Update femtopulse run file epp

cg_lims/EPPs/files/femtopulse_csv.py

@@ -1,51 +1,96 @@
 import logging
+import math
 import sys
 from pathlib import Path
 from typing import List
 
 import click
 import pandas as pd
+from genologics.lims import Artifact, Process
+
 from cg_lims import options
-from cg_lims.exceptions import InvalidValueError, LimsError
+from cg_lims.exceptions import InvalidValueError, LimsError, MissingUDFsError
 from cg_lims.get.artifacts import get_artifacts
 from cg_lims.get.fields import get_artifact_well
-from genologics.lims import Artifact
 
 LOG = logging.getLogger(__name__)
 
 
-WELL_POSITIONS = [f"A{i}" for i in range(1, 13)]  # List with well positions A1-A12
-SAMPLE_NAMES = [""] * len(WELL_POSITIONS)  # List with twelve empty positions for sample names
-DATAFRAME = pd.DataFrame(
-    {"well positions": WELL_POSITIONS, "sample names": SAMPLE_NAMES}
-)  # Dataframe with well positions and sample names
+def get_sample_artifact_name(artifact: Artifact) -> str:
+    artifact_name: str = artifact.samples[0].name
+    return artifact_name
 
 
-def get_sample_artifact_name(artifact: Artifact):
+def get_number_of_ladders(process: Process) -> int:
+    """Returning the number of ladders from a process"""
+    num_of_ladders: int = process.udf.get("Number of ladders")
+    if not num_of_ladders:
+        raise MissingUDFsError(
+            f"Missing the number of ladders, please specify a number between 1-8."
+        )
+    if not 1 <= num_of_ladders <= 8:
+        raise InvalidValueError(
+            f"Number of ladders must be between 1 and 8. Got: {num_of_ladders}"
+        )
+    return num_of_ladders
 
-    artifact_name: str = artifact.samples[0].name
 
-    return artifact_name
+def generate_plate_positions(
+    num_of_artifacts: int, num_of_ladders: int
+) -> pd.DataFrame:
+    """Generate all possible plate positions based on number of artifacts and ladders."""
+
+    ROWS = ["A", "B", "C", "D", "E", "F", "G", "H"]
+    SAMPLES_PER_ROW = 11  # Only using positions 1-11
+
+    # Calculate required number of rows for samples
+    required_rows = math.ceil(num_of_artifacts / SAMPLES_PER_ROW)
+    max_rows = max(required_rows, num_of_ladders)
+    if max_rows > 8:
+        raise InvalidValueError(
+            f"Too many rows required ({max_rows}). Maximum is 8 rows."
+        )
+
+    WELL_POSITIONS = []
+    SAMPLE_NAMES = []
+
+    # Generate positions for samples (1-11 in each required row)
+    for row_id in range(max_rows):
+        row_letter = ROWS[row_id]
+        for col in range(1, 12):  # positions 1-11
+            WELL_POSITIONS.append(f"{row_letter}{col}")
+            SAMPLE_NAMES.append("")
+
+    # Add ladder positions (position 12 in sequential rows)
+    for row_id in range(max_rows):
+        row_letter = ROWS[row_id]
+        WELL_POSITIONS.append(f"{row_letter}12")
+        SAMPLE_NAMES.append("ladder" if row_id < num_of_ladders else "")
+
+    return pd.DataFrame(
+        {"well positions": WELL_POSITIONS, "sample names": SAMPLE_NAMES}
+    )
 
 
-def get_data_and_write(artifacts: List[Artifact], file: str):
+def get_data_and_write(artifacts: List[Artifact], num_of_ladders: int, file: str):
     """Make a csv file for a Femtopulse run start with three columns:
-    one numbered 1-12, one with the sample position/well for the run and
-    a column with the sample name or ladder (in the 12th position)."""
+    index, sample position and sample name or ladder"""
+
+    # Generate the plate layout based on number of artifacts and ladders
+    DATAFRAME = generate_plate_positions(
+        num_of_artifacts=len(artifacts), num_of_ladders=num_of_ladders
+    )
 
     failed_samples: list = []
 
     for artifact in artifacts:
 
         artifact_name: str = get_sample_artifact_name(artifact=artifact)
-
-        # Fetch sample well in format 'A1'
         artifact_well: str = get_artifact_well(artifact=artifact)
 
-        # Checks that the sample well matches with one in the WELL_POSITIONS list (A1-A11)
-        # and adds the sample name to the SAMPLE_NAMES list for that position
+        # Check if well position is valid and not a ladder position
         if artifact_well in DATAFRAME["well positions"].values:
-            if artifact_well == DATAFRAME["well positions"].iloc[-1]:
+            if artifact_well.endswith("12"):
                 failed_samples.append(
                     {
                         "artifact_name": artifact_name,
@@ -54,19 +99,19 @@ def get_data_and_write(artifacts: List[Artifact], file: str):
                     }
                 )
             else:
-                DATAFRAME.loc[DATAFRAME["well positions"] == artifact_well, "sample names"] = (
-                    artifact_name
-                )
+                DATAFRAME.loc[
+                    DATAFRAME["well positions"] == artifact_well, "sample names"
+                ] = artifact_name
         else:
             failed_samples.append(
                 {
                     "artifact_name": artifact_name,
                     "parsed_well": artifact_well,
-                    "error": "This position is not possible for the run.",
+                    "error": "This position is not suitable for the run.",
                 }
             )
 
-    # Prints out error message(s)
+    # Prints out error messages
     if failed_samples:
         all_errors = ""
         for sample in failed_samples:
@@ -76,12 +121,9 @@ def get_data_and_write(artifacts: List[Artifact], file: str):
             all_errors = all_errors + " " + error_message
         raise InvalidValueError(f"Errors found: {all_errors}")
 
-    # The ladder will always be in well A12
-    DATAFRAME["sample names"].iloc[-1] = "ladder"
-
     # Create the csv file
     DATAFRAME.index = range(1, len(DATAFRAME) + 1)
-    DATAFRAME.to_csv(Path(file), index=True, header=False)
+    DATAFRAME.to_csv(Path(file), index=True, header=False, sep=";")
 
 
 @click.command()
@@ -100,8 +142,10 @@ def make_femtopulse_csv(
     artifacts = get_artifacts(process=process, measurement=measurement)
 
     try:
+        num_of_ladders: int = get_number_of_ladders(process=process)
         get_data_and_write(
             artifacts=artifacts,
+            num_of_ladders=num_of_ladders,
             file=f"{file}_femtopulse.csv",
         )
         click.echo("The file was successfully generated.")