Merge pull request #57 from Jumitti/beta

Beta

TFinder-v1.py

@@ -232,12 +232,13 @@ def load_lottiefile(filepath: str):
 
 # streamlit_analytics.stop_tracking()
 # views = streamlit_analytics.main.counts["total_pageviews"]
-local_test = platform.processor()
-if local_test == "":
-    unique_users = st.secrets['unique_users']
-    st.sidebar.markdown(f"Unique users 👥: {unique_users}")
-    st.session_state["LOCAL"] = 'False'
-else:
+try:
+    local_test = platform.processor()
+    if local_test == "":
+        unique_users = st.secrets['unique_users']
+        st.sidebar.markdown(f"Unique users 👥: {unique_users}")
+        st.session_state["LOCAL"] = 'False'
+except Exception as e:
     st.session_state["LOCAL"] = 'True'
     st.sidebar.markdown(f"TFinder Local Version")
 

clock.time

@@ -1 +1 @@
-Last updated at 14:21 on 2023-11-06
+Last updated at 09:04 on 2024-05-02

tfinder/__init__.py

@@ -426,11 +426,11 @@ def transform_matrix(matrix):
 
     @staticmethod
     # Generate random sequences for p_value
-    def generate_ranseq(probabilities, seq_length, progress_bar, num_random_seqs):
+    def generate_ranseq(probabilities, seq_length, progress_bar):
         motif_length = seq_length
         random_sequences = []
 
-        for _ in range(num_random_seqs):
+        for _ in range(1000000):
             random_sequence = IMO.generate_random_sequence(motif_length, probabilities)
             random_sequences.append(random_sequence)
             progress_bar.update(1)
@@ -479,8 +479,6 @@ def individual_motif_finder(dna_sequences, threshold, matrix, progress_bar, calc
 
         matrices = IMO.transform_matrix(matrix)
 
-        num_random_seqs = 1000000
-
         seq_length = len(matrices['+ f']['A'])
 
         if calc_pvalue == 'ATGCPreset':
@@ -491,7 +489,7 @@ def individual_motif_finder(dna_sequences, threshold, matrix, progress_bar, calc
 
             probabilities = [percentage_a, percentage_c, percentage_g, percentage_t]
 
-            random_sequences = IMO.generate_ranseq(probabilities, seq_length, progress_bar, num_random_seqs)
+            random_sequences = IMO.generate_ranseq(probabilities, seq_length, progress_bar)
 
         random_scores = {}
         matrix_random_scores = []
@@ -525,7 +523,7 @@ def individual_motif_finder(dna_sequences, threshold, matrix, progress_bar, calc
 
                 probabilities = [percentage_a, percentage_c, percentage_g, percentage_t]
 
-                random_sequences = IMO.generate_ranseq(probabilities, seq_length, progress_bar, num_random_seqs)
+                random_sequences = IMO.generate_ranseq(probabilities, seq_length, progress_bar)
 
                 if calc_pvalue == 'ATGCProportion':
                     random_scores = {}