Jun-29-2021, 09:17 AM
(Jun-28-2021, 11:20 PM)Yoriz Wrote: output
You may need to add some error checking
Output:CA50_40_ref_data2101_E04_spec0-70 #0 Lifetimes (ns) : 0.4000 0.1250 2.0446 Std deviations : Fixed Fixed 0.0339 Intensities (%) : 69.2721 9.6726 21.0553 Std deviations : 1.0359 0.8128 0.4063 Time-zero Channel number : 41.5603 Std deviations : 0.0588 CA50_40_ref_data2101_E04_spec0-70 #1 Lifetimes (ns) : 0.4000 0.1250 2.0714 Std deviations : Fixed Fixed 0.0344 Intensities (%) : 70.0338 9.0952 20.8710 Std deviations : 1.0308 0.8135 0.4009 Time-zero Channel number : 41.5853 Std deviations : 0.0593 CA50_40_ref_data2101_E04_spec0-70 #2 Lifetimes (ns) : 0.4000 0.1250 2.0568 Std deviations : Fixed Fixed 0.0333 Intensities (%) : 69.5963 8.7445 21.6592 Std deviations : 1.0411 0.8177 0.4072 Time-zero Channel number : 41.5541 Std deviations : 0.0603 CA50_40_ref_data2101_E04_spec0-70 #3 Lifetimes (ns) : 0.4000 0.1250 2.0321 Std deviations : Fixed Fixed 0.0329 Intensities (%) : 70.4228 8.0614 21.5158 Std deviations : 1.0497 0.8219 0.4105 Time-zero Channel number : 41.4507 Std deviations : 0.0604 CA50_40_ref_data2101_E04_spec0-70 #4 Lifetimes (ns) : 0.4000 0.1250 2.0513 Std deviations : Fixed Fixed 0.0331 Intensities (%) : 67.2025 11.0731 21.7244 Std deviations : 1.0204 0.7976 0.4057 Time-zero Channel number : 41.6253 Std deviations : 0.0579
from itertools import zip_longest HEADER = ('Dataset Lifetimes Std deviations ' 'Intensities Std deviations ' 'Time-zero Std deviation\n') def grouper(iterable, n, fillvalue=''): "Collect data into fixed-length chunks or blocks" # grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx" args = [iter(iterable)] * n return zip_longest(*args, fillvalue=fillvalue) class Dataset: def __init__(self, line: str) -> None: self.data = line.strip().split()[1] def __repr__(self) -> str: return f'{self.data:7}' class LifeTimes: def __init__(self, line: str) -> None: self.data = line.strip().split()[3:6] def __repr__(self) -> str: return ' '.join(self.data) class StdDeviations: def __init__(self, line: str) -> None: split_line = line.strip().split() self.data = [split_line[num] if split_line[num:] else '' for num in range(3, 6)] def __repr__(self) -> str: return f"['{self.data[0]:^7}', '{self.data[1]:^7}', '{self.data[2]:^7}']" class Intensities: def __init__(self, line: str) -> None: self.data = line.strip().split()[3:6] def __repr__(self) -> str: return f'{self.data[0]:>7} {self.data[1]:>7} {self.data[2]:>7}' class TimeZero: def __init__(self, line: str) -> None: self.data = line.strip().split()[4] def __repr__(self) -> str: return f'{self.data:9}' class Block: def __init__(self, dataset, lifetimes, std_deviations, intensities, std_deviations2, time_zero, std_deviations3) -> None: self.dataset = Dataset(dataset) self.lifetimes = LifeTimes(lifetimes) self.std_deviations = StdDeviations(std_deviations) self.intensities = Intensities(intensities) self.std_deviations2 = StdDeviations(std_deviations2) self.time_zero = TimeZero(time_zero) self.std_deviations3 = StdDeviations(std_deviations3) def __repr__(self) -> str: return (f'{self.dataset} {self.lifetimes} {self.std_deviations}' f' {self.intensities} {self.std_deviations2}' f' {self.time_zero} {self.std_deviations3}\n') with open('output') as file_in, open('out', 'w') as file_out: file_out.write(HEADER) for group in grouper(file_in, 7): file_out.write(str(Block(*group)))out
Output:Dataset Lifetimes Std deviations Intensities Std deviations Time-zero Std deviation #0 0.4000 0.1250 2.0446 [' Fixed ', ' Fixed ', '0.0339 '] 69.2721 9.6726 21.0553 ['1.0359 ', '0.8128 ', '0.4063 '] 41.5603 ['0.0588 ', ' ', ' '] #1 0.4000 0.1250 2.0714 [' Fixed ', ' Fixed ', '0.0344 '] 70.0338 9.0952 20.8710 ['1.0308 ', '0.8135 ', '0.4009 '] 41.5853 ['0.0593 ', ' ', ' '] #2 0.4000 0.1250 2.0568 [' Fixed ', ' Fixed ', '0.0333 '] 69.5963 8.7445 21.6592 ['1.0411 ', '0.8177 ', '0.4072 '] 41.5541 ['0.0603 ', ' ', ' '] #3 0.4000 0.1250 2.0321 [' Fixed ', ' Fixed ', '0.0329 '] 70.4228 8.0614 21.5158 ['1.0497 ', '0.8219 ', '0.4105 '] 41.4507 ['0.0604 ', ' ', ' '] #4 0.4000 0.1250 2.0513 [' Fixed ', ' Fixed ', '0.0331 '] 67.2025 11.0731 21.7244 ['1.0204 ', '0.7976 ', '0.4057 '] 41.6253 ['0.0579 ', ' ', ' ']
Brilliant, this works perfectly! Using def/class commands is not familiar to me at all but I have to take a much closer look at that, seems very useful for my purposes - and it's a huge plus having reduced the amount of files the code creates. Definitely something to try and learn better. Thank you!
(Jun-29-2021, 12:39 AM)snippsat Wrote: If look at data so should it be turn around this is called transpose() if want data into Pandas for calculation, plot..ect.
If just want display data then can Yoriz method work.
To give example,just using first record.
record = {} with open('ca_data.txt') as f: header = next(f) for line in f: line = line.strip() line = line.replace('Time-zero ', '') line = line.split(':') line_1 = line[0].strip() line_2 = ''.join(line[1:]) record[line_1] = line_2.split() # Read like this so it fill in empty values with None df = pd.DataFrame.from_dict(record, orient='index') print(df)No can use
Output:Lifetimes (ns) 0.4000 0.1250 2.0446 Std deviations 0.0588 None None Intensities (%) 69.2721 9.6726 21.0553 Channel number 41.5603 None Nonetranspose()
,then it will a useful DataFrame.
>>> df = df.transpose() >>> df Lifetimes (ns) Std deviations Intensities (%) Channel number 0 0.4000 0.0588 69.2721 41.5603 1 0.1250 None 9.6726 None 2 2.0446 None 21.0553 None
Big thanks to you as well, I'll take a look at this method!