Completing OFRAnalyser creator, starting on OFRSample creator and mass integrator

.vscode/settings.json

@@ -1,5 +1,9 @@
 {
+    "chat.disableAIFeatures": true,
     "chat.agent.enabled": false,
+    "chat.commandCenter.enabled": false,
+    "inlineChat.accessibleDiffView": "off", 
+    "terminal.integrated.initialHint": false,
     "chat.checkpoints.enabled": false,
     "chat.undoRequests.restoreInput": false,
     "chat.agent.sandbox.allowAutoApprove": false,
@@ -35,5 +39,12 @@
     "python-envs.defaultEnvManager": "ms-python.python:conda",
     "python-envs.defaultPackageManager": "ms-python.python:conda",
     "python.envFile": "${workspaceFolder}/.env",
-    "python.terminal.useEnvFile": true
+    "python.terminal.useEnvFile": true,
+    "editor.quickSuggestions": {
+        "other": "off",
+        "comments": "off",
+        "strings": "off"
+    },
+    "editor.suggestOnTriggerCharacters": false,
+    "window.zoomLevel": -1
 }

defs/debug_scrapyard.py

@@ -1,10 +1,13 @@
 ### -------------------------------------------------------------------------------- ###
 ### SCRAPYARD TO DEBUG AND TEST FUNCTIONALITY
 
-import sys
-print(sys.path)
-
 import pandas as pd
+import numpy as np
 from defs import OFRAnalyser, OFRSample
 
-analyser = OFRAnalyser(sourcefile="/Volumes/5505/People/David_Tschan/data/OFR_SMPS/2026/processed/06_June/20260612/20260612_SET02_EXP01_full.csv")
+analyser = OFRAnalyser(sourcefile="Z:/People/David_Tschan/data/OFR_SMPS/2026/processed/06_June/20260612/20260612_SET02_EXP01_full.csv")
+samplelist = np.linspace(start=1, stop=analyser.max_samples, num=analyser.max_samples, dtype=int).tolist()
+
+analyser.GetTotalMass(samples=samplelist, plot=True)
+
+print("Hello")

defs/defs.py

@@ -1,19 +1,38 @@
 ### -------------------------------------------------------------------------------- ###
 ### IMPORTS AND CONFIGURATIONS
 
-import os
+import numpy as np
 import pandas as pd
+import csv
 
 ### -------------------------------------------------------------------------------- ###
 ### OFR ANALYSIS
 
 class OFRSample:
 
-    def __init__(self, number, diameterlist, countlist):
+    def __init__(self, number, sourcefile, headlines):
+
         self.number = number
-        self.diameterlist = diameterlist
-        self.countlist = countlist
-        self.samplelist = {}
+        self.sourcefile = sourcefile
+        self.headlines = headlines
+
+        self.diameters = np.empty(shape=(self.number, 1))
+        self.counts = np.empty(shape=(self.number, 1))
+
+    def __get_data(self):
+
+        columns = ['Diameter #' + str(self.number), 'Counts #' + str(self.number)]
+        sample_data = pd.read_csv(filepath_or_buffer=self.sourcefile, header=self.headlines, usecols=columns, index=False).to_numpy()
+
+        self.diameters = sample_data[:, 0]
+        self.counts = sample_data[:, 1]
+
+    def mass_integrator(self, method='trapz') -> None:
+
+        self.__get_data()
+        
+
+        pass
 
 class OFRAnalyser:
 
@@ -21,24 +40,37 @@ class OFRAnalyser:
         self.sourcefile = sourcefile
         self.headlines = headlines
 
-        head_row = pd.read_csv(filepath_or_buffer=self.sourcefile, header=self.headlines, nrows=1)
-        self.__max_sample = None
+        with open(self.sourcefile) as file:
+            file_reader = csv.reader(file)
+            for index, row in enumerate(file_reader):
+                if index != self.headlines:
+                    continue
+                else:
+                    head_row = row
 
-    def __get_samples(self) -> None:
+        self.max_samples = int((len(head_row) - 1) / 2)
+
+    def __get_sample(self, sample_number) -> None:
         pass
 
-    def __samplelist_check(self, samplelist) -> None:
+    def __sample_number_list_check(self, sample_number_list) -> None:
 
-        last_sample = samplelist[-1]
+        last_sample = sample_number_list[-1]
 
-        if last_sample > self.__max_sample:
-            raise IndexError("The last sample(s) go out of range of recorded samples")
+        if last_sample > self.max_samples:
+            raise IndexError("The last sample(s) are out of range of the number of recorded samples")
 
-    def __mass_integrator(self, samplelist) -> None:
-        pass
+    def GetTotalMass(self, samples = [1], plot = False) -> None:
 
-    def GetTotalMass(self, samples = 'all', plot = False) -> None:
-        pass
+        self.__sample_number_list_check(samples)
+        masses = []
+
+        for sample in samples:
+            local_sample = OFRSample(number=sample, sourcefile=self.sourcefile, headlines=self.headlines)
+            mass = local_sample.mass_integrator()
+            masses.append(mass)
+
+        
 
     def PlotSampleDistribution(self, sample) -> None:
         pass