during data processing create array looking this:
[array([ 0.08606408]) array([ 0.26071976]) array([ 0.181566 , 0.94154611]) array([ 0.1734347 , 0.94160601]) array([ 0.17859844, 0.94167483]) array([ 0.16880761, 0.94156277]) array([ 0.17624151, 0.94149038]) array([ 0.18770433, 0.94181287]) array([ 0.16707977, 0.94227733]) array([ 0.94162233]) array([ 0.9426902, 0.9615621]) array([ 0.94195127, 0.96174422]) array([ 0.94237795, 0.96195226, 0.98059446]) array([ 0.94249657, 0.96219391, 0.98095329]) array([ 0.94280697, 0.96286183, 0.98109352]) array([ 0.94267473, 0.96304417, 0.98252799])] created in following manner:
peakpositions = [] peakpositions.append(stuff) how extract float values single 1d numpy array? want this:
[0.08606408, 0.26071976, 0.181566 ... 0.98252799] thanks in advance!
you can concatenate inner arrays :
peakpositions=np.concatenate(peakpositions) demo :
>>> l= [[array([ 0.08606408]), array([ 0.26071976]), array([ 0.181566 , 0.94154611]), array([ 0.1734347 , 0.94160601]), array([ 0.17859844, 0.94167483]), array([ 0.16880761, 0.94156277]), array([ 0.17624151, 0.94149038]), array([ 0.18770433, 0.94181287]), array([ 0.16707977, 0.94227733]), array([ 0.94162233]), array([ 0.9426902, 0.9615621]), array([ 0.94195127, 0.96174422]), array([ 0.94237795, 0.96195226, 0.98059446]), array([ 0.94249657, 0.96219391, 0.98095329]), array([ 0.94280697, 0.96286183, 0.98109352]), array([ 0.94267473, 0.96304417, 0.98252799])] >>> np.concatenate(l) array([ 0.08606408, 0.26071976, 0.181566 , 0.94154611, 0.1734347 , 0.94160601, 0.17859844, 0.94167483, 0.16880761, 0.94156277, 0.17624151, 0.94149038, 0.18770433, 0.94181287, 0.16707977, 0.94227733, 0.94162233, 0.9426902 , 0.9615621 , 0.94195127, 0.96174422, 0.94237795, 0.96195226, 0.98059446, 0.94249657, 0.96219391, 0.98095329, 0.94280697, 0.96286183, 0.98109352, 0.94267473, 0.96304417, 0.98252799]) >>> 
Comments
Post a Comment