diff --git a/chromatopy/readers/__init__.py b/chromatopy/readers/__init__.py new file mode 100644 index 0000000..ccd1034 --- /dev/null +++ b/chromatopy/readers/__init__.py @@ -0,0 +1,2 @@ +from .abstractreader import CSVReader +from .abstractreader import ShimadzuReader diff --git a/chromatopy/readers/abstractreader.py b/chromatopy/readers/abstractreader.py new file mode 100644 index 0000000..eb4b5ce --- /dev/null +++ b/chromatopy/readers/abstractreader.py @@ -0,0 +1,158 @@ +from abc import ABC, abstractmethod +from io import StringIO +from typing import TextIO, Optional +import re + +import pandas as pd + + +class AbstractReader(ABC): + + def __init__(self, path: str): + self.path = path + + @abstractmethod + def read(self): + pass + + @abstractmethod + def read_directory(self): + pass + + @abstractmethod + def extract_peaks(self): + pass + + @abstractmethod + def extract_signal(self): + pass + + +class CSVReader(AbstractReader): + + def read_csv(self): + data = pd.read_csv(self.path, header=None) + return data + + def read_directory(self, path: str): + pass + + def extract_peaks(self): + pass + + def extract_signal(self): + pass + + +class ChemStationReader(AbstractReader): + + def read(self): + pass + + +class ShimadzuReader(AbstractReader): + re_sections = re.compile(r"\[(.*)\]") + + def read(self): + pass + + def read_directory(self, path: str): + pass + + def parse_sections(self) -> dict: + """Parse a Shimadzu ASCII-export file into sections.""" + with open(self.path, "r", encoding="ISO-8859-1") as f: + fulltext = f.read() + + # Split file into sections using section header pattern + split = self.re_sections.split(fulltext) + assert len(split[0]) == 0, "the file should start with a section header" + + section_names = [split[i] for i in range(1, len(split), 2)] + section_contents = [split[i] for i in range(2, len(split), 2)] + + sections = { + name: content for name, content in zip(section_names, section_contents) + } + return sections + + def parse_meta(self, sections: dict, section_name: str, nrows: int) -> dict: + """Parse the metadata in a section as keys-values.""" + meta_table = pd.read_table( + StringIO(sections[section_name]), nrows=nrows, header=None + ) + meta = {row[0]: row[1] for _, row in meta_table.iterrows()} + + return meta + + def parse_table( + self, sections: dict, section_name: str, skiprows: int = 1 + ) -> Optional[pd.DataFrame]: + """Parse the data in a section as a table.""" + table_str = sections[section_name] + + # Count number of non-empty lines + num_lines = len([l for l in re.split("[\r\n]+", table_str) if len(l)]) + + if num_lines <= 1: + return None + + return pd.read_table(StringIO(table_str), header=1, skiprows=skiprows) + + def get_peak_table( + self, sections: dict, detector: str = "A" + ) -> Optional[pd.DataFrame]: + section_name = f"Peak Table(Detector {detector})" + meta = self.parse_meta(sections, section_name, 1) + table = self.parse_table(sections, section_name, skiprows=1) + + assert ( + table is None or int(meta["# of Peaks"]) == table.shape[0] + ), "Declared number of peaks and table size differ" + + return table + + def get_compound_table( + self, sections: dict, detector: str = "A" + ) -> Optional[pd.DataFrame]: + section_name = f"Compound Results(Detector {detector})" + meta = self.parse_meta(sections, section_name, 1) + table = self.parse_table(sections, section_name, skiprows=1) + + assert ( + table is None or int(meta["# of IDs"]) == table.shape[0] + ), "Declared number of compounds and table size differ" + + return table + + def get_chromatogram_table( + self, sections: dict, detector: str = "A", channel: int = 1 + ) -> Optional[pd.DataFrame]: + section_name = f"LC Chromatogram(Detector {detector}-Ch{channel})" + + meta = self.parse_meta(sections, section_name, 6) + table = self.parse_table(sections, section_name, skiprows=6) + + # Convert intensity values into what they are supposed to be + table["Value (mV)"] = table["Intensity"] * float(meta["Intensity Multiplier"]) + + assert ( + meta["Intensity Units"] == "mV" + ), f"Assumed intensity units in mV but got {meta['Intensity Units']}" + assert ( + int(meta["# of Points"]) == table.shape[0] + ), "Declared number of points and table size differ" + + return table + + def get_header(self, sections: dict) -> dict: + return self.parse_meta(sections, "Header", nrows=None) + + def get_file_information(self, sections: dict) -> dict: + return self.parse_meta(sections, "File Information", nrows=None) + + def get_original_files(self, sections: dict) -> dict: + return self.parse_meta(sections, "Original Files", nrows=None) + + def get_sample_information(self, sections: dict) -> dict: + return self.parse_meta(sections, "Sample Information", nrows=None) diff --git a/examples/kr/2023-12-08 01-20-41+01-00-01.dx_DAD1A.CSV b/examples/kr/2023-12-08 01-20-41+01-00-01.dx_DAD1A.CSV new file mode 100644 index 0000000..6e04ebc --- /dev/null +++ b/examples/kr/2023-12-08 01-20-41+01-00-01.dx_DAD1A.CSV @@ -0,0 +1,7350 @@ 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"cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "from chromatopy.readers import Reader1" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "path = \"2023-12-08 01-20-41+01-00-01.dx_DAD1A.CSV\"\n", + "reader = Reader1(path)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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lvbLrE9314i7z+Vvf/5JGDUuJXoMAALY0kN/f3IvHhmIvkgIA7IaAYgNh9wokoAAALI6AYgNhRbJUoQAALI6AYgN+f8hz8gkAwOIIKDYQtlAbYzwAAIsjoNhA2N2Mo9QOAAD6i4BiA+E9KFFpBgAA/UZAsYOwWTwkFACAtRFQbCB8Fg8AANZGQLGBsKXuSSgAAIsjoNgAdzMGAMQaAooNcDdjAECsIaDYQNhS91ShAAAsjoBiA0wzBgDEGgKKDYQt1EZAAQBYHAHFBhjiAQDEGgKKDdCDAgCINQQUGwjNI0wzBgBYHQHFBsKHeAAAsDYCig2E9pjQgQIAsDoCii2RUAAA1kZAsYHwpe6j0w4AAPqLgGIDLHUPAIg1BBQbCCuSJaEAACyOgGIDoUM6DPEAAKyOgGIDYUM8FMkCACyOgGIDYSM65BMAgMURUGyIfAIAsDoCig2EFsWy1D0AwOoIKDYQWhRLPgEAWB0BxQa4Fw8AINYQUGwgfKE2IgoAwNoIKDYQvlBbdNoBAEB/EVBsIHyWMQkFAGBtBBQ7MLgXDwAgthBQbICl7gEAsYaAYgMUyQIAYg0BxQaYZgwAiDUEFBsIK5IloQAALI6AYgPh04xJKAAAayOg2EBoICGeAACsjoBiA6E3B6QDBQBgdQQUGwgNJNzNGABgdQQUGwi7m3F0mgEAQL8RUGyAdVAAALGGgGID5BEAQKwhoNhAaI8JNSgAAKsjoNhAWA0K+QQAYHEEFBsIr0GJUkMAAOgnAooNhN/NmIQCALA2AooNcLNAAECsIaDYQNi0YhIKAMDiCCg2EJ5PSCgAAGsjoNhAaM1JaE0KAABWQ0CxAaYZAwBiDQHFBsKmGTPEAwCwOAKKDYTfzTg67QAAoL8IKDYQPouHhAIAsDYCig2E1aBEpxkAAPTbBQWURx99VA6HQ4sWLTK3tbW1qby8XNnZ2UpLS9PcuXNVW1sb9LrDhw9r1qxZSklJUU5Oju655x51dXVdSFNwDqGBhA4UAIDVnXdA2b59u37xi19owoQJQdvvvvtuvfrqq1q3bp0qKyt15MgR3XLLLeZ+n8+nWbNmqaOjQ5s3b9azzz6rtWvXaunSpef/KXBO4dOMSSgAAGs7r4DS3Nys+fPn65e//KWGDRtmbm9oaNCvfvUrPfHEE7rhhhs0efJkPfPMM9q8ebO2bNkiSXrttde0b98+/dd//ZcmTZqkmTNn6pFHHtHq1avV0dExOJ8KwShBAQDEmPMKKOXl5Zo1a5bKysqCtldXV6uzszNo+9ixY1VUVKSqqipJUlVVlcaPH6/c3FzzmBkzZqixsVF79+7t83zt7e1qbGwMeqD/QntMyCcAAKtzD/QFL774onbs2KHt27eH7fN6vUpMTFRWVlbQ9tzcXHm9XvOY3uEksD+wry/Lli3TQw89NNCmokf4JB4iCgDA2gbUg1JTU6O77rpLzz33nJKSkiLVpjD33XefGhoazEdNTc2QnTsehPWgkE8AABY3oIBSXV2turo6XXPNNXK73XK73aqsrNTKlSvldruVm5urjo4O1dfXB72utrZWeXl5kqS8vLywWT2B54FjQnk8HmVkZAQ90H9hs3gY5AEAWNyAAsr06dO1e/du7dq1y3xMmTJF8+fPN79OSEhQRUWF+Zr9+/fr8OHDKi0tlSSVlpZq9+7dqqurM4/ZtGmTMjIyNG7cuEH6WOgtdEiHHhQAgNUNqAYlPT1dV111VdC21NRUZWdnm9tvu+02LV68WMOHD1dGRobuvPNOlZaW6tprr5Uk3XjjjRo3bpy+/vWva/ny5fJ6vbr//vtVXl4uj8czSB8LvYUu1MZS9wAAqxtwkeyn+dnPfian06m5c+eqvb1dM2bM0M9//nNzv8vl0oYNG3THHXeotLRUqampWrBggR5++OHBbgp6hPWgMMQDALA4hxGDUzoaGxuVmZmphoYG6lH6YcGvt6ny/WNyOrp7T+6ZcbnKv3RZtJsFALCZgfz+5l48NhBIoC6nI6rtAACgvwgoNhDoJHM6ugOKnyIUAIDFEVBsIDCIF+hBIZ4AAKyOgGIDgYXaXD09KLFXdQQAsBsCig0EAomzpweFuxkDAKyOgGIDfrMGpfs58QQAYHUEFBsIm8VDDwoAwOIIKDYQOouHeAIAsDoCig2EzuKhBgUAYHUEFBvwh/agkE8AABZHQLEBvzmLp/u/5BMAgNURUGzALJJ1MMQDAIgNBBQbMItkmWcMAIgRBBQbMBdqYxYPACBGEFBsIHypeyIKAMDaCCg2EL7UfRQbAwBAPxBQbMDsQQnM4iGgAAAsjoBiI2dqUEgoAABrI6DYAAu1AQBiDQHFBkKXuqdIFgBgdQQUGwibxRPNxgAA0A8EFBsIzNpxu1hJFgAQGwgoNuDrSSjunmk8TDMGAFgdAcUGAgElMdCDQkIBAFgcAcUGAkM6bqcz6DkAAFZFQLGBQA9KgtvZ8zyarQEA4NMRUGwg0GOSwDRjAECMIKDYgNmD0lMk6yOgAAAsjoBiA4Ga2AQ3NwsEAMQGAooNBGbtmEWyJBQAgMURUGwgMKSTwEJtAIAYQUCxgdCF2nz0oAAALI6AYgPmLB4X66AAAGIDAcUGzFk8TopkAQCxgYAS5wzD6DWLhyEeAEBsIKDEud5ZxO2kSBYAEBsIKHGudxhJdFODAgCIDQSUONd7OMcskuVePAAAiyOgxLnevSWBIR6WugcAWB0BJc717kEJDPFws0AAgNURUOJc7+GcwFL3zOIBAFgdASXO9R7OcbtYBwUAEBsIKHGud28J04wBALGCgBLnAmHE6ZCcBBQAQIwgoMS5QA+Ky+mQy9Ezi4dpxgAAiyOgxLkzPSgOOXsCCrN4AABWR0CJc4FZPC6nQz2TeJjFAwCwPAJKnAvM4nH16kGhBgUAYHUElDgX6C1xOh1yOZlmDACIDQSUOBfoLXE5z/SgMMQDALA6AkqcM3tQHA71dKAwxAMAsDwCSpw7M81YZ4Z46EEBAFgcASXO+fssko1miwAA+HQElDjXu0jWrEFhiAcAYHEElDgXCCgJLqe5DgoLtQEArI6AEue6+lzqnoACALA2Akqc6/J1hxG30yEHNSgAgBhBQIlzXT1r3bt6L9RGQgEAWBwBJc4FhnPcLqc5xMM6KAAAqyOgxLlADUr3EE/3NmbxAACsbkABZdmyZZo6darS09OVk5OjOXPmaP/+/UHHtLW1qby8XNnZ2UpLS9PcuXNVW1sbdMzhw4c1a9YspaSkKCcnR/fcc4+6urou/NMgTKAGxcW9eAAAMWRAAaWyslLl5eXasmWLNm3apM7OTt14441qaWkxj7n77rv16quvat26daqsrNSRI0d0yy23mPt9Pp9mzZqljo4Obd68Wc8++6zWrl2rpUuXDt6ngilQg+LutQ4KNSgAAKtzD+TgjRs3Bj1fu3atcnJyVF1drc9//vNqaGjQr371Kz3//PO64YYbJEnPPPOMrrjiCm3ZskXXXnutXnvtNe3bt09//vOflZubq0mTJumRRx7R97//ff3gBz9QYmJi2Hnb29vV3t5uPm9sbDyfz2pLvWtQAuugUIMCALC6C6pBaWhokCQNHz5cklRdXa3Ozk6VlZWZx4wdO1ZFRUWqqqqSJFVVVWn8+PHKzc01j5kxY4YaGxu1d+/ePs+zbNkyZWZmmo/CwsILabat9K5B6b3UPYu1AQCs7LwDit/v16JFi3T99dfrqquukiR5vV4lJiYqKysr6Njc3Fx5vV7zmN7hJLA/sK8v9913nxoaGsxHTU3N+TbbdnrXoLgDtzMWi7UBAKxtQEM8vZWXl2vPnj166623BrM9ffJ4PPJ4PBE/Tzzy9apBcfUKKF1+Q25XtFoFAMC5nVcPysKFC7Vhwwa98cYbGjVqlLk9Ly9PHR0dqq+vDzq+trZWeXl55jGhs3oCzwPHYPB09apBSXA5w7YDAGBFAwoohmFo4cKFWr9+vV5//XUVFxcH7Z88ebISEhJUUVFhbtu/f78OHz6s0tJSSVJpaal2796turo685hNmzYpIyND48aNu5DPgj74etWgBA3x+AgoAADrGtAQT3l5uZ5//nm98sorSk9PN2tGMjMzlZycrMzMTN12221avHixhg8froyMDN15550qLS3VtddeK0m68cYbNW7cOH3961/X8uXL5fV6df/996u8vJxhnAjo7GMdFEnq7Bn6AQDAigYUUJ566ilJ0he/+MWg7c8884y++c1vSpJ+9rOfyel0au7cuWpvb9eMGTP085//3DzW5XJpw4YNuuOOO1RaWqrU1FQtWLBADz/88IV9EvSpdw2Kw9Hdi9LlN8ziWQAArGhAAaU/U1OTkpK0evVqrV69+qzHjB49Wn/4wx8GcmqcpzM1KA7zv11+Q50+elAAANbFvXji3JkaFGfQf5lmDACwMgJKnOtdgyKd6UnpogYFAGBhBJQ417sGpfu/3d/yTmpQAAAWRkCJc6E1KAmBHhQCCgDAwggocS5Qa+Lq6TkJDPUwxAMAsDICSpzrfbNASeZqsqwkCwCwMgJKnOvqmU5sFsn2/JdpxgAAKyOgxLlAT0mCuQ5KTw8KNSgAAAsjoMS50BqUQA8K66AAAKyMgBLnQmtQArN5GOIBAFgZASXOhdagJDgpkgUAWB8BJc75wmpQAtOMCSgAAOsioMS5rrOtg8IQDwDAwggocc53tnVQmMUDALAwAkqc6zzbOiisJAsAsDACSpwL9JSEzuJhmjEAwMoIKHEu0IOS6O7+VgeGeDq66EEBAFgXASXOdfgCs3i6v9WenqDSTkABAFgYASXOhfageNwuSQQUAIC1EVDiXCCgBHpQkhICPSi+qLUJAIBPQ0CJc509PSWJrpAelE56UAAA1kVAiXNmDYq7e/bOmRoUelAAANZFQIlzHT1B5MwQT3cPShs9KAAACyOgxLnOnh4Uc4iHGhQAQAwgoMS50CJZc4iHHhQAgIURUOKY32+YNwsMTDM2h3joQQEAWBgBJY71vt9OgiukSJYeFACAhRFQ4lhnrzsWm0M89KAAAGIAASWO9b7fTrRqUPzclBAAcB4IKHEsUCDrcjrkcgaGeIZuqfvlG9/TxIdf07aDJyN+LgBAfCGgxLFAD0qg/kQ6s9R9W2fkh3h+/pcP1dTWpdVvfBDxcwEA4gsBJY6ZNwp0nfk2B2bxnI5wQGls6zS/9ja0RfRcAID4Q0CJY+Yibe4z3+Y0j1uS1Nrhk2FErj7k4+Mt5tcnWzsidh4AQHwioMSx0EXaJCm1J6D4/EZEl7s/2CugHGtqN9sCAEB/EFDiWHtXeEBJSXDJ0VOS0tzeFbFz9w4oknSKXhQAwAAQUOLYmR6UM0WyTqdDaYndvShDGlBaOs9yJAAA4QgocSwwUydQGBsQGOZpbhu6gHKyhR4UAED/EVDiWKDGJDSgpCV1B5Sm9sj0ahiGYQaUzOQESQQUAMDAEFDi2JkelOBvc2AmT0t7ZKYan2jpUFNblxwOaVJhliRm8gAABoaAEscCASU5pAclPSlQgxKZHpTAFOOCzGQVZCVJkk42E1AAAP1HQIljgYDiCa1BSYxsDcpHPQHlkpGpGpaSKIlZPACAgSGgxLHTgRoU99lqUCITUAL1Jxdnp2p4KgEFADBw7mg3AJFjDvEkBufQYSndhav1rZEZ4jl4rCegjEhVFkWyAIDzQECJY2aRbEgPSnaaR5J0vLk9Iuf94FizJGlMTpp8/u7l9OlBAQAMBEM8cexs66AEhl1ORKBwtaPLbxbJXpaTpmGBIR4WagMADAA9KHEssA5KcmJwQBmR1hNQWga/B+XQiRZ1+Q2lJrqUn5mkrp4bFjLEAwAYCHpQ4tjpwCwed/C3OTu1e4gnElN/P6jrHt65LCdNDodDw1ITzLac7ojMuisAgPhDQIljp80i2dAalO4elOMtHTIMY1DP+X5tIKCkS+peFC5wLyDqUAAA/UVAiWOBdU4CK8cGjOgpku3o8g/6TJ69RxokSVfkdwcUh8NhroXCMA8AoL8IKHEscK+djKSEoO1JCS7lZnSHlMMnWwf1nHs+6Q4oV12UaW5jLRQAwEARUOJYoAclsLR9b0XDUyRJhwYxoJxobteRhjZJ0pUFGeZ2elAAAANFQIljzT0rxab1GVBSJUmHT7QM2vl29/SeXDIiVem9em1Gpnf31nh7wgsAAJ+GgBLHGs0elISwfZeM7A4oB3pm3QyG3X/vDijjR2UGbR+dPfi9NQCA+EZAiVPtXT51dHWvgxJaJCtJ43tqRP5WUz9o5wz0oIy/KDSgdIehQ4PYWwNYSV1jm/Z80jDos+IAO2OhtjgVWLnV7XQovY+AMqGnl+PjE6062dJhFrKeL8MwVH3olCRpYmFW0L6Le3pQPjpGQEH8qWtq04wVb+pUa6f+aVqRHp59pX791kH9puqQPjdmhEovzdaINI+uKRqmRLdTLqcj2k0GYgIBJU4da+peJTY7LVHOPv6HmJWSqLF56XrP26Q/v1urr04pvKDzfXisRSdaOuRxO83wEzA2P0NOh3S0oU3ehjblZSZd0LmAaPj7qVZ9eKxFv37roD6oa9b6712nnIwkraw4oFM90/Vf2HZYL20/rJ5bUOnF7TV6cXtN0Pssu2W8/mla0VA3P4zfb6ilo0vN7V1q7fCp0+dXZ5ehDp+/++ueR0eXXx0+Q51d3c9TPG5NHJVp9owCkUJAiVPHmrsLUgMFqn358vh8vedt0n/v+PsFB5RtB09Kkq4uypIn5OaEaR63xuZlaN/RRm3/+KRunlhwQecChlpbp09f+flmM/hL0sa9Xl1TNEwvbOsOIPOmFur/7T6qprYupSe59b0vXqYPjzWbwSbw2vv+e7eSE1yac/VFg97OTp9f3oY2/f3UadU1telYU7uONbfreFNHz3/bVd/aoaa2LjV3dOl8R6ScDunh2Vfpa9eOHtwPAPRCQIlTgf8ZBhZl68st11ykVa8f0JaPTurN94/p858Zed7ne2N/nSTp2kuy+9x/3aXZ2ne0URv3egkoiDl7jzQGhRNJWvrKXnncTvn8hsquyNWjcyfo4dlX6ZP608rPTAq6SWdze5eefvMjPb/1sI43t+ve372j0dkpurpo2Hm3qeF0p3bV1Gvn4VPa80mD3j3apKMNp83em/5yOx1KTnTJ43YqwRV4OJTgcgZvczuV4HSorqlduz9p0A9+v1dXXZSpSSFDusBgIaDEqUMnumfMXJSVfNZjRg1L0fyS0Vq7+WMt/u3f9NJ3r9WlI9MGfK7Gtk5Vvn9MknTTVXl9HjN70kX6j7cOatPeWtWcbFVhzzosQCzY722SJF2Rn6G7y8bou/9VLcOQ2rv8+tyYEVr+vyZIkhLdThWPCB/6SPO4tfgfPqNF08fojueq9ae9tfruf1br6W9M+dRf8IZh6FRrpw6daNH7tU3acaheOw6f0gfHmvvsAUl0O3VRVrLyMpI0Mt2jEWkejUhP1Ig0j0amezQ8JVHpSW6lJyUoPcktj9sph6P/dTGGYejOF3ZqwztHtfD5HXrt7s8rJZFfJRh8Uf2pWr16tX7yk5/I6/Vq4sSJWrVqlaZNmxbNJsWND4+duWnfuXz/prHa8tEJvedt0pzVf9W/3DBGX51aqMzk8KnJZ/OfVYfU0eXXZ3LTdHluep/HXHVRhq67NFubPzyhO1/Yqae/MVk56dSiIDa8X9sdUK6/NFs3Xpmnp78+RTsPn9K04uH6wmdG9vsXvNPp0E+/Okkfrf6rDtQ1a87qv2r8RZmaevFwZaclKjnBpbYun+pbO/X3U606dKJVh0+0qqlnTaNQRcNTdE1RliaMytKVBRkqHpGqEWmePuvOBovD4dCPvjJeOw/X6++nTuvXbx3UwhvGROx8sC+HEaV5cS+99JK+8Y1vaM2aNSopKdGKFSu0bt067d+/Xzk5Oed8bWNjozIzM9XQ0KCMjIxzHmtHhmGo5McVqmtq1/P/p0TXXTbinMefaG7Xd37ztnYcrpckJbqcmliYqSsLMjVqWLIykhLkcHTXs4zLz9DIdI8cDocMw9CmfbW684Wdau/y62e3TtRXrh511vN8dKxZtzy1WfWtnUpKcGrGlXn64uUjdd2lI5TT857ncrKlQydbOnTpyNQB/cUHXKiv/2qr/ufAcT16y3jNG4QC12NN7Vr2h3f1+78dUVc/x2TyMpJ08YgUTSocpmuKsnR10bBz1phF2iu7PtFdL+5SSqJLj86doBvG5iglwaUTLR3q8vvlN2QW1nb4/HI6HPK4nfIkdA8nedxOJSe45Hax2oWdDOT3d9QCSklJiaZOnaonn3xSkuT3+1VYWKg777xTS5YsOedrIxVQTrZ06Ej96aBtva+OISNomxF0nNHHtjOvDN3W93FnOBySo9fXUncg6K6wN9QVqLDvVV3f2bPvw2PNem7rYSUnuLRz6T8EjYWfjc9vaN3bNXrmrx9rf89fi2czLCVBqR63mtu7zJsNll2Ro19+Y8qnBof93ibd87u/6Z2eRd0CUhNdKshKVnqSW6ket1IT3XI4uov+mtu7VHPytD7p+d4UZCbps2NGKD8zWcmJLiW4nN3TN3vO3bsJwddQcsj8Qg51/zXokOR0du8zj+vZ3v196N7u7Pk+OEJe63CcOS6Uob7/efX1PT/bv8S+Nvfnn22gfVKvz9/7Opy5FObxwc/D2xX4Muzn3fy5Dvk3YnzK63Tufyfhe/raF7whtL2GYchvGPL7Jb9hyDC6/+szDPmNnv1+Q76erzt9Rs/Mle61hDq6/Hq26pAkad0/l2rqxcM1WI43t+uN9+q039ukxrZOne70y+N2alhKgvIzkzU6O0VFw1NUODylX/+Oh5Lfb2jums3a2fOHTYLLoUSXUy0dvn6/h8MhDU9J1Mh0j0YNS9bF2akqHpmq4uxU5Wcl61wdQef+GTHOsS/snfr5nqH7zvG6Pn5vnP385/e6/n7e/p277x0j0jyDPlvL8gGlo6NDKSkp+t3vfqc5c+aY2xcsWKD6+nq98sorQce3t7ervf1MgVpjY6MKCwsHPaA8t/WQ/m39nkF7v2i7/fOX6P9++YoBvcYwDH18olXbPz6pj461qOZUq053+NTlN/TJqVYdPN4SVISXlODU10pG656bLg+bvXOuc+ysqddre2v1PweOae+Rxn63z+nQgIsAgcGQnODS2/eXKbWPdYXsqr61Q2sqP9LGPUf1cU/dm8PRXXjrcDjkcTnldjnkdjl7anZ8au8JfbC+/11SpB9/ZfygvudAAkpU/qUdP35cPp9Pubm5Qdtzc3P13nvvhR2/bNkyPfTQQxFvV0qiS3kZZ+oiHCF/YXZvC470QX+th/6V/invEfROgSfG2f/adEhBFfWJPZX2vavuA4/L89L0reuL+/GpgzkcDhWPSO2z0E+STnf4dPB4izp8fiW6nLpkZOqA/7JzOBy6pmiYrikapiUzx6qt06e/nzotb0Obmtu71NLepZaO7jH3RJdTyYkujRqWrMtGpsuT4NSb7x/Tu0ebVNfUprbO7u7jji6fGVyCI7cRti3wV7XRs918bnT/1WIYCv6650WGzvzF3fu16vX8bB1I5+xXOkev09n2fNoIl9Hr50ghP0eBz9Zr11l7Os6cr+/eldCf+bCf97O97lPe13x56BXo43OHbgp9D6fD0f1wOuR09Hre87XLGegh697m7umRS+yZxRL4+tpLswknIbJSErVk5lh9/6bL9Un9aTW3d+nSkWlK+JRhG7+/uze4qa1Lx5vbVdvYppqTrTp4vFUHjzfr4xOtqmts+9Qe2bC9ffSems97vVf4z1nfx4XvO/sJz/2eofvOry1hZ+/j909f5+jP6/uSfYELeF6oqPSgHDlyRBdddJE2b96s0tJSc/u9996ryspKbd26Nej4oepBAQAAkWP5HpQRI0bI5XKptrY2aHttba3y8sKnqXo8Hnk80SsGAwAAQysq5dOJiYmaPHmyKioqzG1+v18VFRVBPSoAAMCeojagunjxYi1YsEBTpkzRtGnTtGLFCrW0tOhb3/pWtJoEAAAsImoB5dZbb9WxY8e0dOlSeb1eTZo0SRs3bgwrnAUAAPYTtXVQLgQLtQEAEHsG8vubJfwAAIDlEFAAAIDlEFAAAIDlEFAAAIDlEFAAAIDlEFAAAIDlEFAAAIDlEFAAAIDlEFAAAIDlRG2p+wsRWPy2sbExyi0BAAD9Ffi93Z9F7GMyoDQ1NUmSCgsLo9wSAAAwUE1NTcrMzDznMTF5Lx6/368jR44oPT1dDodjUN+7sbFRhYWFqqmp4T4/Q4DrPbS43kOL6z20uN5D63yut2EYampqUkFBgZzOc1eZxGQPitPp1KhRoyJ6joyMDH7AhxDXe2hxvYcW13tocb2H1kCv96f1nARQJAsAACyHgAIAACyHgBLC4/HowQcflMfjiXZTbIHrPbS43kOL6z20uN5DK9LXOyaLZAEAQHyjBwUAAFgOAQUAAFgOAQUAAFgOAQUAAFgOAaWX1atX6+KLL1ZSUpJKSkq0bdu2aDcpLrz55pu6+eabVVBQIIfDoZdffjlov2EYWrp0qfLz85WcnKyysjIdOHAgOo2NA8uWLdPUqVOVnp6unJwczZkzR/v37w86pq2tTeXl5crOzlZaWprmzp2r2traKLU4tj311FOaMGGCuVhVaWmp/vjHP5r7udaR9eijj8rhcGjRokXmNq754PnBD34gh8MR9Bg7dqy5P5LXmoDS46WXXtLixYv14IMPaseOHZo4caJmzJihurq6aDct5rW0tGjixIlavXp1n/uXL1+ulStXas2aNdq6datSU1M1Y8YMtbW1DXFL40NlZaXKy8u1ZcsWbdq0SZ2dnbrxxhvV0tJiHnP33Xfr1Vdf1bp161RZWakjR47olltuiWKrY9eoUaP06KOPqrq6Wm+//bZuuOEGzZ49W3v37pXEtY6k7du36xe/+IUmTJgQtJ1rPriuvPJKHT161Hy89dZb5r6IXmsDhmEYxrRp04zy8nLzuc/nMwoKCoxly5ZFsVXxR5Kxfv1687nf7zfy8vKMn/zkJ+a2+vp6w+PxGC+88EIUWhh/6urqDElGZWWlYRjd1zchIcFYt26decy7775rSDKqqqqi1cy4MmzYMOM//uM/uNYR1NTUZIwZM8bYtGmT8YUvfMG46667DMPg53uwPfjgg8bEiRP73Bfpa00PiqSOjg5VV1errKzM3OZ0OlVWVqaqqqootiz+HTx4UF6vN+jaZ2ZmqqSkhGs/SBoaGiRJw4cPlyRVV1ers7Mz6JqPHTtWRUVFXPML5PP59OKLL6qlpUWlpaVc6wgqLy/XrFmzgq6txM93JBw4cEAFBQW65JJLNH/+fB0+fFhS5K91TN4scLAdP35cPp9Pubm5Qdtzc3P13nvvRalV9uD1eiWpz2sf2Ifz5/f7tWjRIl1//fW66qqrJHVf88TERGVlZQUdyzU/f7t371Zpaana2tqUlpam9evXa9y4cdq1axfXOgJefPFF7dixQ9u3bw/bx8/34CopKdHatWt1+eWX6+jRo3rooYf0uc99Tnv27In4tSagAHGsvLxce/bsCRozxuC7/PLLtWvXLjU0NOh3v/udFixYoMrKymg3Ky7V1NTorrvu0qZNm5SUlBTt5sS9mTNnml9PmDBBJSUlGj16tH77298qOTk5oudmiEfSiBEj5HK5wiqPa2trlZeXF6VW2UPg+nLtB9/ChQu1YcMGvfHGGxo1apS5PS8vTx0dHaqvrw86nmt+/hITE3XZZZdp8uTJWrZsmSZOnKh///d/51pHQHV1terq6nTNNdfI7XbL7XarsrJSK1eulNvtVm5uLtc8grKysvSZz3xGH3zwQcR/vgko6v6fy+TJk1VRUWFu8/v9qqioUGlpaRRbFv+Ki4uVl5cXdO0bGxu1detWrv15MgxDCxcu1Pr16/X666+ruLg4aP/kyZOVkJAQdM3379+vw4cPc80Hid/vV3t7O9c6AqZPn67du3dr165d5mPKlCmaP3+++TXXPHKam5v14YcfKj8/P/I/3xdcZhsnXnzxRcPj8Rhr16419u3bZ9x+++1GVlaW4fV6o920mNfU1GTs3LnT2LlzpyHJeOKJJ4ydO3cahw4dMgzDMB599FEjKyvLeOWVV4x33nnHmD17tlFcXGycPn06yi2PTXfccYeRmZlp/OUvfzGOHj1qPlpbW81j/vmf/9koKioyXn/9dePtt982SktLjdLS0ii2OnYtWbLEqKysNA4ePGi88847xpIlSwyHw2G89tprhmFwrYdC71k8hsE1H0z/+q//avzlL38xDh48aPz1r381ysrKjBEjRhh1dXWGYUT2WhNQelm1apVRVFRkJCYmGtOmTTO2bNkS7SbFhTfeeMOQFPZYsGCBYRjdU40feOABIzc31/B4PMb06dON/fv3R7fRMayvay3JeOaZZ8xjTp8+bXzve98zhg0bZqSkpBhf+cpXjKNHj0av0THs29/+tjF69GgjMTHRGDlypDF9+nQznBgG13oohAYUrvngufXWW438/HwjMTHRuOiii4xbb73V+OCDD8z9kbzWDsMwjAvvhwEAABg81KAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAsJTVq1fr4osvVlJSkkpKSrRt27ZoNwlAFBBQAFjGSy+9pMWLF+vBBx/Ujh07NHHiRM2YMUN1dXXRbhqAIca9eABYRklJiaZOnaonn3xSkuT3+1VYWKg777xTS5YsiXLrAAwlelAAWEJHR4eqq6tVVlZmbnM6nSorK1NVVVUUWwYgGggoACzh+PHj8vl8ys3NDdqem5srr9cbpVYBiBYCCgAAsBwCCgBLGDFihFwul2pra4O219bWKi8vL0qtAhAtBBQAlpCYmKjJkyeroqLC3Ob3+1VRUaHS0tIotgxANLij3QAACFi8eLEWLFigKVOmaNq0aVqxYoVaWlr0rW99K9pNAzDECCgALOPWW2/VsWPHtHTpUnm9Xk2aNEkbN24MK5wFEP9YBwUAAFgONSgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMBy/j9UQPapcPTpjQAAAABJRU5ErkJggg==", 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\u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 39\u001b[0m calib_nums \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m---> 40\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_extern.inf\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlistdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 41\u001b[0m \u001b[38;5;66;03m# Parse MS polarities from _extern.inf. \u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(path, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_extern.inf\u001b[39m\u001b[38;5;124m'\u001b[39m), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m 43\u001b[0m lines \u001b[38;5;241m=\u001b[39m f\u001b[38;5;241m.\u001b[39mread()\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mascii\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39msplitlines()\n", + "\u001b[0;31mNotADirectoryError\u001b[0m: [Errno 20] Not a directory: '/Users/max/Documents/training_course/lilly/20231108_EGL009_03_pos.wiff'" + ] + } + ], + "source": [ + "rb.waters.read(\"/Users/max/Documents/training_course/lilly/20231108_EGL009_03_pos.wiff\")" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "from chromatopy.readers import ShimadzuReader" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Header': '\\nApplication Name,LCsolution\\nVersion,1.25\\nData File Name,C:\\\\LabSolutions\\\\Data\\\\aldolaze\\\\Martina\\\\aldolna adicija\\\\batch_21022012\\\\EtAc\\\\0.lcd\\nOutput Date,12.12.2023.\\nOutput Time,11:15:12\\n\\n',\n", + " 'File Information': '\\nType,Data File\\nGenerated,21.2.2012. 13:16:32\\nGenerated by,Admin\\nModified,21.2.2012. 13:33:38\\nModified by,Admin\\n\\n',\n", + " 'Sample Information': '\\nOperator Name,Admin\\nAcquired,21.2.2012. 13:16:57\\nSample Type,0:Unknown\\nLevel,0\\nSample Name,0\\nSample ID,\\nISTD Amount 1,1\\nISTD Amount 2,1\\nISTD Amount 3,1\\nISTD Amount 4,1\\nISTD Amount 5,1\\nISTD Amount 6,1\\nISTD Amount 7,1\\nISTD Amount 8,1\\nISTD Amount 9,1\\nISTD Amount 10,1\\nISTD Amount 11,1\\nISTD Amount 12,1\\nISTD Amount 13,1\\nISTD Amount 14,1\\nISTD Amount 15,1\\nISTD Amount 16,1\\nISTD Amount 17,1\\nISTD Amount 18,1\\nISTD Amount 19,1\\nISTD Amount 20,1\\nISTD Amount 21,1\\nISTD Amount 22,1\\nISTD Amount 23,1\\nISTD Amount 24,1\\nISTD Amount 25,1\\nISTD Amount 26,1\\nISTD Amount 27,1\\nISTD Amount 28,1\\nISTD Amount 29,1\\nISTD Amount 30,1\\nISTD Amount 31,1\\nISTD Amount 32,1\\nSample Amount,1\\nDilution Factor,1\\nVial#,1\\nInjection Volume,20\\n\\n',\n", + " 'Original Files': '\\nData File,C:\\\\LabSolutions\\\\Data\\\\aldolaze\\\\Martina\\\\aldolna adicija\\\\batch_21022012\\\\EtAc\\\\0.lcd\\nMethod File,C:\\\\LabSolutions\\\\Data\\\\aldolaze\\\\metoda3_2eluenta.lcm\\nBatch File,C:\\\\LabSolutions\\\\Data\\\\aldolaze\\\\Martina\\\\ba\\x9edarci\\\\aldol-aldehid-01022012\\\\lista.lcb\\nReport Format File,C:\\\\LabSolutions\\\\LCsolution\\\\System\\\\Default.lcr\\nTuning File,\\n\\n',\n", + " 'File Description': '\\n\\n\\n',\n", + " 'Configuration': '\\n# of Detectors,2\\nDetector ID,Detector A,AD2\\nDetector Name,Detector A,AD2\\n# of Channels,1,1\\n\\n',\n", + " 'Peak Table(Detector A-Ch1)': \"\\n# of Peaks,14\\nPeak#,R.Time,I.Time,F.Time,Area,Height,A/H,Conc.,Mark,ID#,Name,k',Plate #,Plate Ht.,Tailing,Resolution,Sep.Factor,Conc. %,Norm 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Groups,0\\n\\n',\n", + " 'Group Results(AD2)': '\\n# of Groups,0\\n\\n',\n", + " 'Group Results(PDA)': '\\n# of Groups,0\\n\\n',\n", + " 'LC Chromatogram(Detector A-Ch1)': '\\nInterval(msec),500\\n# of Points,1801\\nStart Time(min),0.000\\nEnd Time(min),15.000\\nIntensity Units,mV\\nIntensity Multiplier,0.001\\nWavelength(nm),215\\nR.Time 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+ " 'LC Status Trace(Pump A Pressure)': '\\nInterval(msec),1000\\n# of Points,900\\nStart Time(min),0.000\\nEnd Time(min),14.983\\nIntensity Units,kgf/cm2\\nIntensity Multiplier,1\\nR.Time (min),Intensity\\n0.00000,213.9\\n0.01667,213.9\\n0.03333,213.9\\n0.05000,214.7\\n0.06667,216.3\\n0.08333,218.7\\n0.10000,221.3\\n0.11667,224.8\\n0.13333,225.2\\n0.15000,226.0\\n0.16667,224.2\\n0.18333,223.7\\n0.20000,223.2\\n0.21667,223.4\\n0.23333,223.3\\n0.25000,222.5\\n0.26667,220.2\\n0.28333,220.9\\n0.30000,220.9\\n0.31667,221.3\\n0.33333,222.0\\n0.35000,222.1\\n0.36667,221.5\\n0.38333,219.6\\n0.40000,220.6\\n0.41667,220.4\\n0.43333,221.2\\n0.45000,221.7\\n0.46667,221.2\\n0.48333,219.3\\n0.50000,220.2\\n0.51667,220.7\\n0.53333,220.8\\n0.55000,221.3\\n0.56667,221.6\\n0.58333,218.7\\n0.60000,219.1\\n0.61667,220.2\\n0.63333,220.7\\n0.65000,220.8\\n0.66667,221.3\\n0.68333,221.3\\n0.70000,218.7\\n0.71667,219.6\\n0.73333,219.9\\n0.75000,220.8\\n0.76667,220.9\\n0.78333,221.2\\n0.80000,219.5\\n0.81667,219.3\\n0.83333,219.4\\n0.85000,220.3\\n0.86667,220.4\\n0.88333,220.7\\n0.90000,221.2\\n0.91667,218.9\\n0.93333,219.1\\n0.95000,219.9\\n0.96667,220.8\\n0.98333,220.6\\n1.00000,220.7\\n1.01667,218.7\\n1.03333,219.0\\n1.05000,219.0\\n1.06667,220.2\\n1.08333,220.9\\n1.10000,220.4\\n1.11667,220.6\\n1.13333,218.7\\n1.15000,218.7\\n1.16667,219.5\\n1.18333,220.2\\n1.20000,220.8\\n1.21667,220.3\\n1.23333,220.6\\n1.25000,218.7\\n1.26667,219.4\\n1.28333,219.9\\n1.30000,220.6\\n1.31667,220.7\\n1.33333,220.2\\n1.35000,218.5\\n1.36667,219.3\\n1.38333,218.7\\n1.40000,219.6\\n1.41667,220.3\\n1.43333,220.6\\n1.45000,219.8\\n1.46667,218.6\\n1.48333,219.0\\n1.50000,219.4\\n1.51667,220.0\\n1.53333,220.4\\n1.55000,219.3\\n1.56667,217.8\\n1.58333,218.9\\n1.60000,219.0\\n1.61667,219.4\\n1.63333,220.0\\n1.65000,220.7\\n1.66667,218.7\\n1.68333,219.0\\n1.70000,219.3\\n1.71667,219.5\\n1.73333,220.2\\n1.75000,221.1\\n1.76667,221.6\\n1.78333,218.9\\n1.80000,219.8\\n1.81667,220.7\\n1.83333,220.9\\n1.85000,221.3\\n1.86667,221.9\\n1.88333,222.1\\n1.90000,219.3\\n1.91667,220.3\\n1.93333,221.2\\n1.95000,221.1\\n1.96667,221.5\\n1.98333,221.7\\n2.00000,219.5\\n2.01667,219.8\\n2.03333,220.6\\n2.05000,220.8\\n2.06667,220.8\\n2.08333,221.3\\n2.10000,221.3\\n2.11667,219.1\\n2.13333,219.4\\n2.15000,219.4\\n2.16667,220.7\\n2.18333,220.4\\n2.20000,220.8\\n2.21667,221.1\\n2.23333,218.9\\n2.25000,219.3\\n2.26667,219.9\\n2.28333,220.8\\n2.30000,220.4\\n2.31667,220.6\\n2.33333,218.7\\n2.35000,218.9\\n2.36667,219.0\\n2.38333,220.3\\n2.40000,220.8\\n2.41667,220.3\\n2.43333,218.6\\n2.45000,218.6\\n2.46667,218.9\\n2.48333,220.2\\n2.50000,220.8\\n2.51667,220.2\\n2.53333,219.4\\n2.55000,219.3\\n2.56667,219.4\\n2.58333,219.4\\n2.60000,220.2\\n2.61667,220.8\\n2.63333,220.6\\n2.65000,218.2\\n2.66667,219.3\\n2.68333,219.4\\n2.70000,219.4\\n2.71667,220.4\\n2.73333,220.7\\n2.75000,220.2\\n2.76667,218.3\\n2.78333,219.1\\n2.80000,219.6\\n2.81667,219.9\\n2.83333,220.4\\n2.85000,220.8\\n2.86667,218.1\\n2.88333,218.2\\n2.90000,219.3\\n2.91667,219.5\\n2.93333,220.4\\n2.95000,220.7\\n2.96667,220.8\\n2.98333,218.2\\n3.00000,219.1\\n3.01667,219.9\\n3.03333,220.0\\n3.05000,220.3\\n3.06667,220.7\\n3.08333,218.0\\n3.10000,218.2\\n3.11667,218.9\\n3.13333,219.9\\n3.15000,219.8\\n3.16667,220.6\\n3.18333,220.7\\n3.20000,220.6\\n3.21667,218.1\\n3.23333,219.3\\n3.25000,220.2\\n3.26667,219.9\\n3.28333,220.7\\n3.30000,220.3\\n3.31667,218.3\\n3.33333,218.7\\n3.35000,219.6\\n3.36667,220.3\\n3.38333,220.0\\n3.40000,220.6\\n3.41667,218.3\\n3.43333,218.7\\n3.45000,219.1\\n3.46667,220.0\\n3.48333,220.2\\n3.50000,220.3\\n3.51667,218.6\\n3.53333,219.0\\n3.55000,218.6\\n3.56667,219.6\\n3.58333,220.2\\n3.60000,220.2\\n3.61667,220.4\\n3.63333,218.3\\n3.65000,219.1\\n3.66667,219.1\\n3.68333,219.6\\n3.70000,220.6\\n3.71667,220.0\\n3.73333,220.2\\n3.75000,218.3\\n3.76667,218.6\\n3.78333,219.0\\n3.80000,220.0\\n3.81667,220.6\\n3.83333,219.9\\n3.85000,218.0\\n3.86667,219.1\\n3.88333,219.1\\n3.90000,219.5\\n3.91667,220.4\\n3.93333,220.3\\n3.95000,219.9\\n3.96667,218.3\\n3.98333,219.3\\n4.00000,219.1\\n4.01667,220.0\\n4.03333,220.7\\n4.05000,220.6\\n4.06667,219.9\\n4.08333,219.0\\n4.10000,219.0\\n4.11667,219.5\\n4.13333,219.9\\n4.15000,220.4\\n4.16667,219.8\\n4.18333,218.0\\n4.20000,218.2\\n4.21667,219.3\\n4.23333,219.6\\n4.25000,220.3\\n4.26667,220.6\\n4.28333,219.5\\n4.30000,218.3\\n4.31667,218.9\\n4.33333,219.6\\n4.35000,219.8\\n4.36667,220.2\\n4.38333,218.9\\n4.40000,217.8\\n4.41667,218.7\\n4.43333,219.6\\n4.45000,220.2\\n4.46667,220.0\\n4.48333,220.6\\n4.50000,218.2\\n4.51667,218.5\\n4.53333,219.3\\n4.55000,219.8\\n4.56667,219.9\\n4.58333,219.9\\n4.60000,220.6\\n4.61667,218.3\\n4.63333,218.5\\n4.65000,219.3\\n4.66667,220.0\\n4.68333,220.2\\n4.70000,220.0\\n4.71667,218.3\\n4.73333,218.2\\n4.75000,218.7\\n4.76667,219.8\\n4.78333,220.2\\n4.80000,219.9\\n4.81667,220.2\\n4.83333,218.1\\n4.85000,219.0\\n4.86667,219.1\\n4.88333,220.2\\n4.90000,220.4\\n4.91667,220.0\\n4.93333,218.2\\n4.95000,218.3\\n4.96667,218.7\\n4.98333,219.6\\n5.00000,220.3\\n5.01667,220.6\\n5.03333,220.0\\n5.05000,218.2\\n5.06667,218.5\\n5.08333,219.1\\n5.10000,219.6\\n5.11667,220.3\\n5.13333,220.6\\n5.15000,219.4\\n5.16667,218.7\\n5.18333,219.0\\n5.20000,219.0\\n5.21667,219.4\\n5.23333,220.4\\n5.25000,220.0\\n5.26667,218.3\\n5.28333,218.6\\n5.30000,219.3\\n5.31667,218.9\\n5.33333,219.9\\n5.35000,220.4\\n5.36667,217.7\\n5.38333,218.6\\n5.40000,218.9\\n5.41667,219.4\\n5.43333,219.8\\n5.45000,220.4\\n5.46667,220.6\\n5.48333,217.8\\n5.50000,218.7\\n5.51667,219.3\\n5.53333,219.5\\n5.55000,219.6\\n5.56667,220.4\\n5.58333,220.4\\n5.60000,217.8\\n5.61667,218.7\\n5.63333,219.4\\n5.65000,219.6\\n5.66667,219.8\\n5.68333,220.4\\n5.70000,218.1\\n5.71667,218.3\\n5.73333,218.7\\n5.75000,219.6\\n5.76667,219.6\\n5.78333,219.9\\n5.80000,220.3\\n5.81667,217.7\\n5.83333,218.2\\n5.85000,219.4\\n5.86667,220.2\\n5.88333,219.8\\n5.90000,219.9\\n5.91667,218.1\\n5.93333,218.2\\n5.95000,218.3\\n5.96667,219.8\\n5.98333,220.2\\n6.00000,219.8\\n6.01667,219.9\\n6.03333,218.1\\n6.05000,218.3\\n6.06667,218.5\\n6.08333,220.2\\n6.10000,220.2\\n6.11667,219.8\\n6.13333,219.0\\n6.15000,218.7\\n6.16667,218.5\\n6.18333,219.1\\n6.20000,220.2\\n6.21667,220.4\\n6.23333,220.0\\n6.25000,218.2\\n6.26667,218.7\\n6.28333,218.7\\n6.30000,219.6\\n6.31667,220.2\\n6.33333,220.3\\n6.35000,218.0\\n6.36667,218.7\\n6.38333,218.5\\n6.40000,219.5\\n6.41667,220.0\\n6.43333,220.4\\n6.45000,219.8\\n6.46667,218.0\\n6.48333,218.9\\n6.50000,219.1\\n6.51667,219.1\\n6.53333,219.9\\n6.55000,220.4\\n6.56667,217.6\\n6.58333,217.8\\n6.60000,218.9\\n6.61667,219.0\\n6.63333,219.4\\n6.65000,220.3\\n6.66667,220.3\\n6.68333,217.4\\n6.70000,218.5\\n6.71667,219.4\\n6.73333,219.6\\n6.75000,219.8\\n6.76667,220.3\\n6.78333,220.2\\n6.80000,217.8\\n6.81667,218.9\\n6.83333,219.4\\n6.85000,219.4\\n6.86667,220.0\\n6.88333,219.9\\n6.90000,218.0\\n6.91667,218.3\\n6.93333,219.3\\n6.95000,219.8\\n6.96667,219.6\\n6.98333,219.9\\n7.00000,220.3\\n7.01667,218.1\\n7.03333,218.2\\n7.05000,219.4\\n7.06667,219.8\\n7.08333,219.8\\n7.10000,219.8\\n7.11667,218.5\\n7.13333,218.0\\n7.15000,218.1\\n7.16667,219.3\\n7.18333,220.0\\n7.20000,219.6\\n7.21667,219.8\\n7.23333,218.1\\n7.25000,218.2\\n7.26667,218.7\\n7.28333,220.0\\n7.30000,220.0\\n7.31667,219.8\\n7.33333,218.0\\n7.35000,218.7\\n7.36667,218.9\\n7.38333,219.8\\n7.40000,220.0\\n7.41667,219.6\\n7.43333,217.7\\n7.45000,218.1\\n7.46667,218.7\\n7.48333,219.1\\n7.50000,219.8\\n7.51667,220.0\\n7.53333,219.6\\n7.55000,217.4\\n7.56667,218.7\\n7.58333,218.9\\n7.60000,219.0\\n7.61667,220.0\\n7.63333,220.2\\n7.65000,219.8\\n7.66667,218.0\\n7.68333,218.7\\n7.70000,218.5\\n7.71667,219.6\\n7.73333,220.2\\n7.75000,220.3\\n7.76667,217.4\\n7.78333,218.1\\n7.80000,218.7\\n7.81667,219.1\\n7.83333,219.5\\n7.85000,220.2\\n7.86667,219.1\\n7.88333,218.0\\n7.90000,218.6\\n7.91667,219.3\\n7.93333,219.5\\n7.95000,219.6\\n7.96667,220.3\\n7.98333,218.9\\n8.00000,217.4\\n8.01667,218.5\\n8.03333,219.3\\n8.05000,219.6\\n8.06667,219.6\\n8.08333,217.8\\n8.10000,217.8\\n8.11667,218.1\\n8.13333,219.0\\n8.15000,219.1\\n8.16667,219.4\\n8.18333,219.9\\n8.20000,220.2\\n8.21667,217.8\\n8.23333,218.2\\n8.25000,219.3\\n8.26667,219.8\\n8.28333,219.5\\n8.30000,219.9\\n8.31667,218.0\\n8.33333,218.1\\n8.35000,219.0\\n8.36667,219.9\\n8.38333,219.5\\n8.40000,219.8\\n8.41667,217.8\\n8.43333,217.8\\n8.45000,218.1\\n8.46667,219.4\\n8.48333,219.8\\n8.50000,219.6\\n8.51667,219.8\\n8.53333,217.8\\n8.55000,218.6\\n8.56667,218.7\\n8.58333,219.3\\n8.60000,220.0\\n8.61667,219.6\\n8.63333,219.6\\n8.65000,218.1\\n8.66667,218.2\\n8.68333,218.7\\n8.70000,219.9\\n8.71667,220.2\\n8.73333,219.6\\n8.75000,217.7\\n8.76667,218.6\\n8.78333,218.6\\n8.80000,219.1\\n8.81667,220.0\\n8.83333,220.2\\n8.85000,218.6\\n8.86667,218.3\\n8.88333,218.9\\n8.90000,218.6\\n8.91667,219.5\\n8.93333,220.2\\n8.95000,220.2\\n8.96667,217.8\\n8.98333,218.3\\n9.00000,218.6\\n9.01667,218.1\\n9.03333,219.5\\n9.05000,220.2\\n9.06667,220.3\\n9.08333,217.4\\n9.10000,218.5\\n9.11667,218.9\\n9.13333,219.1\\n9.15000,219.9\\n9.16667,220.2\\n9.18333,217.3\\n9.20000,218.1\\n9.21667,218.5\\n9.23333,219.4\\n9.25000,219.4\\n9.26667,219.6\\n9.28333,220.2\\n9.30000,218.1\\n9.31667,218.3\\n9.33333,219.4\\n9.35000,219.6\\n9.36667,219.5\\n9.38333,220.0\\n9.40000,217.4\\n9.41667,218.1\\n9.43333,219.0\\n9.45000,219.8\\n9.46667,219.8\\n9.48333,219.4\\n9.50000,219.9\\n9.51667,217.8\\n9.53333,218.0\\n9.55000,219.0\\n9.56667,219.9\\n9.58333,219.5\\n9.60000,219.8\\n9.61667,217.8\\n9.63333,218.1\\n9.65000,218.2\\n9.66667,219.5\\n9.68333,220.0\\n9.70000,219.5\\n9.71667,219.1\\n9.73333,217.8\\n9.75000,217.6\\n9.76667,218.7\\n9.78333,219.5\\n9.80000,220.0\\n9.81667,219.5\\n9.83333,219.5\\n9.85000,218.3\\n9.86667,218.3\\n9.88333,219.4\\n9.90000,219.9\\n9.91667,219.9\\n9.93333,219.5\\n9.95000,217.7\\n9.96667,218.5\\n9.98333,218.5\\n10.00000,219.3\\n10.01667,219.8\\n10.03333,220.0\\n10.05000,219.5\\n10.06667,217.6\\n10.08333,218.5\\n10.10000,218.7\\n10.11667,219.3\\n10.13333,220.0\\n10.15000,219.4\\n10.16667,217.3\\n10.18333,218.3\\n10.20000,219.0\\n10.21667,218.7\\n10.23333,218.7\\n10.25000,220.2\\n10.26667,220.2\\n10.28333,218.2\\n10.30000,219.1\\n10.31667,218.7\\n10.33333,219.4\\n10.35000,220.0\\n10.36667,219.9\\n10.38333,217.3\\n10.40000,218.1\\n10.41667,219.0\\n10.43333,219.3\\n10.45000,219.4\\n10.46667,219.4\\n10.48333,217.3\\n10.50000,217.3\\n10.51667,217.3\\n10.53333,219.0\\n10.55000,219.1\\n10.56667,219.5\\n10.58333,219.5\\n10.60000,217.7\\n10.61667,217.8\\n10.63333,218.3\\n10.65000,219.4\\n10.66667,219.6\\n10.68333,219.4\\n10.70000,218.7\\n10.71667,217.6\\n10.73333,218.0\\n10.75000,219.0\\n10.76667,219.6\\n10.78333,219.1\\n10.80000,219.6\\n10.81667,217.8\\n10.83333,217.7\\n10.85000,218.2\\n10.86667,218.9\\n10.88333,219.4\\n10.90000,219.4\\n10.91667,219.4\\n10.93333,217.7\\n10.95000,218.5\\n10.96667,218.7\\n10.98333,219.5\\n11.00000,219.9\\n11.01667,219.4\\n11.03333,217.4\\n11.05000,217.7\\n11.06667,217.8\\n11.08333,218.7\\n11.10000,219.3\\n11.11667,219.9\\n11.13333,219.5\\n11.15000,217.4\\n11.16667,218.5\\n11.18333,218.5\\n11.20000,218.5\\n11.21667,219.9\\n11.23333,219.9\\n11.25000,217.3\\n11.26667,218.3\\n11.28333,218.3\\n11.30000,218.9\\n11.31667,219.8\\n11.33333,219.9\\n11.35000,219.3\\n11.36667,217.7\\n11.38333,218.5\\n11.40000,219.0\\n11.41667,218.7\\n11.43333,219.1\\n11.45000,219.9\\n11.46667,219.9\\n11.48333,219.9\\n11.50000,218.2\\n11.51667,218.2\\n11.53333,219.1\\n11.55000,219.1\\n11.56667,219.1\\n11.58333,217.1\\n11.60000,217.6\\n11.61667,218.5\\n11.63333,218.7\\n11.65000,219.4\\n11.66667,219.8\\n11.68333,218.3\\n11.70000,217.7\\n11.71667,218.1\\n11.73333,219.0\\n11.75000,219.4\\n11.76667,219.6\\n11.78333,219.6\\n11.80000,219.6\\n11.81667,217.8\\n11.83333,219.0\\n11.85000,219.5\\n11.86667,219.5\\n11.88333,219.8\\n11.90000,219.8\\n11.91667,217.4\\n11.93333,218.0\\n11.95000,218.6\\n11.96667,219.5\\n11.98333,219.3\\n12.00000,219.5\\n12.01667,217.6\\n12.03333,217.8\\n12.05000,218.1\\n12.06667,219.0\\n12.08333,219.1\\n12.10000,219.1\\n12.11667,219.6\\n12.13333,217.7\\n12.15000,218.2\\n12.16667,218.0\\n12.18333,219.0\\n12.20000,219.0\\n12.21667,219.3\\n12.23333,217.8\\n12.25000,218.3\\n12.26667,218.3\\n12.28333,219.4\\n12.30000,219.6\\n12.31667,219.4\\n12.33333,217.4\\n12.35000,218.0\\n12.36667,217.8\\n12.38333,218.9\\n12.40000,218.9\\n12.41667,219.8\\n12.43333,219.8\\n12.45000,217.2\\n12.46667,217.2\\n12.48333,217.2\\n12.50000,218.3\\n12.51667,219.4\\n12.53333,219.8\\n12.55000,219.8\\n12.56667,218.0\\n12.58333,218.3\\n12.60000,218.5\\n12.61667,219.0\\n12.63333,219.8\\n12.65000,219.9\\n12.66667,217.2\\n12.68333,218.0\\n12.70000,218.6\\n12.71667,219.0\\n12.73333,219.3\\n12.75000,219.3\\n12.76667,217.1\\n12.78333,217.2\\n12.80000,217.2\\n12.81667,218.7\\n12.83333,218.7\\n12.85000,219.4\\n12.86667,219.4\\n12.88333,217.2\\n12.90000,217.8\\n12.91667,218.1\\n12.93333,219.0\\n12.95000,218.7\\n12.96667,219.4\\n12.98333,219.8\\n13.00000,217.1\\n13.01667,217.6\\n13.03333,218.7\\n13.05000,219.4\\n13.06667,219.0\\n13.08333,219.0\\n13.10000,217.4\\n13.11667,217.4\\n13.13333,217.8\\n13.15000,217.8\\n13.16667,217.8\\n13.18333,219.1\\n13.20000,219.1\\n13.21667,217.7\\n13.23333,217.8\\n13.25000,219.1\\n13.26667,219.4\\n13.28333,219.0\\n13.30000,219.3\\n13.31667,217.4\\n13.33333,217.8\\n13.35000,218.5\\n13.36667,219.3\\n13.38333,219.3\\n13.40000,219.3\\n13.41667,219.3\\n13.43333,219.3\\n13.45000,218.2\\n13.46667,218.2\\n13.48333,218.3\\n13.50000,219.5\\n13.51667,219.5\\n13.53333,217.6\\n13.55000,218.1\\n13.56667,218.1\\n13.58333,218.3\\n13.60000,219.5\\n13.61667,219.8\\n13.63333,219.3\\n13.65000,217.4\\n13.66667,218.2\\n13.68333,218.3\\n13.70000,218.3\\n13.71667,218.3\\n13.73333,219.9\\n13.75000,219.1\\n13.76667,218.1\\n13.78333,218.1\\n13.80000,218.1\\n13.81667,218.9\\n13.83333,218.9\\n13.85000,219.6\\n13.86667,219.6\\n13.88333,218.1\\n13.90000,218.7\\n13.91667,218.5\\n13.93333,219.1\\n13.95000,219.8\\n13.96667,219.6\\n13.98333,217.1\\n14.00000,218.0\\n14.01667,218.9\\n14.03333,218.9\\n14.05000,219.4\\n14.06667,219.4\\n14.08333,219.4\\n14.10000,217.1\\n14.11667,217.1\\n14.13333,219.0\\n14.15000,219.0\\n14.16667,219.6\\n14.18333,219.6\\n14.20000,217.6\\n14.21667,218.1\\n14.23333,219.0\\n14.25000,218.9\\n14.26667,219.3\\n14.28333,219.1\\n14.30000,217.3\\n14.31667,217.6\\n14.33333,218.7\\n14.35000,219.3\\n14.36667,219.3\\n14.38333,219.1\\n14.40000,219.1\\n14.41667,217.3\\n14.43333,217.6\\n14.45000,218.6\\n14.46667,218.6\\n14.48333,219.3\\n14.50000,219.3\\n14.51667,219.3\\n14.53333,218.1\\n14.55000,217.7\\n14.56667,219.3\\n14.58333,219.5\\n14.60000,219.6\\n14.61667,219.4\\n14.63333,217.3\\n14.65000,217.7\\n14.66667,218.2\\n14.68333,219.1\\n14.70000,219.5\\n14.71667,219.6\\n14.73333,217.1\\n14.75000,217.1\\n14.76667,218.1\\n14.78333,218.1\\n14.80000,218.1\\n14.81667,219.5\\n14.83333,219.5\\n14.85000,219.5\\n14.86667,218.0\\n14.88333,218.1\\n14.90000,218.3\\n14.91667,219.5\\n14.93333,219.6\\n14.95000,219.1\\n14.96667,218.1\\n14.98333,218.2\\n\\n',\n", + " 'LC Status Trace(Pump B Pressure)': '\\nInterval(msec),1000\\n# of Points,900\\nStart Time(min),0.000\\nEnd Time(min),14.983\\nIntensity Units,kgf/cm2\\nIntensity Multiplier,1\\nR.Time (min),Intensity\\n0.00000,229.8\\n0.01667,229.8\\n0.03333,230.7\\n0.05000,230.7\\n0.06667,232.1\\n0.08333,234.6\\n0.10000,237.5\\n0.11667,241.5\\n0.13333,242.1\\n0.15000,240.1\\n0.16667,240.4\\n0.18333,239.1\\n0.20000,239.1\\n0.21667,239.7\\n0.23333,239.5\\n0.25000,238.6\\n0.26667,236.3\\n0.28333,237.2\\n0.30000,237.2\\n0.31667,237.3\\n0.33333,238.4\\n0.35000,238.4\\n0.36667,235.4\\n0.38333,235.8\\n0.40000,236.7\\n0.41667,236.2\\n0.43333,237.2\\n0.45000,238.0\\n0.46667,238.0\\n0.48333,235.4\\n0.50000,236.2\\n0.51667,236.4\\n0.53333,236.6\\n0.55000,237.5\\n0.56667,237.7\\n0.58333,237.3\\n0.60000,235.3\\n0.61667,235.9\\n0.63333,236.7\\n0.65000,236.8\\n0.66667,237.1\\n0.68333,236.9\\n0.70000,234.7\\n0.71667,235.5\\n0.73333,236.3\\n0.75000,236.8\\n0.76667,236.9\\n0.78333,237.3\\n0.80000,236.2\\n0.81667,235.3\\n0.83333,235.4\\n0.85000,236.4\\n0.86667,236.4\\n0.88333,237.2\\n0.90000,237.5\\n0.91667,235.0\\n0.93333,235.3\\n0.95000,236.2\\n0.96667,236.7\\n0.98333,236.6\\n1.00000,236.9\\n1.01667,235.1\\n1.03333,235.1\\n1.05000,235.1\\n1.06667,236.3\\n1.08333,237.1\\n1.10000,236.6\\n1.11667,236.9\\n1.13333,234.9\\n1.15000,235.1\\n1.16667,235.6\\n1.18333,236.6\\n1.20000,236.9\\n1.21667,236.4\\n1.23333,236.7\\n1.25000,234.7\\n1.26667,235.4\\n1.28333,236.0\\n1.30000,236.0\\n1.31667,236.9\\n1.33333,236.3\\n1.35000,236.3\\n1.36667,235.4\\n1.38333,234.9\\n1.40000,235.8\\n1.41667,236.3\\n1.43333,236.7\\n1.45000,235.4\\n1.46667,233.9\\n1.48333,235.0\\n1.50000,235.0\\n1.51667,235.4\\n1.53333,236.6\\n1.55000,236.0\\n1.56667,233.8\\n1.58333,234.7\\n1.60000,235.1\\n1.61667,235.1\\n1.63333,235.9\\n1.65000,236.8\\n1.66667,236.8\\n1.68333,235.0\\n1.70000,235.4\\n1.71667,235.8\\n1.73333,236.2\\n1.75000,237.3\\n1.76667,237.7\\n1.78333,235.0\\n1.80000,236.0\\n1.81667,236.7\\n1.83333,237.1\\n1.85000,237.2\\n1.86667,238.1\\n1.88333,235.4\\n1.90000,235.3\\n1.91667,236.4\\n1.93333,236.8\\n1.95000,237.1\\n1.96667,237.7\\n1.98333,238.0\\n2.00000,235.6\\n2.01667,235.6\\n2.03333,236.7\\n2.05000,237.1\\n2.06667,236.8\\n2.08333,237.5\\n2.10000,237.6\\n2.11667,234.7\\n2.13333,235.5\\n2.15000,236.2\\n2.16667,236.9\\n2.18333,236.7\\n2.20000,236.7\\n2.21667,237.1\\n2.23333,234.9\\n2.25000,235.4\\n2.26667,235.9\\n2.28333,236.7\\n2.30000,236.7\\n2.31667,236.7\\n2.33333,234.7\\n2.35000,234.9\\n2.36667,235.6\\n2.38333,236.4\\n2.40000,236.8\\n2.41667,236.4\\n2.43333,235.6\\n2.45000,235.0\\n2.46667,235.0\\n2.48333,236.4\\n2.50000,236.8\\n2.51667,236.9\\n2.53333,236.6\\n2.55000,234.7\\n2.56667,235.4\\n2.58333,235.3\\n2.60000,236.2\\n2.61667,236.7\\n2.63333,236.0\\n2.65000,234.3\\n2.66667,234.6\\n2.68333,235.3\\n2.70000,235.4\\n2.71667,236.6\\n2.73333,236.8\\n2.75000,236.3\\n2.76667,234.3\\n2.78333,235.1\\n2.80000,235.5\\n2.81667,236.0\\n2.83333,236.4\\n2.85000,236.9\\n2.86667,234.1\\n2.88333,235.1\\n2.90000,235.4\\n2.91667,235.5\\n2.93333,236.2\\n2.95000,236.8\\n2.96667,236.9\\n2.98333,233.9\\n3.00000,235.3\\n3.01667,236.0\\n3.03333,236.0\\n3.05000,236.3\\n3.06667,236.9\\n3.08333,233.9\\n3.10000,234.3\\n3.11667,235.3\\n3.13333,236.2\\n3.15000,235.9\\n3.16667,236.3\\n3.18333,236.8\\n3.20000,236.7\\n3.21667,234.3\\n3.23333,235.3\\n3.25000,236.2\\n3.26667,236.0\\n3.28333,236.9\\n3.30000,236.9\\n3.31667,234.3\\n3.33333,234.6\\n3.35000,235.8\\n3.36667,236.3\\n3.38333,235.9\\n3.40000,236.7\\n3.41667,235.9\\n3.43333,234.7\\n3.45000,235.1\\n3.46667,235.6\\n3.48333,236.2\\n3.50000,236.3\\n3.51667,236.7\\n3.53333,234.5\\n3.55000,234.6\\n3.56667,235.6\\n3.58333,236.2\\n3.60000,235.9\\n3.61667,236.3\\n3.63333,235.0\\n3.65000,235.1\\n3.66667,235.3\\n3.68333,236.3\\n3.70000,236.7\\n3.71667,236.2\\n3.73333,236.2\\n3.75000,234.5\\n3.76667,234.9\\n3.78333,235.1\\n3.80000,236.0\\n3.81667,236.7\\n3.83333,236.2\\n3.85000,234.1\\n3.86667,235.1\\n3.88333,235.1\\n3.90000,235.4\\n3.91667,236.6\\n3.93333,236.7\\n3.95000,236.2\\n3.96667,234.6\\n3.98333,235.3\\n4.00000,235.3\\n4.01667,235.9\\n4.03333,236.7\\n4.05000,236.8\\n4.06667,233.8\\n4.08333,235.1\\n4.10000,235.3\\n4.11667,235.4\\n4.13333,236.6\\n4.15000,236.7\\n4.16667,235.6\\n4.18333,233.8\\n4.20000,234.5\\n4.21667,235.1\\n4.23333,235.6\\n4.25000,236.4\\n4.26667,236.6\\n4.28333,233.7\\n4.30000,233.7\\n4.31667,234.9\\n4.33333,235.8\\n4.35000,235.9\\n4.36667,236.6\\n4.38333,236.7\\n4.40000,233.8\\n4.41667,234.6\\n4.43333,235.3\\n4.45000,236.2\\n4.46667,235.8\\n4.48333,236.7\\n4.50000,234.6\\n4.51667,234.1\\n4.53333,234.6\\n4.55000,235.9\\n4.56667,236.0\\n4.58333,236.0\\n4.60000,236.6\\n4.61667,234.5\\n4.63333,234.5\\n4.65000,235.0\\n4.66667,236.3\\n4.68333,236.0\\n4.70000,236.2\\n4.71667,234.3\\n4.73333,234.3\\n4.75000,234.7\\n4.76667,235.8\\n4.78333,236.3\\n4.80000,236.0\\n4.81667,236.3\\n4.83333,234.2\\n4.85000,234.5\\n4.86667,235.0\\n4.88333,236.2\\n4.90000,236.6\\n4.91667,236.0\\n4.93333,236.3\\n4.95000,234.3\\n4.96667,234.6\\n4.98333,235.9\\n5.00000,236.2\\n5.01667,236.6\\n5.03333,236.0\\n5.05000,234.2\\n5.06667,235.0\\n5.08333,235.0\\n5.10000,235.8\\n5.11667,236.6\\n5.13333,236.2\\n5.15000,235.3\\n5.16667,234.6\\n5.1833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,236.0\\n10.38333,233.2\\n10.40000,234.1\\n10.41667,234.5\\n10.43333,235.4\\n10.45000,235.3\\n10.46667,235.8\\n10.48333,232.8\\n10.50000,233.2\\n10.51667,234.1\\n10.53333,235.0\\n10.55000,235.1\\n10.56667,235.6\\n10.58333,235.9\\n10.60000,233.7\\n10.61667,233.9\\n10.63333,234.3\\n10.65000,235.5\\n10.66667,235.1\\n10.68333,235.9\\n10.70000,235.5\\n10.71667,233.6\\n10.73333,233.9\\n10.75000,234.9\\n10.76667,235.8\\n10.78333,235.4\\n10.80000,235.6\\n10.81667,233.6\\n10.83333,234.1\\n10.85000,234.3\\n10.86667,235.6\\n10.88333,235.5\\n10.90000,235.6\\n10.91667,234.7\\n10.93333,234.3\\n10.95000,233.9\\n10.96667,234.7\\n10.98333,235.9\\n11.00000,236.0\\n11.01667,235.5\\n11.03333,233.6\\n11.05000,234.3\\n11.06667,234.1\\n11.08333,235.4\\n11.10000,235.4\\n11.11667,235.9\\n11.13333,235.5\\n11.15000,233.7\\n11.16667,234.5\\n11.18333,234.5\\n11.20000,234.7\\n11.21667,235.8\\n11.23333,235.1\\n11.25000,233.3\\n11.26667,233.6\\n11.28333,234.5\\n11.30000,234.6\\n11.31667,235.3\\n11.33333,235.9\\n11.35000,235.4\\n11.36667,233.6\\n11.38333,234.2\\n11.40000,234.9\\n11.41667,234.7\\n11.43333,235.8\\n11.45000,236.0\\n11.46667,235.3\\n11.48333,234.2\\n11.50000,234.5\\n11.51667,235.0\\n11.53333,235.0\\n11.55000,235.8\\n11.56667,235.5\\n11.58333,233.0\\n11.60000,234.1\\n11.61667,235.0\\n11.63333,235.1\\n11.65000,235.4\\n11.66667,236.0\\n11.68333,233.2\\n11.70000,233.7\\n11.71667,234.9\\n11.73333,235.0\\n11.75000,235.1\\n11.76667,235.9\\n11.78333,236.0\\n11.80000,233.2\\n11.81667,233.9\\n11.83333,234.7\\n11.85000,235.4\\n11.86667,235.5\\n11.88333,236.2\\n11.90000,233.8\\n11.91667,233.8\\n11.93333,234.7\\n11.95000,235.1\\n11.96667,235.8\\n11.98333,235.5\\n12.00000,235.9\\n12.01667,233.6\\n12.03333,233.8\\n12.05000,234.5\\n12.06667,235.0\\n12.08333,235.1\\n12.10000,235.1\\n12.11667,235.8\\n12.13333,233.8\\n12.15000,234.2\\n12.16667,235.0\\n12.18333,235.5\\n12.20000,235.9\\n12.21667,235.4\\n12.23333,233.6\\n12.25000,234.5\\n12.26667,233.9\\n12.28333,235.5\\n12.30000,235.8\\n12.31667,235.9\\n12.33333,235.0\\n12.35000,233.8\\n12.36667,234.2\\n12.38333,234.5\\n12.40000,235.4\\n12.41667,235.8\\n12.43333,235.4\\n12.45000,233.2\\n12.46667,233.8\\n12.48333,234.3\\n12.50000,234.9\\n12.51667,235.3\\n12.53333,235.9\\n12.55000,233.3\\n12.56667,233.9\\n12.58333,234.3\\n12.60000,234.5\\n12.61667,235.3\\n12.63333,235.9\\n12.65000,235.9\\n12.66667,233.2\\n12.68333,234.3\\n12.70000,234.5\\n12.71667,234.9\\n12.73333,235.1\\n12.75000,235.9\\n12.76667,233.2\\n12.78333,233.0\\n12.80000,234.2\\n12.81667,235.1\\n12.83333,234.7\\n12.85000,235.5\\n12.86667,236.0\\n12.88333,233.0\\n12.90000,233.9\\n12.91667,234.7\\n12.93333,234.6\\n12.95000,235.0\\n12.96667,235.6\\n12.98333,233.6\\n13.00000,233.0\\n13.01667,233.9\\n13.03333,234.6\\n13.05000,235.4\\n13.06667,235.1\\n13.08333,235.8\\n13.10000,235.8\\n13.11667,233.4\\n13.13333,233.9\\n13.15000,234.6\\n13.16667,235.1\\n13.18333,235.3\\n13.20000,235.5\\n13.21667,233.6\\n13.23333,233.8\\n13.25000,234.5\\n13.26667,235.4\\n13.28333,235.1\\n13.30000,235.4\\n13.31667,235.0\\n13.33333,233.7\\n13.35000,233.9\\n13.36667,234.5\\n13.38333,235.6\\n13.40000,235.3\\n13.41667,235.3\\n13.43333,233.6\\n13.45000,234.2\\n13.46667,233.8\\n13.48333,235.0\\n13.50000,235.8\\n13.51667,235.3\\n13.53333,233.2\\n13.55000,233.8\\n13.56667,233.9\\n13.58333,234.3\\n13.60000,235.4\\n13.61667,235.9\\n13.63333,235.3\\n13.65000,233.3\\n13.66667,234.3\\n13.68333,234.3\\n13.70000,235.0\\n13.71667,235.8\\n13.73333,235.9\\n13.75000,232.9\\n13.76667,234.1\\n13.78333,234.2\\n13.80000,234.3\\n13.81667,235.4\\n13.83333,235.6\\n13.85000,235.6\\n13.86667,233.0\\n13.88333,234.2\\n13.90000,234.6\\n13.91667,234.9\\n13.93333,235.5\\n13.95000,235.8\\n13.96667,232.9\\n13.98333,233.8\\n14.00000,234.2\\n14.01667,234.9\\n14.03333,234.9\\n14.05000,235.4\\n14.06667,235.8\\n14.08333,233.2\\n14.10000,233.2\\n14.11667,234.1\\n14.13333,235.0\\n14.15000,235.0\\n14.16667,235.6\\n14.18333,235.6\\n14.20000,233.4\\n14.21667,233.7\\n14.23333,234.7\\n14.25000,234.9\\n14.26667,235.0\\n14.28333,235.8\\n14.30000,233.4\\n14.31667,233.4\\n14.33333,234.1\\n14.35000,235.0\\n14.36667,235.5\\n14.38333,235.1\\n14.40000,234.7\\n14.41667,233.4\\n14.43333,233.4\\n14.45000,234.6\\n14.46667,235.1\\n14.48333,235.1\\n14.50000,235.5\\n14.51667,234.1\\n14.53333,234.2\\n14.55000,233.9\\n14.56667,235.1\\n14.58333,235.5\\n14.60000,235.1\\n14.61667,233.4\\n14.63333,233.4\\n14.65000,233.4\\n14.66667,234.5\\n14.68333,235.1\\n14.70000,235.6\\n14.71667,235.3\\n14.73333,233.3\\n14.75000,234.1\\n14.76667,234.1\\n14.78333,234.5\\n14.80000,235.5\\n14.81667,235.4\\n14.83333,235.3\\n14.85000,233.6\\n14.86667,234.2\\n14.88333,234.5\\n14.90000,235.0\\n14.91667,235.6\\n14.93333,235.1\\n14.95000,232.9\\n14.96667,234.2\\n14.98333,233.9\\n\\n',\n", + " 'LC Status Trace(Sample Cooler Temp.)': '\\nInterval(msec),1000\\n# of Points,900\\nStart Time(min),0.000\\nEnd Time(min),14.983\\nIntensity Units,C\\nIntensity Multiplier,1\\nR.Time (min),Intensity\\n0.00000,20.27\\n0.01667,20.27\\n0.03333,20.27\\n0.05000,20.27\\n0.06667,20.29\\n0.08333,20.29\\n0.10000,20.29\\n0.11667,20.29\\n0.13333,20.29\\n0.15000,20.29\\n0.16667,20.29\\n0.18333,20.29\\n0.20000,20.28\\n0.21667,20.28\\n0.23333,20.28\\n0.25000,20.28\\n0.26667,20.28\\n0.28333,20.28\\n0.30000,20.28\\n0.31667,20.28\\n0.33333,20.28\\n0.35000,20.28\\n0.36667,20.28\\n0.38333,20.27\\n0.40000,20.27\\n0.41667,20.27\\n0.43333,20.27\\n0.45000,20.27\\n0.46667,20.27\\n0.48333,20.27\\n0.50000,20.27\\n0.51667,20.27\\n0.53333,20.27\\n0.55000,20.27\\n0.56667,20.27\\n0.58333,20.27\\n0.60000,20.27\\n0.61667,20.27\\n0.63333,20.27\\n0.65000,20.27\\n0.66667,20.27\\n0.68333,20.27\\n0.70000,20.27\\n0.71667,20.27\\n0.73333,20.27\\n0.75000,20.27\\n0.76667,20.27\\n0.78333,20.27\\n0.80000,20.27\\n0.81667,20.27\\n0.83333,20.27\\n0.85000,20.27\\n0.86667,20.31\\n0.88333,20.31\\n0.90000,20.31\\n0.91667,20.31\\n0.93333,20.31\\n0.95000,20.31\\n0.96667,20.31\\n0.98333,20.31\\n1.00000,20.31\\n1.01667,20.31\\n1.03333,20.29\\n1.05000,20.29\\n1.06667,20.29\\n1.08333,20.29\\n1.10000,20.29\\n1.11667,20.29\\n1.13333,20.29\\n1.15000,20.29\\n1.16667,20.29\\n1.18333,20.29\\n1.20000,20.31\\n1.21667,20.31\\n1.23333,20.31\\n1.25000,20.31\\n1.26667,20.31\\n1.28333,20.31\\n1.30000,20.31\\n1.31667,20.31\\n1.33333,20.31\\n1.35000,20.31\\n1.36667,20.31\\n1.38333,20.29\\n1.40000,20.29\\n1.41667,20.29\\n1.43333,20.29\\n1.45000,20.29\\n1.46667,20.29\\n1.48333,20.29\\n1.50000,20.29\\n1.51667,20.29\\n1.53333,20.29\\n1.55000,20.29\\n1.56667,20.29\\n1.58333,20.29\\n1.60000,20.29\\n1.61667,20.29\\n1.63333,20.29\\n1.65000,20.29\\n1.66667,20.29\\n1.68333,20.29\\n1.70000,20.32\\n1.71667,20.32\\n1.73333,20.32\\n1.75000,20.32\\n1.76667,20.32\\n1.78333,20.32\\n1.80000,20.32\\n1.81667,20.32\\n1.83333,20.32\\n1.85000,20.32\\n1.86667,20.29\\n1.88333,20.29\\n1.90000,20.29\\n1.91667,20.29\\n1.93333,20.29\\n1.95000,20.29\\n1.96667,20.29\\n1.98333,20.29\\n2.00000,20.29\\n2.01667,20.29\\n2.03333,20.32\\n2.05000,20.32\\n2.06667,20.32\\n2.08333,20.32\\n2.10000,20.32\\n2.11667,20.32\\n2.13333,20.32\\n2.15000,20.32\\n2.16667,20.32\\n2.18333,20.32\\n2.20000,20.32\\n2.21667,20.32\\n2.23333,20.32\\n2.25000,20.32\\n2.26667,20.32\\n2.28333,20.32\\n2.30000,20.32\\n2.31667,20.32\\n2.33333,20.32\\n2.35000,20.32\\n2.36667,20.32\\n2.38333,20.32\\n2.40000,20.32\\n2.41667,20.32\\n2.43333,20.32\\n2.45000,20.32\\n2.46667,20.32\\n2.48333,20.32\\n2.50000,20.32\\n2.51667,20.32\\n2.53333,20.29\\n2.55000,20.29\\n2.56667,20.29\\n2.58333,20.29\\n2.60000,20.29\\n2.61667,20.29\\n2.63333,20.29\\n2.65000,20.29\\n2.66667,20.29\\n2.68333,20.29\\n2.70000,20.35\\n2.71667,20.35\\n2.73333,20.35\\n2.75000,20.35\\n2.76667,20.35\\n2.78333,20.35\\n2.80000,20.35\\n2.81667,20.35\\n2.83333,20.35\\n2.85000,20.35\\n2.86667,20.36\\n2.88333,20.36\\n2.90000,20.36\\n2.91667,20.36\\n2.93333,20.36\\n2.95000,20.36\\n2.96667,20.36\\n2.98333,20.36\\n3.00000,20.36\\n3.01667,20.36\\n3.03333,20.34\\n3.05000,20.34\\n3.06667,20.34\\n3.08333,20.34\\n3.10000,20.34\\n3.11667,20.34\\n3.13333,20.34\\n3.15000,20.34\\n3.16667,20.34\\n3.18333,20.34\\n3.20000,20.33\\n3.21667,20.33\\n3.23333,20.33\\n3.25000,20.33\\n3.26667,20.33\\n3.28333,20.33\\n3.30000,20.33\\n3.31667,20.33\\n3.33333,20.33\\n3.35000,20.33\\n3.36667,20.33\\n3.38333,20.33\\n3.40000,20.33\\n3.41667,20.33\\n3.43333,20.33\\n3.45000,20.33\\n3.46667,20.33\\n3.48333,20.33\\n3.50000,20.33\\n3.51667,20.33\\n3.53333,20.36\\n3.55000,20.36\\n3.56667,20.36\\n3.58333,20.36\\n3.60000,20.36\\n3.61667,20.36\\n3.63333,20.36\\n3.65000,20.36\\n3.66667,20.36\\n3.68333,20.36\\n3.70000,20.36\\n3.71667,20.36\\n3.73333,20.36\\n3.75000,20.36\\n3.76667,20.36\\n3.78333,20.36\\n3.80000,20.36\\n3.81667,20.36\\n3.83333,20.36\\n3.85000,20.36\\n3.86667,20.33\\n3.88333,20.33\\n3.90000,20.33\\n3.91667,20.33\\n3.93333,20.33\\n3.95000,20.33\\n3.96667,20.33\\n3.98333,20.33\\n4.00000,20.33\\n4.01667,20.33\\n4.03333,20.35\\n4.05000,20.35\\n4.06667,20.35\\n4.08333,20.35\\n4.10000,20.35\\n4.11667,20.35\\n4.13333,20.35\\n4.15000,20.35\\n4.16667,20.35\\n4.18333,20.35\\n4.20000,20.34\\n4.21667,20.34\\n4.23333,20.34\\n4.25000,20.34\\n4.26667,20.34\\n4.28333,20.34\\n4.30000,20.34\\n4.31667,20.34\\n4.33333,20.34\\n4.35000,20.34\\n4.36667,20.36\\n4.38333,20.36\\n4.40000,20.36\\n4.41667,20.36\\n4.43333,20.36\\n4.45000,20.36\\n4.46667,20.36\\n4.48333,20.36\\n4.50000,20.36\\n4.51667,20.36\\n4.53333,20.35\\n4.55000,20.35\\n4.56667,20.35\\n4.58333,20.35\\n4.60000,20.35\\n4.61667,20.35\\n4.63333,20.35\\n4.65000,20.35\\n4.66667,20.35\\n4.68333,20.35\\n4.70000,20.36\\n4.71667,20.36\\n4.73333,20.36\\n4.75000,20.36\\n4.76667,20.36\\n4.78333,20.36\\n4.80000,20.36\\n4.81667,20.36\\n4.83333,20.36\\n4.85000,20.36\\n4.86667,20.37\\n4.88333,20.37\\n4.90000,20.37\\n4.91667,20.37\\n4.93333,20.37\\n4.95000,20.37\\n4.96667,20.37\\n4.98333,20.37\\n5.00000,20.37\\n5.01667,20.37\\n5.03333,20.40\\n5.05000,20.40\\n5.06667,20.40\\n5.08333,20.40\\n5.10000,20.40\\n5.11667,20.40\\n5.13333,20.40\\n5.15000,20.40\\n5.16667,20.40\\n5.1833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+ " 'Fraction Collection Report': '\\n# of Fractions,0\\n\\n'}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "path = \"/Users/max/Documents/training_course/martina/Output-sample 0.txt\"\n", + "\n", + "sections = ShimadzuReader(path=path).parse_sections()\n", + "\n", + "sections" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from io import StringIO\n", + "from tokenize import String\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "tab = sections[\"LC Chromatogram(Detector A-Ch1)\"]\n", + "\n", + "pd.read_csv(StringIO(tab), skiprows=8).plot(x=\"R.Time (min)\")\n", + "plt.vlines(8.06, -20000, 400000, color=\"red\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "\n", + "def parse_meta(self, sections: dict, section_name: str, nrows: int) -> dict:\n", + " \"\"\"Parse the metadata in a section as keys-values.\"\"\"\n", + " meta_table = pd.read_table(\n", + " StringIO(sections[section_name]), nrows=nrows, header=None\n", + " )\n", + " meta = {row[0]: row[1] for _, row in meta_table.iterrows()}\n", + "\n", + " return meta\n", + "\n", + "\n", + "def parse_table(\n", + " self, sections: dict, section_name: str, skiprows: int = 1\n", + ") -> Optional[pd.DataFrame]:\n", + " \"\"\"Parse the data in a section as a table.\"\"\"\n", + " table_str = sections[section_name]\n", + "\n", + " # Count number of non-empty lines\n", + " num_lines = len([l for l in re.split(\"[\\r\\n]+\", table_str) if len(l)])\n", + "\n", + " if num_lines <= 1:\n", + " return None\n", + "\n", + " return pd.read_table(StringIO(table_str), header=1, skiprows=skiprows)\n", + "\n", + "\n", + "def get_compound_table(\n", + " sections: dict, detector: str = \"A\"\n", + "):\n", + " section_name = f\"Compound Results(Detector {detector})\"\n", + " meta = parse_meta(sections, section_name, 1)\n", + " table = parse_table(sections, section_name, skiprows=1)\n", + "\n", + " assert (\n", + " table is None or int(meta[\"# of IDs\"]) == table.shape[0]\n", + " ), \"Declared number of compounds and table size differ\"\n", + "\n", + " return table" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'dict' object has no attribute 'get_compound_table'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43msections\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_compound_table\u001b[49m(sections, detector\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mB\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 2\u001b[0m compounds[[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mName\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConc.\u001b[39m\u001b[38;5;124m\"\u001b[39m]]\u001b[38;5;241m.\u001b[39mto_dict()\n", + "\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'get_compound_table'" + ] + } + ], + "source": [ + "sections.get_compound_table(sections, detector=\"B\")\n", + "compounds[[\"Name\", \"Conc.\"]].to_dict()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[Header]\n", + "Application Name,LCsolution\n", + "Version,1.25\n", + "Data File Name,C:\\LabSolutions\\Data\\aldolaze\\Martina\\aldolna adicija\\batch_21022012\\EtAc\\0.lcd\n", + "Output Date,12.12.2023.\n", + "Output Time,11:15:12\n", + "\n", + "[File Information]\n", + "Type,Data File\n", + "Generated,21.2.2012. 13:16:32\n", + "Generated by,Admin\n", + "Modified,21.2.2012. 13:33:38\n", + "Modified by,Admin\n", + "\n", + "[Sample Information]\n", + "Operator Name,Admin\n", + "Acquired,21.2.2012. 13:16:57\n", + "Sample Type,0:Unknown\n", + "Level,0\n", + "Sample Name,0\n", + "Sample ID,\n", + "ISTD Amount 1,1\n", + "ISTD Amount 2,1\n", + "ISTD Amount 3,1\n", + "ISTD Amount 4,1\n", + "ISTD Amount 5,1\n", + "ISTD Amount 6,1\n", + "ISTD Amount 7,1\n", + "ISTD Amount 8,1\n", + "ISTD Amount 9,1\n", + "ISTD Amount 10,1\n", + "ISTD Amount 11,1\n", + "ISTD Amount 12,1\n", + "ISTD Amount 13,1\n", + "ISTD Amount 14,1\n", + "ISTD Amount 15,1\n", + "ISTD Amount 16,1\n", + "ISTD Amount 17,1\n", + "ISTD Amount 18,1\n", + "ISTD Amount 19,1\n", + "ISTD Amount 20,1\n", + "ISTD Amount 21,1\n", + "ISTD Amount 22,1\n", + "ISTD Amount 23,1\n", + "ISTD Amount 24,1\n", + "ISTD Amount 25,1\n", + "ISTD Amount 26,1\n", + "ISTD Amount 27,1\n", + "ISTD Amount 28,1\n", + "ISTD Amount 29,1\n", + "ISTD Amount 30,1\n", + "ISTD Amount 31,1\n", + "ISTD Amount 32,1\n", + "Sample Amount,1\n", + "Dilution Factor,1\n", + "Vial#,1\n", + "Injection Volume,20\n", + "\n", + "[Original Files]\n", + "Data File,C:\\LabSolutions\\Data\\aldolaze\\Martina\\aldolna adicija\\batch_21022012\\EtAc\\0.lcd\n", + "Method File,C:\\LabSolutions\\Data\\aldolaze\\metoda3_2eluenta.lcm\n", + "Batch File,C:\\LabSolutions\\Data\\aldolaze\\Martina\\baždarci\\aldol-aldehid-01022012\\lista.lcb\n", + "Report Format File,C:\\LabSolutions\\LCsolution\\System\\Default.lcr\n", + "Tuning File,\n", + "\n", + "[File Description]\n", + "\n", + "\n", + "[Configuration]\n", + "# of Detectors,2\n", + "Detector ID,Detector A,AD2\n", + "Detector Name,Detector A,AD2\n", + "# of Channels,1,1\n", + "\n", + "[Peak Table(Detector A-Ch1)]\n", + "# of Peaks,14\n", + "Peak#,R.Time,I.Time,F.Time,Area,Height,A/H,Conc.,Mark,ID#,Name,k',Plate #,Plate Ht.,Tailing,Resolution,Sep.Factor,Conc. %,Norm Conc.\n", + "1,0.143,0.017,0.342,1278,107,11.9230,0.0000, ,,,0.000,4,41558.735,1.160,0.000,0.000,0.0000,0.0000\n", + "2,2.677,2.600,2.842,7633,868,8.7930,0.0000, ,,,17.675,2267,66.156,1.540,9.621,0.000,0.0000,0.0000\n", + "3,3.113,2.867,3.492,74069,3235,22.8950,0.0000, ,,,20.715,284,528.740,0.000,0.904,1.172,0.0000,0.0000\n", + "4,3.674,3.492,4.225,62448,1896,32.9390,0.0000, V ,,,24.632,195,767.696,0.000,0.627,1.189,0.0000,0.0000\n", + "5,4.541,4.225,4.858,61821,2075,29.7890,0.0000, V ,,,30.681,11,13168.368,0.000,0.270,1.246,0.0000,0.0000\n", + "6,5.264,4.858,6.025,591150,23289,25.3830,0.0000, V ,,,35.719,1559,96.223,0.000,0.244,1.164,0.0000,0.0000\n", + "7,6.234,6.025,6.417,69898,3040,22.9950,0.0000, V ,,,42.488,8,18539.786,0.000,0.209,1.189,0.0000,0.0000\n", + "8,6.570,6.417,6.708,51229,2962,17.2940,0.0000, V ,,,44.832,6,27270.488,0.000,0.034,1.055,0.0000,0.0000\n", + "9,7.099,6.708,7.442,271461,9085,29.8790,0.0000, V ,,,48.524,1106,135.634,0.000,0.088,1.082,0.0000,0.0000\n", + "10,8.063,7.442,8.950,2838883,74297,38.2100,0.0000, V ,1,RT8.063,55.243,1156,129.804,0.000,1.069,1.138,0.0000,0.0000\n", + "11,9.083,8.950,10.367,458569,7811,58.7060,0.0000, V ,,,62.362,26,5780.190,0.000,0.253,1.129,0.0000,0.0000\n", + "12,10.392,10.367,11.067,150804,3848,39.1900,0.0000, V ,,,71.492,1,157400.235,0.000,0.053,1.146,0.0000,0.0000\n", + 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"13.80000,-522\n", + "13.80833,-530\n", + "13.81667,-536\n", + "13.82500,-540\n", + "13.83333,-543\n", + "13.84167,-547\n", + "13.85000,-552\n", + "13.85833,-557\n", + "13.86667,-563\n", + "13.87500,-567\n", + "13.88333,-575\n", + "13.89167,-585\n", + "13.90000,-596\n", + "13.90833,-606\n", + "13.91667,-614\n", + "13.92500,-620\n", + "13.93333,-626\n", + "13.94167,-631\n", + "13.95000,-634\n", + "13.95833,-641\n", + "13.96667,-648\n", + "13.97500,-655\n", + "13.98333,-664\n", + "13.99167,-673\n", + "14.00000,-684\n", + "14.00833,-693\n", + "14.01667,-700\n", + "14.02500,-710\n", + "14.03333,-719\n", + "14.04167,-726\n", + "14.05000,-730\n", + "14.05833,-737\n", + "14.06667,-743\n", + "14.07500,-748\n", + "14.08333,-754\n", + "14.09167,-759\n", + "14.10000,-766\n", + "14.10833,-772\n", + "14.11667,-780\n", + "14.12500,-786\n", + "14.13333,-791\n", + "14.14167,-796\n", + "14.15000,-797\n", + "14.15833,-799\n", + "14.16667,-800\n", + "14.17500,-804\n", + "14.18333,-809\n", + "14.19167,-815\n", + "14.20000,-820\n", + "14.20833,-825\n", + "14.21667,-831\n", + "14.22500,-841\n", + "14.23333,-851\n", + "14.24167,-857\n", + "14.25000,-862\n", + "14.25833,-866\n", + "14.26667,-868\n", + "14.27500,-873\n", + "14.28333,-878\n", + "14.29167,-881\n", + "14.30000,-887\n", + "14.30833,-894\n", + "14.31667,-898\n", + "14.32500,-906\n", + "14.33333,-916\n", + "14.34167,-923\n", + "14.35000,-929\n", + "14.35833,-934\n", + "14.36667,-940\n", + "14.37500,-945\n", + "14.38333,-950\n", + "14.39167,-951\n", + "14.40000,-955\n", + "14.40833,-961\n", + "14.41667,-969\n", + "14.42500,-975\n", + "14.43333,-980\n", + "14.44167,-985\n", + "14.45000,-993\n", + "14.45833,-1003\n", + "14.46667,-1010\n", + "14.47500,-1013\n", + "14.48333,-1017\n", + "14.49167,-1020\n", + "14.50000,-1022\n", + "14.50833,-1027\n", + "14.51667,-1035\n", + "14.52500,-1045\n", + "14.53333,-1054\n", + "14.54167,-1064\n", + "14.55000,-1074\n", + "14.55833,-1085\n", + "14.56667,-1095\n", + "14.57500,-1102\n", + "14.58333,-1108\n", + "14.59167,-1112\n", + "14.60000,-1116\n", + "14.60833,-1122\n", + "14.61667,-1126\n", + "14.62500,-1129\n", + "14.63333,-1132\n", + "14.64167,-1134\n", + "14.65000,-1136\n", + "14.65833,-1138\n", + "14.66667,-1139\n", + "14.67500,-1140\n", + "14.68333,-1142\n", + "14.69167,-1145\n", + "14.70000,-1148\n", + "14.70833,-1150\n", + "14.71667,-1153\n", + "14.72500,-1155\n", + "14.73333,-1160\n", + "14.74167,-1166\n", + "14.75000,-1173\n", + "14.75833,-1181\n", + "14.76667,-1189\n", + "14.77500,-1198\n", + "14.78333,-1210\n", + "14.79167,-1220\n", + "14.80000,-1225\n", + "14.80833,-1232\n", + "14.81667,-1242\n", + "14.82500,-1253\n", + "14.83333,-1265\n", + "14.84167,-1277\n", + "14.85000,-1287\n", + "14.85833,-1297\n", + "14.86667,-1307\n", + "14.87500,-1318\n", + "14.88333,-1332\n", + "14.89167,-1344\n", + "14.90000,-1355\n", + "14.90833,-1367\n", + "14.91667,-1379\n", + "14.92500,-1387\n", + "14.93333,-1394\n", + "14.94167,-1402\n", + "14.95000,-1409\n", + "14.95833,-1414\n", + "14.96667,-1420\n", + "14.97500,-1425\n", + "14.98333,-1430\n", + "14.99167,-1436\n", + "15.00000,-1440\n", + "\n", + "[LC Status Trace(Pump A Pressure)]\n", + "Interval(msec),1000\n", + "# of Points,900\n", + "Start Time(min),0.000\n", + "End Time(min),14.983\n", + "Intensity Units,kgf/cm2\n", + "Intensity Multiplier,1\n", + "R.Time (min),Intensity\n", + "0.00000,213.9\n", + "0.01667,213.9\n", + "0.03333,213.9\n", + "0.05000,214.7\n", + "0.06667,216.3\n", + "0.08333,218.7\n", + "0.10000,221.3\n", + "0.11667,224.8\n", + "0.13333,225.2\n", + "0.15000,226.0\n", + "0.16667,224.2\n", + "0.18333,223.7\n", + "0.20000,223.2\n", + "0.21667,223.4\n", + "0.23333,223.3\n", + "0.25000,222.5\n", + "0.26667,220.2\n", + "0.28333,220.9\n", + "0.30000,220.9\n", + "0.31667,221.3\n", + "0.33333,222.0\n", + "0.35000,222.1\n", + "0.36667,221.5\n", + "0.38333,219.6\n", + "0.40000,220.6\n", + "0.41667,220.4\n", + "0.43333,221.2\n", + "0.45000,221.7\n", + "0.46667,221.2\n", + 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"14.38333,219.1\n", + "14.40000,219.1\n", + "14.41667,217.3\n", + "14.43333,217.6\n", + "14.45000,218.6\n", + "14.46667,218.6\n", + "14.48333,219.3\n", + "14.50000,219.3\n", + "14.51667,219.3\n", + "14.53333,218.1\n", + "14.55000,217.7\n", + "14.56667,219.3\n", + "14.58333,219.5\n", + "14.60000,219.6\n", + "14.61667,219.4\n", + "14.63333,217.3\n", + "14.65000,217.7\n", + "14.66667,218.2\n", + "14.68333,219.1\n", + "14.70000,219.5\n", + "14.71667,219.6\n", + "14.73333,217.1\n", + "14.75000,217.1\n", + "14.76667,218.1\n", + "14.78333,218.1\n", + "14.80000,218.1\n", + "14.81667,219.5\n", + "14.83333,219.5\n", + "14.85000,219.5\n", + "14.86667,218.0\n", + "14.88333,218.1\n", + "14.90000,218.3\n", + "14.91667,219.5\n", + "14.93333,219.6\n", + "14.95000,219.1\n", + "14.96667,218.1\n", + "14.98333,218.2\n", + "\n", + "[LC Status Trace(Pump B Pressure)]\n", + "Interval(msec),1000\n", + "# of Points,900\n", + "Start Time(min),0.000\n", + "End Time(min),14.983\n", + "Intensity Units,kgf/cm2\n", + "Intensity Multiplier,1\n", + "R.Time (min),Intensity\n", + "0.00000,229.8\n", + "0.01667,229.8\n", + "0.03333,230.7\n", + "0.05000,230.7\n", + "0.06667,232.1\n", + "0.08333,234.6\n", + "0.10000,237.5\n", + "0.11667,241.5\n", + "0.13333,242.1\n", + "0.15000,240.1\n", + "0.16667,240.4\n", + "0.18333,239.1\n", + "0.20000,239.1\n", + "0.21667,239.7\n", + "0.23333,239.5\n", + "0.25000,238.6\n", + "0.26667,236.3\n", + "0.28333,237.2\n", + "0.30000,237.2\n", + "0.31667,237.3\n", + "0.33333,238.4\n", + "0.35000,238.4\n", + "0.36667,235.4\n", + "0.38333,235.8\n", + "0.40000,236.7\n", + "0.41667,236.2\n", + "0.43333,237.2\n", + "0.45000,238.0\n", + "0.46667,238.0\n", + "0.48333,235.4\n", + "0.50000,236.2\n", + "0.51667,236.4\n", + "0.53333,236.6\n", + "0.55000,237.5\n", + "0.56667,237.7\n", + "0.58333,237.3\n", + "0.60000,235.3\n", + "0.61667,235.9\n", + "0.63333,236.7\n", + "0.65000,236.8\n", + "0.66667,237.1\n", + "0.68333,236.9\n", + "0.70000,234.7\n", + "0.71667,235.5\n", + 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"14.63333,233.4\n", + "14.65000,233.4\n", + "14.66667,234.5\n", + "14.68333,235.1\n", + "14.70000,235.6\n", + "14.71667,235.3\n", + "14.73333,233.3\n", + "14.75000,234.1\n", + "14.76667,234.1\n", + "14.78333,234.5\n", + "14.80000,235.5\n", + "14.81667,235.4\n", + "14.83333,235.3\n", + "14.85000,233.6\n", + "14.86667,234.2\n", + "14.88333,234.5\n", + "14.90000,235.0\n", + "14.91667,235.6\n", + "14.93333,235.1\n", + "14.95000,232.9\n", + "14.96667,234.2\n", + "14.98333,233.9\n", + "\n", + "[LC Status Trace(Sample Cooler Temp.)]\n", + "Interval(msec),1000\n", + "# of Points,900\n", + "Start Time(min),0.000\n", + "End Time(min),14.983\n", + "Intensity Units,C\n", + "Intensity Multiplier,1\n", + "R.Time (min),Intensity\n", + "0.00000,20.27\n", + "0.01667,20.27\n", + "0.03333,20.27\n", + "0.05000,20.27\n", + "0.06667,20.29\n", + "0.08333,20.29\n", + "0.10000,20.29\n", + "0.11667,20.29\n", + "0.13333,20.29\n", + "0.15000,20.29\n", + "0.16667,20.29\n", + "0.18333,20.29\n", + "0.20000,20.28\n", 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python = "^3.9" sdRDM = { git = "https://github.com/JR-1991/software-driven-rdm.git", rev = "cc2d1e21e898399ed55c164f8c02a57341a0fb80" } +plotly = "^5.19.0" +rainbow-api = "^1.0.6" [tool.poetry.group.dev.dependencies] mkdocs-material = "^9.5.12" diff --git a/specifications/chromatography.md b/specifications/chromatography.md index 9ed23a5..b4fee41 100644 --- a/specifications/chromatography.md +++ b/specifications/chromatography.md @@ -9,7 +9,7 @@ - Description: Description of the HPLC method - molecules - Type: Molecule - - Description: Molecule which can be assigned to a peak. + - Description: Molecule that can be assigned to a peak. - measurements - Type: Measurement - Description: Measured signals @@ -48,8 +48,8 @@ ### Measurement -- signals - - Type: Signal +- Chromatograms + - Type: Chromatogram - Description: Measured signal - Multiple: True - timestamp @@ -59,15 +59,26 @@ - Type: float - Description: Injection volume - injection_volume_unit - - Type: string + - Type: Unit - Description: Unit of injection volume -### Signal +### Chromatogram - peaks - Type: Peak - Description: Peaks in the signal - Multiple: True +- retention_times + - Type: float + - Description: Retention times of the signal + - Multiple: True +- time_unit + - Type: Unit + - Description: Unit of retention time +- signals + - Type: float + - Description: Signal values + - Multiple: True - type - Type: SignalType - Description: Type of signal @@ -78,28 +89,28 @@ - Type: float - Description: Retention time of the peak - retention_time_unit - - Type: string + - Type: Unit - Description: Unit of retention time - type - Type: string - - Description: Type of peak (baseline-baseline / baseline-valey / ...) + - Description: Type of peak (baseline-baseline / baseline-valley / ...) - width - Type: float - Description: Width of the peak - width_unit - - Type: string + - Type: Unit - Description: Unit of width - area - Type: float - Description: Area of the peak - area_unit - - Type: string + - Type: Unit - Description: Unit of area - height - Type: float - Description: Height of the peak - height_unit - - Type: string + - Type: Unit - Description: Unit of height - percent_area - Type: float @@ -109,7 +120,7 @@ - factor - Type: float - - Description: Factor to convert signal to concentration + - Description: Factor to convert the signal to concentration ## Objects describing the method @@ -125,7 +136,7 @@ - Type: float - Description: Injection volume - injection_volume_unit - - Type: string + - Type: Unit - Description: Unit of injection volume - location - Type: string @@ -182,14 +193,14 @@ Describes properties of a temperature ramp. - Type: float - Description: Duration to hold the final temperature before starting the next ramp - time_unit - - Type: string + - Type: Unit - Description: Unit of time ### Inlet - mode - Type: string - - Description: Mode of the inlet (Split/Splitless) + - Description: Mode of the inlet (Split / Splitless) - init_temp - Type: float - Description: Initial temperature @@ -197,7 +208,7 @@ Describes properties of a temperature ramp. - Type: float - Description: Inlet pressure - pressure_unit - - Type: string + - Type: Unit - Description: Unit of pressure - split_ratio - Type: string @@ -210,7 +221,7 @@ Describes properties of a temperature ramp. - Type: float - Description: Total flow - flow_unit - - Type: string + - Type: Unit - Description: Unit of flow - gas_saver - Type: boolean @@ -248,7 +259,7 @@ Describes properties of a column and its connections to the inlet and detector. - Type: float - Description: Flow rate of the column - flow_unit - - Type: string + - Type: Unit - Description: Unit of flow rate - inlet - Type: Inlet @@ -269,7 +280,7 @@ Base class for detectors. - Description: Type of detector - flow_mode - Type: string - - Description: Air flow mode + - Description: Airflow mode - makeup_flow - Type: float - Description: Makeup flow @@ -277,7 +288,7 @@ Base class for detectors. - Type: string - Description: Makeup gas - flow_unit - - Type: string + - Type: Unit - Description: Unit of flow - reference_flow - Type: float @@ -292,7 +303,7 @@ Describes properties of a thermal conductivity detector. - Description: Hydrogen flow - air_flow - Type: float - - Description: Air flow + - Description: Airflow - flame - Type: boolean - Description: Flame on/off