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Commit f60313d5 authored by tomrink's avatar tomrink
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......@@ -672,7 +672,7 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
nn = SRCNN()
out_sr = nn.run_evaluate(data, ckpt_dir)
#out_sr = denormalize(out_sr, label_params[0], mean_std_dct)
# out_sr = denormalize(out_sr, label_params[0], mean_std_dct)
if out_file is not None:
np.save(out_file, out_sr)
else:
......@@ -682,19 +682,26 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
def analyze():
h5f = h5py.File('/Users/tomrink/clavrx_snpp_viirs.A2019071.0000.001.2019071061610.uwssec_B00038187.level2.h5', 'r')
grd = get_grid_values_all(h5f, 'cloud_fraction')
grd = grd[::2, ::2]
grd = np.where(np.isnan(grd), 0, grd)
grd = grd[1600:, 400:1200]
print(grd.shape)
leny, lenx = grd.shape
grd_lr = grd[::2, ::2]
print(grd_lr.shape)
leny, lenx = grd_lr.shape
x = np.arange(lenx)
y = np.arange(leny)
x_up = np.arange(0, lenx, 0.5)
y_up = np.arange(0, leny, 0.5)
grd_a = resample_2d_linear_one(x, y, grd, x_up, y_up)
print(grd_a.shape)
grd_hr = resample_2d_linear_one(x, y, grd_lr, x_up, y_up)
print(grd_hr.shape)
h5f.close()
return grd, grd_hr
if __name__ == "__main__":
nn = SRCNN()
......
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