Commit 0e5e2fbd authored by Maiterth, Matthias's avatar Maiterth, Matthias
Browse files

Plotting script and ui NaN bug

parent 449699af

raps/dataloaders/plot3.py

0 → 100644
+152 −0
Original line number Diff line number Diff line 
#!/bin/env python3

import pandas as pd

import pyarrow.parquet as pq

import matplotlib.pyplot as plt



style=['seaborn-v0_8', 'tableau-colorblind10']



for j in range(-1,len(style)):

    if j in range(0,len(style)):

        plt.style.use(style[j])



        colors = plt.rcParams['axes.prop_cycle'].by_key()['color']

        # Revert to the default style

        plt.style.use('default')

        # Apply ggplot colors to default style

        plt.rcParams['axes.prop_cycle'] = plt.cycler(color=colors)





    import sys



    if len(sys.argv) > 1:

        path = sys.argv[1]

    else:

        print(f"Usage: python {sys.argv[0]} <simulation_result/dir>")

        exit()



    # e.g. path = "$HOME/Repositories/exadigit/raps/simulation_results/b803010"



    policies = ['fcfs-nobf','fcfs-easy','priority-nobf','priority-easy','priority-ffbf','replay']

    files = ['cooling_model.parquet', 'loss_history.parquet', 'power_history.parquet', 'util.parquet']

    files = ['cooling_model.parquet', 'power_history.parquet', 'util.parquet']

    files = ['util.parquet', 'power_history.parquet', 'cooling_model.parquet']

    #files = ['loss_history.parquet', 'power_history.parquet', 'util.parquet']

    #files = ['power_history.parquet', 'util.parquet', 'cooling_model.parquet']



    policy_path = {f"{policy}":f"{path}/{policy}" for policy in policies}

    full_files = {f"{policy}":f"{path}/{policy}/{file}" for policy in policies for file in files}





    def iter_to_seconds(i):

        return i * 15





    fig, axs = plt.subplots(len(files),figsize=(12, 12))

    for i,file in enumerate(files):

        policy_files = [f"{path}/{policy}/{file}" for policy in policies]

        for policy_file in policy_files:

            # df = pd.read_parquet(policy_file)

            x = 'time'

            policy = policy_file.split('/')[-2]

            if file == "power_history.parquet":

                y = 'power [kw]'

                ylab = 'Power [kW]'

                ylim = 29000

                axs[i].set_ylim(0,ylim)



                df = pd.read_parquet(policy_file)

                df = df.rename(columns={0:'time',1:'power [kw]'})



            elif file == "cooling_model.parquet":

                y = 'pue'

                ylab = 'PUE'



                df = pd.read_parquet(policy_file)

                df['index'] = df.index

                df[x] = df['index'].apply(iter_to_seconds)

                ymax = max(df['pue'])

                #axs[i].plot(df[x],df[y], label=ylab)



            elif file == "loss_history.parquet":

                y = 'loss [kw]'

                ylab = 'Loss [kW]'

                ylim = 29000

                axs[i].set_ylim(0,ylim)



                df = pd.read_parquet(policy_file)

                df = df.rename(columns={0:'time',1:'loss [kw]'})

                #axs[i].plot(df[x],df[y], label=ylab)



            elif file == "util.parquet":

                y = 'utilization'

                ylab = 'Utilization'



                df = pd.read_parquet(policy_file)

                df = df.rename(columns={0:'time', 1:'utilization [%]'})

                df[y] = df['utilization [%]'] / 100

                #axs[i].plot(df[x], df[y], label=ylab)



            else:

                raise KeyError



            axs[i].plot(df[x],df[y], label=policy)

            axs[i].set_ylabel(ylab)

            #$axs[i].plot(df[0],df[1],label=policy)

        if file == "power_history.parquet":

            axs[i].legend(loc='upper right')

            axs[i].set_title('Power')

        elif file == "util.parquet":

            axs[i].set_title('Utilization')

            axs[i].legend(loc='lower right')

        elif file == "cooling_model.parquet":

            axs[i].set_title('PUE')

            axs[i].legend(loc='upper right')

        elif file == "loss_history.parquet":

            axs[i].set_title('Loss')

            axs[i].legend(loc='upper right')

        else:

            raise KeyError()

    #plt.show()

    plt.savefig(f"Type{[j]}.png")





    #for i in [1]:

    #    fig, ax1 = plt.subplots(figsize=(10, 6))

    #

    #    power = path + "/" + files[2]

    #    loss = path + "/" + files[1]

    #    util = path + "/" + files[3]

    #

    #    df_power = pd.read_parquet(power)

    #    df_power = df_power.rename(columns={0:'time',1:'power [kw]'})

    #    ax1.plot(df_power['time'],df_power['power [kw]'], color='black', label='Power kW]')

    #

    #    #df_loss = pd.read_parquet(loss)

    #    #df_loss = df_loss.rename(columns={0:'time',1:'loss [kw]'})

    #    #ax1.plot(df_loss['time'],df_loss['loss [kw]'], color='red', label='Loss [kW]')

    #

    #    ax2 = ax1.twinx()

    #

    #    #df_cooling = pd.read_parquet(cooling)

    #    #df_cooling['index'] = df_cooling.index

    #    #df_cooling['time'] = df_cooling['index'].apply(iter_to_seconds)

    #    #ymax = max(df_cooling['pue'])

    #    #ax2.plot(df_cooling['time'],df_cooling['pue'], color='blue', label='PUE')

    #

    #    df_util = pd.read_parquet(util)

    #    df_util = df_util.rename(columns={0:'time', 1:'utilization [%]'})

    #    df_util['utilization'] = df_util['utilization [%]'] / 100

    #    ax2.plot(df_util['time'],df_util['utilization'], color='orange', label='Utilization')

    #

    #    #ymax = max(max(df_cooling['pue']),max(df_util['utilization']))

    #    ymax = max(0,max(df_util['utilization']))

    #    ax2.set_ylim([0, ymax * 1.05])

    #

    #    ax1.set_xlabel('time [s]')

    #    ax1.set_ylabel('[kW]')

    #    ax2.set_ylabel('[%]')

    #    plt.title(path)

    #    ax1.legend(loc='upper left')

    #    ax2.legend(loc='upper right')

    #    plt.show()

    #    #plt.savefig("test.png")

raps/ui.py

+8 −0
Original line number Diff line number Diff line 
import sys

import pandas as pd

import numpy as np

from rich.align import Align

from rich.console import Console

from rich.layout import Layout
@@ -268,6 +270,9 @@ class LayoutManager: 
        if uncertainties:

            pass

        else:

            power_df = power_df.replace([np.nan],0.0)

            power_df = power_df.replace([np.inf],sys.maxsize)

            power_df = power_df.replace([-np.inf], -sys.maxsize - 1)

            power_df = power_df[power_columns].astype(int)



        # Populate the table with data from the DataFrame, applying the data styles
@@ -332,6 +337,9 @@ class LayoutManager: 
        if uncertainties:

            pass

        else:

            power_df = power_df.replace([np.nan],0.0)

            power_df = power_df.replace([np.inf],sys.maxsize)

            power_df = power_df.replace([-np.inf], -sys.maxsize - 1)

            power_df = power_df[display_columns].round().astype(int)



        # Create table for displaying rack power and loss with styling

scripts/plot_p-util_t.py

+31 −12
Original line number Diff line number Diff line
@@ -5,6 +5,8 @@ import matplotlib.pyplot as plt 


import sys







if len(sys.argv) > 1:

    path = sys.argv[1]

else:
@@ -22,43 +24,60 @@ def iter_to_seconds(i): 
    return i * 15





SMALL_SIZE = 16

MEDIUM_SIZE = 18

BIGGER_SIZE = 22



plt.rc('font', size=SMALL_SIZE)          # controls default text sizes

plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title

plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels

plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels

plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels

plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize

plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title







for i in [1]:

    fig, ax1 = plt.subplots(figsize=(10, 6))



    power = path + "/" + files[2]

    loss = path + "/" + files[1]

    util = path + "/" + files[3]

    cooling = path + "/" + files[0]



    df_power = pd.read_parquet(power)

    df_power = df_power.rename(columns={0:'time',1:'power [kw]'})

    ax1.plot(df_power['time'],df_power['power [kw]'], color='black', label='Power kW]')



    #df_loss = pd.read_parquet(loss)

    #df_loss = df_loss.rename(columns={0:'time',1:'loss [kw]'})

    #ax1.plot(df_loss['time'],df_loss['loss [kw]'], color='red', label='Loss [kW]')

    df_loss = pd.read_parquet(loss)

    df_loss = df_loss.rename(columns={0:'time',1:'loss [kw]'})

    ax1.plot(df_loss['time'],df_loss['loss [kw]'], color='red', label='Loss [kW]')



    ax2 = ax1.twinx()



    #df_cooling = pd.read_parquet(cooling)

    #df_cooling['index'] = df_cooling.index

    #df_cooling['time'] = df_cooling['index'].apply(iter_to_seconds)

    #ymax = max(df_cooling['pue'])

    #ax2.plot(df_cooling['time'],df_cooling['pue'], color='blue', label='PUE')

    df_cooling = pd.read_parquet(cooling)

    df_cooling['index'] = df_cooling.index

    df_cooling['time'] = df_cooling['index'].apply(iter_to_seconds)

    ymax = max(df_cooling['pue'])

    ax2.plot(df_cooling['time'],df_cooling['pue'], color='blue', label='PUE')



    df_util = pd.read_parquet(util)

    df_util = df_util.rename(columns={0:'time', 1:'utilization [%]'})

    df_util['utilization'] = df_util['utilization [%]'] / 100

    ax2.plot(df_util['time'],df_util['utilization'], color='orange', label='Utilization')



    #ymax = max(max(df_cooling['pue']),max(df_util['utilization']))

    ymax = max(0,max(df_util['utilization']))

    ymax = max(max(df_cooling['pue']),max(df_util['utilization']))

    #ymax = max(0,max(df_util['utilization']))

    ax2.set_ylim([0, ymax * 1.05])



    ax1.set_xlabel('time [s]')

    ax1.set_ylabel('[kW]')

    ax2.set_ylabel('[%]')

    plt.title(path)

    #path

    #plt.title(path)

    ax1.legend(loc='upper left')

    ax2.legend(loc='upper right')

    #plt.rcParams.update({'font.size': 30})

    #plt.show()

    plt.savefig("test.png")