230 lines
6.6 KiB
Python
230 lines
6.6 KiB
Python
import re
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import pandas as pd
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import numpy as np
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class Table():
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"""Store spreadsheet-like data."""
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def __init__(self,data,shapes,comments=None):
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"""
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New spreadsheet.
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Parameters
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----------
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data : numpy.ndarray
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Data.
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shapes : dict with str:tuple pairs
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Shapes of the columns. Example 'F':(3,3) for a deformation gradient.
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comments : iterable of str, optional
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Additional, human-readable information.
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"""
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self.data = pd.DataFrame(data=data)
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labels = {}
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i = 0
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for label in shapes.keys():
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for components in range(np.prod(shapes[label])):
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labels[i] = label
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i+=1
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if i != self.data.shape[1]:
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raise IndexError('Shape mismatch between shapes and data')
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self.data.rename(columns=labels,inplace=True)
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if comments is None:
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self.comments = []
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else:
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self.comments = [c for c in comments]
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self.shapes = shapes
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@staticmethod
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def from_ASCII(fname):
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"""
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Create table from ASCII file.
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The first line needs to indicate the number of subsequent header lines as 'n header'.
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Vector data column labels are indicated by '1_v, 2_v, ..., n_v'.
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Tensor data column labels are indicated by '3x3:1_T, 3x3:2_T, ..., 3x3:9_T'.
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Parameters
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----------
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fname : file, str, or pathlib.Path
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Filename or file for reading.
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"""
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try:
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f = open(fname)
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except TypeError:
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f = fname
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header,keyword = f.readline().split()
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if keyword == 'header':
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header = int(header)
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else:
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raise Exception
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comments = [f.readline()[:-1] for i in range(header-1)]
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labels = f.readline().split()
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shapes = {}
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for label in labels:
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tensor_column = re.search(r'[0-9,x]*?:[0-9]*?_',label)
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if tensor_column:
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my_shape = tensor_column.group().split(':',1)[0].split('x')
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shapes[label.split('_',1)[1]] = tuple([int(d) for d in my_shape])
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else:
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vector_column = re.match(r'[0-9]*?_',label)
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if vector_column:
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shapes[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
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else:
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shapes[label]=(1,)
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data = pd.read_csv(f,names=[i for i in range(len(labels))],sep=r'\s+').to_numpy()
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return Table(data,shapes,comments)
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def labels(self):
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"""Return the labels of all columns."""
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return list(self.shapes.keys())
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def get(self,label):
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"""
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Get column data.
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Parameters
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----------
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label : str
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Column label.
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"""
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if re.match(r'[0-9]*?_',label):
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idx,key = label.split('_',1)
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return self.data[key].to_numpy()[:,int(idx)-1]
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else:
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return self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
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def set(self,label,data,info=None):
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"""
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Set column data.
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Parameters
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----------
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label : str
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Column label.
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data : np.ndarray
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New data.
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info : str, optional
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Human-readable information about the new data.
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"""
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if info is not None:
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if np.prod(data.shape[1:],dtype=int) == 1:
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self.comments.append('{}: {}'.format(label,info))
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else:
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self.comments.append('{} {}: {}'.format(label,data.shape[1:],info))
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if re.match(r'[0-9]*?_',label):
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idx,key = label.split('_',1)
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iloc = self.data.columns.get_loc(key).tolist().index(True) + int(idx) -1
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self.data.iloc[:,iloc] = data
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else:
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self.data[label] = data.reshape(self.data[label].shape)
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def add(self,label,data,info=None):
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"""
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Add column data.
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Parameters
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----------
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label : str
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Column label.
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data : np.ndarray
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Modified data.
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info : str, optional
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Human-readable information about the modified data.
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"""
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if info is not None:
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if np.prod(data.shape[1:],dtype=int) == 1:
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self.comments.append('{}: {}'.format(label,info))
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else:
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self.comments.append('{} {}: {}'.format(label,data.shape[1:],info))
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self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
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size = np.prod(data.shape[1:],dtype=int)
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new_data = pd.DataFrame(data=data.reshape(-1,size),
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columns=[label for l in range(size)])
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self.data = pd.concat([self.data,new_data],axis=1)
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def delete(self,label):
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"""
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Delete column data.
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Parameters
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----------
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label : str
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Column label.
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"""
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self.data.drop(columns=label,inplace=True)
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del self.shapes[label]
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def rename(self,label_old,label_new,info=None):
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"""
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Rename column data.
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Parameters
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----------
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label_old : str
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Old column label.
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label_new : str
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New column label.
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"""
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self.data.rename(columns={label_old:label_new},inplace=True)
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comments = '{} => {}'.format(label_old,label_new)
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comments += ': {}'.format(info) if info is not None else ''
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self.comments.append(comments)
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self.shapes[label_new] = self.shapes.pop(label_old)
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def to_ASCII(self,fname):
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"""
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Store as plain text file.
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Parameters
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----------
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fname : file, str, or pathlib.Path
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Filename or file for reading.
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"""
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labels = []
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for l in self.shapes:
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if(self.shapes[l] == (1,)):
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labels.append('{}'.format(l))
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elif(len(self.shapes[l]) == 1):
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labels+=['{}_{}'.format(i+1,l)\
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for i in range(self.shapes[l][0])]
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else:
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labels+=['{}:{}_{}'.format('x'.join([str(d) for d in self.shapes[l]]),i+1,l)\
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for i in range(np.prod(self.shapes[l],dtype=int))]
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header = ['{} header'.format(len(self.comments)+1)]\
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+ self.comments\
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+ [' '.join(labels)]
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try:
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f = open(fname,'w')
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except TypeError:
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f = fname
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for line in header: f.write(line+'\n')
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self.data.to_csv(f,sep=' ',index=False,header=False)
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