Created Python script to transform whole DF to resizes DFs. WIP. iterTimes.py must be removed.

Analysis/CreateResizeDataframe.py

+import sys
+import glob
+import numpy as np
+import pandas as pd
+from enum import Enum
+
+class G_enum(Enum):
+    TOTAL_RESIZES = 0
+    TOTAL_GROUPS = 1
+    TOTAL_STAGES = 2
+    GRANULARITY = 3
+    SDR = 4
+    ADR = 5
+    DR = 6
+    RED_METHOD = 7
+    RED_STRATEGY = 8
+    SPAWN_METHOD = 9
+    SPAWN_STRATEGY = 10
+    GROUPS = 11
+    FACTOR_S = 12
+    DIST = 13
+    STAGE_TYPES = 14
+    STAGE_TIMES = 15
+    STAGE_BYTES = 16
+    ITERS = 17
+    ASYNCH_ITERS = 18
+    T_ITER = 19
+    T_STAGES = 20
+    T_SPAWN = 21
+    T_SPAWN_REAL = 22
+    T_SR = 23
+    T_AR = 24
+    T_TOTAL = 25
+    #Malleability specific
+    NP = 0
+    NC = 1
+
+#columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
+            "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Groups", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
+            "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_total"] #26
+
+columnsM = ["NP", "NC", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
+            "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "FactorS", "Dist", "Stage_Type", "Stage_Time", \
+            "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR"] #24
+
+def copy_resize(row, dataM_it, resize):
+  basic_indexes = [G_enum.TOTAL_STAGES.value, G_enum.GRANULARITY.value, G_enum.SDR.value, \
+          G_enum.ADR.value, G_enum.DR.value, G_enum.STAGE_TYPES.value, \
+          G_enum.STAGE_TIMES.value, G_enum.STAGE_BYTES.value]
+  array_actual_group = [G_enum.FACTOR_S.value, G_enum.ITERS.value, G_enum.ASYNCH_ITERS.value, \
+          G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, \
+          G_enum.T_AR.value, G_enum.T_ITER.value, G_enum.T_STAGES.value]
+  array_next_group = [G_enum.RED_METHOD.value, G_enum.RED_STRATEGY.value, \
+          G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value]
+
+  dataM_it[G_enum.NP.value] = row[G_enum.GROUPS.value][resize]
+  dataM_it[G_enum.NC.value] = row[G_enum.GROUPS.value][resize+1]
+  dataM_it[G_enum.DIST.value] = [None, None]
+  dataM_it[G_enum.DIST.value][0] = row[G_enum.DIST.value][resize]
+  dataM_it[G_enum.DIST.value][1] = row[G_enum.DIST.value][resize+1]
+
+  for index in basic_indexes:
+    dataM_it[index] = row[index]
+
+  for index in array_actual_group:
+    dataM_it[index-1] = row[index][resize] 
+
+  for index in array_next_group:
+    dataM_it[index] = row[index][resize+1]
+
+
+#-----------------------------------------------
+
+def create_resize_dataframe(dfG, dataM):
+  it = -1
+  for row in dfG.itertuples(index=False, name=None):
+    resizes = row[G_enum.TOTAL_RESIZES.value]
+    for resize in range(resizes):
+      it += 1
+      dataM[it].append( [None] * len(columnsM) )
+      copy_resize(row, dataM[it], resize)
+
+#-----------------------------------------------
+if len(sys.argv) < 2:
+    print("The files name is missing\nUsage: python3 CreateResizeDataframe.py input_file.csv output_name.csv")
+    exit(1)
+
+input_name = sys.argv[1]
+if len(sys.argv) > 2:
+  name = sys.argv[2]
+else:
+  name = "dataM"
+print("Csv name will be: " + name + ".csv")
+
+
+dfG = pd.read_csv(input_name)
+dataM = []
+create_resize_dataframe(dfG, dataM)
+
+#dfM = pd.DataFrame(dataM, columns=columnsM)
+
+#Poner en TC el valor real y en TH el necesario para la app
+#cond = dfM.TH != 0
+#dfM.loc[cond, ['TC', 'TH']] = dfM.loc[cond, ['TH', 'TC']].values
+#dfM.to_csv(name + 'M.csv')