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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["interpolation","interpolation-methods","interpolations"],"created_at":"2026-04-09T00:33:57.291Z","updated_at":"2026-04-09T00:33:57.619Z","avatar_url":"https://github.com/ndrwpvlv.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# sinterp\nSimple fast linear interpolation for Python\n\n**sinterp** functions:\n```python\ninterp1d(x: float, xp: list, yp: list, make_checks: bool = CHECK_INPUT)\n```\nx - x-variable for interpolation, float\n\nxp - list with x-values of function, list\n\nyp - list with y-values of function, list\n\nmake_checks - bool-flag of enable/disable for check inputs. Default value is True.\n\n```python\ninterp2d(x: float, y: float, xp: list, yp: list, zp: list, make_checks: bool = CHECK_INPUT)\n```\nx, y - x- and y-variable for interpolation, float\n\nxp - list with x-values of function, list\n\nyp - list with y-values of function, list\n\nzp - list with y-values of function, list\n\nmake_checks - bool-flag of enable/disable for check inputs. Default value is True.\n\n## Benchmarks\nSimple benchmark for compare 1d-interpolation with Numpy:\n```python\nimport random\nimport time\n\nfrom numpy import interp\n\nfrom sinterp import interp1d\n\ntimes = []  # list with time of calculation\nratios = []  # ratio of calc with interp to interp1d\ndeltas = []  # summary delta of difference results by iteration\nsize = []\n\nfor kk in range(2, 5):\n    x1 = 0\n    x2 = int(10 ** kk)\n    size.append(x2)\n\n    xp = [float(_) for _ in range(x1, x2 + 1)]\n    yp = [_ ** 3.0 for _ in xp]\n\n    x = [random.uniform(float(x1), float(x2)) for _ in range(10000)]\n\n    start_time = time.time()\n    v_1 = [interp(_, xp, yp) for _ in x]\n    time_1 = time.time() - start_time\n\n    start_time = time.time()\n    v_2 = [interp1d(_, xp, yp) for _ in x]\n    time_2 = time.time() - start_time\n\n    times.append([time_1, time_2])\n    ratios.append(time_1 / time_2)\n    deltas.append(sum(_[1] - _[0] for _ in zip(v_1, v_2)))\n\n# Print benchmark ratios\nprint('--- Benchmark results ---')\nprint('List size : Ratio')\nfor r, v in zip(size, ratios):\n    print('    %i : %f' % (r, v))\nprint('Check convergence. Difference between interp and interp1d = %f' % max(deltas))\n\n```\nResults Python 3.6 Win10 (at my laptop):\n```\n--- Benchmark results ---\nList size : Ratio\n    10 : 2.312361\n    100 : 1.810310\n    1000 : 7.835562\n    10000 : 54.542985\n    100000 : 514.559448\nCheck convergence. Delta between interp and interp1d = 0.000000\n```\nResults Python 3.7 Linux-Mint 19.3\n```\n--- Benchmark results ---\nList size : Ratio\n    10 : 2.409009\n    100 : 3.836711\n    1000 : 19.986599\n    10000 : 141.633523\n    100000 : 1155.362543\nCheck convergence. Delta between interp and interp1d = 0.000000\n```\n\nSimple benchmark for compare interp2d from SciPy with sinterp\n```python\nimport random\nimport time\n\nfrom numpy import meshgrid, array\nfrom scipy.interpolate import interp2d as sc_interp2d\n\nfrom sinterp import interp2d as si_interp2d\n\ntimes = []  # list with time of calculation\nratios = []  # ratio of calc with interp to interp1d\ndeltas = []  # summary delta of difference results by iteration\nsize = []\n\nfor kk in range(2, 5):\n    x1 = 0\n    x2 = int(10 ** kk)\n    size.append(x2)\n    xp = [float(_) for _ in range(0, x2 + 1)]\n    yp = [float(_) for _ in range(0, x2 + 1)]\n    zp = [[x * y for y in yp] for x in xp]\n\n    XP_GRID, YP_GRID = meshgrid(xp, yp)\n    ZP_GRID = array(zp)\n\n    xv = [random.uniform(0.0, x2) for _ in range(1000)]\n    yv = [random.uniform(0.0, x2) for _ in range(1000)]\n\n    start_time = time.time()\n    sci_interp2d = sc_interp2d(xp, yp, zp)\n    v_1 = [sci_interp2d(x, y) for x, y in zip(xv, yv)]\n    time_1 = time.time() - start_time\n\n    start_time = time.time()\n    v_2 = [si_interp2d(x, y, xp, yp, zp) for x, y in zip(xv, yv)]\n    time_2 = time.time() - start_time\n\n    times.append([time_1, time_2])\n    ratios.append(time_1 / time_2)\n    deltas.append(sum(_[1] - _[0] for _ in zip(v_1, v_2)))\n\n# Print benchmark ratios\nprint('--- Benchmark results ---')\nprint('List size : Ratio')\nfor r, v in zip(size, ratios):\n    print('    %i : %f' % (r, v))\nprint('Check convergence. Difference between interp2d (scipy) and interp2d (sinterp) = %f' % max(deltas))\n\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fndrwpvlv%2Fsinterp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fndrwpvlv%2Fsinterp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fndrwpvlv%2Fsinterp/lists"}