Add plotting notebook and web scrape test

Computing TESS RV Semi-Amplitudes.py

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+import requests
+url = 'https://exofop.ipac.caltech.edu/tess/download_toi.php?sort=toi&output=csv'
+r = requests.get(url, allow_redirects=True) 
+open('All Rows (CSV)', 'wb').write(r.content) #this downloads and saves the file to wherever this notebook is saved
+r.status_code #200 means the request was successful, 404 indicates an unsuccessful request
+
+import pandas as pd
+pd.set_option('display.max_columns', 100)
+data = pd.read_csv("All Rows (CSV)")
+exofop = pd.DataFrame(data)
+
+#make sure you have astroquery pip installed before running this code
+
+#Need to import stellar mass values from other source
+#import astroquery.mast catalogs
+from astroquery.mast import Catalogs
+#Make list of TIC IDs to pull from the catalog
+TICID_list = (exofop['TIC ID']).tolist()
+#pull the data for the TIC ID's that are also in EXOFOP
+catalog_data = Catalogs.query_criteria(catalog='Tic',objType='STAR', ID = TICID_list)
+#Turn it into panda df
+catalog_data_df = catalog_data.to_pandas()
+#Only pull the masses and IDs since that's all I need
+catalog_data_df2 = catalog_data_df[['ID','mass']]
+
+OP = exofop['Period (days)']
+M_sol = catalog_data_df2['mass']
+#assume e = 0
+#sin(i) = 1
+#M2 = 1/317.8
+#M1 >> M2
+RV = 28.4329 * (1/317.8) * (M_sol)**(-2/3) * (OP / 365.25)**(-1/3)
+
+import matplotlib.pyplot as plt
+import numpy as np
+plt.figure(figsize = (8, 8))
+plt.hist(RV[np.isfinite(RV)], color = 'green', bins = np.linspace(0, 1, 50))
+plt.axvline(x=.3, color = 'red', linestyle = '--', label = 'representative detection limit')
+plt.legend(fontsize = 14)
+plt.xlabel('RV Semi-Amplitude (m/s)', fontsize = 15)
+plt.ylabel('Count', fontsize = 15)
+plt.ylim(0, 110)
+plt.tick_params(labelsize = 12)
+plt.title('TOI RV Semi-Amplitude Distribution', fontsize = 18)
+plt.savefig('TOI Semi-Amplitude Distribution.png')

ExoFop Plots.py

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+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+data = pd.read_csv("exofop_tess_tois.csv")
+exofop = pd.DataFrame(data)
+#print(exofop)
+exofop
+
+Period = exofop["Period (days)"]
+P_Radius = exofop["Planet Radius (R_Earth)"]
+Distance = (Period / 365.25)**(2/3)
+
+plt.plot(Period, Distance, 'r.')
+plt.xlabel("Period (Days)")
+plt.ylabel("Distance (AU)")
+
+plt.plot(Period, P_Radius, 'r.')
+plt.xlabel("Period (Days)")
+plt.ylabel("Planetary Radius (R_Earth)")
+plt.xscale("log")
+plt.yscale("log")
+
+App_Mag = exofop["TESS mag"]
+
+plt.plot(P_Radius, App_Mag, 'b.')
+plt.xlabel("Planetary Radius (R_Earth)")
+plt.ylabel("Apparent Magnitude (from TESS)")
+
+S_Radius = exofop["Stellar Radius (R_Sun)"]
+plt.plot(S_Radius, App_Mag, 'b.')
+plt.xlabel("Stellar Radius (R_Sun)")
+plt.ylabel("Apparent Magnitude (from TESS)")
+
+Stellar_D = exofop["Stellar Distance (pc)"]
+Stellar_Mag = App_Mag - 5*np.log10(Stellar_D) + 5
+
+plt.plot(P_Radius, Stellar_Mag, 'g.')
+plt.xlabel("Planetary Radius (R_Earth)")
+plt.ylabel("Stellar Magnitude (Absolute)")
+
+plt.plot(S_Radius, Stellar_Mag, 'g.')
+plt.xlabel("Stellar Radius (R_Sun)")
+plt.ylabel("Stellar Magnitude (Absolute)")
+
+P_Insol = exofop["Planet Insolation (Earth flux)"]
+P_Eq_Temp = exofop["Planet Eq Temp (K)"]
+
+plt.plot(P_Insol, P_Eq_Temp, 'r.')
+plt.xlabel("Planet Insolation (Earth Flux)")
+plt.ylabel ("Planet Eq Temperature (K)")

Finding Habitable TOI's.py

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+import requests
+url = 'https://exofop.ipac.caltech.edu/tess/download_toi.php?sort=toi&output=csv'
+r = requests.get(url, allow_redirects=True) 
+open('All Rows (CSV)', 'wb').write(r.content) #this downloads and saves the file to wherever this notebook is saved
+r.status_code #200 means the request was successful, 404 indicates an unsuccessful request
+
+import pandas as pd
+pd.set_option('display.max_columns', 100)
+data = pd.read_csv("All Rows (CSV)")
+exofop = pd.DataFrame(data)
+
+#Planets with insolation flux 0.5-1.5 earth flux
+P_Insol = exofop['Planet Insolation (Earth Flux)']
+exofop.loc[(P_Insol >= 0.5) & (P_Insol <= 1.5)]
+
+#Planets with an earth radius of 0.5-2.5
+P_Rad = exofop['Planet Radius (R_Earth)']
+exofop.loc[(E_Rad >= 0.5) & (E_Rad <= 2.5)]
+
+#Planets with both conditions
+exofop.loc[(P_Insol >= 0.5) & (P_Insol <= 1.5) & (P_Rad >= 0.5) & (P_Rad <= 2.5)]
+
+#Zink and Hansen (2019) parameters
+Sol_Rad = exofop['Stellar Radius (R_Sun)']
+Log = exofop['Stellar log(g) (cm/s^2)']
+Depth = exofop['Depth (ppm)']
+Temp = exofop['Stellar Eff Temp (K)']
+OP = exofop['Period (days)']
+#Semimajor axis constraint will be applied via an approximation of Kepller's 3rd law (p**2 = a**3)
+#Period: p = (0.95**3)**0.5 = 0.926 years = 338 days, p = (1.68**3)**0.5 = 2.18 years = 795 days
+exofop.loc[(Temp >= 4200) & (Temp <= 6100) & (Sol_Rad <= 2) & (Log >= 4) & (Depth <= 1000) & (P_Rad >= 0.72) & (P_Rad <= 1.7) & (OP >= 338) & (OP <= 795)]
+
+#Hsu et al (2020) parameters
+exofop.loc[(P_Rad >= 0.75) & (P_Rad <= 1.5) & (Sol_Rad >= 0.75) & (OP >= 237) & (OP <= 500)]

Web Scrape Test Run.py

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+
+import requests
+url = 'https://exofop.ipac.caltech.edu/tess/download_toi.php?sort=toi&output=csv'
+r = requests.get(url, allow_redirects=True) 
+open('All Rows (CSV)', 'wb').write(r.content) #this downloads and saves the file to wherever this notebook is saved
+r.status_code #200 means the request was successful, 404 indicates an unsuccessful request
+
+import pandas as pd
+pd.set_option('display.max_columns', 100)
+data = pd.read_csv("All Rows (CSV)")
+exofop = pd.DataFrame(data)
+exofop