need to move computers/backup

Author: jagoosw

campyros/new_wind.py

@@ -0,0 +1,69 @@
+import getgfs, dateutil.parser, pickle
+from datetime import datetime
+from pathlib import Path 
+
+__copyright__ = """
+
+    Copyright 2021 Jago Strong-Wright
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+"""
+
+Path("data/wind").mkdir(parents=True,exist_ok=True)
+
+class Wind:
+    def __init__(self,datetime,cache=False):
+        """Initites wind object so wind for some position can be searched
+
+        Note
+        ----
+        - Historic forcasts are not yet implimented in getgfs so historics not available in this
+
+        Args:
+            datetime (string): datetime of flight, can be in 'any' format as long as datetime parser can work it out (for now this will need to be UTC)
+            cache (bool, optional): cache lat/long/time profile, useful for stats models where downloading for each run is a bottle neck. Defaults to False.
+        """
+        self.launch_time=dateutil.parser.parse(datetime).timestamp()
+        self.cache=cache
+
+        self.forecast=getgfs.Forecast("0p25")
+        self.profiles={}#(lat,long,datetime):interp profile
+        self.points=[]#tuples (lat,long,forecast)
+
+    
+    def get(self,lat,long,alt,flight_time):
+        lat=[float(self.forecast.coords["lat"]["resolution"])*n+float(self.forecast.coords["lat"]["minimum"]) for n in range(0,int(self.forecast.coords["lat"]["grads_size"]))][self.forecast.value_to_index("lat",lat)]
+        long=[float(self.forecast.coords["lon"]["resolution"])*n+float(self.forecast.coords["lon"]["minimum"]) for n in range(0,int(self.forecast.coords["lon"]["grads_size"]))][self.forecast.value_to_index("lon",long)]
+        request_timestamp=self.launch_time+flight_time
+        request_datetime=datetime.fromtimestamp(request_timestamp).strftime("%Y-%m-%d %H:%M")
+        forecast_to_use=self.forecast.datetime_to_forecast(request_datetime)
+        if (lat,long, forecast_to_use) not in self.points:
+            if self.cache==False or not Path("data/wind/%s_%s_%s.pkl"%(lat,long,forecast_to_use)).is_file():
+                self.profiles[(lat,long,forecast_to_use)]=self.forecast.get_windprofile(request_datetime,lat,long)
+                self.points.append((lat,long,forecast_to_use))
+                
+                if self.cache==True:
+                    with open("data/wind/%s_%s_%s.pkl"%(lat,long,forecast_to_use),"wb") as dump_file:
+                        pickle.dump(self.profiles[(lat,long,forecast_to_use)],dump_file)
+            else:
+                with open("data/wind/%s_%s_%s.pkl"%(lat,long,forecast_to_use),"rb") as dump_file:
+                    self.profiles[(lat,long,forecast_to_use)]=pickle.load(dump_file)
+                self.points.append((lat,long,forecast_to_use))
+        
+        return self.profiles[(lat,long,forecast_to_use)][0](alt),self.profiles[(lat,long,forecast_to_use)][2](alt)
+
+if __name__=="__main__":
+    w=Wind("20210321 15:00",cache=True)
+    print(w.get(0,0,0,0))

data/pyro.json

@@ -38,7 +38,7 @@
 
 # Import drag coefficients from RASAero II
 aero_data = pyro.AeroData.from_rasaero(
-    "data/Martlet4RASAeroII.CSV", REF_AREA, C_DAMP_PITCH, C_DAMP_ROLL
+    "data/Martlet4RasAeroII.CSV", REF_AREA, C_DAMP_PITCH, C_DAMP_ROLL
 )
 # aero_data.show_plot()   #Show plots of how the program interpreted the data, so you can visually check if it's correct
 
@@ -87,7 +87,7 @@
     run_date="20210216",
 )  # Use this version if you don't want to use the real wind (e.g. to test something else)
 
-parachute_Data = pd.read_csv("data/Sample_Parachute_Cd.CSV")
+parachute_Data = pd.read_csv("data/Sample_Parachute_Cd.csv")
 mach_array = parachute_Data["Mach_Number"].to_numpy()
 main_cd_array = parachute_Data["Main_Cd"].to_numpy()
 dro_cd_array = parachute_Data["Drogue_Cd"].to_numpy()