def test_LISA_params_Aaccvz(source_space_based, LISA_ESA):
# Variable on x-axis
var_x = "A_acc"
# Variable on y-axis
var_y = "z"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_space_based, LISA_ESA, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True,
dl_axis=True,
)
plt.close(fig)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True,
lb_axis=True,
smooth_contours=False,
)
plt.close(fig)
def test_NANOGrav_WN_params_Mvchi1(source_pta, NANOGrav_WN):
# Variable on x-axis
var_x = "M"
# Variable on y-axis
var_y = "chi1"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_pta, NANOGrav_WN, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
cfill=False,
display=False,
return_plt=True,
)
plt.close(fig)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
smooth_contours=False,
cfill=True,
display=False,
return_plt=True,
)
plt.close(fig)
def test_aLIGO_params_SGvMST(source_ground_based, aLIGO_gwinc):
# Variable on x-axis
var_x = "Seismic Gamma"
# Variable on y-axis
var_y = "Materials Substrate Temp"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_ground_based, aLIGO_gwinc, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
cfill=False,
display=False,
return_plt=True,
)
plt.close(fig)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
smooth_contours=False,
cfill=True,
display=False,
return_plt=True,
x_axis_label=False,
y_axis_label=False,
)
plt.close(fig)
def test_aLIGO_params_LPvz(source_ground_based, aLIGO_gwinc):
# Variable on x-axis
var_x = "Laser Power"
# Variable on y-axis
var_y = "z"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_ground_based, aLIGO_gwinc, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
cfill=False,
display=False,
return_plt=True,
x_axis_line=125,
)
plt.close(fig)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
smooth_contours=False,
cfill=True,
display=False,
return_plt=True,
x_axis_label=False,
y_axis_label=False,
)
plt.close(fig)
def test_aLIGO_params_ILvIT(source_ground_based, aLIGO_gwinc):
# Variable on x-axis
var_x = "Infrastructure Length"
# Variable on y-axis
var_y = "Infrastructure Temp"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_ground_based, aLIGO_gwinc, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
cfill=False,
display=False,
return_plt=True,
x_axis_line=3995,
)
plt.close(fig)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
smooth_contours=False,
cfill=True,
display=False,
return_plt=True,
x_axis_label=False,
y_axis_label=False,
)
plt.close(fig)
def test_NANOGrav_WN_params_Mvcadence(source_pta, NANOGrav_WN):
source_pta.q = 1.0
source_pta.chi1 = 0.0
source_pta.chi2 = 0.0
source_pta.z = 0.1
source_pta.f_min = 1e-9
T_obs = 15.0 * u.yr # Observing time in years
T_obs_min = 5.0 * u.yr
T_obs_max = 30.0 * u.yr
NANOGrav_WN.T_obs = [T_obs, T_obs_min, T_obs_max]
NANOGrav_WN.sigma = [sigma, sigma_min, sigma_max]
NANOGrav_WN.n_p = [N_p, N_p_min, N_p_max]
NANOGrav_WN.cadence = [cadence, cadence_min, cadence_max]
# Variable on x-axis
var_x = "M"
# Variable on y-axis
var_y = "cadence"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_pta, NANOGrav_WN, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True)
plt.close(fig)
def test_aLIGO_params_MvIL(source_ground_based, aLIGO_gwinc):
# Variable on x-axis
var_x = "M"
# Variable on y-axis
var_y = "Infrastructure Temp"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_ground_based, aLIGO_gwinc, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display_cbar=True,
y_axis_label=False,
smooth_contours=False,
logLevels_min=-1.0,
logLevels_max=5.0,
y_axis_line=295,
yticklabels_kwargs={
"rotation": 70,
"y": 0.02
},
xlabels_kwargs={"labelpad": 0.45},
display=False,
return_plt=True,
)
plt.close(fig)
def test_LISA_params_MvAIFO(source_space_based, LISA_ESA):
# Variable on x-axis
var_x = "chi1"
# Variable on y-axis
var_y = "A_IFO"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_space_based, LISA_ESA, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True)
plt.close(fig)
def test_LISA_params_Tobsvfaccbreakhigh(source_space_based, LISA_ESA):
# Variable on x-axis
var_x = "T_obs"
# Variable on y-axis
var_y = "f_acc_break_high"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_space_based, LISA_ESA, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True)
plt.close(fig)
def test_NANOGrav_WN_params_Mvsigma(source_pta, NANOGrav_WN):
# Variable on x-axis
var_x = "M"
# Variable on y-axis
var_y = "sigma"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_pta, NANOGrav_WN, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True)
plt.close(fig)
def test_LISA_params_MvAacc(source_space_based, LISA_ESA):
# Variable on x-axis
var_x = "z"
# Variable on y-axis
var_y = "A_acc"
[sample_x, sample_y, SNRMatrix] = snr.Get_SNR_Matrix(
source_space_based,
LISA_ESA,
var_x,
sampleRate_x,
var_y,
sampleRate_y,
inc=0.0,
integral_consts=4.0,
)
fig, ax = snrplot.Plot_SNR(var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True)
plt.close(fig)
def test_NANOGrav_WN_params_MvTobs(source_pta, NANOGrav_WN):
# Variable on x-axis
var_x = "M"
# Variable on y-axis
var_y = "T_obs"
[sample_x, sample_y,
SNRMatrix] = snr.Get_SNR_Matrix(source_pta, NANOGrav_WN, var_x,
sampleRate_x, var_y, sampleRate_y)
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
display=False,
return_plt=True,
xticklabels_kwargs={
"rotation": 70,
"y": 0.02
},
ylabels_kwargs={"labelpad": -5},
)
plt.close(fig)
def test_NANOGrav_WN_params_chiivM(source_pta, NANOGrav_WN):
# Variable on x-axis
var_x = "chii"
# Variable on y-axis
var_y = "M"
[sample_x, sample_y, SNRMatrix] = snr.Get_SNR_Matrix(source_pta,
NANOGrav_WN,
var_x,
sampleRate_x,
var_y,
sampleRate_y,
method="PN")
fig, ax = snrplot.Plot_SNR(
var_x,
sample_x,
var_y,
sample_y,
SNRMatrix,
cfill=False,
display=False,
return_plt=True,
)
plt.close(fig)