# Paul's slightly corrected version
temp_out = (np.fft.ifft2(np.fft.fft2(pad_img) *
np.fft.fft2(pad_filt))).real
temp_out = temp_out / normtemp
# extract the appropriate portion of the filtered image
filtered = temp_out[(s_filt[0] / 2):-(s_filt[0] / 2),
s_filt[1] / 2:-(s_filt[1] / 2)]
return filtered
if __name__ == '__main__':
import matplotlib.pyplot as plt
filtparams = par.FilterParams(maindir="../")
# for friendlyname in ["Whites", "Howe var B"]:
for stimname in [
"Whites", "Howe var B", "Howe var D", "Howe", "SBC", "Anderson",
"Rings", "Radial", "Zigzag", "Jacob 1", "Jacob 2"
]:
temp = Stim(stimname, filtparams)
tempfilename = temp.stimtype + temp.variant + ".png"
outputdir = "../../experiments/output/"
fig = plt.imshow(temp.img, interpolation="none", cmap="gray")
plt.colorbar()
plt.suptitle(tempfilename)
plt.savefig(outputdir + tempfilename)
"""
import sys
sys.path.insert(0, "/home/AD/e1morgan/PycharmProjects/pyLapdog/")
import contrastmodel.params.paramsDef as par
import contrastmodel.functions.stimuli as stimclass
import contrastmodel.functions.models as modelclass
import contrastmodel.functions.subjects as subj
#mainDir = "C:\\Users\\Eric\\Documents\\PyLapdog_Output\\initialtest\\"
mainDir = "/home/AD/e1morgan/Documents/e1morgan_data/pyLapdog_output/all_models_initial_test/"
print("Generating params:")
params = par.FilterParams(mainDir, verbosity=3)
# #reduce the parameters for now, for quicker testing of later stuff
# params.filt_orientations = params.filt_orientations[0:3]
# params.filt_stdev_pixels = params.filt_stdev_pixels[0:3]
params.load_filtermasks()
print("Generating models:")
# variant="", npow=None, conn_weights=None, sig1mult=None, sr=None, sdmix=None
modellist = [{
"variant": "flodog",
"sig1mult": [4.0, 2.0],
"sr": [1.0],
"sdmix": [0.5, 3.0]
}, {
generates set of masks for default filters, saves them to files, then opens them and generates images for each mask
"""
import matplotlib.pyplot as plt
import cPickle as pickle
if __name__ == "__main__":
import sys
import os
#sys.path.insert(0, "/home/AD/e1morgan/PycharmProjects/pyLapdog/")
#sys.path.insert(0, "C:\\Users\\Eric\\PycharmProjects\\pyLapdog\\")
import contrastmodel.functions.masks as msk
import contrastmodel.params.paramsDef as par
params = par.FilterParams()
# # reduce the number of options so it processes more quickly
# params.filt_orientations = range(0, 89, 30)
# params.filt_stdev_pixels = [4.0, 8.0, 16.0]
print("Generating masks...")
msk.generate_correlation_mask_fft(params)
print("loading filtermasks from file...")
filtermasks = pickle.load(
open("{}_filtermasks_FFT.pkl".format(params.filttype), mode="rb"))
print("loading ap_filtermasks from file...")
ap_filtermasks = pickle.load(
open("{}_ap_filtermasks_FFT.pkl".format(params.filttype), mode="rb"))