in our script</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_p&nbsp;&nbsp;&nbsp; <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'D:\Correlation\Significance.TIF'</SPAN> <SPAN class="comment token"># this one i want to add </SPAN>
&nbsp;&nbsp;&nbsp; ‍‍‍‍‍‍‍‍‍‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

ShouvikJha

Hi Xander Bakker‌, I am facing same problem here also.

we eagerly await your response

Thanks & regards

Shouvik Jha

XanderBakker

Hi shouvik jha , I branched this question to give it more visibility and to avoid letting the post grow too much and contain multiple questions.

Basically, what I would do is define a second numpy that will hold the pearson value. This is what it would look like:

line 11 defined the pearson output raster path and name
line 35 creates the pearson numpy array
line 57 and 58 will call the pearson function and store the result in the numpy array
line 76 to 80 will store the output pearson raster
line 103 to 112 contains the function that calculated the pearson value

<SPAN class="keyword token">def</SPAN> <SPAN class="token function">main</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"load modules..."</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> arcpy
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>env<SPAN class="punctuation token">.</SPAN>overwriteOutput <SPAN class="operator token">=</SPAN> <SPAN class="token boolean">True</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy <SPAN class="keyword token">as</SPAN> np
&nbsp;&nbsp;&nbsp; template1 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Parameter1\r{0}_NPP.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; template2 <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Parameter2\r{0}_WUE.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; nodata <SPAN class="operator token">=</SPAN> <SPAN class="operator token">-</SPAN><SPAN class="number token">3.4028235e+38</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_corr <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Pearson\correlation.TIF'</SPAN>
&nbsp;&nbsp;&nbsp; out_ras_pear <SPAN class="operator token">=</SPAN> r<SPAN class="string token">'C:\GeoNet\Correlation\Pearson\pearson.TIF'</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"create nested numpy array list..."</SPAN>
&nbsp;&nbsp;&nbsp; lst_np_ras <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> i <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">14</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_path1 <SPAN class="operator token">=</SPAN> template1<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN>i<SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> ras_path1
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np1 <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>ras_path1<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_path2 <SPAN class="operator token">=</SPAN> template2<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN>i<SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> ras_path2
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np2 <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>ras_path2<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_np_ras<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN>ras_np1<SPAN class="punctuation token">,</SPAN> ras_np2<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"read props numpy raster..."</SPAN>
&nbsp;&nbsp;&nbsp; ras_np <SPAN class="operator token">=</SPAN> lst_np_ras<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>&nbsp; <SPAN class="comment token"># take first numpy array from list</SPAN>
&nbsp;&nbsp;&nbsp; rows <SPAN class="operator token">=</SPAN> ras_np<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; cols <SPAN class="operator token">=</SPAN> ras_np<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - rows:"</SPAN><SPAN class="punctuation token">,</SPAN> rows
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - cols:"</SPAN><SPAN class="punctuation token">,</SPAN> cols

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"create output numpy array..."</SPAN>
&nbsp;&nbsp;&nbsp; ras_path <SPAN class="operator token">=</SPAN> template1<SPAN class="punctuation token">.</SPAN>format<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"%03d"</SPAN> <SPAN class="operator token">%</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; raster <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>Raster<SPAN class="punctuation token">(</SPAN>ras_path<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_np_res_corr <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>ndarray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">,</SPAN> cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_np_res_pear <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>ndarray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">,</SPAN> cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - out rows:"</SPAN><SPAN class="punctuation token">,</SPAN> ras_np_res_corr<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - out cols:"</SPAN><SPAN class="punctuation token">,</SPAN> ras_np_res_corr<SPAN class="punctuation token">.</SPAN>shape<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"loop through pixels..."</SPAN>
&nbsp;&nbsp;&nbsp; pix_cnt <SPAN class="operator token">=</SPAN> <SPAN class="number token">0</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> row <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN>rows<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> col <SPAN class="keyword token">in</SPAN> range<SPAN class="punctuation token">(</SPAN>cols<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; pix_cnt <SPAN class="operator token">+=</SPAN> <SPAN class="number token">1</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">if</SPAN> pix_cnt <SPAN class="operator token">%</SPAN> <SPAN class="number token">5000</SPAN> <SPAN class="operator token">==</SPAN> <SPAN class="number token">0</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - row:"</SPAN><SPAN class="punctuation token">,</SPAN> row<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; col:"</SPAN><SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; pixel:"</SPAN><SPAN class="punctuation token">,</SPAN> pix_cnt
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1 <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2 <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> lst_pars <SPAN class="keyword token">in</SPAN> lst_np_ras<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>lst_pars<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>lst_pars<SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals1 <SPAN class="operator token">=</SPAN> ReplaceNoData<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lst_vals2 <SPAN class="operator token">=</SPAN> ReplaceNoData<SPAN class="punctuation token">(</SPAN>lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="comment token"># perform calculation on list</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; correlation <SPAN class="operator token">=</SPAN> CalculateCorrelation<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np_res_corr<SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> correlation
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; pearson <SPAN class="operator token">=</SPAN> CalculatePearsons<SPAN class="punctuation token">(</SPAN>lst_vals1<SPAN class="punctuation token">,</SPAN> lst_vals2<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ras_np_res_pear<SPAN class="punctuation token">[</SPAN>row<SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> pearson
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN> Exception <SPAN class="keyword token">as</SPAN> e<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"ERR:"</SPAN><SPAN class="punctuation token">,</SPAN> e
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - row:"</SPAN><SPAN class="punctuation token">,</SPAN> row<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; col:"</SPAN><SPAN class="punctuation token">,</SPAN> col<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"&nbsp; pixel:"</SPAN><SPAN class="punctuation token">,</SPAN> pix_cnt
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - lst_vals1:"</SPAN><SPAN class="punctuation token">,</SPAN> lst_vals1
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - lst_vals2:"</SPAN><SPAN class="punctuation token">,</SPAN> lst_vals2

&nbsp;&nbsp;&nbsp; pnt <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>Point<SPAN class="punctuation token">(</SPAN>raster<SPAN class="punctuation token">.</SPAN>extent<SPAN class="punctuation token">.</SPAN>XMin<SPAN class="punctuation token">,</SPAN> raster<SPAN class="punctuation token">.</SPAN>extent<SPAN class="punctuation token">.</SPAN>YMin<SPAN class="punctuation token">)</SPAN> <SPAN class="comment token">#&nbsp; - raster.meanCellHeight</SPAN>
&nbsp;&nbsp;&nbsp; xcellsize <SPAN class="operator token">=</SPAN> raster<SPAN class="punctuation token">.</SPAN>meanCellWidth
&nbsp;&nbsp;&nbsp; ycellsize <SPAN class="operator token">=</SPAN> raster<SPAN class="punctuation token">.</SPAN>meanCellHeight

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">"Write output rasters..."</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> out_ras_corr
&nbsp;&nbsp;&nbsp; ras_res_corr <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>NumPyArrayToRaster<SPAN class="punctuation token">(</SPAN>ras_np_res_corr<SPAN class="punctuation token">,</SPAN> lower_left_corner<SPAN class="operator token">=</SPAN>pnt<SPAN class="punctuation token">,</SPAN> x_cell_size<SPAN class="operator token">=</SPAN>xcellsize<SPAN class="punctuation token">,</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y_cell_size<SPAN class="operator token">=</SPAN>ycellsize<SPAN class="punctuation token">,</SPAN> value_to_nodata<SPAN class="operator token">=</SPAN>nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_res_corr<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_ras_corr<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>DefineProjection_management<SPAN class="punctuation token">(</SPAN>in_dataset<SPAN class="operator token">=</SPAN>out_ras_corr<SPAN class="punctuation token">,</SPAN> coor_system<SPAN class="operator token">=</SPAN><SPAN class="string token">"GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]"</SPAN><SPAN class="punctuation token">)</SPAN>

&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">print</SPAN> <SPAN class="string token">" - "</SPAN><SPAN class="punctuation token">,</SPAN> out_ras_pear
&nbsp;&nbsp;&nbsp; ras_res_pear <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>NumPyArrayToRaster<SPAN class="punctuation token">(</SPAN>ras_np_res_pear<SPAN class="punctuation token">,</SPAN> lower_left_corner<SPAN class="operator token">=</SPAN>pnt<SPAN class="punctuation token">,</SPAN> x_cell_size<SPAN class="operator token">=</SPAN>xcellsize<SPAN class="punctuation token">,</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y_cell_size<SPAN class="operator token">=</SPAN>ycellsize<SPAN class="punctuation token">,</SPAN> value_to_nodata<SPAN class="operator token">=</SPAN>nodata<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; ras_res_pear<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_ras_pear<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; arcpy<SPAN class="punctuation token">.</SPAN>DefineProjection_management<SPAN class="punctuation token">(</SPAN>in_dataset<SPAN class="operator token">=</SPAN>out_ras_pear<SPAN class="punctuation token">,</SPAN> coor_system<SPAN class="operator token">=</SPAN><SPAN class="string token">"GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]"</SPAN><SPAN class="punctuation token">)</SPAN>



<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculateCorrelation</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; coef <SPAN class="operator token">=</SPAN> numpy<SPAN class="punctuation token">.</SPAN>corrcoef<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> coef<SPAN class="punctuation token">[</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata


<SPAN class="keyword token">def</SPAN> <SPAN class="token function">ReplaceNoData</SPAN><SPAN class="punctuation token">(</SPAN>lst<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; res <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">]</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">for</SPAN> a <SPAN class="keyword token">in</SPAN> lst<SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">if</SPAN> a <SPAN class="operator token"><</SPAN> nodata <SPAN class="operator token">/</SPAN> <SPAN class="number token">2.0</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; res<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>None<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">else</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; res<SPAN class="punctuation token">.</SPAN>append<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> res


<SPAN class="keyword token">def</SPAN> <SPAN class="token function">CalculatePearsons</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> b<SPAN class="punctuation token">,</SPAN> nodata<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">import</SPAN> numpy
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">from</SPAN> scipy<SPAN class="punctuation token">.</SPAN>stats <SPAN class="keyword token">import</SPAN> pearsonr
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; x <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; y <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>array<SPAN class="punctuation token">(</SPAN>b<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; r<SPAN class="punctuation token">,</SPAN> p <SPAN class="operator token">=</SPAN> pearsonr<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> y<SPAN class="punctuation token">)</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> p
&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <SPAN class="keyword token">return</SPAN> nodata


<SPAN class="keyword token">if</SPAN> __name__ <SPAN class="operator token">==</SPAN> <SPAN class="string token">'__main__'</SPAN><SPAN class="punctuation token">:</SPAN>
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ShouvikJha

Hi Xander Bakker Thank you very much for such wonderful script.

However I am running the script on my system and will inform you shortly.

ShouvikJha

Hi xander_bakker‌, Thank you very much for your such great cooperation. We are really very thankful for such wonderful and useful script from you.

The updated script is running perfectly and produced the exact result.

Thanks & regards

Shouvik Jha

Barjeece_Bashir

How did you calculate the (statistical not raster) correlation using script. I don't need output in raster format but i need r and p value. I also have time series data of two different variables (ndvi and rainfall). Please if you can guide me. Shouvik Jha Xander Bakker

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