File:Delta t against 200 years moving northern hemisphere 100 1600 ad 1.svg

1. 3. drawing climate data diagram in python 3
   4. version 4000.0009
   5. miving value - average elta plot
   6. 08.12.2022

import matplotlib.pyplot as plt import numpy as np import pandas as pd from scipy import interpolate from matplotlib.ticker import (MultipleLocator, AutoMinorLocator) import scipy.signal import matplotlib.colors as colors import math as math

1. datafilename="macal2016uvl_1.csv"

datafilename="moberg1.csv"

1. captioni="Macal UV-luminance"
2. savename="macal_uvl_1.svg"

captioni="Temperature delta of Northern hemisphere, DT200" subtitle="Delta-T against moving average of temperature of 200 years" savename="temperature_delta_northern_hemisphere_1.svg"

1. s1='age_calBP'

s1='Year' s2='T'

beginx=100 endx=1600

convert_bp_to_ad=0

beginy=-0.65 endy=0.6

figsizex=18 figsizey=7

yearspan=int(math.fabs(endx-beginx))

dfin0=pd.read_csv(datafilename, sep=";")

dfin0=dfin0.drop_duplicates(subset=[s1])

lst1=[s1, s2]

dfin1 = dfin0[dfin0.columns.intersection(lst1)]

x0=dfin1[s1]

y0=dfin1[s2]

1. initialize data of lists.

data={'x0':x0,'y0':y0}

1. Create DataFrame

df = pd.DataFrame(data)

1. dfin2=dfin1

df['moving10'] = df.y0.rolling(10, min_periods=1).mean() df['moving50'] = df.y0.rolling(50, min_periods=1).mean() df['moving200'] = df.y0.rolling(200, min_periods=1).mean()

print(df)

ya0=df['y0'] moving1=df['moving10'] moving2=df['moving50'] moving3=df['moving200']

delta1=ya0-moving2

1. delta1=moving2-moving3

1. plt.plot(x0,moving3)
2. plt.plot(x0,delta1)
3. plt.xlim([beginx, endx])
4. plt.show()

1. quit(-1)

x=np.array(x0)

1. y=np.array(y0)

y=delta1

1. 1. !!!!!!!!!!!!!!! bp to ce, ad!

if(convert_bp_to_ad==1): x=1950-x

1. print (x)

1. quit(-1)

yy2=y[:2000]

ymean1=np.mean(yy2)

1. 1. ad hoc drought limit
2. ylimit1=ymean1-50

1. print (y)
2. quit(-1)

size0=14 size1=16 size2=18 size3=22

x_sm = x y_sm = y

x_smooth = np.linspace(beginx,endx, yearspan)

1. quit(-1)

funk1 = interpolate.interp1d(x_sm, y_sm, kind="cubic")

1. quit(-1)

y_smooth = funk1(x_smooth) y_savgol1 = scipy.signal.savgol_filter(y_smooth,3, 2) y_savgol2 = scipy.signal.savgol_filter(y_smooth,11, 3)

1. delta1=y_savgol1-y_savgol2

a=np.outer(np.ones(2),y_smooth) a=np.outer(np.ones(2),y_savgol2)

1. cmap1="RdBu"
2. cmap1="hsv"
3. cmap1="seismic"
4. cmap1="bwr"
5. cmap1="coolwarm"

cmap1="RdBu_r"

1. cmap1="gist_earth_r"
2. cmap1="terrain_r"
3. cmap1="twilight_shifted_r"

1. cmap1="cividis"

1. cmap1="YlGnBu"

1. cmap1="BrBG"

print (type(cmap1))

1. fig=plt.gca()
2. plt.figure(figsize=(figsizex, figsizey))

1. quit(-1)

plt.xlim([beginx, endx])

plt.rcParams["figure.figsize"] = [figsizex, figsizey]

1. plt.imshow(a,aspect='auto', cmap=cmap1, extent=[beginx, endx,-50,-30], alpha=0.5)

plt.imshow(a,aspect='auto', cmap=cmap1, extent=[beginx, endx,endy,beginy], alpha=0.5)

1. plt.imshow(a,aspect='auto', cmap=cmap1, vmin=endy-0, vmax=beginy+0, extent=[beginx, endx,endy,beginy], alpha=1.0)

1. plt.show()

1. quit(-1)

1. plt.xlim(beginx, endx)
2. plt.ylim(endy, beginy)

1. plt.plot(x, y, color="#7f0000", alpha=1.0, linewidth=1)
2. plt.plot(x, y, color="#700000", alpha=0.7, linewidth=1)

plt.plot(x, delta1, color="#700000", alpha=1.0, linewidth=2)

1. plt.plot(x_smooth, y_savgol1, color="#0000ff", alpha=0.33, linewidth=1)

1. plt.plot(x_smooth, y_savgol2, color="#0000ff", linewidth=2)

1. plt.axhline(y = ylimit1, color = 'g', linestyle = ':', linewidth=2)

plt.locator_params(axis='x', nbins=20)

plt.title(captioni, fontsize=size3, color="#0000af") plt.suptitle(subtitle,fontsize=14) plt.xlabel('Year AD', color="darkgreen", fontsize=21) plt.ylabel('Delta avg T 200 years', color="darkgreen", fontsize=21) plt.xticks(fontsize=17) plt.yticks(fontsize=17)

plt.gca().invert_yaxis()

1. mng = plt.get_current_fig_manager()
2. mng.window.state('zoomed')

plt.savefig('figure.svg')

plt.show()