Tools: update for pyDatView scripter

Author: ebranlard

pyFAST/common.py

@@ -0,0 +1,3 @@
+
+class PYFASTException(Exception):
+    pass

pyFAST/input_output/wetb/hawc2/htc_file.py

@@ -157,8 +157,8 @@ def isfile_case_insensitive(f):
             relpath = "../" * np.argmax(found)
             return abspath(pjoin(os.path.dirname(self.filename), relpath))
         else:
-            raise ValueError(
-                "Modelpath cannot be autodetected for '%s'.\nInput files not found near htc file" % self.filename)
+            print("Modelpath cannot be autodetected for '%s'.\nInput files not found near htc file" % self.filename)
+            return 'unknown'
 
     def load(self):
         self.contents = OrderedDict()

pyFAST/postpro/postpro.py

@@ -4,10 +4,14 @@
 import numpy as np
 import re
 
+import pyFAST.input_output as weio
+from pyFAST.common import PYFASTException as WELIBException
+
 # --- fast libraries
 from pyFAST.input_output.fast_input_file import FASTInputFile
 from pyFAST.input_output.fast_output_file import FASTOutputFile
 from pyFAST.input_output.fast_input_deck import FASTInputDeck
+import pyFAST.fastfarm.fastfarm as fastfarm
 
 # --------------------------------------------------------------------------------}
 # --- Tools for IO 
@@ -903,6 +907,57 @@ def spanwisePostPro(FST_In=None,avgMethod='constantwindow',avgParam=5,out_ext='.
     # Combine all into a dictionary
     return out
 
+def radialAvg(filename, avgMethod, avgParam, raw_name='', df=None, raiseException=True):
+    """
+    Wrapper function, for instance used by pyDatView apply either:
+       spanwisePostPro or spanwisePostProFF (FAST.Farm)
+    """
+
+    base,out_ext = os.path.splitext(filename)
+    if df is None:
+        df = FASTOutputFile(filename).toDataFrame()
+
+    # --- Detect if it's a FAST Farm file
+    sCols = ''.join(df.columns)
+    if sCols.find('WkDf')>1 or sCols.find('CtT')>0:
+        # --- FAST FARM files
+        Files=[base+ext for ext in ['.fstf','.FSTF','.Fstf','.fmas','.FMAS','.Fmas'] if os.path.exists(base+ext)]
+        if len(Files)==0:
+            fst_in=None
+            #raise Exception('Error: No .fstf file found with name: '+base+'.fstf')
+        else:
+            fst_in=Files[0]
+
+        dfRad,_,dfDiam =  fastfarm.spanwisePostProFF(fst_in,avgMethod=avgMethod,avgParam=avgParam,D=1,df=df)
+        dfs_new  = [dfRad,dfDiam]
+        names_new=[raw_name+'_rad', raw_name+'_diam']
+    else:
+        # --- FAST files
+        # HACK for AD file to find the right .fst file
+        iDotAD=base.lower().find('.ad')
+        if iDotAD>1:
+            base=base[:iDotAD]
+        #
+        Files=[base+ext for ext in ['.fst','.FST','.Fst','.dvr','.Dvr','.DVR'] if os.path.exists(base+ext)]
+        if len(Files)==0:
+            fst_in=None
+            #raise Exception('Error: No .fst file found with name: '+base+'.fst')
+        else:
+            fst_in=Files[0]
+
+        try:
+            out = spanwisePostPro(fst_in, avgMethod=avgMethod, avgParam=avgParam, out_ext=out_ext, df = df)
+            dfRadED=out['ED_bld']; dfRadAD = out['AD']; dfRadBD = out['BD']
+            dfs_new  = [dfRadAD, dfRadED, dfRadBD]
+            names_new=[raw_name+'_AD', raw_name+'_ED', raw_name+'_BD'] 
+        except:
+            if raiseException:
+                raise
+            else:
+                print('[WARN] radialAvg failed for filename {}'.format(filename))
+                dfs_new =[None]
+                names_new=['']
+    return dfs_new, names_new
 
 def spanwisePostProRows(df, FST_In=None):
     """ 

pyFAST/tools/pandalib.py

@@ -128,3 +128,82 @@ def remap_df(df, ColMap, bColKeepNewOnly=False, inPlace=False, dataDict=None, ve
             print('[WARN] Signals missing and omitted for ColKeep:\n       '+'\n       '.join(ColKeepMiss))
         df=df[ColKeepSafe]
     return df
+
+def changeUnits(df, flavor='SI', inPlace=True):
+    """ Change units of a dataframe
+
+    # TODO harmonize with dfToSIunits in welib.fast.tools.lin.py !
+    """
+    def splitunit(s):
+        iu=s.rfind('[')
+        if iu>0:
+            return s[:iu], s[iu+1:].replace(']','')
+        else:
+            return s, ''
+    def change_units_to_WE(s, c):
+        """ 
+        Change units to wind energy units
+        s: channel name (string) containing units, typically 'speed_[rad/s]'
+        c: channel (array)
+        """
+        svar, u = splitunit(s)
+        u=u.lower()
+        scalings = {}
+        #        OLD      =     NEW
+        scalings['rad/s'] =  (30/np.pi,'rpm') # TODO decide
+        scalings['rad' ]  =   (180/np.pi,'deg')
+        scalings['n']     =   (1e-3, 'kN')
+        scalings['nm']    =   (1e-3, 'kNm')
+        scalings['n-m']   =   (1e-3, 'kNm')
+        scalings['n*m']   =   (1e-3, 'kNm')
+        scalings['w']     =   (1e-3, 'kW')
+        if u in scalings.keys():
+            scale, new_unit = scalings[u]
+            s = svar+'['+new_unit+']'
+            c *= scale
+        return s, c
+
+    def change_units_to_SI(s, c):
+        """ 
+        Change units to SI units
+        TODO, a lot more units conversion needed...will add them as we go
+        s: channel name (string) containing units, typically 'speed_[rad/s]'
+        c: channel (array)
+        """
+        svar, u = splitunit(s)
+        u=u.lower()
+        scalings = {}
+        #        OLD      =     NEW
+        scalings['rpm']   =  (np.pi/30,'rad/s') 
+        scalings['rad' ]  =   (180/np.pi,'deg')
+        scalings['deg/s' ] =   (np.pi/180,'rad/s')
+        scalings['kn']     =   (1e3, 'N')
+        scalings['knm']    =   (1e3, 'Nm')
+        scalings['kn-m']   =   (1e3, 'Nm')
+        scalings['kn*m']   =   (1e3, 'Nm')
+        scalings['kw']     =   (1e3, 'W')
+        if u in scalings.keys():
+            scale, new_unit = scalings[u]
+            s = svar+'['+new_unit+']'
+            c *= scale
+        return s, c
+
+    if not inPlace:
+        raise NotImplementedError()
+
+    if flavor == 'WE':
+        cols = []
+        for i, colname in enumerate(df.columns):
+            colname_new, df.iloc[:,i] = change_units_to_WE(colname, df.iloc[:,i])
+            cols.append(colname_new)
+        df.columns = cols
+    elif flavor == 'SI':
+        cols = []
+        for i, colname in enumerate(df.columns):
+            colname_new, df.iloc[:,i] = change_units_to_SI(colname, df.iloc[:,i])
+            cols.append(colname_new)
+        df.columns = cols
+    else:
+        raise NotImplementedError(flavor)
+    return df
+