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In [1]:

from pathlib    import Path
from typing     import Callable, Iterable, Optional, Tuple, Union

import sys
import  matplotlib.pyplot as plt
import  numpy as np

PROJECT_ROOT    =   Path.cwd().parent
sys.path.insert(0, str(PROJECT_ROOT))

print("Project Root:", PROJECT_ROOT)

from    src.visualizacion   import  (plot_xy, comparar_rondas, comparar_experimentos,
                                     plot_3D, plot_color_map, plot_dual_axis,
                                     plot_con_ajuste, marcar_zonas, sombrear_zonas, percent_change)
from    src.analysis        import  (calcular_pendiente, calcular_r2, derivada_numerica,
                                     segunda_derivada, variación_resistencia,
                                     comparar_pendientes, zonas_manual, detectar_zonas_auto,)
from    src.data_loader     import  (apply_filter, load_all)

DATA_DIR    =   PROJECT_ROOT / "data"
data        =   load_all(DATA_DIR)
print("Uploaded Data:", len(data))

Project Root: /Users/mguillermo/Desktop/MGPH/Maestria/Hydrogen_Exp/Analysis/2nd_AMIDIQ_Analysis

/Users/mguillermo/Desktop/MGPH/Maestria/Hydrogen_Exp/Analysis/2nd_AMIDIQ_Analysis/src/visualizacion.py:66: SyntaxWarning: "is" with 'str' literal. Did you mean "=="?
  if title is "False":
/Users/mguillermo/Desktop/MGPH/Maestria/Hydrogen_Exp/Analysis/2nd_AMIDIQ_Analysis/src/visualizacion.py:96: SyntaxWarning: "is" with 'str' literal. Did you mean "=="?
  if title is "False":

Uploaded Data: 8

Gráficas Generales de ambos experimentos¶

In [21]:

# Comparacion de Velec vs Ielec en ambos experimentos 

comparar_experimentos(data, ronda=1, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")
comparar_experimentos(data, ronda=2, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")

# Definicion de zonas de operacion ronda 1
zonas   =   [0.9692, 1.8713, 3.7383, 5.4]

fig, ax =   comparar_experimentos(data, ronda=1, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")
marcar_zonas(ax=ax, limites=zonas,
             labels=[
                 "No Conducción",
                 "Conducción",
                 "Generación",
                 "Saturación"
             ])
fig1, ax1 =   comparar_experimentos(data, ronda=1, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")
marcar_zonas(ax=ax1, limites=zonas,
             labels=[
                 "No Conducción",
                 "Conducción",
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax1, limites=zonas)

#Definicion de zonas de operacion ronda 2
fig2, ax2 =   comparar_experimentos(data, ronda=2, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")
marcar_zonas(ax=ax2, limites=zonas,
             labels=[
                 "No Conducción",
                 "Conducción",
                 "Generación",
                 "Saturación"
             ])
fig3, ax3 =   comparar_experimentos(data, ronda=2, x_col="Voltaje Electrodos (V)",
                      y_col="Corriente Electrodos (A)")
marcar_zonas(ax=ax3, limites=zonas,
             labels=[
                 "No Conducción",
                 "Conducción",
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax3, limites=zonas)
plt.show()

No description has been provided for this image

Evolucion de la Resistencia a traves de las distintas zonas¶

Conduccion - Saturación Ronda 1¶

In [22]:

st  = 10
end = 19
x   = "Voltaje Electrodos (V)"
y   = "Resistencia"

comparar_experimentos(data, ronda=1, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 1 - Comparación Resistencia en Zona de Conducción"
                      )

st  =   20
end =   45
comparar_experimentos(data, ronda=1, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 1 - Comparación Resistencia en Zona de Generación"
                      )

st  =   46
end =   66
comparar_experimentos(data, ronda=1, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 1 - Comparación Resistencia en Zona de Saturación"
                      )

Out[22]:

(<Figure size 700x500 with 1 Axes>,
 <Axes: title={'center': 'Ronda 1 - Comparación Resistencia en Zona de Saturación'}, xlabel='Voltaje Electrodos (V)', ylabel='Resistencia'>)

Conducción vs Saturación - Ronda 2¶

In [23]:

st  = 10
end = 19
x   = "Voltaje Electrodos (V)"
y   = "Resistencia"

comparar_experimentos(data, ronda=2, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 2 - Comparación Resistencia en Zona de Conducción"
                      )

st  =   20
end =   45
comparar_experimentos(data, ronda=2, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 2 - Comparación Resistencia en Zona de Generación"
                      )

st  =   46
end =   60
comparar_experimentos(data, ronda=2, x_col=x, y_col=y, 
                      filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                      title="Ronda 2 - Comparación Resistencia en Zona de Saturación"
                      )
comparar_rondas(data, experimento=1, x_col=x, y_col=y,
                filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                title="Experimento 1 - Comparativa de Resistencia de las Rondas 1 y 2 en Zona de Saturación")

comparar_rondas(data, experimento=2, x_col=x, y_col=y,
                filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                title="Experimento 2 - Comparativa de Resistencia de las Rondas 1 y 2 en Zona de Saturación")

comparar_rondas(data, experimento=3, x_col=x, y_col=y,
                filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                title="Experimento 3 - Comparativa de Resistencia de las Rondas 1 y 2 en Zona de Saturación")

comparar_rondas(data, experimento=4, x_col=x, y_col=y,
                filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end),
                title="Experimento 4 - Comparativa de Resistencia de las Rondas 1 y 2 en Zona de Saturación")

Out[23]:

(<Figure size 700x500 with 1 Axes>,
 <Axes: title={'center': 'Experimento 4 - Comparativa de Resistencia de las Rondas 1 y 2 en Zona de Saturación'}, xlabel='Voltaje Electrodos (V)', ylabel='Resistencia'>)

Resistencia vs Temperatura¶

Se realiza un analisis de la resistencia contra la temperatura de las respectivas rondas y solo de los experimentos 1 y 4. Esto en las zonas que comprende la conduccion y la saturación.

In [24]:

st      =   20
end     =   66
rnd1_1  =   apply_filter(data[(1,1)], row_start=20, row_end=end)
rnd1_4  =   apply_filter(data[(1,4)], row_start=st, row_end=end)
x       =   "Voltaje Electrodos (V)"
y       =   "Resistencia"
y1      =   "Temperatura"
zonas   =   [3.7383, 5.4]

fig, ax1, ax2 = plot_dual_axis(rnd1_1, x_col=x, y1_col=y, y2_col=y1,
               title= "Ronda 1 - Experimento 1 : Resistencia y Temperatura vs Voltaje Electrodos",)
marcar_zonas(ax=ax1, limites=zonas,
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax1, limites=zonas, colores=["blue", "green", "red"])

fig, ax3, ax4 = plot_dual_axis(rnd1_4, x_col=x, y1_col=y, y2_col=y1,
               title= "Ronda 1 - Experimento 4 : Resistencia y Temperatura vs Voltaje Electrodos",)
marcar_zonas(ax=ax3, limites=zonas,
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax3, limites=zonas, colores=["blue", "green", "red"])

In [25]:

st      =   20
end     =   60
rnd1_1  =   apply_filter(data[(2,1)], row_start=st, row_end=end)
rnd1_4  =   apply_filter(data[(2,4)], row_start=st, row_end=end)
x       =   "Voltaje Electrodos (V)"
y       =   "Resistencia"
y1      =   "Temperatura"
zonas   =   [3.7383, 5.4]

fig, ax1, ax2 = plot_dual_axis(rnd1_1, x_col=x, y1_col=y, y2_col=y1,
               title= "Ronda 2 - Experimento 1 : Resistencia y Temperatura vs Voltaje Electrodos",)
marcar_zonas(ax=ax1, limites=zonas,
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax1, limites=zonas, colores=["blue", "green", "red"])

fig, ax3, ax4 = plot_dual_axis(rnd1_4, x_col=x, y1_col=y, y2_col=y1,
               title= "Ronda 2 - Experimento 4 : Resistencia y Temperatura vs Voltaje Electrodos",)
marcar_zonas(ax=ax3, limites=zonas,
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax3, limites=zonas, colores=["blue", "green", "red"])

In [2]:

exp1    =   data[1,1]
exp2    =   data[1,2]
x       =   "Voltaje Electrodos (V)"
y       =   "Corriente Electrodos (A)"
r       =   "Resistencia"
t       =   "Temperatura"

# Definicion de zonas de operacion ronda 1
zonas   =   [0.9692, 1.8713, 3.7383, 5.4]

fig1, ax1 =   comparar_experimentos(data, ronda=1, x_col=x, y_col=y, experimentos=(1,2), title="False")
marcar_zonas(ax=ax1, limites=zonas,
             labels=[
                 "No Conducción",
                 "Conducción",
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax1, limites=zonas)
plt.show()

comparar_experimentos(data, ronda=1, x_col=x, y_col=r, 
                      filter_fn= lambda df: apply_filter(df, row_start=46, row_end=66),
                      experimentos=(1,2),title="")


exp1    =   apply_filter(data[1,1], row_start=20, row_end=66)
exp2    =   apply_filter(data[1,2], row_start=20, row_end=66)
fig, ax =   plt.subplots(1, 2, figsize=(12,5))

_, ax1, ax1b = plot_dual_axis(df=exp1,  x_col=x, y1_col=r, y2_col=t, ax=ax[0], title="(a)")
marcar_zonas(ax=ax[0], limites=[3.7383, 5.4], 
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax[0], limites=[3.7383, 5.4], colores=["blue","red"])

_, ax2, ax2b = plot_dual_axis(df=exp2,  x_col=x, y1_col=r, y2_col=t, ax=ax[1], title="(b)")
marcar_zonas(ax=ax[1], limites=[3.7383, 5.4], 
             labels=[
                 "Generación",
                 "Saturación"
             ])
sombrear_zonas(ax=ax[1], limites=[3.7383, 5.4], colores=["blue","red"])

ax1.set_ylim(0, 45)
ax2.set_ylim(0, 45)

ax1b.set_ylim(20, 60)
ax2b.set_ylim(20, 60)

plt.tight_layout()
plt.show()

Process data of the variance of the resistance in all the operation zones¶

$$ \% cambio = \frac{x_2-x_1}{x_1}*100 $$ {#eq:calc_res}

In [27]:

FilterFn    =   Callable[[object], object]
x           =   "Voltaje Electrodos (V)"
y           =   "Resistencia"
st          =   46
end         =   66

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(1,2),
               show=False, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(1,3),
               show=True, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(1,4),
               show=True, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(2,3),
               show=True, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(2,4),
               show=True, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(3,4),
               show=True, filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

percent_change(data=data, ronda=1, x_col=x, y_col=y, experimentos=(1,2),
               show=True, btween_exp=True,
               filter_fn= lambda df: apply_filter(df, row_start=st, row_end=end))

Δ% Experiment:1 between data 0 and 1: -3.48%
Δ% Experiment:1 between data 1 and 2: -3.14%
Δ% Experiment:1 between data 2 and 3: -3.14%
Δ% Experiment:1 between data 3 and 4: -3.23%
Δ% Experiment:1 between data 4 and 5: -2.77%
Δ% Experiment:1 between data 5 and 6: -2.97%
Δ% Experiment:1 between data 6 and 7: -3.19%
Δ% Experiment:1 between data 7 and 8: -4.55%
Δ% Experiment:1 between data 8 and 9: -2.77%
Δ% Experiment:1 between data 9 and 10: -2.97%
Δ% Experiment:1 between data 10 and 11: -2.62%
Δ% Experiment:1 between data 11 and 12: -3.04%
Δ% Experiment:1 between data 12 and 13: -2.64%
Δ% Experiment:1 between data 13 and 14: -2.71%
Δ% Experiment:1 between data 14 and 15: -2.51%
Δ% Experiment:1 between data 15 and 16: -2.45%
Δ% Experiment:1 between data 16 and 17: -2.68%
Δ% Experiment:1 between data 17 and 18: -2.25%
Δ% Experiment:1 between data 18 and 19: -2.72%
Δ% Experiment:2 between data 0 and 1: -3.22%
Δ% Experiment:2 between data 1 and 2: -4.05%
Δ% Experiment:2 between data 2 and 3: -2.92%
Δ% Experiment:2 between data 3 and 4: -3.08%
Δ% Experiment:2 between data 4 and 5: -3.01%
Δ% Experiment:2 between data 5 and 6: -2.90%
Δ% Experiment:2 between data 6 and 7: -2.71%
Δ% Experiment:2 between data 7 and 8: -2.89%
Δ% Experiment:2 between data 8 and 9: -3.12%
Δ% Experiment:2 between data 9 and 10: -3.04%
Δ% Experiment:2 between data 10 and 11: -2.72%
Δ% Experiment:2 between data 11 and 12: -3.13%
Δ% Experiment:2 between data 12 and 13: -2.52%
Δ% Experiment:2 between data 13 and 14: -2.96%
Δ% Experiment:2 between data 14 and 15: -2.50%
Δ% Experiment:2 between data 15 and 16: -2.82%
Δ% Experiment:2 between data 16 and 17: -2.63%
Δ% Experiment:2 between data 17 and 18: -2.19%
Δ% Experiment:2 between data 18 and 19: -0.63%
Δ% Experiment:1 between data 0 and 1: -3.48%
Δ% Experiment:1 between data 1 and 2: -3.14%
Δ% Experiment:1 between data 2 and 3: -3.14%
Δ% Experiment:1 between data 3 and 4: -3.23%
Δ% Experiment:1 between data 4 and 5: -2.77%
Δ% Experiment:1 between data 5 and 6: -2.97%
Δ% Experiment:1 between data 6 and 7: -3.19%
Δ% Experiment:1 between data 7 and 8: -4.55%
Δ% Experiment:1 between data 8 and 9: -2.77%
Δ% Experiment:1 between data 9 and 10: -2.97%
Δ% Experiment:1 between data 10 and 11: -2.62%
Δ% Experiment:1 between data 11 and 12: -3.04%
Δ% Experiment:1 between data 12 and 13: -2.64%
Δ% Experiment:1 between data 13 and 14: -2.71%
Δ% Experiment:1 between data 14 and 15: -2.51%
Δ% Experiment:1 between data 15 and 16: -2.45%
Δ% Experiment:1 between data 16 and 17: -2.68%
Δ% Experiment:1 between data 17 and 18: -2.25%
Δ% Experiment:1 between data 18 and 19: -2.72%
Δ% Experiment:3 between data 0 and 1: -2.96%
Δ% Experiment:3 between data 1 and 2: -2.98%
Δ% Experiment:3 between data 2 and 3: -3.08%
Δ% Experiment:3 between data 3 and 4: -2.76%
Δ% Experiment:3 between data 4 and 5: -2.76%
Δ% Experiment:3 between data 5 and 6: -4.61%
Δ% Experiment:3 between data 6 and 7: -2.98%
Δ% Experiment:3 between data 7 and 8: -3.10%
Δ% Experiment:3 between data 8 and 9: -2.09%
Δ% Experiment:3 between data 9 and 10: -2.81%
Δ% Experiment:3 between data 10 and 11: -2.91%
Δ% Experiment:3 between data 11 and 12: -2.65%
Δ% Experiment:3 between data 12 and 13: -2.82%
Δ% Experiment:3 between data 13 and 14: -2.60%
Δ% Experiment:3 between data 14 and 15: -2.81%
Δ% Experiment:3 between data 15 and 16: -2.56%
Δ% Experiment:3 between data 16 and 17: -3.54%
Δ% Experiment:3 between data 17 and 18: -2.35%
Δ% Experiment:3 between data 18 and 19: -3.28%

Δ% Experiment:1 between data 0 and 1: -3.48%
Δ% Experiment:1 between data 1 and 2: -3.14%
Δ% Experiment:1 between data 2 and 3: -3.14%
Δ% Experiment:1 between data 3 and 4: -3.23%
Δ% Experiment:1 between data 4 and 5: -2.77%
Δ% Experiment:1 between data 5 and 6: -2.97%
Δ% Experiment:1 between data 6 and 7: -3.19%
Δ% Experiment:1 between data 7 and 8: -4.55%
Δ% Experiment:1 between data 8 and 9: -2.77%
Δ% Experiment:1 between data 9 and 10: -2.97%
Δ% Experiment:1 between data 10 and 11: -2.62%
Δ% Experiment:1 between data 11 and 12: -3.04%
Δ% Experiment:1 between data 12 and 13: -2.64%
Δ% Experiment:1 between data 13 and 14: -2.71%
Δ% Experiment:1 between data 14 and 15: -2.51%
Δ% Experiment:1 between data 15 and 16: -2.45%
Δ% Experiment:1 between data 16 and 17: -2.68%
Δ% Experiment:1 between data 17 and 18: -2.25%
Δ% Experiment:1 between data 18 and 19: -2.72%
Δ% Experiment:4 between data 0 and 1: -2.97%
Δ% Experiment:4 between data 1 and 2: -3.02%
Δ% Experiment:4 between data 2 and 3: -4.44%
Δ% Experiment:4 between data 3 and 4: -2.78%
Δ% Experiment:4 between data 4 and 5: -3.90%
Δ% Experiment:4 between data 5 and 6: -2.38%
Δ% Experiment:4 between data 6 and 7: -2.67%
Δ% Experiment:4 between data 7 and 8: -2.58%
Δ% Experiment:4 between data 8 and 9: -2.79%
Δ% Experiment:4 between data 9 and 10: -2.68%
Δ% Experiment:4 between data 10 and 11: -3.77%
Δ% Experiment:4 between data 11 and 12: -1.36%
Δ% Experiment:4 between data 12 and 13: -2.80%
Δ% Experiment:4 between data 13 and 14: -2.68%
Δ% Experiment:4 between data 14 and 15: -2.70%
Δ% Experiment:4 between data 15 and 16: -4.72%
Δ% Experiment:4 between data 16 and 17: -2.29%
Δ% Experiment:4 between data 17 and 18: -2.33%
Δ% Experiment:4 between data 18 and 19: -2.31%

Δ% Experiment:2 between data 0 and 1: -3.22%
Δ% Experiment:2 between data 1 and 2: -4.05%
Δ% Experiment:2 between data 2 and 3: -2.92%
Δ% Experiment:2 between data 3 and 4: -3.08%
Δ% Experiment:2 between data 4 and 5: -3.01%
Δ% Experiment:2 between data 5 and 6: -2.90%
Δ% Experiment:2 between data 6 and 7: -2.71%
Δ% Experiment:2 between data 7 and 8: -2.89%
Δ% Experiment:2 between data 8 and 9: -3.12%
Δ% Experiment:2 between data 9 and 10: -3.04%
Δ% Experiment:2 between data 10 and 11: -2.72%
Δ% Experiment:2 between data 11 and 12: -3.13%
Δ% Experiment:2 between data 12 and 13: -2.52%
Δ% Experiment:2 between data 13 and 14: -2.96%
Δ% Experiment:2 between data 14 and 15: -2.50%
Δ% Experiment:2 between data 15 and 16: -2.82%
Δ% Experiment:2 between data 16 and 17: -2.63%
Δ% Experiment:2 between data 17 and 18: -2.19%
Δ% Experiment:2 between data 18 and 19: -0.63%
Δ% Experiment:3 between data 0 and 1: -2.96%
Δ% Experiment:3 between data 1 and 2: -2.98%
Δ% Experiment:3 between data 2 and 3: -3.08%
Δ% Experiment:3 between data 3 and 4: -2.76%
Δ% Experiment:3 between data 4 and 5: -2.76%
Δ% Experiment:3 between data 5 and 6: -4.61%
Δ% Experiment:3 between data 6 and 7: -2.98%
Δ% Experiment:3 between data 7 and 8: -3.10%
Δ% Experiment:3 between data 8 and 9: -2.09%
Δ% Experiment:3 between data 9 and 10: -2.81%
Δ% Experiment:3 between data 10 and 11: -2.91%
Δ% Experiment:3 between data 11 and 12: -2.65%
Δ% Experiment:3 between data 12 and 13: -2.82%
Δ% Experiment:3 between data 13 and 14: -2.60%
Δ% Experiment:3 between data 14 and 15: -2.81%
Δ% Experiment:3 between data 15 and 16: -2.56%
Δ% Experiment:3 between data 16 and 17: -3.54%
Δ% Experiment:3 between data 17 and 18: -2.35%
Δ% Experiment:3 between data 18 and 19: -3.28%

Δ% Experiment:2 between data 0 and 1: -3.22%
Δ% Experiment:2 between data 1 and 2: -4.05%
Δ% Experiment:2 between data 2 and 3: -2.92%
Δ% Experiment:2 between data 3 and 4: -3.08%
Δ% Experiment:2 between data 4 and 5: -3.01%
Δ% Experiment:2 between data 5 and 6: -2.90%
Δ% Experiment:2 between data 6 and 7: -2.71%
Δ% Experiment:2 between data 7 and 8: -2.89%
Δ% Experiment:2 between data 8 and 9: -3.12%
Δ% Experiment:2 between data 9 and 10: -3.04%
Δ% Experiment:2 between data 10 and 11: -2.72%
Δ% Experiment:2 between data 11 and 12: -3.13%
Δ% Experiment:2 between data 12 and 13: -2.52%
Δ% Experiment:2 between data 13 and 14: -2.96%
Δ% Experiment:2 between data 14 and 15: -2.50%
Δ% Experiment:2 between data 15 and 16: -2.82%
Δ% Experiment:2 between data 16 and 17: -2.63%
Δ% Experiment:2 between data 17 and 18: -2.19%
Δ% Experiment:2 between data 18 and 19: -0.63%
Δ% Experiment:4 between data 0 and 1: -2.97%
Δ% Experiment:4 between data 1 and 2: -3.02%
Δ% Experiment:4 between data 2 and 3: -4.44%
Δ% Experiment:4 between data 3 and 4: -2.78%
Δ% Experiment:4 between data 4 and 5: -3.90%
Δ% Experiment:4 between data 5 and 6: -2.38%
Δ% Experiment:4 between data 6 and 7: -2.67%
Δ% Experiment:4 between data 7 and 8: -2.58%
Δ% Experiment:4 between data 8 and 9: -2.79%
Δ% Experiment:4 between data 9 and 10: -2.68%
Δ% Experiment:4 between data 10 and 11: -3.77%
Δ% Experiment:4 between data 11 and 12: -1.36%
Δ% Experiment:4 between data 12 and 13: -2.80%
Δ% Experiment:4 between data 13 and 14: -2.68%
Δ% Experiment:4 between data 14 and 15: -2.70%
Δ% Experiment:4 between data 15 and 16: -4.72%
Δ% Experiment:4 between data 16 and 17: -2.29%
Δ% Experiment:4 between data 17 and 18: -2.33%
Δ% Experiment:4 between data 18 and 19: -2.31%

Δ% Experiment:3 between data 0 and 1: -2.96%
Δ% Experiment:3 between data 1 and 2: -2.98%
Δ% Experiment:3 between data 2 and 3: -3.08%
Δ% Experiment:3 between data 3 and 4: -2.76%
Δ% Experiment:3 between data 4 and 5: -2.76%
Δ% Experiment:3 between data 5 and 6: -4.61%
Δ% Experiment:3 between data 6 and 7: -2.98%
Δ% Experiment:3 between data 7 and 8: -3.10%
Δ% Experiment:3 between data 8 and 9: -2.09%
Δ% Experiment:3 between data 9 and 10: -2.81%
Δ% Experiment:3 between data 10 and 11: -2.91%
Δ% Experiment:3 between data 11 and 12: -2.65%
Δ% Experiment:3 between data 12 and 13: -2.82%
Δ% Experiment:3 between data 13 and 14: -2.60%
Δ% Experiment:3 between data 14 and 15: -2.81%
Δ% Experiment:3 between data 15 and 16: -2.56%
Δ% Experiment:3 between data 16 and 17: -3.54%
Δ% Experiment:3 between data 17 and 18: -2.35%
Δ% Experiment:3 between data 18 and 19: -3.28%
Δ% Experiment:4 between data 0 and 1: -2.97%
Δ% Experiment:4 between data 1 and 2: -3.02%
Δ% Experiment:4 between data 2 and 3: -4.44%
Δ% Experiment:4 between data 3 and 4: -2.78%
Δ% Experiment:4 between data 4 and 5: -3.90%
Δ% Experiment:4 between data 5 and 6: -2.38%
Δ% Experiment:4 between data 6 and 7: -2.67%
Δ% Experiment:4 between data 7 and 8: -2.58%
Δ% Experiment:4 between data 8 and 9: -2.79%
Δ% Experiment:4 between data 9 and 10: -2.68%
Δ% Experiment:4 between data 10 and 11: -3.77%
Δ% Experiment:4 between data 11 and 12: -1.36%
Δ% Experiment:4 between data 12 and 13: -2.80%
Δ% Experiment:4 between data 13 and 14: -2.68%
Δ% Experiment:4 between data 14 and 15: -2.70%
Δ% Experiment:4 between data 15 and 16: -4.72%
Δ% Experiment:4 between data 16 and 17: -2.29%
Δ% Experiment:4 between data 17 and 18: -2.33%
Δ% Experiment:4 between data 18 and 19: -2.31%

Δ% Punto 0: Exp1 vs Exp2 = -4.31%
Δ% Punto 1: Exp1 vs Exp2 = -4.05%
Δ% Punto 2: Exp1 vs Exp2 = -4.95%
Δ% Punto 3: Exp1 vs Exp2 = -4.74%
Δ% Punto 4: Exp1 vs Exp2 = -4.59%
Δ% Punto 5: Exp1 vs Exp2 = -4.82%
Δ% Punto 6: Exp1 vs Exp2 = -4.75%
Δ% Punto 7: Exp1 vs Exp2 = -4.28%
Δ% Punto 8: Exp1 vs Exp2 = -2.61%
Δ% Punto 9: Exp1 vs Exp2 = -2.96%
Δ% Punto 10: Exp1 vs Exp2 = -3.04%
Δ% Punto 11: Exp1 vs Exp2 = -3.14%
Δ% Punto 12: Exp1 vs Exp2 = -3.24%
Δ% Punto 13: Exp1 vs Exp2 = -3.12%
Δ% Punto 14: Exp1 vs Exp2 = -3.37%
Δ% Punto 15: Exp1 vs Exp2 = -3.36%
Δ% Punto 16: Exp1 vs Exp2 = -3.72%
Δ% Punto 17: Exp1 vs Exp2 = -3.66%
Δ% Punto 18: Exp1 vs Exp2 = -3.60%
Δ% Punto 19: Exp1 vs Exp2 = -1.53%

Out[27]:

(<Figure size 700x500 with 1 Axes>,
 <Axes: title={'center': 'Round 1 - Experiments Comparative'}, xlabel='Voltaje Electrodos (V)', ylabel='Resistencia'>)

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