post refactor test

Author: yoachim

runs/baseline_tests/v2/base_try.py

@@ -0,0 +1,127 @@
+import numpy as np
+import lsst.sims.featureScheduler as fs
+from lsst.sims.featureScheduler.utils import (sim_runner, set_default_nside, standard_goals,
+                                              calc_norm_factor, generate_goal_map)
+import lsst.sims.featureScheduler.surveys as survey
+import lsst.sims.featureScheduler.basis_functions as basis_functions
+from lsst.sims.speedObservatory import Speed_observatory
+import matplotlib.pylab as plt
+import healpy as hp
+import time
+
+# Let's add a zenith mask to see if that brings the slewtime down
+
+t0 = time.time()
+
+survey_length = 365.25*10  # days
+nside = set_default_nside(nside=32)
+# Define what we want the final visit ratio map to look like
+years = np.round(survey_length/365.25)
+# get rid of silly northern strip.
+target_map = standard_goals(nside=nside)
+norm_factor = calc_norm_factor(target_map)
+
+# set up a cloud map
+cloud_map = target_map['r']*0 + 0.7
+
+# List to hold all the surveys (for easy plotting later)
+surveys = []
+
+# Set up observations to be taken in blocks
+filter1s = ['u', 'g', 'r', 'i', 'z', 'y']
+filter2s = [None, 'g', 'r', 'i', None, None]
+pair_surveys = []
+for filtername, filtername2 in zip(filter1s, filter2s):
+    bfs = []
+    bfs.append(basis_functions.M5_diff_basis_function(filtername=filtername, nside=nside))
+    if filtername2 is not None:
+        bfs.append(basis_functions.M5_diff_basis_function(filtername=filtername2, nside=nside))
+    bfs.append(basis_functions.Target_map_basis_function(filtername=filtername,
+                                            target_map=target_map[filtername],
+                                            out_of_bounds_val=hp.UNSEEN, nside=nside,
+                                            norm_factor=norm_factor))
+    if filtername2 is not None:
+        bfs.append(basis_functions.Target_map_basis_function(filtername=filtername2,
+                                                target_map=target_map[filtername2],
+                                                out_of_bounds_val=hp.UNSEEN, nside=nside,
+                                                norm_factor=norm_factor))
+    bfs.append(basis_functions.Slewtime_basis_function(filtername=filtername, nside=nside))
+    bfs.append(basis_functions.Strict_filter_basis_function(filtername=filtername))
+    # Masks, give these 0 weight
+    bfs.append(basis_functions.Zenith_shadow_mask_basis_function(nside=nside, shadow_minutes=60., max_alt=76.))
+    bfs.append(basis_functions.Moon_avoidance_basis_function(nside=nside, moon_distance=40.))
+    bfs.append(basis_functions.Bulk_cloud_basis_function(max_cloud_map=cloud_map, nside=nside))
+    weights = np.array([3.0, 3.0, .3, .3, 3., 3., 0., 0., 0.])
+    if filtername2 is None:
+        # Need to scale weights up so filter balancing still works properly.
+        weights = np.array([6.0, 0.6, 3., 3., 0., 0., 0.])
+    # XXX-
+    # This is where we could add a look-ahead basis function to include m5_diff in the future.
+    # Actually, having a near-future m5 would also help prevent switching to u or g right at twilight?
+    # Maybe just need a "filter future" basis function?
+    if filtername2 is None:
+        survey_name = 'blob, %s' % filtername
+    else:
+        survey_name = 'blob, %s%s' % (filtername, filtername2)
+    surveys.append(survey.Blob_survey(bfs, weights, filtername1=filtername, filtername2=filtername2,
+                                      survey_note=survey_name, ignore_obs='DD'))
+    pair_surveys.append(surveys[-1])
+
+
+# Let's set up some standard surveys as well to fill in the gaps. This is my old silly masked version.
+# It would be good to put in Tiago's verion and lift nearly all the masking. That way this can also
+# chase sucker holes.
+#filters = ['u', 'g', 'r', 'i', 'z', 'y']
+filters = ['i', 'z', 'y']
+
+greedy_target_map = standard_goals(nside=nside)
+# Let's take out the NES area on the target maps. This way we won't
+# take images in the NES that aren't paired.
+temp_map = generate_goal_map(nside=nside, NES_fraction=1.,
+                                WFD_fraction=0, SCP_fraction=0,
+                                 GP_fraction=0, WFD_upper_edge_fraction=0.)
+nes_pix = np.where(temp_map == 1)
+for filtername in greedy_target_map:
+    greedy_target_map[filtername][nes_pix] = 0
+
+greedy_surveys = []
+for filtername in filters:
+    bfs = []
+    bfs.append(basis_functions.M5_diff_basis_function(filtername=filtername, nside=nside))
+    bfs.append(basis_functions.Target_map_basis_function(filtername=filtername,
+                                            target_map=greedy_target_map[filtername],
+                                            out_of_bounds_val=hp.UNSEEN, nside=nside,
+                                            norm_factor=norm_factor))
+
+    #bfs.append(fs.North_south_patch_basis_function(zenith_min_alt=50., nside=nside))
+    bfs.append(basis_functions.Slewtime_basis_function(filtername=filtername, nside=nside))
+    bfs.append(basis_functions.Strict_filter_basis_function(filtername=filtername))
+    bfs.append(basis_functions.Zenith_shadow_mask_basis_function(nside=nside, shadow_minutes=60., max_alt=76.))
+    bfs.append(basis_functions.Moon_avoidance_basis_function(nside=nside, moon_distance=40.))
+    bfs.append(basis_functions.Bulk_cloud_basis_function(max_cloud_map=cloud_map, nside=nside))
+    weights = np.array([3.0, 0.3, 3., 3., 0., 0., 0.])
+    # Might want to try ignoring DD observations here, so the DD area gets covered normally--DONE
+    surveys.append(survey.Greedy_survey(bfs, weights, block_size=1, filtername=filtername,
+                                        dither=True, nside=nside, ignore_obs='DD'))
+    greedy_surveys.append(surveys[-1])
+
+# Set up the DD surveys
+dd_surveys = survey.generate_dd_surveys()
+surveys.extend(dd_surveys)
+
+survey_list_o_lists = [dd_surveys, pair_surveys, greedy_surveys]
+
+# Debug to stop at a spot if needed
+n_visit_limit = None
+
+# put in as list-of-lists so pairs get evaluated first.
+scheduler = fs.Core_scheduler(survey_list_o_lists, nside=nside)
+observatory = Speed_observatory(nside=nside, quickTest=True)
+observatory, scheduler, observations = sim_runner(observatory, scheduler,
+                                                     survey_length=survey_length,
+                                                     filename='baseline_test%iyrs.db' % years,
+                                                     delete_past=True, n_visit_limit=n_visit_limit)
+t1 = time.time()
+delta_t = t1-t0
+print('ran in %.1f min = %.1f hours' % (delta_t/60., delta_t/3600.))
+

upload.sh

@@ -1,3 +1,3 @@
 #!/bin/bash
-rsync -av --progress .  lsst-dev.ncsa.illinois.edu:"/datasets/public_html/sim-data/beta_slair_surveys/"
+rsync -av --progress --delete .  lsst-dev.ncsa.illinois.edu:"/datasets/public_html/sim-data/beta_slair_surveys/"
 #