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COMPASS
5.0.0
End-to-end AO simulation tool using GPU acceleration
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Functions | |
def | dphi_highpass (r, x0, tabx, taby) |
def | dphi_lowpass (r, x0, L0, tabx, taby) |
def | Ij0t83 (x, tabx, taby) |
def | unMoinsJ0 (x) |
def | tabulateIj0 (L0) |
def | asymp_macdo (x) |
def | macdo (x) |
def | rodconan (r, L0) |
def | variance (f, contributors, method="Default") |
Return the error variance of specified contributors params: f (h5py.File) : roket hdf5 file opened with h5py contributors (list of string) : list of the contributors method (optional, default="Default") : if "Independence", the function returns ths sum of the contributors variances. More... | |
def | varianceMultiFiles (fs, frac_per_layer, contributors) |
Return the variance computed from the sum of contributors of roket files fs, ponderated by frac params: fs (list) : list of hdf5 files opened with h5py frac_per_layer (dict) : frac for each layer contributors (list of string) : list of the contributors return: v (np.array(dim=1)) : variance vector. More... | |
def | cumulativeSR (v, Lambda_tar) |
Returns the cumulative Strehl ratio over the modes from the variance on each mode params: v (np.array(dim=1)) : variance vector return: s (np.array(dim=1)) : cumulative SR. More... | |
def | update (attrs, old, new) |
Variables | |
string | datapath = "/home/fferreira/Data/correlation/" |
filenames = glob.glob(datapath + "roket_8m_1layer_dir*_cpu.h5") | |
list | files = [] |
ff = h5py.File(f, mode='r') | |
tuple | nmodes = (files[0])["P"][:].shape[0] |
list | xpos = files[0].attrs["wfs.xpos"][0] |
list | ypos = files[0].attrs["wfs.ypos"][0] |
list | contributors = ["tomography", "bandwidth"] |
list | Lambda_tar = files[0].attrs["target.Lambda"][0] |
list | Lambda_wfs = files[0].attrs["wfs.Lambda"][0] |
list | L0 = files[0].attrs["L0"][0] |
list | dt = files[0].attrs["ittime"] |
list | H = files[0].attrs["atm.alt"][0] |
int | RASC = 180 / np.pi * 3600. |
int | Htheta |
list | r0 = files[0].attrs["r0"] * (Lambda_tar / Lambda_wfs)**(6. / 5.) |
nfiles = len(files) | |
data = np.zeros((nmodes, 4, nfiles)) | |
theta = np.zeros(nfiles) | |
speeds = np.zeros(nfiles) | |
gain = np.zeros(nfiles) | |
tabx | |
taby | |
int | ind = 0 |
f | |
method | |
tuple | covar = (data[:, 0, :] - data[:, 3, :]) / 2. |
xaxis_select | |
yaxis_select | |
speed_select | |
dir_select | |
gain_select | |
source = ColumnDataSource(data=dict(x=[], y=[], speed=[], theta=[], gain=[])) | |
source_model = ColumnDataSource(data=dict(x=[], y=[], speed=[], theta=[], gain=[])) | |
hover | |
string | TOOLS = "resize,save,pan,box_zoom,tap, box_select, wheel_zoom, lasso_select,reset" |
p = figure(plot_height=600, plot_width=700, title="", tools=[hover, TOOLS]) | |
x | |
y | |
size | |
color | |
dictionary | xmap = {"Windspeed": speeds, "Winddir": theta, "Gain": gain} |
dictionary | ymap |
list | buttons = [xaxis_select, speed_select, dir_select, yaxis_select, gain_select] |
def correlation_bokeh.asymp_macdo | ( | x | ) |
def correlation_bokeh.cumulativeSR | ( | v, | |
Lambda_tar | |||
) |
Returns the cumulative Strehl ratio over the modes from the variance on each mode params: v (np.array(dim=1)) : variance vector return: s (np.array(dim=1)) : cumulative SR.
Definition at line 190 of file correlation_bokeh.py.
def correlation_bokeh.dphi_highpass | ( | r, | |
x0, | |||
tabx, | |||
taby | |||
) |
Definition at line 23 of file correlation_bokeh.py.
def correlation_bokeh.dphi_lowpass | ( | r, | |
x0, | |||
L0, | |||
tabx, | |||
taby | |||
) |
Definition at line 29 of file correlation_bokeh.py.
def correlation_bokeh.Ij0t83 | ( | x, | |
tabx, | |||
taby | |||
) |
def correlation_bokeh.macdo | ( | x | ) |
def correlation_bokeh.rodconan | ( | r, | |
L0 | |||
) |
Definition at line 113 of file correlation_bokeh.py.
def correlation_bokeh.tabulateIj0 | ( | L0 | ) |
def correlation_bokeh.unMoinsJ0 | ( | x | ) |
def correlation_bokeh.update | ( | attrs, | |
old, | |||
new | |||
) |
def correlation_bokeh.variance | ( | f, | |
contributors, | |||
method = "Default" |
|||
) |
Return the error variance of specified contributors params: f (h5py.File) : roket hdf5 file opened with h5py contributors (list of string) : list of the contributors method (optional, default="Default") : if "Independence", the function returns ths sum of the contributors variances.
If "Default", it returns the variance of the contributors sum
Definition at line 135 of file correlation_bokeh.py.
def correlation_bokeh.varianceMultiFiles | ( | fs, | |
frac_per_layer, | |||
contributors | |||
) |
Return the variance computed from the sum of contributors of roket files fs, ponderated by frac params: fs (list) : list of hdf5 files opened with h5py frac_per_layer (dict) : frac for each layer contributors (list of string) : list of the contributors return: v (np.array(dim=1)) : variance vector.
Definition at line 168 of file correlation_bokeh.py.
list correlation_bokeh.buttons = [xaxis_select, speed_select, dir_select, yaxis_select, gain_select] |
Definition at line 333 of file correlation_bokeh.py.
correlation_bokeh.color |
Definition at line 321 of file correlation_bokeh.py.
correlation_bokeh.contributors = ["tomography", "bandwidth"] |
Definition at line 268 of file correlation_bokeh.py.
Definition at line 300 of file correlation_bokeh.py.
Definition at line 280 of file correlation_bokeh.py.
string correlation_bokeh.datapath = "/home/fferreira/Data/correlation/" |
Definition at line 256 of file correlation_bokeh.py.
correlation_bokeh.dir_select |
Definition at line 310 of file correlation_bokeh.py.
list correlation_bokeh.dt = files[0].attrs["ittime"] |
Definition at line 272 of file correlation_bokeh.py.
correlation_bokeh.f |
Definition at line 294 of file correlation_bokeh.py.
correlation_bokeh.ff = h5py.File(f, mode='r') |
Definition at line 261 of file correlation_bokeh.py.
correlation_bokeh.filenames = glob.glob(datapath + "roket_8m_1layer_dir*_cpu.h5") |
Definition at line 257 of file correlation_bokeh.py.
list correlation_bokeh.files = [] |
Definition at line 259 of file correlation_bokeh.py.
correlation_bokeh.gain = np.zeros(nfiles) |
Definition at line 283 of file correlation_bokeh.py.
correlation_bokeh.gain_select |
Definition at line 312 of file correlation_bokeh.py.
list correlation_bokeh.H = files[0].attrs["atm.alt"][0] |
Definition at line 273 of file correlation_bokeh.py.
correlation_bokeh.hover |
Definition at line 316 of file correlation_bokeh.py.
int correlation_bokeh.Htheta |
Definition at line 275 of file correlation_bokeh.py.
int correlation_bokeh.ind = 0 |
Definition at line 291 of file correlation_bokeh.py.
list correlation_bokeh.L0 = files[0].attrs["L0"][0] |
Definition at line 271 of file correlation_bokeh.py.
list correlation_bokeh.Lambda_tar = files[0].attrs["target.Lambda"][0] |
Definition at line 269 of file correlation_bokeh.py.
list correlation_bokeh.Lambda_wfs = files[0].attrs["wfs.Lambda"][0] |
Definition at line 270 of file correlation_bokeh.py.
correlation_bokeh.method |
Definition at line 294 of file correlation_bokeh.py.
correlation_bokeh.nfiles = len(files) |
Definition at line 279 of file correlation_bokeh.py.
tuple correlation_bokeh.nmodes = (files[0])["P"][:].shape[0] |
Definition at line 265 of file correlation_bokeh.py.
Definition at line 320 of file correlation_bokeh.py.
list correlation_bokeh.r0 = files[0].attrs["r0"] * (Lambda_tar / Lambda_wfs)**(6. / 5.) |
Definition at line 278 of file correlation_bokeh.py.
int correlation_bokeh.RASC = 180 / np.pi * 3600. |
Definition at line 274 of file correlation_bokeh.py.
correlation_bokeh.size |
Definition at line 321 of file correlation_bokeh.py.
Definition at line 314 of file correlation_bokeh.py.
correlation_bokeh.source_model = ColumnDataSource(data=dict(x=[], y=[], speed=[], theta=[], gain=[])) |
Definition at line 315 of file correlation_bokeh.py.
correlation_bokeh.speed_select |
Definition at line 308 of file correlation_bokeh.py.
correlation_bokeh.speeds = np.zeros(nfiles) |
Definition at line 282 of file correlation_bokeh.py.
correlation_bokeh.tabx |
Definition at line 285 of file correlation_bokeh.py.
correlation_bokeh.taby |
Definition at line 285 of file correlation_bokeh.py.
correlation_bokeh.theta = np.zeros(nfiles) |
Definition at line 281 of file correlation_bokeh.py.
string correlation_bokeh.TOOLS = "resize,save,pan,box_zoom,tap, box_select, wheel_zoom, lasso_select,reset" |
Definition at line 318 of file correlation_bokeh.py.
correlation_bokeh.x |
Definition at line 321 of file correlation_bokeh.py.
correlation_bokeh.xaxis_select |
Definition at line 302 of file correlation_bokeh.py.
dictionary correlation_bokeh.xmap = {"Windspeed": speeds, "Winddir": theta, "Gain": gain} |
Definition at line 324 of file correlation_bokeh.py.
list correlation_bokeh.xpos = files[0].attrs["wfs.xpos"][0] |
Definition at line 266 of file correlation_bokeh.py.
correlation_bokeh.y |
Definition at line 321 of file correlation_bokeh.py.
correlation_bokeh.yaxis_select |
Definition at line 304 of file correlation_bokeh.py.
dictionary correlation_bokeh.ymap |
Definition at line 325 of file correlation_bokeh.py.
list correlation_bokeh.ypos = files[0].attrs["wfs.ypos"][0] |
Definition at line 267 of file correlation_bokeh.py.