password=password)
# --- Begin execution ----------------------
# estimate dates for start/end of rotation
CR_start = datetime.datetime(1853, 11, 9)
CR_dur = datetime.timedelta(days=27.2753)
estimated_center_date = CR_start + (cr_rot - 0.5) * CR_dur
# get the decimal Carrington number for Earth at this time
cr_earth = sunpy.coordinates.sun.carrington_rotation_number(
estimated_center_date)
# calc reasonable estimate of rotation start/end
movie_start = estimated_center_date - (cr_earth - cr_rot) * CR_dur
movie_end = estimated_center_date + (cr_rot + 1 - cr_earth) * CR_dur
# query maps in time range
map_info, data_info, method_info, image_assoc = db_funs.query_euv_maps(
db_session,
mean_time_range=(movie_start, movie_end),
methods=map_methods,
var_val_range=map_vars)
psi_plot.euv_map_movie(map_info,
png_dir=temp_png,
movie_path=full_path,
map_dir=map_dir,
int_range=int_range,
fps=fps,
dpi=dpi)
db_session.close()
# 'mysql-Q' Use the remote MySQL database on Q
# 'mysql-Q_test' Use the development database on Q
user = "******" # only needed for remote databases.
password = "" # See example109 for setting-up an encrypted password. In this case leave password="", and
# init_db_conn_old() will automatically find and use your saved password. Otherwise, enter your MySQL password here.
# Establish connection to database
if use_db == 'sqlite':
# setup database connection to local sqlite file
sqlite_path = os.path.join(database_dir, sqlite_filename)
db_session = db_funcs.init_db_conn_old(db_name=use_db,
chd_base=db_class.Base,
sqlite_path=sqlite_path)
elif use_db in ('mysql-Q', 'mysql-Q_test'):
# setup database connection to MySQL database on Q
db_session = db_funcs.init_db_conn_old(db_name=use_db,
chd_base=db_class.Base,
user=user,
password=password)
# query the maps to be deleted
map_info, data_info, method_info, image_assoc = db_funcs.query_euv_maps(
db_session,
mean_time_range=(query_time_min, query_time_max),
methods=map_methods)
db_session = db_funcs.remove_euv_map(db_session, map_info, map_data_dir)
db_session.close()
def coronal_flux(db_session,
chd_contour,
frame_timestamp,
map_dir,
window_half_width=datetime.timedelta(hours=12)):
window_min = frame_timestamp - window_half_width
window_max = frame_timestamp + window_half_width
# find PSI magnetic map before and after CHD timestamp
map_info, data_info, method_info, image_assoc = db_funs.query_euv_maps(
db_session,
mean_time_range=[window_min, window_max],
n_images=1,
methods=["ProjFlux2Map"])
below_index = map_info.date_mean <= frame_timestamp
if any(below_index):
first_below_index = np.max(np.where(below_index))
else:
first_below_index = None
above_index = map_info.date_mean >= frame_timestamp
if any(above_index):
first_above_index = np.min(np.where(above_index))
else:
first_above_index = None
if first_below_index is None:
if first_above_index is None:
print(
"No B_r maps in the specified window. Flux calculation canceled."
)
else:
# use first_above_index map
full_path = os.path.join(map_dir,
map_info.fname[first_above_index])
interp_map = psi_datatype.read_psi_map(full_path)
else:
if first_above_index is None:
# use first_below index map
full_path = os.path.join(map_dir,
map_info.fname[first_below_index])
interp_map = psi_datatype.read_psi_map(full_path)
else:
# load both maps
full_path = os.path.join(map_dir,
map_info.fname[first_above_index])
first_above = psi_datatype.read_psi_map(full_path)
full_path = os.path.join(map_dir,
map_info.fname[first_below_index])
first_below = psi_datatype.read_psi_map(full_path)
# do linear interpolation
interp_map = first_above.__copy__()
below_weight = (frame_timestamp -
map_info.date_mean[first_below_index]) / (
map_info.date_mean[first_above_index] -
map_info.date_mean[first_below_index])
above_weight = 1. - below_weight
interp_map.data = below_weight * first_below.data + above_weight * first_above.data
# double check that Contour and Br map have same mesh???
# temporary solution for testing purposes
y_index = chd_contour.contour_pixels_theta
x_index = chd_contour.contour_pixels_phi
br_shape = interp_map.data.shape
keep_ind = (y_index <= br_shape[0]) & (x_index <= br_shape[1])
y_index = y_index[keep_ind]
x_index = x_index[keep_ind]
# use contour indices and Br linear approx to calc flux
# calc theta from sin(lat). increase float precision to reduce numeric
# error from np.arcsin()
theta_y = np.pi / 2 - np.arcsin(np.flip(interp_map.y.astype('float64')))
# generate a mesh
map_mesh = map_manip.MapMesh(interp_map.x, theta_y)
# convert area characteristic of mesh back to map grid
map_da = np.flip(map_mesh.da.transpose(), axis=0)
# sum total flux
chd_flux = map_manip.br_flux_indices(interp_map, y_index, x_index, map_da)
return chd_flux
# Establish connection to database
if use_db == 'sqlite':
# setup database connection to local sqlite file
sqlite_path = os.path.join(database_dir, sqlite_filename)
db_session = db_funs.init_db_conn_old(db_name=use_db, chd_base=db_class.Base,
sqlite_path=sqlite_path)
elif use_db in ('mysql-Q', 'mysql-Q_test'):
# setup database connection to MySQL database on Q
db_session = db_funs.init_db_conn_old(db_name=use_db, chd_base=db_class.Base,
user=user, password=password)
# find PSI magnetic map before and after CHD timestamp
map_info, data_info, method_info, image_assoc = db_funs.query_euv_maps(
db_session, mean_time_range=[window_min, window_max], n_images=1,
methods=["ProjFlux2Map"])
below_index = map_info.date_mean <= frame_timestamp
if any(below_index):
first_below_index = np.max(np.where(below_index))
else:
first_below_index = None
above_index = map_info.date_mean >= frame_timestamp
if any(above_index):
first_above_index = np.min(np.where(above_index))
else:
first_above_index = None
if first_below_index is None:
if first_above_index is None: