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DAMASK_EICMD
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improved robustness of labels_index determination. 

fixed errors in data_readArray and improved functionality. Can now cope with list of columns. reads all valid columns returning list of invalid ones. updates table.labels accordingly.
This commit is contained in:
Philip Eisenlohr 2015-05-21 00:02:32 +00:00
parent 439d778cc0
commit 99adf42f0f
1 changed files with 24 additions and 18 deletions
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42
lib/damask/asciitable.py
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@ -167,28 +167,30 @@ class ASCIItable():
def labels_index(self, def labels_index(self,
labels): labels):
''' '''
tell index of column label(s) tell index of column label(s).
return numpy array if asked for list of labels.
transparently deals with label positions implicitly given as numbers or their headings given as strings.
''' '''
if isinstance(labels,list): if isinstance(labels,list): # check whether list of labels is requested
idx = [] idx = []
for label in labels: for label in labels:
try: try:
idx.append(label+0) idx.append(int(label)) # column given as integer number?
except TypeError: except ValueError:
try: try:
idx.append(self.labels.index(label)) idx.append(self.labels.index(label)) # locate string in label list
except ValueError: except ValueError:
if label != None: idx.append(-1) if label != None: idx.append(-1) # not found...
else: else:
try: try:
idx = labels+0 idx = int(labels)
except TypeError: except ValueError:
try: try:
idx = self.labels.index(labels) idx = self.labels.index(labels)
except(ValueError): except(ValueError):
idx = None if labels == None else -1 idx = None if labels == None else -1
return idx return np.array(idx) if isinstance(idx,list) else idx
# ------------------------------------------------------------------ # ------------------------------------------------------------------
def info_append(self, def info_append(self,
@ -264,20 +266,24 @@ class ASCIItable():
read whole data of all (given) labels as numpy array read whole data of all (given) labels as numpy array
''' '''
if labels != []: # read only some labels if labels == []:
indices = self.labels_index(labels) # get indices to read use = np.arange(self.__IO__['validReadSize']) # use all columns (and keep labels intact)
tempDict = dict(zip(indices, labels)) # column <> label connections labels_missing = []
self.labels = [tempDict[label] for label in sorted(tempDict)] # sort labels to reflect order from np.readtxt
self.__IO__['validReadSize'] = len(labels)
else: else:
indices = range(self.__IO__['validReadSize']) # use all columns indices = self.labels_index(labels) # check requested labels
present = np.where(indices >= 0)[0] # positions in request list of labels that are present ...
missing = np.where(indices < 0)[0] # ... and missing in table
labels_missing = np.array( labels) [missing] # corresponding labels ...
self.labels = list(np.array(self.labels)[indices[present]]) # ... for missing and present columns
self.__IO__['validReadSize'] = len(present) # update data width
use = indices[present]
try: try:
self.data_rewind() # try to wind back to start of data self.data_rewind() # try to wind back to start of data
except: except:
pass # assume/hope we are at data start already... pass # assume/hope we are at data start already...
self.data = np.loadtxt(self.__IO__['in'], usecols=indices,ndmin=2) self.data = np.loadtxt(self.__IO__['in'], usecols=use,ndmin=2)
return self.data.shape return labels_missing
# ------------------------------------------------------------------ # ------------------------------------------------------------------
def data_write(self,delimiter = '\t'): def data_write(self,delimiter = '\t'):