Dr. Pataky, Nice to meet you.
I have a question about the post-hoc power analysis using Power1D.

I am testing the reproducibility of sensor data with 101 time points and I have 2 sessions of data for 30 people.
The data from the first and second session did not differ according to the Paired t-test in SPM1d.

I have performed a posteriori power test for this test using the following code.

#########################
J = 30 # No of subjects
Q = 101 # time points

data0 = np.loadtxt(file)
first_data = data0[:,0] # mean data in 30 subjects. 1101 array
second_data = data0[:,1] # mean data in 30 subjects. 1101 array
diff_data = data0[:,2] # diff_data: first_data-second_data
diff_sd = data0[0,3] # standard deviation of diff_data

data_bl = power1d.geom.Null( Q ) # baseline
data0_sig0 = power1d.geom.Null( Q ) # null signal - needed for null power model
data0_sig1 = power1d.geom.Continuum1D( diff_data ) #signal
data0_nse = power1d.noise.SmoothGaussian( J , Q , mu = 0 , sigma = diff_sd , fwhm = 20 ) #Noise
data0_mod0 = power1d.models.DataSample( data0_bl, data_sig0, data0_nse, J ) # null for power analysis
data0_mod1 = power1d.models.DataSample( data0_bl, data_sig1, data0_nse, J ) # alternative

power_analysis(data0_mod0,data0_mod1)
########################

According to your papter in J of Biomech.(doi: 10.1016/j.jbiomech.2021.110451.)
and its supplementary code (https://github.com/m-a-robinson/sample-size/blob/main/creating_1d_effects.py),
you made the data_sig1 using GaussianPulse objects.

Since my analysis is a post-hoc power analysis and we already know the mean data to be compared,
I made the data0_sig1 as a Continuum1D objects containing the difference data between 1st and 2nd sessions.
It it appropreate procedure?

I would appreciate it if you could help me.

Hello,

I am new to Python. Managed to download and work it in vscode, but I am not able to install power1d. I installed spm1d, but
it gives me this error when I try to install power1d using either of the below methods:

PS F:> py -m easy_install power1d
WARNING: The easy_install command is deprecated and will be removed in a future version.
Processing power1d
error: Couldn't find a setup script in F:\power1d

PS F:> py -m pip install power1d
ERROR: Could not find a version that satisfies the requirement power1d
ERROR: No matching distribution found for power1d

Your help would be much appreciated.

Thank you.
Mat

Dr. Pataky, Nice to meet you.
When I ran the sample size calculation code, an error happened when aiming at some signal location (q). I have no idea how to solve it. I would appreciate it if you could help me.

############################################################ The code is

(0) Create geometry and noise models:

JA, JB, Q = 55, 55, 101 # J(X) = No of subjects; Q= time points;

sample I

xata01 = pd.read_csv("D:\Python\learnsample\data1.csv", sep=',', header=None)
m_data1 = np.array(xata01.values)[0]
signal1 = power1d.geom.Continuum1D(m_data1)

Sample II

xata02 = pd.read_csv("D:\Python\learnsample\data2.csv", sep=',', header=None)
m_data2 = np.array(xata02.values)[0]
signal2 = power1d.geom.Continuum1D(m_data2)

Baseline

baseline = power1d.geom.Continuum1D(m_data1)

noise

data03 = pd.read_csv("D:\Python\learnsample\allstd.csv", sep=',', header=None)
std003 = np.array(data03.values)[0]
noise3 = power1d.noise.SmoothGaussian(JB, Q, mu=0, sigma=std003[0], fwhm=28)

Create data sample models:

modelA0 = power1d.models.DataSample(baseline, signal1, noise3, J=JA) # null A
modelB0 = power1d.models.DataSample(baseline, signal1, noise3, J=JB) # null B
modelA1 = power1d.models.DataSample(baseline, signal1, noise3, J=JA) # alternative A
modelB1 = power1d.models.DataSample(baseline, signal2, noise3, J=JB) # alternative B

iteratively simulate for a range of sample sizes:

np.random.seed(0) #seed the random number generator
JJ = [3, 4, 5, 6, 7, 8, 9, 10] #sample sizes
teststat = power1d.stats.t_2sample_fn(JA, JB)
expmodel0 = power1d.models.Experiment([modelA0, modelB0], teststat) #null
expmodel1 = power1d.models.Experiment([modelA1, modelB1], teststat) #alternative
sim = power1d.ExperimentSimulator(expmodel0, expmodel1)
q = 80 # signal location
results = sim.sample_size(power=0.8, alpha=0.05, niter0=200, niter=2000, coi=dict(q=q, r=3))

retrieve estimated sample size:

n = results['nstar']
print(f'Estimate sample size = {n}')

plot:

plt.figure()
ax = plt.axes()
ax.plot( results['n'], results['p'], 'o-')
ax.axhline( results['target_power'] , color='k', linestyle='--')
ax.set_xlabel('Sample size', size=14)
ax.set_ylabel('Power', size=14)
plt.show()

################################################### the error showed
D:\Python\Python312\python.exe "D:\Python\project\pythonProject\samplesize-two sample.py"
Traceback (most recent call last):
File "D:\Python\project\pythonProject\samplesize-two sample.py", line 48, in
results = sim.sample_size(power=0.8, alpha=0.05, niter0=200, niter=2000, coi=dict(q=q, r=3))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Python\Python312\Lib\site-packages\power1d\models.py", line 711, in sample_size
ind = np.argwhere( ps > power ).ravel()[0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^
IndexError: index 0 is out of bounds for axis 0 with size 0

Process finished with exit code 1

######################################################