easier understanding of from_ang data layout interpretation
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14d3b7e66d
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@ -25,7 +25,7 @@ class Table:
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"""
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self.comments = [] if comments is None else [c for c in comments]
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self.data = pd.DataFrame(data=data)
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self.shapes = { k:(v,) if isinstance(v,(np.integer,int)) else v for k,v in shapes.items() }
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self.shapes = { k:(v,) if isinstance(v,(np.int,int)) else v for k,v in shapes.items() }
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self._label_condensed()
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@ -126,8 +126,6 @@ class Table:
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Filename or file for reading.
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"""
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shapes = {'eu':(3,), 'pos':(2,),
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'IQ':(1,), 'CI':(1,), 'ID':(1,), 'intensity':(1,), 'fit':(1,)}
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try:
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f = open(fname)
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except TypeError:
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@ -144,8 +142,11 @@ class Table:
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break
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data = np.loadtxt(content)
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for c in range(data.shape[1]-10):
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shapes[f'n/a_{c+1}'] = (1,)
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shapes = {'eu':3, 'pos':2, 'IQ':1, 'CI':1, 'ID':1, 'intensity':1, 'fit':1}
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remainder = data.shape[1]-sum(shapes.values())
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if remainder > 0: # 3.8 can do: if (remainder := data.shape[1]-sum(shapes.values())) > 0
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shapes['unknown'] = remainder
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return Table(data,shapes,comments)
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@ -234,7 +235,6 @@ class Table:
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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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