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cuda-based-raytrace
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Updated TODOs

This commit is contained in:
Martin Opat 2024-12-30 12:12:58 +01:00
parent 3c7f4d22da
commit 47e23dc12e
4 changed files with 1 additions and 100 deletions
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2
src/objs/sphere.h
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@ -80,7 +80,7 @@ __host__ void generateVolume(float* volumeData, int volW, int volH, int volD) {
} }
} }
// Samples the voxel nearest to the given coordinates. TODO: Can be re-used in other places // Samples the voxel nearest to the given coordinates. TODO: Can be re-used in other places so move
__device__ float sampleVolumeNearest(float* volumeData, const int volW, const int volH, const int volD, int vx, int vy, int vz) { __device__ float sampleVolumeNearest(float* volumeData, const int volW, const int volH, const int volD, int vx, int vy, int vz) {
if (vx < 0) vx = 0; if (vx < 0) vx = 0;
if (vy < 0) vy = 0; if (vy < 0) vy = 0;

51
test_read.py
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@ -1,51 +0,0 @@
import numpy as np
from netCDF4 import Dataset
# Load the NetCDF file
file_path = 'data/MERRA2_400.inst6_3d_ana_Np.20120101.nc4'
ncfile = Dataset(file_path, 'r')
# Check the available variables in the file
print(ncfile.variables.keys())
U = ncfile.variables['T'][:]
# Check the shape of the variable
print("Shape of U:", U.shape)
# Compute the mean of the variable across all axes (for all elements in U)
U_mean = np.mean(U)
U_sum = np.sum(U)
# Print the mean
print("Mean of U:", U_mean)
print("Sum of U:", U_sum)
sumval = 0
row = U[2,20,100]
print("Shape of row", row.shape)
print("Row data for first 20 entries", row[0:5])
row = row[0:5]
print(f"{type(row)} {row.dtype}")
n = 0
for val in row:
#if not np.ma.is_masked(val):
n+=1
sumval += np.float64(val)
Mean1 = np.mean(row)
Mean2 = sumval/n
print(type(Mean1))
print(type(Mean2))
print(Mean1)
print(Mean2)
print(f"Why does {np.mean(row):.10f} not equal {sumval/n:.10f} ?!")
# Close the NetCDF file
ncfile.close()

18
test_read2.py
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@ -1,18 +0,0 @@
import numpy as np
from netCDF4 import Dataset
# Load the NetCDF file
file_path = 'data/MERRA2_400.inst6_3d_ana_Np.20120101.nc4'
ncfile = Dataset(file_path, 'r')
# Check the available variables in the file
print(ncfile.variables.keys())
Temp = ncfile.variables['T'][:]
print(f"{Temp[1, 20, 100, 100]=}")
print(f"{Temp.flat[12949732]=}")
# Close the NetCDF file
ncfile.close()

30
test_read3.py
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@ -1,30 +0,0 @@
import numpy as np
from netCDF4 import Dataset
# file_path = 'data/MERRA2_400.inst6_3d_ana_Np.20120101.nc4'
# ncfile = Dataset(file_path, 'r')
file_paths = [
'data/atmosphere_MERRA-wind-speed[179253532]/MERRA2_400.inst6_3d_ana_Np.20120101.nc4',
'data/atmosphere_MERRA-wind-speed[179253532]/MERRA2_400.inst6_3d_ana_Np.20120102.nc4',
'data/atmosphere_MERRA-wind-speed[179253532]/MERRA2_400.inst6_3d_ana_Np.20120103.nc4'
]
ncfiles = [Dataset(file_path) for file_path in file_paths]
# print(f"{Temp[0, 20, 100, 100]=}")
for i in range(10):
Temp = ncfiles[i//4].variables['T'][:]
x = Temp[i%4, 20, 100, 100]
Temp2 = ncfiles[(i+1)//4].variables['T'][:]
y = Temp2[(i+1)%4, 20, 100, 100]
print(f"{(x+y)/2=}")
# Close the NetCDF file
for ncfile in ncfiles:
ncfile.close()