Merge pull request #9 from GEUS-SICE/dev

pySICEv1.5

bav_lib.py

@@ -22,6 +22,43 @@
 months = mdates.MonthLocator()  # every month
 years_fmt = mdates.DateFormatter('%Y')
 
+#%% 
+from math import radians, cos, sin, asin, sqrt
+def haversine(lat1, lon1, lat2, lon2, to_radians=True, earth_radius=6371):
+    """
+    slightly modified version: of http://stackoverflow.com/a/29546836/2901002
+
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees or in radians)
+
+    All (lat, lon) coordinates must have numeric dtypes and be of equal length.
+
+    """
+    if to_radians:
+        lat1, lon1, lat2, lon2 = np.radians([lat1, lon1, lat2, lon2])
+
+    a = np.sin((lat2-lat1)/2.0)**2 + \
+        np.cos(lat1) * np.cos(lat2) * np.sin((lon2-lon1)/2.0)**2
+
+    return earth_radius * 2 * np.arcsin(np.sqrt(a))
+
+# %% 
+def stat_title(x,y,ax):
+    ind = np.logical_and(pd.notnull(x),pd.notnull(y))
+    x = x[ind]
+    y=y[ind]
+    x = x.values.reshape(-1,1)
+    y = y.values.reshape(-1,1)    
+
+    lr = linear_model.LinearRegression()
+    lr.fit(x,y)
+    # print('Coefficients: \n', lr.coef_)    
+    preds = lr.predict(x)
+    ax.set_title('R2=%.3f\nRMSE=%.2f\nN=%.0f' % (r2_score(y,preds),
+                                              mean_squared_error(y,preds), 
+                                              len(x)))
+    return ax
+  #%% 
 def multi_plot(data_out, 
                sites = ['KAN_M', 'KAN_U'],sp1 = 4, sp2 = 2,
                title = '', OutputFolder='figures/',
@@ -267,5 +304,36 @@ def mosaic_albedo_fit(df, Rad_in):
             ax[i, j].set_ylim([0.01, 1.05])
             ax[i, j].grid(True)
     fig.savefig('./output/linear_'+Rad_in+'oa.png',bbox_inches='tight')
+#%% 
+def overall_axis_label(fig, xlab, ylab):
+    ax0 = fig.add_subplot(111)    # The big subplot
+
+    # Turn off axis lines and ticks of the big subplot
+    ax0.spines['top'].set_color('none')
+    ax0.spines['bottom'].set_color('none')
+    ax0.spines['left'].set_color('none')
+    ax0.spines['right'].set_color('none')
+    ax0.tick_params(labelcolor='w', top=False, bottom=False, left=False, right=False)
+    ax0.patch.set_visible(False)
+
+    # Set common labels
+    ax0.set_xlabel('Date')
+
+    if isinstance(ylab,str):
+        ax0.set_ylabel(ylab)
+        ax0_2 = []
+    else 
+        ax0.set_ylabel(ylab[0])
 
+        ax0_2 = ax0.twinx()  
+        ax0_2.set_ylabel(ylab[1])
+
+        ax0_2.spines['top'].set_color('none')
+        ax0_2.spines['bottom'].set_color('none')
+        ax0_2.spines['left'].set_color('none')
+        ax0_2.spines['right'].set_color('none')
+        ax0_2.tick_params(labelcolor='w', top=False, bottom=False, left=False, right=False)
+
+        ax0_2.patch.set_visible(False)
+    return ax0, ax0_2
 

misc/gains_olci.csv

@@ -0,0 +1,22 @@
+platform,band,wavelength,average_gain,standard_deviation
+A,1,400,0.975458,0.005544
+A,2,412.5,0.974061,0.005897
+A,3,442.5,0.974919,0.005435
+A,4,490,0.968897,0.005645
+A,5,510,0.971844,0.004139
+A,6,560,0.975705,0.003086
+A,7,620,0.980013,0.002107
+A,8,665,0.978339,0.001412
+A,9,673.75,0.978597,0.002128
+A,10,681.25,0.979083,0.001504
+A,11,708.75,0.980135,0.004555
+A,12,753.75,0.985516,0.003723
+A,13,761.25,1,0
+A,14,764.375,1,0
+A,15,767.5,1,0
+A,16,778.75,0.987718,0.00352
+A,17,865,0.986,
+A,18,885,0.986569,0.00176
+A,19,900,1,0
+A,20,940,1,0
+A,21,1020,0.913161,0.008537