Merge pull request #68 from acisops/namespace_and_answers

Change namespace package imports and update answers after updated sun position calculation

Author: jzuhone

acis_thermal_check/apps/acisfp_check.py

@@ -16,7 +16,7 @@
 import matplotlib
 from astropy.table import Table
 from cxotime import CxoTime
-from Ska.Matplotlib import cxctime2plotdate
+from ska_matplotlib import cxctime2plotdate
 
 from acis_thermal_check import ACISThermalCheck, get_options, mylog
 

acis_thermal_check/apps/cea_check.py

@@ -14,7 +14,7 @@
 import sys
 
 import matplotlib
-from Ska.Matplotlib import pointpair
+from ska_matplotlib import pointpair
 
 from acis_thermal_check import ACISThermalCheck, get_options, mylog
 from acis_thermal_check.utils import PredictPlot

acis_thermal_check/main.py

@@ -7,17 +7,16 @@
 from pathlib import Path, PurePath
 from pprint import pformat
 
+import cheta.fetch_sci as fetch
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
-import Ska.DBI
-import Ska.engarchive.fetch_sci as fetch
-import Ska.Numpy
+import ska_numpy
 from astropy.io import ascii
 from astropy.table import Table
 from cxotime import CxoTime
 from kadi import events
-from Ska.Matplotlib import cxctime2plotdate, plot_cxctime, pointpair
+from ska_matplotlib import cxctime2plotdate, plot_cxctime, pointpair
 from xija.get_model_spec import get_xija_model_spec
 
 import acis_thermal_check
@@ -280,7 +279,7 @@ def get_ephemeris(self, start, stop, times):
         e = fetch.MSIDset(msids, start - 2000.0, stop + 2000.0)
         ephem = {}
         for msid in msids:
-            ephem[msid] = Ska.Numpy.interpolate(e[msid].vals, e[msid].times, times)
+            ephem[msid] = ska_numpy.interpolate(e[msid].vals, e[msid].times, times)
         return ephem
 
     def get_states(self, tlm, T_init):
@@ -940,7 +939,7 @@ def make_validation_plots(self, tlm, model_spec, outdir):
             pred["roll"] = model.comp["roll"].mvals
 
         # Interpolate the model and data to a consistent set of times
-        idxs = Ska.Numpy.interpolate(
+        idxs = ska_numpy.interpolate(
             np.arange(len(tlm)),
             tlm["date"],
             model.times,
@@ -1541,7 +1540,7 @@ def get_telem_values(self, tstart, days=14):
         outnames = ["date"] + [name_map.get(x, x) for x in telem_msids]
         vals = {name_map.get(x, x): msidset[x].vals for x in telem_msids}
         vals["date"] = msidset.times
-        out = Ska.Numpy.structured_array(vals, colnames=outnames)
+        out = ska_numpy.structured_array(vals, colnames=outnames)
 
         # tscpos needs to be converted to steps and must be in the right direction
         out["tscpos"] *= -397.7225924607