Add block for processing GPC/SEC data from Agilent Technologies 1260 Infinity II multidetector SEC/GPC system

pydatalab/src/pydatalab/apps/__init__.py

@@ -91,6 +91,21 @@ def load_app_blocks():
     except ImportError as e:
         _check_error(e)
 
+    try:
+        from pydatalab.apps.gpc_sec import GPCBlock
+
+        app_blocks.append(GPCBlock)
+    except ImportError as e:
+        _check_error(e)
+
+    try:
+        from pydatalab.apps.dsc import DSCBlock
+
+        app_blocks.append(DSCBlock)
+    except ImportError as e:
+        _check_error(e)
+
+
     return app_blocks
 
 

pydatalab/src/pydatalab/apps/ftir/__init__.py

@@ -6,14 +6,16 @@
 import pandas as pd
 from bokeh.models import HoverTool, LogColorMapper
 
+import codecs
+
 from pydatalab.blocks.base import DataBlock
 from pydatalab.bokeh_plots import DATALAB_BOKEH_THEME, selectable_axes_plot
 from pydatalab.file_utils import get_file_info_by_id
 from pydatalab.logger import LOGGER
 
 
 class FTIRBlock(DataBlock):
-    accepted_file_extensions: tuple[str, ...] = (".asp",)
+    accepted_file_extensions: tuple[str, ...] = (".asp",".txt")
     blocktype = "ftir"
     name = "FTIR"
     description = (
@@ -36,7 +38,7 @@ def parse_ftir_asp(cls, filename: Path) -> pd.DataFrame:
             filename: Path to the .asp file
 
         Returns:
-            FTIR dataframe with columns "Wavenumber" and "Absorbance"" with the wavenumber in cm^-1
+            FTIR dataframe with columns "Wavenumber" and "Absorbance"" with the wavenumber in cm^-1 and string 'default' for the x and y units
         """
 
         ftir = pd.read_csv(filename, header=None)
@@ -46,10 +48,37 @@ def parse_ftir_asp(cls, filename: Path) -> pd.DataFrame:
         x_range = np.linspace(start_wavenumber, end_wavenumber, number_of_points)
         y = ftir[0].iloc[-number_of_points:]
         ftir = pd.DataFrame.from_dict({"Wavenumber": x_range, "Absorbance": y})
-        return ftir
+        return ftir, 'default', 'default'
+
+    @classmethod
+    def parse_ftir_txt(cls, filename: Path) -> pd.DataFrame:
+        """Parses .txt FTIR data generated by a Shimadzu IR Tracer-100 FT-IR spectrophotometer
+
+        The file consists of a header with metadata: a title, data type, x units and y units,
+        and then the IR data
+        This function reads the file and extracts the data as a pandas DataFrame, and the x units and y units as strings.
+        This function does not read the original .ispd file generated by the spectrometer
+
+        Args:
+            filename: Path to the .txt file
+
+        Returns:
+            FTIR dataframe with columns "Wavenumber" and "Absorbance", and strings giving the x and y units
+        """
+        with open(filename,'r') as f:
+            alldata = f.readlines()
+        title = alldata[0].split('=')[1]
+        dtype = alldata[1].split('=')[1]
+        xunits = alldata[2].split('=')[1]
+        yunits = alldata[3].split('=')[1]
+        data = alldata[4:]
+        x = [float(line.split()[0]) for line in data]
+        y = [float(line.split()[1]) for line in data]
+        ftir = pd.DataFrame.from_dict({'Wavenumber':x, 'Absorbance':y})
+        return ftir, xunits, yunits
 
     @classmethod
-    def _format_ftir_plot(self, ftir_data: pd.DataFrame) -> bokeh.layouts.layout:
+    def _format_ftir_plot(self, ftir_data: pd.DataFrame,xunits:str,yunits:str) -> bokeh.layouts.layout:
         """Formats FTIR data for plotting in Bokeh, inverted x-axis with a buffer of 50 cm^-1 on either side
 
         Args:
@@ -58,6 +87,14 @@ def _format_ftir_plot(self, ftir_data: pd.DataFrame) -> bokeh.layouts.layout:
         Returns:
             bokeh.layouts.layout: Bokeh layout with FTIR data plotted
         """
+        if xunits == 'default':
+            toollabsx = "Wavenumber / cm⁻¹"
+        else:
+            toollabsx = "Wavenumber /{0}".format(xunits)
+        if yunits == 'default':
+            toollabsy = "Absorbance"
+        else:
+            toollabsy = yunits
         layout = selectable_axes_plot(
             ftir_data,
             x_options=["Wavenumber"],
@@ -69,16 +106,22 @@ def _format_ftir_plot(self, ftir_data: pd.DataFrame) -> bokeh.layouts.layout:
             plot_line=True,
             tools=HoverTool(
                 tooltips=[
-                    ("Wavenumber / cm⁻¹", "@Wavenumber{0.00}"),
-                    ("Absorbance", "@Absorbance{0.0000}"),
+                    (toollabsx, "@Wavenumber{0.00}"),
+                    (toollabsy, "@Absorbance{0.0000}"),
                 ],  # Display x and y values to specified decimal places
                 mode="vline",  # Ensures hover follows the x-axis
             ),
         )
-        # Adding cm^-1 to the x-axis label using unicode characters - might be a more logical way
-        layout.children[1].xaxis.axis_label = "Wavenumber / cm⁻¹"
+        if xunits == 'default':
+            # Adding cm^-1 to the x-axis label using unicode characters - might be a more logical way
+            layout.children[1].xaxis.axis_label = "Wavenumber / cm⁻¹"
+        else:
+            layout.children[1].xaxis.axis_label = "Wavenumber /{0}".format(xunits)
+        if yunits != 'default':
+            layout.children[1].yaxis.axis_label = yunits
         return layout
 
+
     def generate_ftir_plot(self):
         file_info = None
         # all_files = None
@@ -97,9 +140,12 @@ def generate_ftir_plot(self):
                     ext,
                 )
                 return
+            elif ext == '.asp':
+                ftir_data,xunits,yunits = self.parse_ftir_asp(Path(file_info["location"]))
+            elif ext == '.txt':
+                ftir_data,xunits,yunits = self.parse_ftir_txt(Path(file_info["location"]))
 
-            ftir_data = self.parse_ftir_asp(Path(file_info["location"]))
-
+        print(ftir_data)
         if ftir_data is not None:
-            layout = self._format_ftir_plot(ftir_data)
+            layout = self._format_ftir_plot(ftir_data,xunits,yunits)
             self.data["bokeh_plot_data"] = bokeh.embed.json_item(layout, theme=DATALAB_BOKEH_THEME)