Parsing¶

Chromstream presently supports parsing of the folling types of files:

Chromatograms¶

• .txt files exported from chromeleon
• .ch files (Agilent)
• .d directories containing multiple .ch files
• .dx files (Agilent)

If your file formats varies, you can create your own chromatogram object a shown below.

Logfiles¶

• Logfiles generated by Labview (limited support, preferebly add otehr data as pandas DataFrame)

Parsing single chromatograms¶

There are in general two ways of parsing a chromatogram. 1) parsing it directly to a chromatogram object 2) Adding a Chromatogram to a experiment or channel object. You can also construct your own chromatogram object.

For agilent .d directories and .dx files, the simple parsing commands return lists, as these formats can contain multiple chromatograms.

Parsing to an object¶

In [1]:

# Chromeleon
from pathlib import Path
import chromstream as cs
import pandas as pd
chrompaths = Path("../..") /"tests" / "testdata" / "chroms" 
chromeleon_test = chrompaths / "format_6.txt"
chromatogram_1 = cs.parse_chromatogram(chromeleon_test)

# Agilent
agilent_test_path = chrompaths / "agilent.d" / "FID1A.ch"
chromatogram_2 = cs.parse_chromatogram(agilent_test_path)

# if you know the specific format, you can also use the more specific parser
chromatogram_1 = cs.parse_chromatogram_txt(chromeleon_test) #chromeleon .txt format
chromatogram_2 = cs.parse_agilent_ch(agilent_test_path) # Agilent .ch format

# custom chromatogram
mychromatogram = cs.Chromatogram(
        data=pd.DataFrame({"time": [0, 1, 2], "signal": [10, 20, 15]}), # must be a dataframe with "time" and "signal" columns
        injection_time=pd.Timestamp("2024-01-01 12:00:00"), # pandas Timestamp for injection time
        metadata={"time_unit": "s", "signal_unit": "mV"}, # any dict
        channel="FID",
        path=None
    )

# Agilent .d directory
agilent_d_path = chrompaths / "agilent.d" # returns a list of chromatograms from the .d directory
chromlist_1 = cs.parse_agilent_dot_d(agilent_d_path)

# Agilent .dx file
agilent_dx_path = chrompaths / "test_dx.dx"
chromlist_2 = cs.parse_agilent_dx(agilent_dx_path)

# Chromeleon from pathlib import Path import chromstream as cs import pandas as pd chrompaths = Path("../..") /"tests" / "testdata" / "chroms" chromeleon_test = chrompaths / "format_6.txt" chromatogram_1 = cs.parse_chromatogram(chromeleon_test) # Agilent agilent_test_path = chrompaths / "agilent.d" / "FID1A.ch" chromatogram_2 = cs.parse_chromatogram(agilent_test_path) # if you know the specific format, you can also use the more specific parser chromatogram_1 = cs.parse_chromatogram_txt(chromeleon_test) #chromeleon .txt format chromatogram_2 = cs.parse_agilent_ch(agilent_test_path) # Agilent .ch format # custom chromatogram mychromatogram = cs.Chromatogram( data=pd.DataFrame({"time": [0, 1, 2], "signal": [10, 20, 15]}), # must be a dataframe with "time" and "signal" columns injection_time=pd.Timestamp("2024-01-01 12:00:00"), # pandas Timestamp for injection time metadata={"time_unit": "s", "signal_unit": "mV"}, # any dict channel="FID", path=None ) # Agilent .d directory agilent_d_path = chrompaths / "agilent.d" # returns a list of chromatograms from the .d directory chromlist_1 = cs.parse_agilent_dot_d(agilent_d_path) # Agilent .dx file agilent_dx_path = chrompaths / "test_dx.dx" chromlist_2 = cs.parse_agilent_dx(agilent_dx_path)

Adding to an Experiment or Channel¶

You can also start by inilizing an experiment and using a method to add the chromatogram. Note that if you want to add multiple chromatograms at the same time, you need a seperate method. The channel is inferred automatically from the metadata. When parsing to a channel, the injeciton number needs to be specified.

In [ ]:

myexp = cs.Experiment(name="My Experiment")

# From a path
myexp.add_chromatogram(chromeleon_test)

# From a Chromatogram object
myexp.add_chromatogram(chromatogram_1)

# From a dx file or a .d directory (adds all chromatograms in the file/directory)
myexp.add_mult_chromatograms(agilent_d_path)

# adding to channel works analogously
mychannel = cs.ChannelChromatograms(channel="My Channel")
mychannel.add_chromatogram(1, chromatogram_1)

myexp = cs.Experiment(name="My Experiment") # From a path myexp.add_chromatogram(chromeleon_test) # From a Chromatogram object myexp.add_chromatogram(chromatogram_1) # From a dx file or a .d directory (adds all chromatograms in the file/directory) myexp.add_mult_chromatograms(agilent_d_path) # adding to channel works analogously mychannel = cs.ChannelChromatograms(channel="My Channel") mychannel.add_chromatogram(1, chromatogram_1)