from matplotlib import pyplot as plt import numpy as np from clase_graficar import Graficar from clase_crear_lienzo import Crear_lienzo import EC_kinetics as ec_data import pHkinetics_datos as ph_data ##Instancias de clases ph_data = ph_data.ph_kinetics.drop(0) ec_data = ec_data.ec_kinetics.drop(0) lienzo = Crear_lienzo(12, 6, 0, 0) graficar = Graficar(15, 14, 15, 13, 13, 12) ec_data = ec_data ph_data = ph_data ##Varibles comunes marker = '.' linewidth = 0.5 elinewidth = 0.25 capsize = 2 capthick = 0.5 markersize = 5 ylim = (2, 10) ##Crear lienzo del gráfico fig = lienzo.crear_figura(left=0.07, bottom=0.2, right=0.99, top=0.92) time = ec_data['Monitoring time (days)'][1:6] ###Batch 1
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from clase_crear_lienzo import Crear_lienzo
from clase_gestionar_datos import Gestionar_datos
from clase_graficar import Graficar
import Morphology_graphs as Morphology
from clase_crear_lienzo import Crear_lienzo
morpho = Morphology
graficar = Graficar(14, 16, 13, 13, 13, 10)
lienzo = Crear_lienzo(20, 12, 0.1, 0.3)
treatments = ['S0', 'S1', 'S2', 'S3', 'S4', 'S5']
x = np.arange(len(treatments))
width = 0.25
error_kw = {
"elinewidth": 0.5,
"capsize": 2,
"capthick": 0.5,
"barsabove": True,
}
linewidth = 1.5
y_lim_length = (0, 800)
y_lim_width = (0, 13)
y_lim_spiralization = (0, 180)
y_lim_helix = (0, 100)
# fig = plt.figure(figsize=(20, 12))
# fig.subplots_adjust(left=0.08, bottom=0.2, right=0.98, top=0.92)
##################################Length#################################################################
from matplotlib import pyplot as plt import numpy as np from clase_graficar import Graficar from clase_crear_lienzo import Crear_lienzo import EC_kinetics as ec_data import pHkinetics_datos as ph_data ##Instancias de clases lienzo = Crear_lienzo(12, 6, 0.1, 0.3) graficar = Graficar(12, 12, 10, 10, 10, 10) ec_data = ec_data ph_data = ph_data ##Varibles comunes treatments = ['DW1', 'DW2', 'DW3', 'DW4', 'DW5', 'DW6'] marker = '.' linewidth = 0.5 elinewidth = 0.25 capsize = 2 capthick = 0.5 color_dww = '#2B2B2B' color_sup1 = '#6A6A6A' color_sup2 = '#9D9D9D' color_sup4 = '#B9B9B9' color_sup5 = '#C3C3C3' color_sup3 = '#D7D7D7' ##Crear lienzo del gráfico fig = lienzo.crear_figura(left=0.03, bottom=0.2, right=0.98, top=0.92) ##Gráfico EC
x_lim = (0, 12)
batch1_color = '#6A6A6A'
batch2_color = '#9D9D9D'
batch3_color = '#D7D7D7'
treatments = ['DW', 'DW1', 'DW2', 'DW3', 'DW4', 'DW5']
barwidth = 0.25
error_kw = {"elinewidth": 0.5,
"capsize": 2,
"capthick": 0.5,
"barsabove": True,
}
##Instanciar clases
lienzo = Crear_lienzo(10, 6, 0.5, 0.5)
excel = Gestionar_datos()
graficar = Graficar(11, 11, 14, 12, 12, 10)
##Crear lienzo del gráfico
fig = lienzo.crear_figura()
##Leer excel
spiralization_dataframe = excel.leer_excel('D:\Cindy\Ingeniería\Maestría\Resultados\R2L\Summup data.xlsx', 'Spiralization_triplicate')
##Arrays lote 1
##ARL Lote 1
arl1_day12 = excel.crear_array(spiralization_dataframe, 'ARL_12', 0, 20)
arl_prom_1 = np.average(arl1_day12)
arlsd_1 = np.std(arl1_day12, ddof=sample_sd)
arlsem_1 = sem(arl1_day12)
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import Figure
import matplotlib.pylab as pylab
from scipy.stats import sem
from clase_gestionar_datos import Gestionar_datos
from clase_graficar import Graficar
from clase_crear_lienzo import Crear_lienzo
##Instancias de clases
excel = Gestionar_datos()
lienzo = Crear_lienzo(12, 6, 0.1, 0.3)
graficar = Graficar(15, 15, 13, 13, 13, 11)
##Varibles comunes
treatments = ['S0', 'S1', 'S2', 'S3', 'S4', 'S5']
barwidth = 0.25
batch1_color = '#6A6A6A'
batch2_color = '#9D9D9D'
batch3_color = '#D7D7D7'
#Leer datos de excel
pmax_df = excel.leer_excel(
'D:\Cindy\Ingeniería\Maestría\Resultados\R2L\Summup data.xlsx', 'pmax')
batch = pmax_df['Batch']
pmax = pmax_df.drop(columns=['Batch'])
# pmax_arl = np.array(list(pmax['ARL']))
# pmax_arl_mean = np.mean(pmax_arl)
marker_linewidth = 0.2
marker_size = 100
ylim = (100, 600)
xlim = (1.25, 1.9)
ypad = 9
xpad = 4
marker_scatter = 'o'
marker_dispersion = 's'
line_style = '--'
norm_nitrogen = mpl.colors.Normalize(vmin=0, vmax=7)
norm_phosphorus = mpl.colors.Normalize(vmin=0, vmax=0.5)
#Instanciar clases
lienzo = Crear_lienzo(15, 5, 0.5, 0.2)
excel = Gestionar_datos()
graficar = Graficar(12, 12, 12, 10, 10, 15)
##Crear lienzo del gráfico
fig = lienzo.crear_figura()
##Leer excel
length_data = excel.leer_excel(
'D:\Cindy\Ingeniería\Maestría\Resultados\R2L\AnalisisN-P-C-12.xlsx',
'Graph data length')
##Data
carbon = np.array(excel.crear_lista(length_data, 'total carbon', 0, 15))
carbon_nitrogen = np.array(
excel.crear_lista(length_data, 'nitrogen_carbon', 0, 15))
carbon_phosphorus = np.array(
excel.crear_lista(length_data, 'phosphorus_carbon', 0, 15))
from matplotlib.pyplot import Figure
import matplotlib.pylab as pylab
from clase_crear_lienzo import Crear_lienzo
from clase_gestionar_datos import Gestionar_datos
from clase_graficar import Graficar
#Variables comunes
days = [3, 6, 9, 12]
sample_sd = 1
y_lim = (0, 800)
x_lim = (0, 12)
##Instanciar clases
lienzo = Crear_lienzo(15, 6, 0.5, 0.5)
excel = Gestionar_datos()
graficar = Graficar(11, 11, 14, 12, 12, 10)
##Crear lienzo del gráfico
fig = lienzo.crear_figura()
##Leer excel
length_dataframe = excel.leer_excel('D:\Cindy\Ingeniería\Maestría\Resultados\R2L\Summup data.xlsx', 'Length_triplicate')
##Arrays lote 1
##ARL Lote 1
arl1_day3 = excel.crear_array(length_dataframe, 'ARL_3', 0, 20)
arl1_day6 = excel.crear_array(length_dataframe, 'ARL_6', 0, 20)
arl1_day9 = excel.crear_array(length_dataframe, 'ARL_9', 0, 20)
arl1_day12 = excel.crear_array(length_dataframe, 'ARL_12', 0, 20)
from matplotlib import cm
#Variables comunes
line_color = 'black'
marker = 'o'
marker_edge = 'black'
marker_linewidth = 0.2
marker_size = 100
ylim = (0, 900)
ypad = 9
xpad = 4
#Instanciar clases
lienzo = Crear_lienzo(15, 15, 0.6, 0.4)
excel = Gestionar_datos()
graficar = Graficar(13, 13, 16, 14, 12, 12)
##Crear lienzo del gráfico
fig = lienzo.crear_figura()
##Leer excel
correlacion_data = excel.leer_excel('D:\Cindy\Ingeniería\Maestría\Resultados\R2L\AnalisisN-P-C.xlsx', 'Graph data')
##Carbon data
carbon = excel.crear_lista(correlacion_data, 'Total carbon', 0, 15)
carbon_biomass = excel.crear_lista(correlacion_data, ' Biomass carbon', 0, 15)
carbon_nitrogen = excel.crear_lista(correlacion_data, 'Carbon_Nitrogen', 0, 15)
carbon_phosphorus = excel.crear_lista(correlacion_data, 'Carbon_Phosphorus', 0, 15)
##Nitrogen data
nitrogen = excel.crear_lista(correlacion_data, 'Total nitrogen', 0, 15)
from numpy.lib.arraypad import pad import pandas as pd import numpy as np import matplotlib.pyplot as plt from matplotlib.pyplot import Figure import matplotlib.pylab as pylab from clase_crear_lienzo import Crear_lienzo from clase_gestionar_datos import Gestionar_datos from clase_graficar import Graficar #Instanciar clases #lienzo = Crear_lienzo(10, 20, 0.6, 0.4) lienzo = Crear_lienzo(30, 12, 0, 0) graficar = Graficar(34, 34, 34, 32, 32, 2) excel = Gestionar_datos() #Parámetros comunes ylim = (0, 1600) ypad = 2 xpad = 7 xticks = [0, 3, 6, 9, 12] yticks = [0, 200, 400, 600, 800, 1000, 1200, 1400, 1600] font_size = 16 markersize = 13 ##Crear lienzo del gráfico # lienzo.largo_fig = 30 fig = lienzo.crear_figura(left=0.06, bottom=0.2, right=0.98, top=0.92) ##Leer excel
batch1_color = '#6A6A6A'
batch2_color = '#9D9D9D'
batch3_color = '#D7D7D7'
treatments = ['S0', 'S1', 'S2', 'S3', 'S4', 'S5']
barwidth = 0.25
error_kw = {
"elinewidth": 0.5,
"capsize": 2,
"capthick": 0.5,
"barsabove": True,
}
##Instanciar clases
lienzo = Crear_lienzo(15, 12, 0.2, 0.2)
excel = Gestionar_datos()
graficar = Graficar(11, 11, 14, 12, 12, 10)
##Crear lienzo del gráfico
fig = lienzo.crear_figura()
####################################Length##############################################
##Leer excel
length_dataframe = excel.leer_excel(
'D:\Cindy\Ingeniería\Maestría\Resultados\R2L\Summup data.xlsx',
'Length_triplicate')
##Arrays lote 1
##ARL Lote 1
s01_day12_length = excel.crear_array(length_dataframe, 'ARL_12', 0, 20)
s0_prom_1_length = np.nanmean(s01_day12_length)