Cleaned plotter and modified yaml file. Also added np to requirements

scrape.yaml

@@ -10,4 +10,11 @@ metrics_to_scrape:
   - "rate(container_network_receive_bytes_total{namespace='zerotesting'}[$__rate_interval])": "pod-node"
   - "rate(container_network_transmit_bytes_total{namespace='zerotesting'}[$__rate_interval])": "pod-node"
   - "sum by(job) (libp2p_gossipsub_low_peers_topics)" : "job"
-  - "sum by(job) (libp2p_gossipsub_healthy_peers_topics)": "job"
+  - "sum by(job) (libp2p_gossipsub_healthy_peers_topics)": "job"
+plotting:
+  "bandwidth":
+    "folder":
+      - "test/nwaku/1000-1KB-1msgs/"
+    "data":
+      - "libp2p-rx"
+      - "libp2p-tx"

src/plotting/plotter.py

@@ -1,38 +1,17 @@
 # Python Imports
+import logging
 import os
-
 import numpy as np
-
-import logger
 import pandas as pd
 import seaborn as sns
-from typing import List, Dict
 import matplotlib.pyplot as plt
-from matplotlib import ticker
+from typing import List, Dict
-from matplotlib.axis import Axis
 
 # Project Imports
 from utils.file_utils import get_files_from_folder_path, get_file_name_from_path
 
-# logger = logging.getLogger(__name__)
+logger = logging.getLogger(__name__)
 sns.set_theme()
-# En carpeta: metrica1, metrica2, metrica3...
-# o bien, metrica1_1, metrica1_2...
-# La carpeta padre, es carpetas de carpetas de metricas ()
-
-
-# Cuando se descarga, se crea la carpeta del experimento
-# Del experimento, se pueden crear plots (metrica),
-# Del experimento, se pueden meter varios plots juntos (metricas para comparar, RX-TX)
-# Pensar que del mismo experimento, se puedan meter varios plots por fila (compactación)
-# De varios experimentos, se pueden meter en el mismo plot (metrica)
-
-
-# test = {"bandwidth": {"folder": ["waku"], "data": ["RX", "TX"], "include": ["experiment1", "experiment2"]}}
-# Del tipo de programa "FOLDER", quiero que me plotees rx contra tx, y que me incluyas los experimentos x y z
-# en este caso se plotearán tantos plots como "data" haya. con INCLUDE boxplots, y FOLDER tipos de boxplots.
-# test = {"bandwidth": {"folder": ["../../data/plotter_data_test/rust/", "../../data/plotter_data_test/go/"], "data": ["rx", "tx"], "include": ["0.5KB-1.csv", "0.5KB-1.csv"]}}
-test = {"bandwidth": {"folder": ["../../test/nwaku/1000-1KB-1msgs/"], "data": ["libp2p-rx", "libp2p-tx"], "include": ["0.5KB-1.csv", "0.5KB-1.csv"]}}
 
 
 class Plotter:
@@ -66,9 +45,9 @@ class Plotter:
             data_files_path = get_files_from_folder_path(subplot_path)
 
             for file_path in data_files_path:
-                group_df = self._dump_file_mean_into_df(file_path, group_df)
+                group_df = self._dump_file_mean_into_df(subplot_path+"/"+file_path, group_df)
 
-            subplot_df["class"] = subplot_path.split("/")[-2]
+            group_df["class"] = subplot_path.split("/")[-2]
             subplot_df = pd.concat([subplot_df, group_df])
 
         subplot_df = pd.melt(subplot_df, id_vars=["class"])
@@ -101,103 +80,3 @@ class Plotter:
         ]
 
         return subplot_path
-
-
-def add_data_to_df(main_df, df: pd.DataFrame, name):
-    df_avg = df.mean()
-    df_avg = pd.DataFrame(df_avg, columns=[name])
-
-    concat_df = pd.concat([main_df, df_avg], axis=1)
-
-    return concat_df
-
-
-def create_plot():
-    fig, axs = plt.subplots(nrows=1, ncols=2, sharey='row')
-
-    folders_grouped = [
-        [f"{folder}{data}" for folder in test["bandwidth"]["folder"]]
-        for data in test["bandwidth"]["data"]
-    ]
-
-    for k, group in enumerate(folders_grouped):
-        main_df = pd.DataFrame()
-        for folder_path in group:
-            folder_df = pd.DataFrame()
-            files = [f for f in os.listdir(folder_path) if
-                     os.path.isfile(os.path.join(folder_path, f))]
-            for file in files:
-                if not os.path.exists(folder_path+"/"+file): continue  # todo delete this line
-                df = pd.read_csv(folder_path+"/"+file, parse_dates=['Time'],
-                                 index_col='Time')
-                folder_df = add_data_to_df(folder_df, df, file)
-
-            folder_df["class"] = folder_path.split("/")[-2]
-            main_df = pd.concat([main_df, folder_df])
-
-        main_df = pd.melt(main_df, id_vars=["class"])
-
-        box_plot = sns.boxplot(data=main_df, x="variable", y="value", hue="class", ax=axs[k])
-        box_plot.set(xlabel='Payload size (KB)', ylabel=f"Kbytes")
-        box_plot.tick_params(labelbottom=True)
-        box_plot.xaxis.set_tick_params(rotation=45)
-
-        # formatter = ticker.FuncFormatter(lambda x, pos: '{:.0f}'.format(x / 1000))
-        # Apply the custom formatter to the x-axis ticks
-        # box_plot.yaxis.set_major_formatter(formatter)
-
-    plt.tight_layout()
-    plt.savefig(f"teestt.png")
-    plt.show()
-
-
-create_plot()
-
-
-def plot_merged(folders_grouped: List, metrics: List):
-    fig, axs = plt.subplots(nrows=3, ncols=2, figsize=(14, 16), sharex=True, sharey='row')
-
-    for j, group in enumerate(folders_grouped):
-        final_df = pd.DataFrame()
-        for i, folder_path in enumerate(group):
-            if not os.path.exists(folder_path): continue
-            files = [f for f in os.listdir(folder_path) if
-                     os.path.isfile(os.path.join(folder_path, f))]
-            files = sorted(files, key=lambda x: float(x.split("-")[1].split("KB")[0]))
-            folder_df = pd.DataFrame()
-
-            for file in files:
-                df = pd.read_csv(folder_path + file, parse_dates=['Time'], index_col='Time')
-
-                column_name = file.split("-")[1]
-
-                df_avg = df.mean()
-
-                folder_df = pd.concat([folder_df, df_avg.rename(column_name)], axis=1)
-            folder_df["node"] = language[i]
-            final_df = pd.concat([final_df, folder_df])
-
-        final_df = pd.melt(final_df, id_vars=["node"])
-
-        box_plot = sns.boxplot(data=final_df, x="variable", y="value", hue="node",
-                               ax=axs[j // 2, j % 2])
-        box_plot.set_title(f'{data_to_plot[j]} (N=300)')
-
-        box_plot.set(xlabel='Payload size (KB)', ylabel=f"{y_label[j]}")
-        box_plot.tick_params(labelbottom=True)
-        # plt.ylabel(f"{y_label[j]}")
-        # plt.xlabel('Payload size (KB)')
-
-        # sns.move_legend(box_plot, "upper left", bbox_to_anchor=(1, 1))
-        # plt.tight_layout()
-
-        if scale[j]:
-            # Create a custom formatter to divide x-axis ticks by 1000
-            formatter = ticker.FuncFormatter(lambda x, pos: '{:.0f}'.format(x / 1000))
-            # Apply the custom formatter to the x-axis ticks
-            box_plot.yaxis.set_major_formatter(formatter)
-
-    plt.tight_layout()
-    plt.savefig(f"all.png")
-    plt.show()
-    # box_plot.figure.savefig(f"{data_to_plot[j]}-melted.png")