I'm trying to convert a numpy array of dimensions (22227,2) into a csv file with 2 columns and 22227 rows. However, whenever I try to do this with the following code I get one row with twice the amount of columns.
# using open function
sample_data = np.genfromtxt("wg1_regular_baseline_trial6.csv",delimiter=",", dtype=float)
sample_data = np.array(sample_data)
s_data=sample_data[1000:-4000]
#find mean of original data
adjusted_value=[]
mean_wave=sample_data[:,1].mean()
#adjust data for mean value
for i in range(len(sample_data)):
value=sample_data[i]
adjusted_value+=[[value[0],value[1]-mean_wave]]
#create array
adjusted_data = np.array(adjusted_value)
a_data=adjusted_data[1000:-4000]
print(np.shape(adjusted_data))
#create csv file
adjusted_data.tofile('BL_Trial6.csv', sep = ',')
and the code output when I print the array for the adjusted data is
[[0.00000000e+00 2.63267449e-02]
[1.00000000e-02 2.64037449e-02]
[2.00000000e-02 2.62877449e-02]
...
[2.22240000e+02 9.33474486e-03]
[2.22250000e+02 1.04347449e-02]
[2.22260000e+02 1.15347449e-02]]
I tried to use the numpy reshape tool with no success as it still printed one row with many, many columns.
For a simple (2,2) array:
In [251]: arr
Out[251]:
array([[ 1, 2],
[ 3, -40]])
compare tofile:
In [252]: arr.tofile('test',sep=',')
In [253]: more test
1,2,3,-40
with savetxt:
In [254]: np.savetxt('test',arr, delimiter=',', fmt='%d')
In [255]: more test
1,2
3,-40