File:Near selerika 1990-2019 1.svg

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Original file (SVG file, nominally 1,080 × 720 pixels, file size: 41 KB)

Captions

Captions

Climate near Selerika 1990-2019

Summary

[edit]
Description
English: Climate near Selerika 1990-2019
Date
Source Own work
Author Merikanto
Camera location64° 44′ 34.8″ N, 147° 57′ 50.4″ E  Heading=1° Kartographer map based on OpenStreetMap.View this and other nearby images on: OpenStreetMapinfo

Source of data to fraw image is [1]

Data is processed wwith text edittor and drawn with python script

Data

Month;T;P 1;-39.1;8.9 2;-36.8;8.9 3;-28.1;6.8 4;-15.1;9.1 5;-1.9;18.4 6;7.4;45.3 7;10.6;63.5 8;7.9;53.4 9;0.7;28.8 10;-13.2;15.5 11;-29.7;15.3 12;-38.2;9.9

Python script

    3. drawing climate diagram in python 3
    4. version 2.11
    5. 11.9.2020

import matplotlib.pyplot as plt import numpy as np import pandas as pd from scipy import interpolate import sys

print ('Argument List:', str(sys.argv))

pohjanimi=sys.argv[1] ika=sys.argv[2] isonimi=pohjanimi.capitalize()

print(pohjanimi, isonimi, ika)

  1. quit(-1)

pohjanimi="selerika" ika="ca. 30 - 0 " captioni=isonimi+", "+ika+" BP" maxrainfall=120 mintemperature=-60 maxtemperature=20

datafilename=pohjanimi+".csv" savename=pohjanimi+"_"+ika+"_climate_diagram.svg"

figsizex=12 figsizey=8

x0 = [] y0 = [] y20= []

x = [] y = [] y2= []

dfin0=pd.read_csv(datafilename, sep=";") lst1 = ['Month','T','P']

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

x0=dfin1['Month'] y0=dfin1['T'] y20=dfin1['P']

x.append(0) y.append(y0[11]) y2.append(y0[11])

for n in range(0, 12): x.append(x0[n]) y.append(y0[n]) y2.append(y20[n])

x.append(13) y.append(y0[0]) y2.append(y0[0])

print(x)

  1. print(y)
  2. print (type(x))
  3. print (type(y))
  1. quit(0)

yearprecip=0 yeartemp=0

for n in range(1, 13): yearprecip=yearprecip+y2[n] yeartemp=yeartemp+y[n] print (n,y[n],y2[n])


size1=22 size2=26 size3=30

yeartemp=round((yeartemp/12.0),1) mintemp=min(y) maxtemp=max(y) yearprecip=round(yearprecip,0) maxprecip=max(y2) minprecip=min(y2)

print(yearprecip) print(minprecip) print(maxprecip)

print(yeartemp) print(mintemp) print(maxtemp)

ymax1=int((maxprecip+60)/20)*20 ymax2=int((maxtemp+15)/5)*5 ymin2=int((mintemp-10)/5)*5

x_sm = np.array(x) y_sm = np.array(y) x_smooth = np.linspace(x_sm.min(), x_sm.max(), 200) funk1 = interpolate.interp1d(x_sm, y_sm, kind="quadratic") y_smooth = funk1(x_smooth)

fig, ax1 = plt.subplots()

  1. plt.rcParams["figure.figsize"] = (12,16)

ax1.axis((1,12,0,ymax1))

ax1.bar(x, y2, color='#0000ff', label="Precip. mm", width=0.9, align="center")

ax1.set_ylabel('Precipitation mm', color='#00007f', fontsize=size2)

for tl in ax1.get_yticklabels(): 

tl.set_color('b')
tl.set_fontsize(size1)

ax2 = ax1.twinx() ax2.set_ylabel('Temperature °C', color='#7f0000', fontsize=size2)

ax2.axis((1,12,ymin2, ymax2))

  1. ax2.plot(x,y, label='Temperature °C',color="#ff0000", linewidth=7)

ax2.plot(x_smooth,y_smooth, label='Temperature °C',color="red", linewidth=10)

for t2 in ax2.get_yticklabels(): 

t2.set_color('r')
t2.set_fontsize(size1)

ax1.set_xlabel('Month', color="darkgreen", fontsize=size2)

for tix in ax1.get_xticklabels(): 

tix.set_color("Black")
tix.set_fontsize(size1)

ax1.set_title(captioni, fontsize=size3)

ax2.text(1, ymax2-4, " P annual "+str(int(yearprecip))+ " mm", color="#00007f", fontsize=size1) ax2.text(1, ymax2-8, " T year "+str(yeartemp) + " °C", color="#7f0000",fontsize=size1) ax2.text(1, ymax2-12, " T max "+str(maxtemp)+ " °C", color="#7f0000", fontsize=size1) ax2.text(1, ymax2-16, " T min "+str(mintemp) + " °C", color="#7f0000",fontsize=size1)

fig = plt.gcf() fig.set_size_inches(figsizex, figsizey, forward=True)

plt.plot()

plt.savefig(savename, format="svg", dpi = 100)

plt.show()

Licensing

[edit]
I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
  1. ↑ Laura Zepner, Pierre Karrasch, Felix Wiemann & Lars Bernard (2020) ClimateCharts.net – an interactive climate analysis web platform, International Journal of Digital Earth, DOI: 10.1080/17538947.2020.1829112

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Date/TimeThumbnailDimensionsUserComment
current17:35, 30 October 2021Thumbnail for version as of 17:35, 30 October 20211,080 × 720 (41 KB)Merikanto (talk | contribs)Uploaded own work with UploadWizard

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