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103 lines
3.8 KiB
103 lines
3.8 KiB
import os |
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from collections import namedtuple |
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class ValidationError(ValueError): |
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pass |
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Validator = namedtuple('Validator', 'type extension validate id_fields data_fields defaults') |
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DataFile = namedtuple('DataFile', 'path separator skip validator') |
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def validate_stx(lines): |
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iterator = enumerate(lines) |
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_, line = next(iterator) |
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if not line.startswith('Report_Format:\t2'): |
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raise ValidationError('1 Unsupported File;' + line) |
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for i, line in iterator: |
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if line.startswith('Probe_Name\t'): |
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break |
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else: |
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raise ValidationError('1 Unsupported File') |
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try: |
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_, line = next(iterator) |
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_, numeric_data = line.split('\t', 1) |
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except (ValueError, StopIteration): |
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raise ValidationError('No Data Present') |
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separator = ',' if numeric_data.count(',') > numeric_data.count('.') else '.' |
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return separator, i |
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def validate_dat(lines): |
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iterator = enumerate(lines) |
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_, line = next(iterator) |
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if not line.startswith('Report_Format:\t2'): |
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raise ValidationError('Unsupported File') |
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for i, line in iterator: |
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if line.startswith('Dot_Number\t'): |
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break |
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else: |
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raise ValidationError('Unsupported File') |
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try: |
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_, line = next(iterator) |
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_, _, _, numeric_data = line.split('\t', 3) |
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except (ValueError, StopIteration): |
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raise ValidationError('No Data Present') |
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separator = ',' if numeric_data.count(',') > numeric_data.count('.') else '.' |
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return separator, i |
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def validate_csv(lines): |
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iterator = iter(lines) |
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if not next(iterator).startswith(' ID '): |
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raise ValidationError('Unsupported File') |
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try: |
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line = next(iterator) |
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_, numeric_data = line.split('\t', 1) |
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except (ValueError, StopIteration): |
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raise ValidationError('No Data Present') |
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separator = ',' if numeric_data.count(',') > numeric_data.count('.') else '.' |
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return separator, 0 |
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stx_validator = Validator( |
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'Signalyse Statistic Files', '.stx', validate_stx, |
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['Probe_Name'], |
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['Count', 'Net_Signal', 'Net_Signal_SD', 'Net_Integral', 'Net_Integral_SD', 'Proc_Control'], |
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['Net_Signal', 'Net_Signal_SD', 'Net_Integral', 'Net_Integral_SD']) |
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dat_validator = Validator( |
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'Signalyse Data Files', '.dat', validate_dat, |
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['Dot_Number', 'Probe_Name', 'Gene_Name', 'Col', 'Row'], |
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['X[Pix]', 'Y[Pix]', 'DX[Pix]', 'DY[Pix]', 'Spot_Diameter', 'ROI_Width', 'ROI_Heigth', 'Pixels', 'Bkg', |
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'Bkg_SD', 'Net_Signal', 'Net_Signal_SD', 'Net_Integral', 'Net_Integral_SD', 'Acc_Number', 'Proc_Control'], |
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['Bkg', 'Net_Signal', 'Net_Integral'] ) |
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csv_validator = Validator( |
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'Sensovation Data Files', '.csv', validate_csv, |
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[' ID '], |
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['Pos.X', 'Pos.Y', 'Bkg.Mean', 'Spot.Mean', 'Bkg.Median', 'Spot.Median', 'Bkg.StdDev', 'Spot.StdDev', |
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'Bkg.Sum', 'Spot.Sum', 'Bkg.Area', 'Spot.Area', 'Spot.Sat. (%)', 'Found', 'Pos.Nom.X', 'Pos.Nom.Y', 'Dia.', |
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'Rect.', 'Contour'], |
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['Bkg.Mean', 'Spot.Mean', 'Bkg.Median', 'Spot.Median', 'Bkg.StdDev', 'Spot.StdDev', 'Bkg.Sum', 'Spot.Sum'] ) |
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validation_map = { |
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stx_validator.extension: stx_validator, |
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dat_validator.extension: dat_validator, |
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csv_validator.extension: csv_validator |
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} |
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def guess_validator(unvalidated): |
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# get the validation method by examining the first file |
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_, extension = os.path.splitext(unvalidated[0]) |
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return validation_map.get(extension, None) |
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def validate_files(unvalidated, selected_validator): |
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# get the validation method by examining the first file |
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for file_path in unvalidated: |
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try: |
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with open(file_path, mode='r', encoding='utf-8') as file_handle: |
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separator, skip = selected_validator.validate(file_handle) |
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yield DataFile(file_path, separator, skip, selected_validator) |
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except (IOError, UnicodeError, ValidationError) as e: |
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print(e)
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