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isowater_SEPregion.py
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isowater_SEPregion.py
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"""
Code made by Francisco Garcia Araya garcicia@gmail.com
this code was written for a specific scientific research, and its reproduction for commercial use is forbidden
IMPORTANT!!!!
read and complete the configuration parameters before use
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from scipy.stats import linregress
from scipy.stats import mannwhitneyu
def isNaN(num):
if float('-inf') < float(num) < float('inf'):
return 0
else:
return 1
"""
__
/ \
| STOP |
\ __ /
||
||
||
||
||
~~~~~~~
if the code is not working apropiately comente the next line
"""
np.warnings.filterwarnings('ignore')
"""
names of files and list of names
"""
print("The whale means a successful execution of this code")
print("don't worry about warnings or other messages that code can give you")
print(" ")
boats= ('13C_coast.boat','18O_ocean.boat', 'dd_coast.boat', '13C_ocean.boat', 'dd_ocean.boat', '18O_coast.boat') # names of files with isotopic values
boatsT= ('13C Coast','18O Ocean', 'dd Coast', '13C Ocean', 'dd Ocean', '18O Coast') #names for the titles writting
c_o=(1,0,1,0,0,1) #configuration if is acoastal or oceanic value
sal_isotopic_x=([32.5,36.],[32.5,36.] , [32.5,36.], [32.5,36.],[32.5,36.], [32.5,36.])
sal_isotopic_y=([-1.6,2.5], [-1.,1.5], [-4.,4.], [-1.6,2.5],[-4.,4.], [-1.,1.5])
c_data=np.loadtxt('coast_data.boat', dtype=str)
o_data=np.loadtxt('ocean_data.boat', dtype=str)
c_data_M=np.loadtxt('coast_data.boat', dtype=float,skiprows=1)
o_data_M=np.loadtxt('ocean_data.boat', dtype=float,skiprows=1)
c_data_M=c_data_M.T
o_data_M=o_data_M.T
"""
Values of plot parameter
"""
v_mins=(-1, -1, -4, -1, -4, -1) #list of values to use in the isotopic histograms
v_maxs=(2.3, 1, 3, 2.3, 3, 1) #list of values to use in the isotopic histograms
Nbins_ESSW=20
Nbins_AAIW=20
Nbins_PDW=20
Nbins_STW=20
Nbins_SAAW=20
lw_broad=4
lw_narrow=2
scatter_fontsize=15
histograms_fontsize =20
p_limit = 0.05
number_data = 3 # recomend at least 3, is minimun data in a list for the code to create histograms ans thoer graps
percent_value = 49.99999999 # minimum percent of a certain water mass
size_font = 25
size_font_sal = 25
number_decimal = '.2f'
range_temp = [0,25]
range_sal = [32.5,36]
range_oxigen = [0,400]
range_PO4 = [0,3.5]
range_NO2 = [0,9]
range_NO3 = [0,50]
range_SiO4 = [0,130]
range_13C_corrected=[-1.6 , 2.5]
marker_ocean= 'D'
marker_coast= 'o'
marker_raw= 'x'
"""
triggers to select the parts of the code that actually going to run
# positive in ('s','S','y','Y','O','o',1)
"""
print("possitive answers are ", 's','S','y','Y','O','o',1)
manual= input("Do you want to manually select what to do? y/n ")
if manual in ('s','S','y','Y','O','o',1):
chemical_histograms=input('Do you want to make the chemical histograms? y/n ')
isotopic_histograms=input('Do you want to make the isotopic histograms? y/n ')
matt_w=input('Do you want to make the Mann Whitney analysis? y/n ')
corr_13C=input('Do you want to calculate 13Csea-air exange?')
if corr_13C in ('s','S','y','Y','O','o',1):
o_13C_as_O=1
c_13C_as_O=1
o_13C_as_PO4=1
c_13C_as_PO4=1
corrected_13C_histograms=1
else:
o_13C_as_O=0
c_13C_as_O=0
o_13C_as_PO4=0
c_13C_as_PO4=0
corrected_13C_histograms=0
plot_salinity_o =input('Do you want to make the linear regression for isotopic values vs salinity in the oceanic sectios? y/n ')
plot_salinity_c =input('Do you want to make the linear regression for isotopic values vs salinity in the coastal section? y/n ')
else:
chemical_histograms = 1
isotopic_histograms = 1
o_13C_as_O=1
c_13C_as_O=1
o_13C_as_PO4=1
c_13C_as_PO4=1
corrected_13C_histograms=1
matt_w = 1
plot_salinity_o = 1
plot_salinity_c = 1
for j in range(len(boats)):
DATA = np.loadtxt(boats[j], dtype=str)
DATA_M = np.loadtxt(boats[j], dtype=float, skiprows=1)
DATA_M = DATA_M.T
DATA_M2=DATA_M
o_data_M2=o_data_M
c_data_M2=c_data_M
ESSW=[[],[],[],[]]
AAIW=[[],[],[],[]]
PDW =[[],[],[],[]]
STW =[[],[],[],[]]
SAAW=[[],[],[],[]]
ESSW_salinity=[]
AAIW_salinity=[]
PDW_salinity=[]
STW_salinity=[]
SAAW_salinity=[]
S_limit= -10.
N_limit= -54.
L_limit=4100.
U_limit=49.
for k in range(len(DATA_M[0])):
if DATA_M[3][k] > percent_value:
if DATA_M[1][k] > U_limit and DATA_M[1][k] < L_limit:
if DATA_M[0][k] < S_limit and DATA_M[0][k]> N_limit:
if isNaN(DATA_M[2][k]) == 0:
ESSW[0].append(DATA_M[0][k])
ESSW[1].append(DATA_M[1][k]*(-1.))
ESSW[2].append(DATA_M[2][k])
ESSW[3].append(DATA_M[3][k])
if c_o[j]== 1:
ESSW_salinity.append(c_data_M2[6][k])
else:
ESSW_salinity.append(o_data_M2[6][k])
if DATA_M[4][k] > percent_value:
if DATA_M[1][k] > U_limit and DATA_M[1][k] < L_limit:
if DATA_M[0][k] < S_limit and DATA_M[0][k]> N_limit:
if isNaN(DATA_M[2][k]) == 0:
AAIW[0].append(DATA_M[0][k])
AAIW[1].append(DATA_M[1][k]*(-1.))
AAIW[2].append(DATA_M[2][k])
AAIW[3].append(DATA_M[4][k])
if c_o[j]== 1:
AAIW_salinity.append(c_data_M2[6][k])
else:
AAIW_salinity.append(o_data_M2[6][k])
if DATA_M[5][k] > percent_value:
if DATA_M[1][k] > U_limit and DATA_M[1][k] < L_limit:
if DATA_M[0][k] < S_limit and DATA_M[0][k]> N_limit:
if isNaN(DATA_M[2][k]) == 0:
PDW[0].append(DATA_M[0][k])
PDW[1].append(DATA_M[1][k]*(-1.))
PDW[2].append(DATA_M[2][k])
PDW[3].append(DATA_M[5][k])
if c_o[j]== 1:
PDW_salinity.append(c_data_M2[6][k])
else:
PDW_salinity.append(o_data_M2[6][k])
if DATA_M[6][k] > percent_value:
if DATA_M[1][k] > U_limit and DATA_M[1][k] < L_limit:
if DATA_M[0][k] < S_limit and DATA_M[0][k]> N_limit:
if isNaN(DATA_M[2][k]) == 0:
STW[0].append(DATA_M[0][k])
STW[1].append(DATA_M[1][k]*(-1.))
STW[2].append(DATA_M[2][k])
STW[3].append(DATA_M[6][k])
if c_o[j]== 1:
STW_salinity.append(c_data_M2[6][k])
else:
STW_salinity.append(o_data_M2[6][k])
if DATA_M[7][k] > percent_value:
if DATA_M[1][k] > U_limit and DATA_M[1][k] < L_limit:
if DATA_M[0][k] < S_limit and DATA_M[0][k]> N_limit:
if isNaN(DATA_M[2][k]) == 0:
SAAW[0].append(DATA_M[0][k])
SAAW[1].append(DATA_M[1][k]*(-1.))
SAAW[2].append(DATA_M[2][k])
SAAW[3].append(DATA_M[7][k])
if c_o[j]== 1:
SAAW_salinity.append(c_data_M2[6][k])
else:
SAAW_salinity.append(o_data_M2[6][k])
mtt_list = [ESSW[2], AAIW[2],PDW[2],STW[2],SAAW[2]]
mtt_names = ('ESSW','AAIW','PDW','STW','SAAW')
if matt_w in ('s','S','y','Y','O','o',1):
print("Mann Whitney statistical values")
for jj in range(len(mtt_list)):
for kk in range(len(mtt_list)):
if mtt_list[jj] != mtt_list[kk]:
results = mannwhitneyu(mtt_list[jj] , mtt_list[kk] )
print(boatsT[j], mtt_names[jj],len(mtt_list[jj]), mtt_names[kk],len(mtt_list[kk]), "p value = " ,format(results[1],number_decimal) )
if plot_salinity_c in ('s','S','y','Y','O','o',1):
if c_o[j] == 1:
print("Linear regression statistical values")
plt.title('Salinity vs isotopic value for '+str(boatsT[j]))
plt.scatter(c_data_M2[6],DATA_M2[2], c='k', zorder=1, s=10, marker= marker_raw,label='Raw data')
if len(ESSW[2]) > number_data:
plt.scatter(ESSW_salinity, ESSW[2], c='m', zorder=2, edgecolor='k', s=40, label='ESSW')
a_ESSW, b_ESSW, r_ESSW, p_ESSW, str_ESSW = linregress(ESSW_salinity, ESSW[2])
print(boatsT[j],'ESSW','a',format(a_ESSW, number_decimal), 'c',format(b_ESSW,number_decimal), 'r',format(r_ESSW,number_decimal), 'r2',format(r_ESSW**2,number_decimal), 'p',format(p_ESSW, number_decimal), 'str',format(str_ESSW,number_decimal))
if p_ESSW <= p_limit:
XX_ESSW = np.linspace(np.nanmin(ESSW_salinity),np.nanmax(ESSW_salinity),5)
YY_ESSW = (XX_ESSW*a_ESSW)+b_ESSW
plt.plot(XX_ESSW,YY_ESSW, ls='-', marker='None',zorder=7,lw=lw_broad, c='k')
plt.plot(XX_ESSW,YY_ESSW, ls='-', marker='None',zorder=8,lw=lw_narrow, c='m')
if len(AAIW[2]) > number_data:
plt.scatter(AAIW_salinity, AAIW[2], c='lime', zorder=3, edgecolor='k', s=40, label='AAIW')
a_AAIW, b_AAIW, r_AAIW, p_AAIW, str_AAIW = linregress(AAIW_salinity, AAIW[2])
print(boatsT[j],'AAIW','a',format(a_AAIW, number_decimal), 'c',format(b_AAIW,number_decimal), 'r',format(r_AAIW,number_decimal), 'r2',format(r_AAIW**2,number_decimal), 'p',format(p_AAIW, number_decimal), 'str',format(str_AAIW,number_decimal))
if p_AAIW <= p_limit:
XX_AAIW = np.linspace(np.nanmin(AAIW_salinity),np.nanmax(AAIW_salinity),5)
YY_AAIW = (XX_AAIW*a_AAIW)+b_AAIW
plt.plot(XX_AAIW,YY_AAIW, ls='-', marker='None',zorder=9,lw=lw_broad, c='k')
plt.plot(XX_AAIW,YY_AAIW, ls='-', marker='None',zorder=10,lw=lw_narrow, c='lime')
if len(PDW[2]) > number_data:
plt.scatter(PDW_salinity, PDW[2], c='r', zorder=4, edgecolor='k', s=40, label='PDW')
a_PDW, b_PDW, r_PDW, p_PDW, str_PDW = linregress(PDW_salinity, PDW[2])
print(boatsT[j],'PDW','a',format(a_PDW, number_decimal), 'c',format(b_PDW,number_decimal), 'r',format(r_PDW,number_decimal), 'r2',format(r_PDW**2,number_decimal), 'p',format(p_PDW, number_decimal), 'str',format(str_PDW,number_decimal))
if p_PDW <= p_limit:
XX_PDW = np.linspace(np.nanmin(PDW_salinity),np.nanmax(PDW_salinity),5)
YY_PDW = (XX_PDW*a_PDW)+b_PDW
plt.plot(XX_PDW,YY_PDW, ls='-', marker='None',zorder=11,lw=lw_broad, c='k')
plt.plot(XX_PDW,YY_PDW, ls='-', marker='None',zorder=12,lw=lw_narrow , c='r')
if len(STW[2]) > number_data:
plt.scatter(STW_salinity, STW[2], c='c', zorder=5, edgecolor='k', s=40, label='STW')
a_STW, b_STW, r_STW, p_STW, str_STW = linregress(STW_salinity, STW[2])
print(boatsT[j],'STW','a',format(a_STW, number_decimal), 'c',format(b_STW,number_decimal), 'r',format(r_STW,number_decimal), 'r2',format(r_STW**2,number_decimal), 'p',format(p_STW, number_decimal), 'str',format(str_STW,number_decimal))
if p_STW <= p_limit:
XX_STW = np.linspace(np.nanmin(STW_salinity),np.nanmax(STW_salinity),5)
YY_STW = (XX_STW*a_STW)+b_STW
plt.plot(XX_STW,YY_STW, ls='-', marker='None',zorder=13,lw=lw_broad, c='k')
plt.plot(XX_STW,YY_STW, ls='-', marker='None',zorder=14,lw=lw_narrow, c='c')
if len(SAAW[2]) > number_data:
plt.scatter(SAAW_salinity, SAAW[2], c='y', zorder=6, edgecolor='k', s=40, label='SAAW')
a_SAAW, b_SAAW, r_SAAW, p_SAAW, str_SAAW = linregress(SAAW_salinity, SAAW[2])
print(boatsT[j],'SAAW','a',format(a_SAAW, number_decimal), 'c',format(b_SAAW,number_decimal), 'r',format(r_SAAW,number_decimal), 'r2',format(r_SAAW**2,number_decimal), 'p',format(p_SAAW, number_decimal), 'str',format(str_SAAW,number_decimal))
if p_SAAW <= p_limit:
XX_SAAW = np.linspace(np.nanmin(SAAW_salinity),np.nanmax(SAAW_salinity),5)
YY_SAAW = (XX_SAAW*a_SAAW)+b_SAAW
plt.plot(XX_SAAW,YY_SAAW, ls='-', marker='None',zorder=15,lw=lw_broad, c='k')
plt.plot(XX_SAAW,YY_SAAW, ls='-', marker='None',zorder=16,lw=lw_narrow, c='y')
plt.yticks(fontsize= scatter_fontsize)
plt.xticks(fontsize= scatter_fontsize)
plt.legend(fontsize=12, markerscale=int(2))
plt.xlim(sal_isotopic_x[j])
plt.ylim(sal_isotopic_y[j])
plt.savefig(str(boatsT[j])+"Coastal_salinity_ratios.svg", format='svg', dpi=300)
plt.close()
if plot_salinity_o in ('s','S','y','Y','O','o',1):
if c_o[j] == 0 :
print("Linear regression statistical values")
plt.title('Salinity vs isotopic value for '+str(boatsT[j]))
plt.scatter(o_data_M2[6],DATA_M2[2], c='k', zorder=1, s=10, marker= marker_raw,label='Raw data')
if len(ESSW[2]) > number_data:
plt.scatter(ESSW_salinity, ESSW[2],marker= marker_ocean, c='m', zorder=2, edgecolor='k', s=40, label='ESSW')
a_ESSW, b_ESSW, r_ESSW, p_ESSW, str_ESSW = linregress(ESSW_salinity, ESSW[2])
print(boatsT[j],'ESSW','a',format(a_ESSW, number_decimal), 'c',format(b_ESSW,number_decimal), 'r',format(r_ESSW,number_decimal), 'r2',format(r_ESSW**2,number_decimal), 'p',format(p_ESSW, number_decimal), 'str',format(str_ESSW,number_decimal))
if p_ESSW <= p_limit:
XX_ESSW = np.linspace(np.nanmin(ESSW_salinity),np.nanmax(ESSW_salinity),5)
YY_ESSW = (XX_ESSW*a_ESSW)+b_ESSW
plt.plot(XX_ESSW,YY_ESSW, ls='-', marker='None',zorder=7,lw=lw_broad, c='k')
plt.plot(XX_ESSW,YY_ESSW, ls='-', marker='None',zorder=8,lw=lw_narrow, c='m')
if len(AAIW[2]) > number_data:
plt.scatter(AAIW_salinity, AAIW[2],marker= marker_ocean, c='lime', zorder=3, edgecolor='k', s=40, label='AAIW')
a_AAIW, b_AAIW, r_AAIW, p_AAIW, str_AAIW = linregress(AAIW_salinity, AAIW[2])
print(boatsT[j],'AAIW','a',format(a_AAIW, number_decimal), 'c',format(b_AAIW,number_decimal), 'r',format(r_AAIW,number_decimal), 'r2',format(r_AAIW**2,number_decimal), 'p',format(p_AAIW, number_decimal), 'str',format(str_AAIW,number_decimal))
if p_AAIW <= p_limit:
XX_AAIW = np.linspace(np.nanmin(AAIW_salinity),np.nanmax(AAIW_salinity),5)
YY_AAIW = (XX_AAIW*a_AAIW)+b_AAIW
plt.plot(XX_AAIW,YY_AAIW, ls='-', marker='None',zorder=9,lw=lw_broad, c='k')
plt.plot(XX_AAIW,YY_AAIW, ls='-', marker='None',zorder=10,lw=lw_narrow, c='lime')
if len(PDW[2]) > number_data:
plt.scatter(PDW_salinity, PDW[2],marker= marker_ocean, c='r', zorder=4, edgecolor='k', s=40, label='PDW')
a_PDW, b_PDW, r_PDW, p_PDW, str_PDW = linregress(PDW_salinity, PDW[2])
print(boatsT[j],'PDW','a',format(a_PDW, number_decimal), 'c',format(b_PDW,number_decimal), 'r',format(r_PDW,number_decimal), 'r2',format(r_PDW**2,number_decimal), 'p',format(p_PDW, number_decimal), 'str',format(str_PDW,number_decimal))
if p_PDW <= p_limit:
XX_PDW = np.linspace(np.nanmin(PDW_salinity),np.nanmax(PDW_salinity),5)
YY_PDW = (XX_PDW*a_PDW)+b_PDW
plt.plot(XX_PDW,YY_PDW, ls='-', marker='None',zorder=11,lw=lw_broad, c='k')
plt.plot(XX_PDW,YY_PDW, ls='-', marker='None',zorder=12,lw=lw_narrow , c='r')
if len(STW[2]) > number_data:
plt.scatter(STW_salinity, STW[2],marker= marker_ocean, c='c', zorder=5, edgecolor='k', s=40, label='STW')
a_STW, b_STW, r_STW, p_STW, str_STW = linregress(STW_salinity, STW[2])
print(boatsT[j],'STW','a',format(a_STW, number_decimal), 'c',format(b_STW,number_decimal), 'r',format(r_STW,number_decimal), 'r2',format(r_STW**2,number_decimal), 'p',format(p_STW, number_decimal), 'str',format(str_STW,number_decimal))
if p_STW <= p_limit:
XX_STW = np.linspace(np.nanmin(STW_salinity),np.nanmax(STW_salinity),5)
YY_STW = (XX_STW*a_STW)+b_STW
plt.plot(XX_STW,YY_STW, ls='-', marker='None',zorder=13,lw=lw_broad, c='k')
plt.plot(XX_STW,YY_STW, ls='-', marker='None',zorder=14,lw=lw_narrow, c='c')
if len(SAAW[2]) > number_data:
plt.scatter(SAAW_salinity, SAAW[2],marker= marker_ocean, c='y', zorder=6, edgecolor='k', s=40, label='SAAW')
a_SAAW, b_SAAW, r_SAAW, p_SAAW, str_SAAW = linregress(SAAW_salinity, SAAW[2])
print(boatsT[j],'SAAW','a',format(a_SAAW, number_decimal), 'c',format(b_SAAW,number_decimal), 'r',format(r_SAAW,number_decimal), 'r2',format(r_SAAW**2,number_decimal), 'p',format(p_SAAW, number_decimal), 'str',format(str_SAAW,number_decimal))
if p_SAAW <= p_limit:
XX_SAAW = np.linspace(np.nanmin(SAAW_salinity),np.nanmax(SAAW_salinity),5)
YY_SAAW = (XX_SAAW*a_SAAW)+b_SAAW
plt.plot(XX_SAAW,YY_SAAW, ls='-', marker='None',zorder=15,lw=lw_broad, c='k')
plt.plot(XX_SAAW,YY_SAAW, ls='-', marker='None',zorder=16,lw=lw_narrow, c='y')
plt.yticks(fontsize=scatter_fontsize)
plt.xticks(fontsize=scatter_fontsize)
plt.legend(fontsize=12, markerscale=int(2))
plt.xlim(sal_isotopic_x[j])
plt.ylim(sal_isotopic_y[j])
plt.savefig(str(boatsT[j])+"Oceanic_salinity_ratios.svg", format='svg', dpi=300)
plt.close()
#plt.show()
if isotopic_histograms in ('s','S','y','Y','O','o',1):
if len(ESSW[2]) > number_data:
plt.xlim([v_mins[j] , v_maxs[j]])
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(ESSW[2], facecolor="r", edgecolor="k")
plt.title(str(boats[j])+"ESSW"+str(len(ESSW[2]))+"points \n Mean = "+str(np.nanmean(ESSW[2]))+"\n std = "+str(np.nanstd(ESSW[2])))
plt.savefig(str(boatsT[j])+"ESSW.svg", format='svg', dpi=300)
plt.close()
else:
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.title(str(boats[j])+"ESSW"+str(len(ESSW[2]))+"points")
plt.savefig(str(boatsT[j])+"ESSW.svg", format='svg', dpi=300)
plt.close()
if len(AAIW[2]) > number_data:
plt.xlim([v_mins[j] , v_maxs[j]])
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(AAIW[2], facecolor="r", edgecolor="k", range=(v_mins[j] , v_maxs[j]))
plt.title(str(boats[j])+"AAIW"+str(len(AAIW[2]))+"points \n Mean = "+str(np.nanmean(AAIW[2]))+"\n std = "+str(np.nanstd(AAIW[2])))
plt.savefig(str(boatsT[j])+"AAIW.svg", format='svg', dpi=300)
plt.close()
else:
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.title(str(boats[j])+"AAIW"+str(len(AAIW[2]))+"points")
plt.savefig(str(boatsT[j])+"AAIW.svg", format='svg', dpi=300)
plt.close()
if len(PDW[2]) > number_data:
plt.xlim([v_mins[j] , v_maxs[j]])
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(PDW[2], facecolor="r", edgecolor="k", range=(v_mins[j] , v_maxs[j]))
plt.title(str(boats[j])+"PDW"+str(len(PDW[2]))+"points \n Mean = "+str(np.nanmean(PDW[2]))+"\n std = "+str(np.nanstd(PDW[2])))
plt.savefig(str(boatsT[j])+"PDW.svg", format='svg', dpi=300)
plt.close()
else:
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.title(str(boats[j])+"PDW"+str(len(PDW[2]))+"points")
plt.savefig(str(boatsT[j])+"PDW.svg", format='svg', dpi=300)
plt.close()
if len(STW[2]) > number_data:
plt.xlim([v_mins[j] , v_maxs[j]])
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(STW[2], facecolor="r", edgecolor="k", range=(v_mins[j] , v_maxs[j]))
plt.title(str(boats[j])+"STW"+str(len(STW[2]))+"points \n Mean = "+str(np.nanmean(STW[2]))+"\n std = "+str(np.nanstd(STW[2])))
plt.savefig(str(boatsT[j])+"STW.svg", format='svg', dpi=300)
plt.close()
else:
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.title(str(boats[j])+"STW"+str(len(STW[2]))+"points")
plt.savefig(str(boatsT[j])+"STW.svg", format='svg', dpi=300)
plt.close()
if len(SAAW[2]) > number_data:
plt.xlim([v_mins[j] , v_maxs[j]])
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(SAAW[2], facecolor="r", edgecolor="k", range=(v_mins[j] , v_maxs[j]))
plt.title(str(boats[j])+"SAAW"+str(len(SAAW[2]))+"points \n Mean = "+str(np.nanmean(SAAW[2]))+"\n std = "+str(np.nanstd(SAAW[2])))
plt.savefig(str(boatsT[j])+"SAAW.svg", format='svg', dpi=300)
plt.close()
else:
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.title(str(boats[j])+"SAAW"+str(len(SAAW[2]))+"points")
plt.savefig(str(boatsT[j])+"SAAW.svg", format='svg', dpi=300)
plt.close()
if chemical_histograms in ('s','S','y','Y','O','o',1):
c_ESSW_salinity=[]
c_AAIW_salinity=[]
c_PDW_salinity=[]
c_STW_salinity=[]
c_SAAW_salinity=[]
c_ESSW_NO2 =[]
c_AAIW_NO2 =[]
c_PDW_NO2 =[]
c_STW_NO2 =[]
c_SAAW_NO2 =[]
c_ESSW_NO3 =[]
c_AAIW_NO3 =[]
c_PDW_NO3 =[]
c_STW_NO3 =[]
c_SAAW_NO3 =[]
c_ESSW_O =[]
c_AAIW_O =[]
c_PDW_O =[]
c_STW_O =[]
c_SAAW_O =[]
c_ESSW_PO4 =[]
c_AAIW_PO4 =[]
c_PDW_PO4 =[]
c_STW_PO4 =[]
c_SAAW_PO4 =[]
c_ESSW_SiO4 =[]
c_AAIW_SiO4 =[]
c_PDW_SiO4 =[]
c_STW_SiO4 =[]
c_SAAW_SiO4 =[]
c_ESSW_temp =[]
c_AAIW_temp =[]
c_PDW_temp =[]
c_STW_temp =[]
c_SAAW_temp =[]
for k in range(len(c_data_M2[0])):
if c_data_M2[10][k] > percent_value:
c_ESSW_NO2.append(c_data_M2[2][k])
c_ESSW_NO3.append(c_data_M2[3][k])
c_ESSW_O.append(c_data_M2[4][k])
c_ESSW_PO4.append(c_data_M2[5][k])
c_ESSW_salinity.append(c_data_M2[6][k])
c_ESSW_SiO4.append(c_data_M2[7][k])
c_ESSW_temp.append(c_data_M2[8][k])
if c_data_M2[11][k] > percent_value:
c_AAIW_NO2.append(c_data_M2[2][k])
c_AAIW_NO3.append(c_data_M2[3][k])
c_AAIW_O.append(c_data_M2[4][k])
c_AAIW_PO4.append(c_data_M2[5][k])
c_AAIW_salinity.append(c_data_M2[6][k])
c_AAIW_SiO4.append(c_data_M2[7][k])
c_AAIW_temp.append(c_data_M2[8][k])
if c_data_M2[12][k] > percent_value:
c_PDW_NO2.append(c_data_M2[2][k])
c_PDW_NO3.append(c_data_M2[3][k])
c_PDW_O.append(c_data_M2[4][k])
c_PDW_PO4.append(c_data_M2[5][k])
c_PDW_salinity.append(c_data_M2[6][k])
c_PDW_SiO4.append(c_data_M2[7][k])
c_PDW_temp.append(c_data_M2[8][k])
if c_data_M2[13][k] > percent_value:
c_STW_NO2.append(c_data_M2[2][k])
c_STW_NO3.append(c_data_M2[3][k])
c_STW_O.append(c_data_M2[4][k])
c_STW_PO4.append(c_data_M2[5][k])
c_STW_salinity.append(c_data_M2[6][k])
c_STW_SiO4.append(c_data_M2[7][k])
c_STW_temp.append(c_data_M2[8][k])
if c_data_M2[14][k] > percent_value:
c_SAAW_NO2.append(c_data_M2[2][k])
c_SAAW_NO3.append(c_data_M2[3][k])
c_SAAW_O.append(c_data_M2[4][k])
c_SAAW_PO4.append(c_data_M2[5][k])
c_SAAW_salinity.append(c_data_M2[6][k])
c_SAAW_SiO4.append(c_data_M2[7][k])
c_SAAW_temp.append(c_data_M2[8][k])
if len(c_ESSW_NO2 ) > number_data:
plt.xlim(range_NO2)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_NO2 , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW NO2"+str(len(c_ESSW_NO2))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_NO2)), number_decimal) )+"\n std = "+str(format((np.nanstd(c_ESSW_NO2)), number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_NO2.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_NO3 ) > number_data:
plt.xlim(range_NO3)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_NO3 , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW NO3"+str(len(c_ESSW_NO3))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_NO3)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_NO3)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_NO3.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_O ) > number_data:
plt.xlim(range_oxigen)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_O , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW O "+str(len(c_ESSW_O))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_O)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_O)),number_decimal)) , fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_O.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_PO4 ) > number_data:
plt.xlim(range_PO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_PO4 , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW PO4 "+str(len(c_ESSW_PO4))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_PO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_PO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_PO4.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_SiO4 ) > number_data:
plt.xlim(range_SiO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_SiO4 , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW SiO4 "+str(len(c_ESSW_SiO4))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_SiO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_SiO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_SiO4.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_temp ) > number_data:
plt.xlim(range_temp)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_temp , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW temp "+str(len(c_ESSW_temp))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_temp)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_temp)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_temp.svg", format='svg', dpi=300)
plt.close()
if len(c_ESSW_salinity ) > number_data:
plt.xlim(range_sal)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_ESSW_salinity , facecolor="r", edgecolor="k")
plt.title("coast c_ESSW salinity "+str(len(c_ESSW_salinity))+"points \n Mean = "+str(format((np.nanmean(c_ESSW_salinity)),number_decimal))+"\n std = "+str(format((np.nanstd(c_ESSW_salinity)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_ESSW_salinity.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_NO2 ) > number_data:
plt.xlim(range_NO2)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_NO2 , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW NO2"+str(len(c_AAIW_NO2))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_NO2)), number_decimal) )+"\n std = "+str(format((np.nanstd(c_AAIW_NO2)), number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_NO2.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_NO3 ) > number_data:
plt.xlim(range_NO3)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_NO3 , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW NO3"+str(len(c_AAIW_NO3))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_NO3)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_NO3)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_NO3.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_O ) > number_data:
plt.xlim(range_oxigen)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_O , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW O "+str(len(c_AAIW_O))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_O)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_O)),number_decimal)) , fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_O.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_PO4 ) > number_data:
plt.xlim(range_PO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_PO4 , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW PO4 "+str(len(c_AAIW_PO4))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_PO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_PO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_PO4.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_SiO4 ) > number_data:
plt.xlim(range_SiO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_SiO4 , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW SiO4 "+str(len(c_AAIW_SiO4))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_SiO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_SiO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_SiO4.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_temp ) > number_data:
plt.xlim(range_temp)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_temp , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW temp "+str(len(c_AAIW_temp))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_temp)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_temp)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_temp.svg", format='svg', dpi=300)
plt.close()
if len(c_AAIW_salinity ) > number_data:
plt.xlim(range_sal)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_AAIW_salinity , facecolor="r", edgecolor="k")
plt.title("coast c_AAIW salinity "+str(len(c_AAIW_salinity))+"points \n Mean = "+str(format((np.nanmean(c_AAIW_salinity)),number_decimal))+"\n std = "+str(format((np.nanstd(c_AAIW_salinity)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_AAIW_salinity.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_NO2 ) > number_data:
plt.xlim(range_NO2)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_NO2 , facecolor="r", edgecolor="k")
plt.title("coast c_PDW NO2"+str(len(c_PDW_NO2))+"points \n Mean = "+str(format((np.nanmean(c_PDW_NO2)), number_decimal) )+"\n std = "+str(format((np.nanstd(c_PDW_NO2)), number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_NO2.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_NO3 ) > number_data:
plt.xlim(range_NO3)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_NO3 , facecolor="r", edgecolor="k")
plt.title("coast c_PDW NO3"+str(len(c_PDW_NO3))+"points \n Mean = "+str(format((np.nanmean(c_PDW_NO3)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_NO3)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_NO3.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_O ) > number_data:
plt.xlim(range_oxigen)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_O , facecolor="r", edgecolor="k")
plt.title("coast c_PDW O "+str(len(c_PDW_O))+"points \n Mean = "+str(format((np.nanmean(c_PDW_O)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_O)),number_decimal)) , fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_O.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_PO4 ) > number_data:
plt.xlim(range_PO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_PO4 , facecolor="r", edgecolor="k")
plt.title("coast c_PDW PO4 "+str(len(c_PDW_PO4))+"points \n Mean = "+str(format((np.nanmean(c_PDW_PO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_PO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_PO4.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_SiO4 ) > number_data:
plt.xlim(range_SiO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_SiO4 , facecolor="r", edgecolor="k")
plt.title("coast c_PDW SiO4 "+str(len(c_PDW_SiO4))+"points \n Mean = "+str(format((np.nanmean(c_PDW_SiO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_SiO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_SiO4.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_temp ) > number_data:
plt.xlim(range_temp)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_temp , facecolor="r", edgecolor="k")
plt.title("coast c_PDW temp "+str(len(c_PDW_temp))+"points \n Mean = "+str(format((np.nanmean(c_PDW_temp)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_temp)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_temp.svg", format='svg', dpi=300)
plt.close()
if len(c_PDW_salinity ) > number_data:
plt.xlim(range_sal)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_PDW_salinity , facecolor="r", edgecolor="k")
plt.title("coast c_PDW salinity "+str(len(c_PDW_salinity))+"points \n Mean = "+str(format((np.nanmean(c_PDW_salinity)),number_decimal))+"\n std = "+str(format((np.nanstd(c_PDW_salinity)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_PDW_salinity.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_NO2 ) > number_data:
plt.xlim(range_NO2)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_NO2 , facecolor="r", edgecolor="k")
plt.title("coast c_STW NO2"+str(len(c_STW_NO2))+"points \n Mean = "+str(format((np.nanmean(c_STW_NO2)), number_decimal) )+"\n std = "+str(format((np.nanstd(c_STW_NO2)), number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_NO2.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_NO3 ) > number_data:
plt.xlim(range_NO3)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_NO3 , facecolor="r", edgecolor="k")
plt.title("coast c_STW NO3"+str(len(c_STW_NO3))+"points \n Mean = "+str(format((np.nanmean(c_STW_NO3)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_NO3)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_NO3.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_O ) > number_data:
plt.xlim(range_oxigen)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_O , facecolor="r", edgecolor="k")
plt.title("coast c_STW O "+str(len(c_STW_O))+"points \n Mean = "+str(format((np.nanmean(c_STW_O)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_O)),number_decimal)) , fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_O.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_PO4 ) > number_data:
plt.xlim(range_PO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_PO4 , facecolor="r", edgecolor="k")
plt.title("coast c_STW PO4 "+str(len(c_STW_PO4))+"points \n Mean = "+str(format((np.nanmean(c_STW_PO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_PO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_PO4.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_SiO4 ) > number_data:
plt.xlim(range_SiO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_SiO4 , facecolor="r", edgecolor="k")
plt.title("coast c_STW SiO4 "+str(len(c_STW_SiO4))+"points \n Mean = "+str(format((np.nanmean(c_STW_SiO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_SiO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_SiO4.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_temp ) > number_data:
plt.xlim(range_temp)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_temp , facecolor="r", edgecolor="k")
plt.title("coast c_STW temp "+str(len(c_STW_temp))+"points \n Mean = "+str(format((np.nanmean(c_STW_temp)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_temp)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_temp.svg", format='svg', dpi=300)
plt.close()
if len(c_STW_salinity ) > number_data:
plt.xlim(range_sal)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_STW_salinity , facecolor="r", edgecolor="k")
plt.title("coast c_STW salinity "+str(len(c_STW_salinity))+"points \n Mean = "+str(format((np.nanmean(c_STW_salinity)),number_decimal))+"\n std = "+str(format((np.nanstd(c_STW_salinity)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_STW_salinity.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_NO2 ) > number_data:
plt.xlim(range_NO2)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_NO2 , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW NO2"+str(len(c_SAAW_NO2))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_NO2)), number_decimal) )+"\n std = "+str(format((np.nanstd(c_SAAW_NO2)), number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_NO2.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_NO3 ) > number_data:
plt.xlim(range_NO3)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_NO3 , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW NO3"+str(len(c_SAAW_NO3))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_NO3)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_NO3)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_NO3.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_O ) > number_data:
plt.xlim(range_oxigen)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_O , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW O "+str(len(c_SAAW_O))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_O)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_O)),number_decimal)) , fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_O.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_PO4 ) > number_data:
plt.xlim(range_PO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_PO4 , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW PO4 "+str(len(c_SAAW_PO4))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_PO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_PO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_PO4.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_SiO4 ) > number_data:
plt.xlim(range_SiO4)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_SiO4 , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW SiO4 "+str(len(c_SAAW_SiO4))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_SiO4)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_SiO4)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_SiO4.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_temp ) > number_data:
plt.xlim(range_temp)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_temp , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW temp "+str(len(c_SAAW_temp))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_temp)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_temp)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_temp.svg", format='svg', dpi=300)
plt.close()
if len(c_SAAW_salinity ) > number_data:
plt.xlim(range_sal)
plt.yticks(fontsize= histograms_fontsize)
plt.xticks(fontsize= histograms_fontsize)
plt.hist(c_SAAW_salinity , facecolor="r", edgecolor="k")
plt.title("coast c_SAAW salinity "+str(len(c_SAAW_salinity))+"points \n Mean = "+str(format((np.nanmean(c_SAAW_salinity)),number_decimal))+"\n std = "+str(format((np.nanstd(c_SAAW_salinity)),number_decimal)), fontsize=histograms_fontsize)
plt.savefig("coast_c_SAAW_salinity.svg", format='svg', dpi=300)
plt.close()
o_ESSW_salinity=[]
o_AAIW_salinity=[]
o_PDW_salinity=[]
o_STW_salinity=[]
o_SAAW_salinity=[]
o_ESSW_NO2 =[]
o_AAIW_NO2 =[]
o_PDW_NO2 =[]
o_STW_NO2 =[]
o_SAAW_NO2 =[]
o_ESSW_NO3 =[]
o_AAIW_NO3 =[]
o_PDW_NO3 =[]
o_STW_NO3 =[]
o_SAAW_NO3 =[]
o_ESSW_O =[]
o_AAIW_O =[]
o_PDW_O =[]
o_STW_O =[]
o_SAAW_O =[]
o_ESSW_PO4 =[]
o_AAIW_PO4 =[]
o_PDW_PO4 =[]
o_STW_PO4 =[]
o_SAAW_PO4 =[]
o_ESSW_SiO4 =[]
o_AAIW_SiO4 =[]
o_PDW_SiO4 =[]
o_STW_SiO4 =[]
o_SAAW_SiO4 =[]
o_ESSW_temp =[]
o_AAIW_temp =[]
o_PDW_temp =[]
o_STW_temp =[]
o_SAAW_temp =[]
for k in range(len(o_data_M2[0])):
if o_data_M2[10][k] > percent_value:
o_ESSW_NO2.append(o_data_M2[2][k])
o_ESSW_NO3.append(o_data_M2[3][k])
o_ESSW_O.append(o_data_M2[4][k])
o_ESSW_PO4.append(o_data_M2[5][k])
o_ESSW_salinity.append(o_data_M2[6][k])
o_ESSW_SiO4.append(o_data_M2[7][k])
o_ESSW_temp.append(o_data_M2[8][k])
if o_data_M2[11][k] > percent_value: