def __init__(self, normal, degree=None, axis=None, time=None, rad = None, height = None):
MarsSpicer.__init__(self, time)
self.r = rad
self._h = height
if degree and axis:
rot_axis = zeros(3)
rot_axis[axis] = 1
self.normal = vrotv(normal,deg2rad(degree), rot_axis)
self.gamma = degree
else:
self.normal = normal
dem = ImgData(os.path.join(folder, 'big_spider_dem.cub'))
slopes = ImgData(os.path.join(folder,'big_spider_slopes.tif'))
aspects = ImgData(os.path.join(folder,'big_spider_aspects.tif'))
spider1 = ImgData(os.path.join(folder,'ESP_022607_0985_cropped_big_spider.cub'))
# spider2 = ImgData(os.path.join(folder,'ESP_022699_0985_cropped_big_spider.cub'))
# read in required data
dem.read_all()
slopes.read_all()
aspects.read_all()
spider1.read_all()
correct_azimuth(dem, aspects)
# create MarsSpicer object
mspice = MarsSpicer()
mspice.goto_ls_0()
mspice.advance_time_by(24*3600*356)
utc = mspice.utc
# seconds per step
timestep = 600
# how many steps for the time series
nsteps = 500
mspice.goto('inca')
# getting l_s times
times, _ = mspice.time_series('F_aspect',timestep, nsteps, provide_times='l_s')
insol = np.zeros_like(dem.data)
diff_angle = vsep(mspicer.trnormal, mspicer.sun_direction)
if (mspicer.illum_angles.dsolar > 90) or (np.degrees(diff_angle) > 90):
to_append = 0
else:
to_append = mspicer.solar_constant * dt.seconds * math.cos(diff_angle)
energies.append(to_append)
mspicer.time += dt
return np.array((ets, energies))
def save_data_to_file(data, fname, start, dt):
with open(fname,'w') as f:
f.write('# Start: {1}, dt: {0} s, Intensities in J/(dt*m**2)\n'.format(dt.seconds,start.isoformat()))
np.savetxt(f, data.T)
# location setup
mspicer = MarsSpicer()
mspicer.set_spoint_by(lat=85,lon=0)
# timing setup
mspicer.goto_ls_0()
mspicer.time -= dt.timedelta(days=10,hours=12)
# dt, the time step
my_dt = dt.timedelta(hours=1)
# saving for restart later
start_time = mspicer.time
out_flat = create_arrays(mspicer, 50, my_dt)
save_data_to_file(out_flat[1], 'insolation_flat.txt', start_time, my_dt)
def __init__(self, time = None, dt = None):
MarsSpicer.__init__(self, time)
def main():
# default time is now:
mspice = MarsSpicer()
# set up location
mspice.set_spoint_by(lat=85, lon = 0)
# set up starting time of analysis, l_s = 0
mspice.utc = '2011-09-13T14:24:33.733548'
# mspice.time += dt.timedelta(30)
# ls1 = mspice.l_s
# utc1 = mspice.utc
# mspice.time += dt.timedelta(1)
# ls2 = mspice.l_s
# mspice.utc = utc1
# stopping l_s value
end_ls = 360
# l_s resolution
# ls_res = 0.02
ls_res = 5.0
# time resolution
time_res = 3600
# save this time for multiple runs for resetting mspice each time
start_time = mspice.time
# container for all energy arrays
energies = []
# labels for the plotting
labels = []
# tilt the surface normal by 30 degree to the north (north = default)
# this creates an instance variable called 'tnormal'
mspice.tilt = 30
# first time, save the bigtimes array
bigtimes, energies_t30 = outer_loop(mspice, end_ls, ls_res, 'tilted_normal',time_res=time_res)
energies.append(energies_t30)
labels.append('t30')
# rotate the tilted vector around the local surface normal to create an aspect
# angle
# this creates an instance variable called 'trnormal'
mspice.aspect = 90
mspice.time = start_time
energies.append(outer_loop(mspice, end_ls, ls_res, 'tilted_rotated_normal',time_res=time_res)[1])
labels.append('t30_a90')
mspice.time = start_time
energies.append(outer_loop(mspice, end_ls, ls_res, 'snormal',time_res=time_res)[1])
labels.append('flat')
mspice.aspect = 180
mspice.time = start_time
energies.append(outer_loop(mspice, end_ls, ls_res, 'tilted_rotated_normal',time_res=time_res)[1])
labels.append('t30,a180')
fig = figure()
ax = fig.add_subplot(111)
grid()
for energy,label in zip(energies,labels):
ax.plot(bigtimes,energy, '-*', label=label)
ax.set_xlabel('L_s [deg]')
ax.set_ylabel('Insolation per 10 L_s [MJ]')
ax.set_title('Insolation of t_ilted and a_spected (rotated) surfaces at 85 N')
ax.legend(loc='best')
show()
return (energies, labels)
from __future__ import division
import numpy as np
from matplotlib.pyplot import figure, show, cm, grid, subplots
from matplotlib.ticker import MultipleLocator
from use_mspicer import outer_loop
from kmaspice import MarsSpicer
# default time is now:
mspice = MarsSpicer()
# set up location
mspice.set_spoint_by(lat=85, lon = 0)
# set up starting time of analysis, l_s = 0
mspice.utc = '2011-09-13T14:24:33.733548'
# stopping l_s value
end_ls = 360
# l_s resolution
ls_res = 10
# save this time for multiple runs for resetting mspice each time
start_time = mspice.time
# container for all energy arrays
energies = []
# labels for the plotting
labels = []
"""
from __future__ import print_function
from kmaspice import MarsSpicer
from numpy import array
import pdstools
labels = pdstools.PDSLabel('/Users/maye/data/hirise/inca/ESP_022607_0985_RED.LBL')
# taking these from the grayscale label of ESP_022607_0985
max_lat = labels.maxlat
min_lat = labels.minlat
east_lon = labels.eastmost
west_lon = labels.westmost
start_time = labels.time
event = MarsSpicer(time=start_time)
inc_angles = []
for lat,lon in [(max_lat,east_lon),
(max_lat,west_lon),
(min_lat,east_lon),
(min_lat,west_lon)]:
event.set_spoint_by(lat=lat,lon=lon)
inc_angles.append(event.illum_angles.dsolar)
print("Lat = {0}, Lon = {1}, \nIncidence angle:{2}\n".format(
lat,lon,event.illum_angles.dsolar))
angles = array(inc_angles)
delta = angles.max()-angles.min()
# delta between north and top of image
delta_angle = np.degrees(np.arctan2(v1[1],v1[0]))-90.0
# dsample = newPoint.sample - dem.center.sample
# dline = newPoint.line - dem.center.line
# plt.quiver(dem.center.sample,dem.center.line,dsample,dline,angles='xy', scale_units='xy', scale=1)
# correct aspects for delta angle
# it needs to be added, because aspects go clock-wise
aspects.data += delta_angle
# bend around data > 360
mask = aspects.data > 360.0
aspects.data[mask] = aspects.data[mask] - 360.0
# # create MarsSpicer object
mspice = MarsSpicer()
utc1 = '2011-05-24T00:58:08.402'
utc2 = '2011-05-31T05:01:50.854'
mspice.utc = utc2
mspice.obs = 'MRO'
mspice.instrument = 'MRO_HIRISE'
mspice.set_spoint_by('sincpt')
phase = np.zeros_like(dem.data)
emissions = []
incidences = []
rev_srfvec = spice.vminus(mspice.srfvec)
for sample in xrange(phase.shape[0]):
if sample % 10 == 0:
print('Sample {0}'.format(sample))
