{"abstract":"A spurious turning point appears at the start of the prediction window.","category":"Tide and marine navigation tables","checks":7,"contract":"Input [h, dt, minr]: equally spaced heights every dt minutes. Interior extrema (plateaus collapse to their midpoint time) are candidates; series endpoints never are. A candidate of the same type as the last accepted event replaces it only if more extreme; otherwise a candidate whose height differs from the last accepted event by less than minr is ignored. Return [[type, minutes, height], ...].","evaluation_group":"w2-tide_and_marine_navigation_tables-turning_points","failed_approach":"Padding the series with its first sample shifts every event time by one interval.","family":"w2-tide_and_marine_navigation_tables-turning_points-series-endpoint","id":"FA-69046","implementations":{"attempt":{"sha256":"9a605ebf5cca5b0a13336768ea3822cc72ac60a090665aaaf637dfc5ae4f4816","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(x):\n h,dt,minr=x\n h=[h[0]]+h\n n=len(h)\n ev=[]\n i=1\n while ih[i-1] and h[i]>h[j+1]: ev.append(['HW',(i+j)*dt/2,h[i]])\n elif h[i]out[-1][2])==(e[0]=='HW'): out[-1]=e\n continue\n if out and abs(e[2]-out[-1][2])h[i-1] and h[i]>h[j+1]: ev.append(['HW',(i+j)*dt/2,h[i]])\n elif h[i]out[-1][2])==(e[0]=='HW'): out[-1]=e\n continue\n if out and abs(e[2]-out[-1][2])h[i-1] and h[i]>h[j+1]: ev.append(['HW',(i+j)*dt/2,h[i]])\n elif h[i]out[-1][2])==(e[0]=='HW'): out[-1]=e\n continue\n if out and abs(e[2]-out[-1][2])