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import os
import geopandas #to install: pip install git+git://github.com/geopandas/geopandas.git
import matplotlib
import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib.colors as colors
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
@thomascamminady
thomascamminady / Order2.txt
Created November 18, 2019 09:52
Icosahedron quadrature points and weights.
+0.0000000000000000, +0.0000000000000000, +1.0000000000000000, +0.7370796188178727
+0.0000000000000000, -0.8944271909999159, +0.4472135954999580, +0.7370796188178727
+0.5257311121191336, -0.4472135954999580, +0.7236067977499790, +1.3293827143261787
-0.5257311121191336, -0.4472135954999580, +0.7236067977499790, +1.3293827143261787
+0.5257311121191336, +0.7236067977499790, +0.4472135954999580, +1.0751303204457423
-0.5257311121191336, +0.7236067977499790, +0.4472135954999580, +1.0751303204457423
+0.0000000000000000, +0.8944271909999159, -0.4472135954999580, +0.7370796188178727
-0.5257311121191336, +0.4472135954999580, -0.7236067977499790, +1.3293827143261787
+0.5257311121191336, +0.4472135954999580, -0.7236067977499790, +1.3293827143261787
+0.0000000000000000, +0.0000000000000000, -1.0000000000000000, +0.7370796188178727
@thomascamminady
thomascamminady / Order3.txt
Created November 18, 2019 09:53
Icosahedron quadrature points and weights.
+0.0000000000000000, +0.0000000000000000, +1.0000000000000000, +0.1750515508961119
+0.0000000000000000, -0.5257311121191336, +0.8506508083520400, +0.1656066358399360
+0.2831584861794965, -0.2408689951603286, +0.9283336678560082, +0.2026535539227139
+0.0000000000000000, -0.8944271909999159, +0.4472135954999580, +0.1750515508961119
+0.2831584861794965, -0.7226069854809859, +0.6306032161657743, +0.2026535539227202
+0.5257311121191336, -0.4472135954999580, +0.7236067977499790, +0.3024160051841469
-0.2831584861794965, -0.2408689951603286, +0.9283336678560082, +0.2026535539227139
-0.2831584861794965, -0.7226069854809859, +0.6306032161657743, +0.2026535539227202
-0.5257311121191336, -0.4472135954999580, +0.7236067977499790, +0.3024160051841469
+0.3090169943749474, +0.4253254041760200, +0.8506508083520400, +0.2853963720068315
@thomascamminady
thomascamminady / Order4.txt
Created November 18, 2019 09:53
Icosahedron quadrature points and weights.
+0.0000000000000000, +0.0000000000000000, +1.0000000000000000, +0.0770879880786079
+0.0000000000000000, -0.3607291593156859, +0.9326706136784833, +0.0725057874234372
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+0.0000000000000000, -0.6728829727813683, +0.7397489472387969, +0.0730619972031414
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+0.3704152569884241, -0.3150940377831316, +0.8737896112587527, +0.0888144070297263
+0.0000000000000000, -0.8944271909999159, +0.4472135954999580, +0.0770879880786079
+0.1913433861380803, -0.7929544816574379, +0.5784556150653200, +0.0863235493243060
+0.3704152569884241, -0.6406268499654808, +0.6725992688767251, +0.0890565284997334
+0.5257311121191336, -0.4472135954999580, +0.7236067977499790, +0.1322002012302700
@thomascamminady
thomascamminady / Order5.txt
Created November 18, 2019 09:54
Icosahedron quadrature points and weights.
+0.0000000000000000, +0.0000000000000000, +1.0000000000000000, +0.0432235023352426
+0.0000000000000000, -0.2732665289126717, +0.9619383577839175, +0.0405219038229034
+0.1441861322126741, -0.1226520499198653, +0.9819199732809208, +0.0474217047270837
+0.0000000000000000, -0.5257311121191336, +0.8506508083520400, +0.0408037508115632
+0.1446373830629677, -0.3915794114763158, +0.9087054483871870, +0.0406974874138345
+0.2831584861794965, -0.2408689951603286, +0.9283336678560082, +0.0484647533732056
+0.0000000000000000, -0.7381753163429122, +0.6746089254835290, +0.0409066008448976
+0.1448879475284992, -0.6322683016527550, +0.7610809926585472, +0.0412027822569089
+0.2840258384296597, -0.5012689407723848, +0.8173486233678138, +0.0403706561819274
+0.4118918141546002, -0.3503761046641989, +0.8411787673929809, +0.0493548485485585
Subscript b Geopotential height above MSL (m) Geopotential height above MSL (ft) Static pressure (pascals) Static pressure (inHg) Standard temperature (K) Temperature Lapse Rate (K/m) Temperature Lapse Rate (K/ft)
0 0 0 101325 29.92126 288.15 -0.0065 -0.001981
1 11000 36089 22632.1 6.683245 216.65 0 0
2 20000 65617 5474.89 1.616734 216.65 0.001 0.0003048
3 32000 104987 868.019 0.2563258 228.65 0.0028 0.0008534
4 47000 154199 110.906 0.0327506 270.65 0 0
5 51000 167323 66.9389 0.01976704 270.65 -0.0028 -0.0008534
6 71000 232940 3.95642 0.00116833 214.65 -0.002 -0.0006096
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_context("poster")
df = pd.read_csv("US_Standard_Atmosphere_1976.csv")
cols = list(df)
R = 287.058
df[r"Density (kg/m${}^3$)"] = df["Static pressure (pascals)"]/df["Standard temperature (K) "]/R
cols = list(df)
heights = [int(height/1000) for height in df[cols[1]]]