IO: Update of 2D fields

pydatview/io/__init__.py

@@ -245,6 +245,7 @@ def detectFormat(filename, **kwargs):
             else:
                 extMatch = False
         if extMatch: # we have a match on the extension
+            #print('Trying format: ',myformat)
             valid, F = isRightFormat(myformat, filename, **kwargs)
             if valid:
                 #print('File detected as :',myformat)

pydatview/io/csv_file.py

@@ -1,8 +1,12 @@
 import os
-
-from .file import File, WrongFormatError
 import pandas as pd
 
+try:
+    from .file import File, WrongFormatError
+except:
+    File=dict
+    WrongFormatError  = type('WrongFormatError', (Exception,),{})
+
 class CSVFile(File):
     """ 
     Read/write a CSV file. 
@@ -51,7 +55,23 @@ def __init__(self, filename=None, sep=None, colNames=None, commentChar=None, com
             raise Exception('Provide either `commentChar` or `commentLines` for CSV file types')
         if (len(self.colNames)>0) and (self.colNamesLine is not None):
             raise Exception('Provide either `colNames` or `colNamesLine` for CSV file types')
-        super(CSVFile, self).__init__(filename=filename,**kwargs)
+        if filename:
+            self.read(filename, **kwargs)
+        else:
+            self.filename = None
+
+    def read(self, filename=None, **kwargs):
+        if filename:
+            self.filename = filename
+        if not self.filename:
+            raise Exception('No filename provided')
+        if not os.path.isfile(self.filename):
+            raise OSError(2,'File not found:',self.filename)
+        if os.stat(self.filename).st_size == 0:
+            raise EmptyFileError('File is empty:',self.filename)
+        # Calling children function
+        self._read(**kwargs)
+
 
     def _read(self):
         COMMENT_CHAR=['#','!',';']
@@ -283,3 +303,47 @@ def __repr__(self):
     def _toDataFrame(self):
         return self.data
 
+    def to2DFields(self, **kwargs):
+        import xarray as xr
+        if len(kwargs.keys())>0:
+            print('[WARN] CSVFile: to2DFields: ignored keys: ',kwargs.keys())
+        if len(self.data)==0:
+            return None
+        M = self.data.values
+        if self.data.columns[0].lower()=='index':
+            M = M[:,1:]
+        s1 = 'rows'
+        s2 = 'columns'
+        ds = xr.Dataset(coords={s1: range(M.shape[0]), s2: range(M.shape[1])})
+        ds['data'] = ([s1, s2], M)
+        return ds
+
+    # --------------------------------------------------------------------------------
+    # --- Properties NOTE: copy pasted from file.py to make this file standalone..
+    # --------------------------------------------------------------------------------
+    @property
+    def size(self):
+        return os.path.getsize(self.filename)
+    @property
+    def encoding(self):	
+        import codecs
+        import chardet 
+        """  Detects encoding"""
+        try:
+            byts = min(32, self.size)
+        except TypeError:
+            return None
+        with open(self.filename, 'rb') as f:
+            raw = f.read(byts)
+        if raw.startswith(codecs.BOM_UTF8):
+            return 'utf-8-sig'
+        else:
+            result = chardet.detect(raw)
+            return result['encoding']
+
+if __name__ == '__main__':
+    f = CSVFile('C:/Work/Courses/440/project_solution/data/CFD_u.dat')
+    print(f)
+    ds = f.to2DFields()
+    print(ds)
+

pydatview/io/fast_output_file.py

@@ -214,7 +214,7 @@ def writeDataFrame(self, df, filename, binary=True):
 
     def __repr__(self):
         s='<{} object> with attributes:\n'.format(type(self).__name__)
-        s+=' - filename:    {}\n'.format(filename)
+        s+=' - filename:    {}\n'.format(self.filename)
         s+=' - data ({})\n'.format(type(self.data))
         s+=' - description: {}\n'.format(self.description)
         s+='and keys: {}\n'.format(self.keys())

pydatview/io/gnuplot_file.py

@@ -20,11 +20,11 @@ class GNUPlotFile(File):
     
     Main methods
     ------------
-    - read, write, toDataFrame, keys
+    - read, write, toDataFrame, to2DFields, keys
     
     Examples
     --------
-        f = GNUPlotFile('file.xxx')
+        f = GNUPlotFile('file.dat')
         print(f.keys())
         print(f.toDataFrame().columns)  
     
@@ -175,7 +175,7 @@ def is_meshgrid(self):
     @property
     def x_values(self):
         if len(self['data'])==1:
-            x= self['data'][:,0]
+            x = self['data'][0][:,0]
         else:
             x = check_first_column_same(self['data'])
             if x is None:
@@ -186,7 +186,9 @@ def x_values(self):
     @property
     def y_values(self):
         if len(self['data'])==1:
-            y= self['data'][:,1]
+            if self['data'][0].shape[1]<2:
+                return None
+            y= self['data'][0][:,1]
         else:
             y = check_second_column_unique(self['data'])
             if y is None:
@@ -236,13 +238,24 @@ def to2DFields(self, **kwargs):
         if self['column_names'] is None:
             colNames = default_colnames(self['data'][0].shape[1])
 
-        if not self.is_meshgrid:
-            return None
-
-
         if len(kwargs.keys())>0:
             print('[WARN] GNUPlotFile: to2DFields: ignored keys: ',kwargs.keys())
 
+        if not self.is_meshgrid:
+            if len(self['data'])>1:
+                # Probably hard to do, or have to provide different sets
+                return None
+            # --- Single table..., likely dubious results
+            M = self['data'][0]
+            if M.shape[1]<2:
+                return None
+            s1 = 'rows'
+            s2 = 'columns'
+            ds = xr.Dataset(coords={s1: range(M.shape[0]), s2: range(M.shape[1])})
+            ds['data'] = ([s1, s2], M)
+            return ds
+
+        # --- Mesh grid
         ds = xr.Dataset()
         ds = xr.Dataset(coords={colNames[0]: x, colNames[1]: y})
         data = np.array(self['data'])
@@ -323,7 +336,11 @@ def check_second_column_unique(arrays):
     if not arrays:
         return None
     unique_values = []
+    if len(arrays[0].shape)!=2:
+        return None
     for array in arrays:
+        if array.shape[1]<2:
+            return None
         second_column = array[:, 1]
         unique_value = np.unique(second_column)
         if len(unique_value) != 1:
@@ -341,12 +358,14 @@ def find_string_with_n_splits(strings, n):
 def default_colnames(n):
     colNames=['C{}'.format(i) for i in range(n)]
     colNames[0] = 'x'
-    colNames[1] = 'y'
+    if len(colNames)>1:
+        colNames[1] = 'y'
     return colNames
 
 if __name__ == '__main__':
     from welib.essentials import *
-    plt = GNUPlotFile('diff.000000.dat')
+    #plt = GNUPlotFile('diff.000000.dat')
+    plt = GNUPlotFile('C:/Work/Courses/440/project_solution/data/CFD_x.dat')
     print(plt)
     df =plt.toDataFrame()
     print(df)

pydatview/io/rosco_performance_file.py

@@ -19,7 +19,7 @@ class ROSCOPerformanceFile(File):
     
     Main methods
     ------------
-    - read, write, toDataFrame, keys
+    - read, write, toDataFrame, to2DFields, keys
     
     Examples
     --------

pydatview/io/turbsim_file.py

@@ -726,26 +726,38 @@ def to2DFields(self, nTOut=10, nYOut=3, nZOut=3, **kwargs):
         ds['y'].attrs['unit'] = 'm'
         ds['z'].attrs['unit'] = 'm'
 
+        ds['(y,z)_u_avg_[m/s]']= (['y','z'], np.squeeze(np.mean(self['u'][0,:,:,:], axis=0)))
+        ds['(y,z)_v_avg_[m/s]']= (['y','z'], np.squeeze(np.mean(self['u'][1,:,:,:], axis=0)))
+        ds['(y,z)_w_avg_[m/s]']= (['y','z'], np.squeeze(np.mean(self['u'][2,:,:,:], axis=0)))
+
+        ds['(t,y)_u_avg_[m/s]']= (['t','y'], np.squeeze(np.mean(self['u'][0,:,:,:], axis=2)))
+        ds['(t,y)_v_avg_[m/s]']= (['t','y'], np.squeeze(np.mean(self['u'][1,:,:,:], axis=2)))
+        ds['(t,y)_w_avg_[m/s]']= (['t','y'], np.squeeze(np.mean(self['u'][2,:,:,:], axis=2)))
+
+        ds['(t,z)_u_avg_[m/s]']= (['t','z'], np.squeeze(np.mean(self['u'][0,:,:,:], axis=1)))
+        ds['(t,z)_v_avg_[m/s]']= (['t','z'], np.squeeze(np.mean(self['u'][1,:,:,:], axis=1)))
+        ds['(t,z)_w_avg_[m/s]']= (['t','z'], np.squeeze(np.mean(self['u'][2,:,:,:], axis=1)))
+
         for it in IT:
-            ds['u_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][0,it,:,:]))
+            ds['(y,z)_u_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][0,it,:,:]))
         for it in IT:
-            ds['v_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][1,it,:,:]))
+            ds['(y,z)_v_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][1,it,:,:]))
         for it in IT:
-            ds['w_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][2,it,:,:]))
+            ds['(y,z)_w_t={:.2f}_[m/s]'.format(self.t[it])] = (['y','z'], np.squeeze(self['u'][2,it,:,:]))
         # --- TZ planes
         for iy in IY:
-            ds['u_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][0,:,iy,:]))
+            ds['(t,z)_u_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][0,:,iy,:]))
         for iy in IY:
-            ds['v_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][1,:,iy,:]))
+            ds['(t,z)_v_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][1,:,iy,:]))
         for iy in IY:
-            ds['w_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][2,:,iy,:]))
+            ds['(t,z)_w_y={:.2f}_[m/s]'.format(self['y'][iy])] = (['t','z'], np.squeeze(self['u'][2,:,iy,:]))
         # --- TY planes
         for iz in IZ:
-            ds['u_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][0,:,:,iz]))
+            ds['(t,y)_u_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][0,:,:,iz]))
         for iz in IZ:
-            ds['v_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][1,:,:,iz]))
+            ds['(t,y)_v_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][1,:,:,iz]))
         for iz in IZ:
-            ds['w_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][2,:,:,iz]))
+            ds['(t,y)_w_z={:.2f}_[m/s]'.format(self['z'][iz])] = (['t','y'], np.squeeze(self['u'][2,:,:,iz]))
         return ds
 
     def toDataset(self):