{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "gYOll3X06Qu-" }, "source": [ "# Chapter 10 - Qwen Omni Fine-Tuning Notebook\n", "\n", "We isolated the training of Qwen Omni in a single Notebook, the reason behind it is that it relies on particular versions of some libraries." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "CqEHaId26RD6", "outputId": "e3a93067-0692-47c3-d25a-7eb2a50d8741" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: pip in /usr/local/lib/python3.12/dist-packages (24.1.2)\n", "Collecting pip\n", " Downloading pip-26.0.1-py3-none-any.whl.metadata (4.7 kB)\n", "Downloading pip-26.0.1-py3-none-any.whl (1.8 MB)\n", "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/1.8 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K 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nvidia-cublas-cu12\n", "\u001b[2K Found existing installation: nvidia-cublas-cu12 12.8.4.1\n", "\u001b[2K Uninstalling nvidia-cublas-cu12-12.8.4.1:\n", "\u001b[2K Successfully uninstalled nvidia-cublas-cu12-12.8.4.1\n", "\u001b[2K Attempting uninstall: nvidia-cusparse-cu12\n", "\u001b[2K Found existing installation: nvidia-cusparse-cu12 12.5.8.93\n", "\u001b[2K Uninstalling nvidia-cusparse-cu12-12.5.8.93:\n", "\u001b[2K Successfully uninstalled nvidia-cusparse-cu12-12.5.8.93\n", "\u001b[2K Attempting uninstall: nvidia-cudnn-cu12\n", "\u001b[2K Found existing installation: nvidia-cudnn-cu12 9.10.2.21\n", "\u001b[2K Uninstalling nvidia-cudnn-cu12-9.10.2.21:\n", "\u001b[2K Successfully uninstalled nvidia-cudnn-cu12-9.10.2.21\n", "\u001b[2K Attempting uninstall: nvidia-cusolver-cu12\n", "\u001b[2K Found existing installation: nvidia-cusolver-cu12 11.7.3.90\n", "\u001b[2K Uninstalling nvidia-cusolver-cu12-11.7.3.90:\n", "\u001b[2K Successfully uninstalled nvidia-cusolver-cu12-11.7.3.90\n", "\u001b[2K Attempting uninstall: torch\n", "\u001b[2K Found existing installation: torch 2.10.0+cu128\n", "\u001b[2K Uninstalling torch-2.10.0+cu128:\n", "\u001b[2K Successfully uninstalled torch-2.10.0+cu128\n", "\u001b[2K Attempting uninstall: torchvision\n", "\u001b[2K Found existing installation: torchvision 0.25.0+cu128\n", "\u001b[2K Uninstalling torchvision-0.25.0+cu128:\n", "\u001b[2K Successfully uninstalled torchvision-0.25.0+cu128\n", "\u001b[2K Attempting uninstall: torchaudio\n", "\u001b[2K Found existing installation: torchaudio 2.10.0+cu128\n", "\u001b[2K Uninstalling torchaudio-2.10.0+cu128:\n", "\u001b[2K Successfully uninstalled torchaudio-2.10.0+cu128\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m18/18\u001b[0m [torchaudio]\n", "\u001b[1A\u001b[2KSuccessfully installed nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-cusparselt-cu12-0.6.2 nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 sympy-1.13.1 torch-2.6.0+cu124 torchaudio-2.6.0+cu124 torchvision-0.21.0+cu124 triton-3.2.0\n", "Collecting transformers==4.57.1\n", " Downloading transformers-4.57.1-py3-none-any.whl.metadata (43 kB)\n", "Collecting datasets==3.6.0\n", " Downloading datasets-3.6.0-py3-none-any.whl.metadata (19 kB)\n", "Collecting peft==0.18.0\n", " Downloading peft-0.18.0-py3-none-any.whl.metadata (14 kB)\n", "Collecting trl==0.25.1\n", " Downloading trl-0.25.1-py3-none-any.whl.metadata (11 kB)\n", "Collecting accelerate==1.11.0\n", " Downloading accelerate-1.11.0-py3-none-any.whl.metadata (19 kB)\n", "Collecting qwen-omni-utils==0.0.8\n", " Downloading qwen_omni_utils-0.0.8-py3-none-any.whl.metadata (9.3 kB)\n", "Collecting librosa==0.10.2\n", " Downloading librosa-0.10.2-py3-none-any.whl.metadata (8.6 kB)\n", "Collecting soundfile==0.12.1\n", " Downloading soundfile-0.12.1-py2.py3-none-manylinux_2_31_x86_64.whl.metadata (14 kB)\n", "Collecting numpy==2.2.6\n", " Downloading numpy-2.2.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (62 kB)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from transformers==4.57.1) (3.24.3)\n", "Collecting huggingface-hub<1.0,>=0.34.0 (from transformers==4.57.1)\n", " Downloading huggingface_hub-0.36.2-py3-none-any.whl.metadata (15 kB)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from transformers==4.57.1) (26.0)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.12/dist-packages (from transformers==4.57.1) (6.0.3)\n", "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.12/dist-packages (from transformers==4.57.1) (2025.11.3)\n", "Requirement 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lazy-loader>=0.1 in /usr/local/lib/python3.12/dist-packages (from librosa==0.10.2) (0.4)\n", "Requirement already satisfied: msgpack>=1.0 in /usr/local/lib/python3.12/dist-packages (from librosa==0.10.2) (1.1.2)\n", "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.12/dist-packages (from soundfile==0.12.1) (2.0.0)\n", "Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.12/dist-packages (from fsspec[http]<=2025.3.0,>=2023.1.0->datasets==3.6.0) (3.13.3)\n", "Requirement already satisfied: hf-xet<2.0.0,>=1.1.3 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<1.0,>=0.34.0->transformers==4.57.1) (1.3.1)\n", "Requirement already satisfied: aiohappyeyeballs>=2.5.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets==3.6.0) (2.6.1)\n", "Requirement already satisfied: aiosignal>=1.4.0 in /usr/local/lib/python3.12/dist-packages (from 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uninstalled numba-0.60.0\n", "\u001b[2K Attempting uninstall: huggingface-hub\n", "\u001b[2K Found existing installation: huggingface_hub 1.5.0\n", "\u001b[2K Uninstalling huggingface_hub-1.5.0:\n", "\u001b[2K Successfully uninstalled huggingface_hub-1.5.0\n", "\u001b[2K Attempting uninstall: transformers\n", "\u001b[2K Found existing installation: transformers 5.0.0\n", "\u001b[2K Uninstalling transformers-5.0.0:\n", "\u001b[2K Successfully uninstalled transformers-5.0.0\n", "\u001b[2K Attempting uninstall: librosa\n", "\u001b[2K Found existing installation: librosa 0.11.0\n", "\u001b[2K Uninstalling librosa-0.11.0:\n", "\u001b[2K Successfully uninstalled librosa-0.11.0\n", "\u001b[2K Attempting uninstall: datasets\n", "\u001b[2K Found existing installation: datasets 4.0.0\n", "\u001b[2K Uninstalling datasets-4.0.0:\n", "\u001b[2K Successfully uninstalled datasets-4.0.0\n", "\u001b[2K Attempting uninstall: accelerate\n", "\u001b[2K Found existing installation: accelerate 1.12.0\n", "\u001b[2K Uninstalling accelerate-1.12.0:\n", "\u001b[2K Successfully uninstalled accelerate-1.12.0\n", "\u001b[2K Attempting uninstall: peft\n", "\u001b[2K Found existing installation: peft 0.18.1\n", "\u001b[2K Uninstalling peft-0.18.1:\n", "\u001b[2K Successfully uninstalled peft-0.18.1\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13/13\u001b[0m [peft]\n", "\u001b[1A\u001b[2K\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "cuml-cu12 26.2.0 requires numba<0.62.0,>=0.60.0, but you have numba 0.64.0 which is incompatible.\n", "tensorflow 2.19.0 requires numpy<2.2.0,>=1.26.0, but you have numpy 2.2.6 which is incompatible.\n", "cudf-cu12 26.2.1 requires numba<0.62.0,>=0.60.0, but you have numba 0.64.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed accelerate-1.11.0 av-16.1.0 datasets-3.6.0 huggingface-hub-0.36.2 librosa-0.10.2 llvmlite-0.46.0 numba-0.64.0 numpy-2.2.6 peft-0.18.0 qwen-omni-utils-0.0.8 soundfile-0.12.1 transformers-4.57.1 trl-0.25.1\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "numpy" ] }, "id": "40a957cfd92a4dc9b828f26f8483111e" } }, "metadata": {} } ], "source": [ "# We have to fix some versions of the libraries to make the training script work.\n", "# Important: remember to restart your session after running this cell!\n", "!pip install --upgrade pip\n", "\n", "!pip install \\\n", " \"torch==2.6.0\" \\\n", " \"torchvision==0.21.0\" \\\n", " \"torchaudio==2.6.0\" \\\n", " --index-url https://download.pytorch.org/whl/cu124\n", "\n", "!pip install \\\n", " \"transformers==4.57.1\" \\\n", " \"datasets==3.6.0\" \\\n", " \"peft==0.18.0\" \\\n", " \"trl==0.25.1\" \\\n", " \"accelerate==1.11.0\" \\\n", " \"qwen-omni-utils==0.0.8\" \\\n", " \"librosa==0.10.2\" \\\n", " \"soundfile==0.12.1\" \\\n", " \"numpy==2.2.6\"" ] }, { "cell_type": "markdown", "metadata": { "id": "WFqz8IU26JIH" }, "source": [ "## Imports and configuration\n", "\n", "In the cell below we set some basic configuration such as the base model we are going to use and the dataset that we will use for training" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "id": "fDk6PYdc6MqW" }, "outputs": [], "source": [ "import numpy as np\n", "import torch\n", "from datasets import load_dataset\n", "from peft import LoraConfig, get_peft_model\n", "from transformers import AutoProcessor, Qwen2_5OmniThinkerForConditionalGeneration, Trainer, TrainingArguments\n", "\n", "# Configuration\n", "MODEL_ID = \"Qwen/Qwen2.5-Omni-3B\"\n", "DERIVED_DATASET_ID = \"orrzohar/EMID-Emotion-Matching\"\n", "OUTPUT_DIR = \"./book_demo_output\"\n", "MAX_EVAL_EXAMPLES = 200\n", "SEED = 42\n", "\n", "SYSTEM_PROMPT = (\n", " \"You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and \"\n", " \"visual inputs, as well as generating text and speech.\"\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "bcBpBEOu6NG6" }, "source": [ "## Helper functions\n", "Below some functionalities to prepare audio samples and the collator function. Pay special attention to that one!" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "id": "kcyX4y2k0o8I" }, "outputs": [], "source": [ "import numpy as np\n", "import torch\n", "import torchaudio\n", "\n", "def _mixdown_to_mono(x):\n", " if isinstance(x, torch.Tensor):\n", " if x.ndim == 1:\n", " return x\n", " if x.ndim == 2:\n", " # Usually [channels, time] for torchcodec/torchaudio\n", " if x.shape[0] <= 8 and x.shape[1] > x.shape[0]:\n", " return x.mean(dim=0)\n", " return x.mean(dim=-1)\n", " return x.reshape(-1)\n", "\n", " x = np.asarray(x, dtype=np.float32)\n", " if x.ndim == 1:\n", " return x\n", " if x.ndim == 2:\n", " if x.shape[0] <= 8 and x.shape[1] > x.shape[0]:\n", " return x.mean(axis=0)\n", " return x.mean(axis=-1)\n", " return x.reshape(-1)\n", "\n", "def to_waveform(audio, processor) -> np.ndarray:\n", " \"\"\"\n", " Convert HF audio payloads / AudioDecoder / tensors / arrays into a mono\n", " float32 waveform at the processor's expected sampling rate.\n", " \"\"\"\n", " target_sr = int(processor.feature_extractor.sampling_rate)\n", " wave = None\n", " sample_rate = None\n", "\n", " # HF-style decoded dict: {\"array\": ..., \"sampling_rate\": ...}\n", " if isinstance(audio, dict):\n", " if audio.get(\"array\") is not None:\n", " wave = audio[\"array\"]\n", " sample_rate = audio.get(\"sampling_rate\")\n", " elif audio.get(\"path\"):\n", " wave, sample_rate = torchaudio.load(audio[\"path\"])\n", " else:\n", " raise ValueError(f\"Unsupported audio dict keys: {list(audio.keys())}\")\n", "\n", " # TorchCodec / HF AudioDecoder object\n", " elif hasattr(audio, \"get_all_samples\"):\n", " audio_samples = audio.get_all_samples()\n", " wave = audio_samples.data\n", " sample_rate = getattr(audio_samples, \"sample_rate\", None)\n", " if sample_rate is None and hasattr(audio, \"metadata\"):\n", " sample_rate = getattr(audio.metadata, \"sample_rate\", None)\n", "\n", " # Some wrappers expose .array / .sampling_rate\n", " elif hasattr(audio, \"array\"):\n", " wave = audio.array\n", " sample_rate = getattr(audio, \"sampling_rate\", None)\n", "\n", " # Some wrappers expose a .path\n", " elif hasattr(audio, \"path\") and getattr(audio, \"path\"):\n", " wave, sample_rate = torchaudio.load(audio.path)\n", "\n", " elif isinstance(audio, torch.Tensor):\n", " wave = audio\n", "\n", " elif isinstance(audio, (np.ndarray, list, tuple)):\n", " wave = audio\n", "\n", " else:\n", " raise TypeError(f\"Unsupported audio type: {type(audio)}\")\n", "\n", " wave = _mixdown_to_mono(wave)\n", "\n", " if isinstance(wave, torch.Tensor):\n", " wave = wave.detach().cpu().float()\n", " if sample_rate is not None and int(sample_rate) != target_sr:\n", " wave = torchaudio.functional.resample(\n", " wave.unsqueeze(0), int(sample_rate), target_sr\n", " ).squeeze(0)\n", " return wave.numpy().astype(np.float32, copy=False)\n", "\n", " wave = np.asarray(wave, dtype=np.float32)\n", " if sample_rate is not None and int(sample_rate) != target_sr:\n", " wave_t = torch.from_numpy(wave).float().unsqueeze(0)\n", " wave = torchaudio.functional.resample(\n", " wave_t, int(sample_rate), target_sr\n", " ).squeeze(0).numpy()\n", " return wave.astype(np.float32, copy=False)\n", "\n", "def format_messages(question: str, same: bool, emotion: str, train: bool):\n", " base = [\n", " {\"role\": \"system\", \"content\": [{\"type\": \"text\", \"text\": SYSTEM_PROMPT}]},\n", " {\"role\": \"user\", \"content\": [{\"type\": \"audio\"}, {\"type\": \"image\"}, {\"type\": \"text\", \"text\": question}]},\n", " ]\n", " if not train:\n", " return base\n", " target = f\"yes - {emotion}\" if same else \"no\"\n", " return base + [{\"role\": \"assistant\", \"content\": [{\"type\": \"text\", \"text\": target}]}]\n", "\n", "def build_collator(processor):\n", " tok = processor.tokenizer\n", " pad_id = tok.pad_token_id\n", " im_start = tok.convert_tokens_to_ids(\"<|im_start|>\")\n", " im_end = tok.convert_tokens_to_ids(\"<|im_end|>\")\n", "\n", " def to_ids(role):\n", " enc = tok(f\"{role}\\n\", add_special_tokens=False)\n", " ids = enc.input_ids if hasattr(enc, \"input_ids\") else enc[\"input_ids\"]\n", " return tuple(ids[0] if isinstance(ids[0], list) else ids)\n", "\n", " role_ids = {role: to_ids(role) for role in (\"system\", \"user\", \"assistant\")}\n", "\n", " def mask(ids):\n", " labels = ids.clone()\n", " role = None\n", " i = 0\n", " while i < labels.size(0):\n", " token = ids[i].item()\n", " if token == im_start:\n", " labels[i] = -100\n", " i += 1\n", " for name, seq in role_ids.items():\n", " if ids[i : i + len(seq)].tolist() == list(seq):\n", " labels[i : i + len(seq)] = -100\n", " role = name\n", " i += len(seq)\n", " break\n", " continue\n", " labels[i] = ids[i] if role == \"assistant\" else -100\n", " if token == im_end:\n", " role = None\n", " i += 1\n", " if pad_id is not None:\n", " labels[ids == pad_id] = -100\n", " return labels\n", "\n", " def collate(batch):\n", " texts = [\n", " processor.apply_chat_template(\n", " format_messages(item[\"question\"], bool(item[\"same\"]), item[\"emotion\"], True),\n", " tokenize=False,\n", " add_generation_prompt=False,\n", " )\n", " for item in batch\n", " ]\n", " encoded = processor(\n", " text=texts,\n", " audio=[to_waveform(item[\"audio\"], processor) for item in batch],\n", " images=[item[\"image\"] for item in batch],\n", " padding=True,\n", " return_tensors=\"pt\",\n", " )\n", " encoded[\"labels\"] = torch.stack([mask(ids) for ids in encoded[\"input_ids\"]])\n", " return encoded\n", "\n", " return collate\n" ] }, { "cell_type": "markdown", "metadata": { "id": "LYGWUVUi6Z0I" }, "source": [ "## Evaluation helpers\n", "Below you can find some functions that we use to clean the output of the model and evaluate it against the particular dataset that we chose as example in this notebook" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "id": "9dl0JFKK6Z_t" }, "outputs": [], "source": [ "import re\n", "\n", "def normalize_emotion(s: str) -> str:\n", " s = str(s).strip().lower()\n", "\n", " for marker in (\n", " \"<|im_end|>\",\n", " \"<|endoftext|>\",\n", " \"human:\",\n", " \"user:\",\n", " \"assistant:\",\n", " \"system:\",\n", " ):\n", " if marker in s:\n", " s = s.split(marker, 1)[0]\n", "\n", " s = s.splitlines()[0].strip() if s else \"\"\n", "\n", " for stop in (\".\", \",\", \";\", \"!\", \"?\"):\n", " if stop in s:\n", " s = s.split(stop, 1)[0]\n", "\n", " s = s.strip(\" \\t\\r\\n-–—:_'\\\"`()[]{}\")\n", " s = (\n", " s.replace(\"-\", \"_\")\n", " .replace(\"–\", \"_\")\n", " .replace(\"—\", \"_\")\n", " .replace(\"/\", \"_\")\n", " .replace(\" \", \"_\")\n", " )\n", "\n", " while \"__\" in s:\n", " s = s.replace(\"__\", \"_\")\n", "\n", " return s.strip(\"_\")\n", "\n", "\n", "def parse_completion(completion: str):\n", " c = str(completion).strip().lower()\n", "\n", " for marker in (\n", " \"<|im_end|>\",\n", " \"<|endoftext|>\",\n", " \"human:\",\n", " \"user:\",\n", " \"assistant:\",\n", " \"system:\",\n", " ):\n", " if marker in c:\n", " c = c.split(marker, 1)[0]\n", "\n", " c = c.strip()\n", " first_line = c.splitlines()[0].strip() if c else \"\"\n", "\n", " if first_line.startswith(\"yes\"):\n", " tail = first_line[len(\"yes\"):].lstrip(\" \\t-–—:,.\")\n", " pred_emotion = normalize_emotion(tail) if tail else \"\"\n", " return True, pred_emotion\n", "\n", " if first_line.startswith(\"no\"):\n", " return False, \"\"\n", "\n", " return False, \"\"\n", "\n", "\n", "def build_gen_kwargs(processor, max_new_tokens: int = 12):\n", " tok = processor.tokenizer\n", "\n", " pad_token_id = tok.pad_token_id\n", " if pad_token_id is None:\n", " pad_token_id = tok.eos_token_id\n", "\n", " im_end_id = tok.convert_tokens_to_ids(\"<|im_end|>\")\n", "\n", " eos_ids = []\n", " for tid in (tok.eos_token_id, im_end_id):\n", " if isinstance(tid, int) and tid >= 0 and tid not in eos_ids:\n", " eos_ids.append(tid)\n", "\n", " gen_kwargs = {\n", " \"max_new_tokens\": max_new_tokens,\n", " \"do_sample\": False,\n", " \"pad_token_id\": pad_token_id,\n", " }\n", "\n", " if len(eos_ids) == 1:\n", " gen_kwargs[\"eos_token_id\"] = eos_ids[0]\n", " elif len(eos_ids) > 1:\n", " gen_kwargs[\"eos_token_id\"] = eos_ids\n", "\n", " return gen_kwargs\n", "\n", "\n", "def evaluate(model, processor, records):\n", " device = next(model.parameters()).device\n", " gen_kwargs = build_gen_kwargs(processor, max_new_tokens=12)\n", "\n", " total = min(len(records), MAX_EVAL_EXAMPLES)\n", " same_hits = 0\n", " emotion_hits = 0\n", " joint_hits = 0\n", " positives = 0\n", "\n", " was_training = model.training\n", " model.eval()\n", "\n", " try:\n", " with torch.no_grad():\n", " for idx in range(total):\n", " sample = records[idx]\n", " is_same = bool(sample[\"same\"])\n", " actual_emotion = normalize_emotion(sample[\"emotion\"])\n", "\n", " if is_same:\n", " positives += 1\n", "\n", " prompt = processor.apply_chat_template(\n", " format_messages(\n", " sample[\"question\"],\n", " is_same,\n", " sample[\"emotion\"],\n", " train=False,\n", " ),\n", " tokenize=False,\n", " add_generation_prompt=True,\n", " )\n", "\n", " inputs = processor(\n", " text=[prompt],\n", " audio=[to_waveform(sample[\"audio\"], processor)],\n", " images=[sample[\"image\"]],\n", " return_tensors=\"pt\",\n", " ).to(device)\n", "\n", " output = model.generate(**inputs, **gen_kwargs)\n", "\n", " completion = processor.batch_decode(\n", " output[:, inputs[\"input_ids\"].shape[-1]:],\n", " skip_special_tokens=False,\n", " clean_up_tokenization_spaces=False,\n", " )[0]\n", "\n", " pred_same, pred_emotion = parse_completion(completion)\n", "\n", " if pred_same == is_same:\n", " same_hits += 1\n", "\n", " if not is_same:\n", " joint_hits += 1\n", " elif pred_emotion == actual_emotion:\n", " emotion_hits += 1\n", " joint_hits += 1\n", " finally:\n", " if was_training:\n", " model.train()\n", "\n", " return (\n", " same_hits / total if total else 0.0,\n", " emotion_hits / positives if positives else 0.0,\n", " joint_hits / total if total else 0.0,\n", " )\n" ] }, { "cell_type": "markdown", "metadata": { "id": "8t8Usnv66cA0" }, "source": [ "## Prepare model and processor" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "29753daf2657486b9066d546c2ca6be3", "724110d3e8404ef19f9bad8cd6aa4ef8", "7cb659828b8b4bcc9d80582df066da05", "0eb2061d58e749218b24b70104481243", "e40c28be292b4bdd9e0d0344e694ac86", "06ee67ffe51f4ef6a45e452eed064c5f", "f01791f1c6924540a12f7bf503a25ab5", "d002c24078914ac28880e25b7def3cf7", "5189a1347c4144b3a291f95ffca110ac", "6264f71ed22f412eb96773008f6cd8cc", "2c613dc4ce9846a3874a82c2e88e12c8", "84237223ca3d4c8cb1e0e0e4bddaca1b", "dc084d29a92f4399a7319a689e769783", "ff748bf5669b4168bf6c197f2f707cc6", "450f1431d6c44714b05694806bdcbf5b", "69d9c4b92d7548ef8d400977e0b266a8", "55ee18a36d354f96b78d03b3dda6ee32", 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`Qwen2VLImageProcessor` is now loaded as a fast processor by default, even if the model checkpoint was saved with a slow processor. This is a breaking change and may produce slightly different outputs. To continue using the slow processor, instantiate this class with `use_fast=False`. Note that this behavior will be extended to all models in a future release.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "tokenizer_config.json: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "84237223ca3d4c8cb1e0e0e4bddaca1b" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "vocab.json: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "5b5932927fd3448883c56b9adc96f68e" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "merges.txt: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "0dbbefdfb2c64c31999be7c4d5367b99" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "tokenizer.json: 0%| | 0.00/11.4M [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "3b522560efee4cb6b7b6bd1c0bcd0235" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "added_tokens.json: 0%| | 0.00/579 [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "08907dc152e449e4b5f6e68b16558639" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "special_tokens_map.json: 0%| | 0.00/832 [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "8c6610f2922242cd9317787ae0411df5" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "chat_template.json: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "bb970a430b154bb5991972e9ccd2ef81" } }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "`torch_dtype` is deprecated! Use `dtype` instead!\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "config.json: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "6d5f54c9415048a1a303ce9056be179e" } }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "model.safetensors.index.json: 0.00B [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "d5599165bfdf4aadb06fa7976c1922a0" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Fetching 3 files: 0%| | 0/3 [00:00, ?it/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "6ac1b842779f46a1ba6d8d9196759768" } }, "metadata": {} }, { "output_type": "display_data", "data": 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"application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "c1da466886054cd69cc5fdb1547b4c28" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "data/test-00004-of-00006.parquet: 0%| | 0.00/483M [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "ab1176147d9f456fb92c41bc3964ab2b" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "data/test-00005-of-00006.parquet: 0%| | 0.00/481M [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "cead7b470258495ab8a2c60786b5ba33" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Generating train split: 0%| | 0/24000 [00:00, ? examples/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "eb5bc94e4d1146a9b9348b96826553b9" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Generating test split: 0%| | 0/6000 [00:00, ? examples/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "cce39ee7fff1408eb5d77003285b4bee" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Loading dataset shards: 0%| | 0/22 [00:00, ?it/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "d67927f1da854f43b24ef74355915f27" } }, "metadata": {} } ], "source": [ "\n", "\n", "processor = AutoProcessor.from_pretrained(MODEL_ID, trust_remote_code=True)\n", "dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32\n", "thinker = Qwen2_5OmniThinkerForConditionalGeneration.from_pretrained(MODEL_ID, trust_remote_code=True, torch_dtype=dtype)\n", "thinker.to(dtype=dtype, device=torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\"))\n", "\n", "datasets_dict = load_dataset(DERIVED_DATASET_ID)\n", "train_dataset = datasets_dict[\"train\"]\n", "eval_dataset = datasets_dict[\"test\"]\n" ] }, { "cell_type": "markdown", "metadata": { "id": "wB2AkvuE6hZx" }, "source": [ "## We evaluate the base model in the evaluation fragment of the dataset\n", "You will use that later to compare performance against the fine-tuned model" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "id": "XJmYyVn56iQJ" }, "outputs": [], "source": [ "baseline = evaluate(thinker, processor, eval_dataset)" ] }, { "cell_type": "markdown", "metadata": { "id": "u8vSOrQi6lrN" }, "source": [ "## Train code" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "QSYIP8Sb6lzZ", "outputId": "d96a50ec-e500-42a2-dc4e-8051ccbb895f" }, "outputs": [ { "data": { "text/html": [ "\n", "
| Step | \n", "Training Loss | \n", "
|---|---|
| 2 | \n", "11.120700 | \n", "
| 4 | \n", "12.752000 | \n", "
| 6 | \n", "12.770500 | \n", "
| 8 | \n", "9.409800 | \n", "
| 10 | \n", "8.352200 | \n", "
| 12 | \n", "7.326300 | \n", "
| 14 | \n", "5.519600 | \n", "
| 16 | \n", "4.076400 | \n", "
| 18 | \n", "3.979900 | \n", "
| 20 | \n", "3.921200 | \n", "
| 22 | \n", "3.146400 | \n", "
| 24 | \n", "2.703000 | \n", "
| 26 | \n", "2.341300 | \n", "
| 28 | \n", "2.402500 | \n", "
| 30 | \n", "3.587200 | \n", "
| 32 | \n", "3.418400 | \n", "
| 34 | \n", "3.016600 | \n", "
| 36 | \n", "4.271700 | \n", "
| 38 | \n", "4.183500 | \n", "
| 40 | \n", "2.487100 | \n", "
| 42 | \n", "1.097400 | \n", "
| 44 | \n", "1.437600 | \n", "
| 46 | \n", "3.918300 | \n", "
| 48 | \n", "3.086200 | \n", "
| 50 | \n", "1.670800 | \n", "
| 52 | \n", "1.581400 | \n", "
| 54 | \n", "2.796000 | \n", "
| 56 | \n", "2.437700 | \n", "
| 58 | \n", "1.653400 | \n", "
| 60 | \n", "2.771800 | \n", "
| 62 | \n", "2.438400 | \n", "
| 64 | \n", "3.086200 | \n", "
| 66 | \n", "1.426800 | \n", "
| 68 | \n", "1.242500 | \n", "
| 70 | \n", "1.128600 | \n", "
| 72 | \n", "0.873500 | \n", "
| 74 | \n", "2.578600 | \n", "
| 76 | \n", "1.075300 | \n", "
| 78 | \n", "2.393000 | \n", "
| 80 | \n", "1.035200 | \n", "
| 82 | \n", "1.096900 | \n", "
| 84 | \n", "1.065600 | \n", "
| 86 | \n", "0.786100 | \n", "
| 88 | \n", "1.359100 | \n", "
| 90 | \n", "0.904300 | \n", "
| 92 | \n", "2.244100 | \n", "
| 94 | \n", "2.556300 | \n", "
| 96 | \n", "1.950200 | \n", "
| 98 | \n", "2.228000 | \n", "
| 100 | \n", "2.259800 | \n", "
| 102 | \n", "0.838400 | \n", "
| 104 | \n", "0.762100 | \n", "
| 106 | \n", "1.795600 | \n", "
| 108 | \n", "1.362700 | \n", "
| 110 | \n", "1.852800 | \n", "
| 112 | \n", "1.579700 | \n", "
| 114 | \n", "0.857700 | \n", "
| 116 | \n", "1.279900 | \n", "
| 118 | \n", "1.558000 | \n", "
| 120 | \n", "2.141400 | \n", "
| 122 | \n", "2.241900 | \n", "
| 124 | \n", "2.734300 | \n", "
| 126 | \n", "1.248000 | \n", "
| 128 | \n", "2.037600 | \n", "
| 130 | \n", "1.368600 | \n", "
| 132 | \n", "0.953100 | \n", "
| 134 | \n", "1.323600 | \n", "
| 136 | \n", "1.227000 | \n", "
| 138 | \n", "1.342800 | \n", "
| 140 | \n", "1.456100 | \n", "
| 142 | \n", "1.600900 | \n", "
| 144 | \n", "1.108200 | \n", "
| 146 | \n", "1.074000 | \n", "
| 148 | \n", "3.252900 | \n", "
| 150 | \n", "1.346700 | \n", "
| 152 | \n", "1.374700 | \n", "
| 154 | \n", "0.842500 | \n", "
| 156 | \n", "0.971200 | \n", "
| 158 | \n", "2.049300 | \n", "
| 160 | \n", "0.975700 | \n", "
| 162 | \n", "1.952500 | \n", "
| 164 | \n", "0.483800 | \n", "
| 166 | \n", "1.597200 | \n", "
| 168 | \n", "0.886000 | \n", "
| 170 | \n", "2.572800 | \n", "
| 172 | \n", "1.063800 | \n", "
| 174 | \n", "1.363500 | \n", "
| 176 | \n", "1.340800 | \n", "
| 178 | \n", "0.896700 | \n", "
| 180 | \n", "1.081900 | \n", "
| 182 | \n", "0.546600 | \n", "
| 184 | \n", "0.901900 | \n", "
| 186 | \n", "0.630600 | \n", "
| 188 | \n", "0.931300 | \n", "
| 190 | \n", "1.405000 | \n", "
| 192 | \n", "1.526200 | \n", "
| 194 | \n", "2.008500 | \n", "
| 196 | \n", "1.442600 | \n", "
| 198 | \n", "0.549100 | \n", "
| 200 | \n", "1.914800 | \n", "
| 202 | \n", "1.910200 | \n", "
| 204 | \n", "0.990300 | \n", "
| 206 | \n", "1.065800 | \n", "
| 208 | \n", "1.287500 | \n", "
| 210 | \n", "1.467100 | \n", "
| 212 | \n", "1.433100 | \n", "
| 214 | \n", "0.953000 | \n", "
| 216 | \n", "1.470500 | \n", "
| 218 | \n", "1.354900 | \n", "
| 220 | \n", "1.720400 | \n", "
| 222 | \n", "1.200300 | \n", "
| 224 | \n", "0.864700 | \n", "
| 226 | \n", "1.522300 | \n", "
| 228 | \n", "0.700000 | \n", "
| 230 | \n", "1.039000 | \n", "
| 232 | \n", "0.964000 | \n", "
| 234 | \n", "1.384300 | \n", "
| 236 | \n", "1.770100 | \n", "
| 238 | \n", "1.222300 | \n", "
| 240 | \n", "1.252300 | \n", "
| 242 | \n", "2.850700 | \n", "
| 244 | \n", "1.293600 | \n", "
| 246 | \n", "2.354200 | \n", "
| 248 | \n", "2.195700 | \n", "
| 250 | \n", "1.395100 | \n", "
| 252 | \n", "1.226300 | \n", "
| 254 | \n", "1.166000 | \n", "
| 256 | \n", "0.848600 | \n", "
| 258 | \n", "1.658100 | \n", "
| 260 | \n", "1.259900 | \n", "
| 262 | \n", "0.525200 | \n", "
| 264 | \n", "0.694000 | \n", "
| 266 | \n", "1.134800 | \n", "
| 268 | \n", "1.003500 | \n", "
| 270 | \n", "1.064600 | \n", "
| 272 | \n", "1.547900 | \n", "
| 274 | \n", "1.584700 | \n", "
| 276 | \n", "2.003800 | \n", "
| 278 | \n", "0.696200 | \n", "
| 280 | \n", "1.445000 | \n", "
| 282 | \n", "1.555300 | \n", "
| 284 | \n", "1.564100 | \n", "
| 286 | \n", "0.991900 | \n", "
| 288 | \n", "0.519500 | \n", "
| 290 | \n", "2.197500 | \n", "
| 292 | \n", "1.093000 | \n", "
| 294 | \n", "0.763400 | \n", "
| 296 | \n", "0.303000 | \n", "
| 298 | \n", "2.354600 | \n", "
| 300 | \n", "0.312800 | \n", "
| 302 | \n", "0.846800 | \n", "
| 304 | \n", "1.666600 | \n", "
| 306 | \n", "1.181000 | \n", "
| 308 | \n", "1.555600 | \n", "
| 310 | \n", "1.137700 | \n", "
| 312 | \n", "1.479300 | \n", "
| 314 | \n", "0.700600 | \n", "
| 316 | \n", "1.922900 | \n", "
| 318 | \n", "1.479200 | \n", "
| 320 | \n", "0.801200 | \n", "
| 322 | \n", "1.004900 | \n", "
| 324 | \n", "1.280200 | \n", "
| 326 | \n", "0.639000 | \n", "
| 328 | \n", "1.101200 | \n", "
| 330 | \n", "1.988100 | \n", "
| 332 | \n", "1.479500 | \n", "
| 334 | \n", "1.397500 | \n", "
| 336 | \n", "1.235600 | \n", "
| 338 | \n", "0.875900 | \n", "
| 340 | \n", "1.705500 | \n", "
| 342 | \n", "0.715800 | \n", "
| 344 | \n", "0.978000 | \n", "
| 346 | \n", "1.136500 | \n", "
| 348 | \n", "1.194100 | \n", "
| 350 | \n", "0.988600 | \n", "
| 352 | \n", "1.675000 | \n", "
| 354 | \n", "1.718400 | \n", "
| 356 | \n", "0.830000 | \n", "
| 358 | \n", "1.212100 | \n", "
| 360 | \n", "0.584600 | \n", "
| 362 | \n", "0.933100 | \n", "
| 364 | \n", "2.028500 | \n", "
| 366 | \n", "0.851000 | \n", "
| 368 | \n", "2.295700 | \n", "
| 370 | \n", "0.995300 | \n", "
| 372 | \n", "2.204300 | \n", "
| 374 | \n", "1.306200 | \n", "
| 376 | \n", "0.724000 | \n", "
| 378 | \n", "1.037400 | \n", "
| 380 | \n", "1.317600 | \n", "
| 382 | \n", "0.701900 | \n", "
| 384 | \n", "1.359500 | \n", "
| 386 | \n", "1.212000 | \n", "
| 388 | \n", "1.149900 | \n", "
| 390 | \n", "0.860500 | \n", "
| 392 | \n", "1.142100 | \n", "
| 394 | \n", "1.037400 | \n", "
| 396 | \n", "1.188500 | \n", "
| 398 | \n", "0.372900 | \n", "
| 400 | \n", "1.433800 | \n", "
| 402 | \n", "0.647300 | \n", "
| 404 | \n", "1.454000 | \n", "
| 406 | \n", "1.278200 | \n", "
| 408 | \n", "0.482300 | \n", "
| 410 | \n", "0.688400 | \n", "
| 412 | \n", "0.800100 | \n", "
| 414 | \n", "0.391200 | \n", "
| 416 | \n", "1.257500 | \n", "
| 418 | \n", "3.013200 | \n", "
| 420 | \n", "1.147500 | \n", "
| 422 | \n", "0.999800 | \n", "
| 424 | \n", "0.919100 | \n", "
| 426 | \n", "0.421900 | \n", "
| 428 | \n", "1.621000 | \n", "
| 430 | \n", "0.622600 | \n", "
| 432 | \n", "0.803200 | \n", "
| 434 | \n", "0.611900 | \n", "
| 436 | \n", "0.866000 | \n", "
| 438 | \n", "1.916700 | \n", "
| 440 | \n", "1.810700 | \n", "
| 442 | \n", "1.765600 | \n", "
| 444 | \n", "2.003900 | \n", "
| 446 | \n", "0.505300 | \n", "
| 448 | \n", "0.808400 | \n", "
| 450 | \n", "0.938600 | \n", "
| 452 | \n", "0.556700 | \n", "
| 454 | \n", "0.941500 | \n", "
| 456 | \n", "0.699600 | \n", "
| 458 | \n", "1.069600 | \n", "
| 460 | \n", "1.366800 | \n", "
| 462 | \n", "1.650700 | \n", "
| 464 | \n", "1.414000 | \n", "
| 466 | \n", "0.777300 | \n", "
| 468 | \n", "1.461500 | \n", "
| 470 | \n", "1.868000 | \n", "
| 472 | \n", "1.620300 | \n", "
| 474 | \n", "0.637300 | \n", "
| 476 | \n", "1.593700 | \n", "
| 478 | \n", "1.283800 | \n", "
| 480 | \n", "1.187200 | \n", "
| 482 | \n", "1.294500 | \n", "
| 484 | \n", "0.983900 | \n", "
| 486 | \n", "0.927400 | \n", "
| 488 | \n", "0.425500 | \n", "
| 490 | \n", "0.758300 | \n", "
| 492 | \n", "0.578300 | \n", "
| 494 | \n", "1.093600 | \n", "
| 496 | \n", "1.172000 | \n", "
| 498 | \n", "0.983800 | \n", "
| 500 | \n", "1.297400 | \n", "
| 502 | \n", "0.860500 | \n", "
| 504 | \n", "0.682000 | \n", "
| 506 | \n", "1.114700 | \n", "
| 508 | \n", "1.723100 | \n", "
| 510 | \n", "1.386300 | \n", "
| 512 | \n", "1.458500 | \n", "
| 514 | \n", "0.553000 | \n", "
| 516 | \n", "1.596700 | \n", "
| 518 | \n", "0.641100 | \n", "
| 520 | \n", "0.754300 | \n", "
| 522 | \n", "0.789700 | \n", "
| 524 | \n", "1.019200 | \n", "
| 526 | \n", "0.595700 | \n", "
| 528 | \n", "0.755800 | \n", "
| 530 | \n", "1.536700 | \n", "
| 532 | \n", "1.353400 | \n", "
| 534 | \n", "1.809200 | \n", "
| 536 | \n", "0.918000 | \n", "
| 538 | \n", "1.457100 | \n", "
| 540 | \n", "0.857100 | \n", "
| 542 | \n", "1.381300 | \n", "
| 544 | \n", "1.471000 | \n", "
| 546 | \n", "0.983500 | \n", "
| 548 | \n", "0.625900 | \n", "
| 550 | \n", "0.748200 | \n", "
| 552 | \n", "1.105200 | \n", "
| 554 | \n", "0.995600 | \n", "
| 556 | \n", "0.564600 | \n", "
| 558 | \n", "1.525300 | \n", "
| 560 | \n", "0.788300 | \n", "
| 562 | \n", "1.078600 | \n", "
| 564 | \n", "1.328000 | \n", "
| 566 | \n", "1.793500 | \n", "
| 568 | \n", "0.756900 | \n", "
| 570 | \n", "0.717400 | \n", "
| 572 | \n", "0.994700 | \n", "
| 574 | \n", "0.704000 | \n", "
| 576 | \n", "1.470000 | \n", "
| 578 | \n", "1.752500 | \n", "
| 580 | \n", "1.067100 | \n", "
| 582 | \n", "1.697500 | \n", "
| 584 | \n", "1.780200 | \n", "
| 586 | \n", "1.127400 | \n", "
| 588 | \n", "0.952100 | \n", "
| 590 | \n", "1.029400 | \n", "
| 592 | \n", "1.641100 | \n", "
| 594 | \n", "0.355100 | \n", "
| 596 | \n", "0.660800 | \n", "
| 598 | \n", "1.105100 | \n", "
| 600 | \n", "1.944600 | \n", "
| 602 | \n", "1.135500 | \n", "
| 604 | \n", "0.738500 | \n", "
| 606 | \n", "0.932500 | \n", "
| 608 | \n", "1.010000 | \n", "
| 610 | \n", "1.371100 | \n", "
| 612 | \n", "1.125500 | \n", "
| 614 | \n", "1.715800 | \n", "
| 616 | \n", "0.760200 | \n", "
| 618 | \n", "0.199600 | \n", "
| 620 | \n", "1.093800 | \n", "
| 622 | \n", "0.882500 | \n", "
| 624 | \n", "1.208300 | \n", "
| 626 | \n", "3.057200 | \n", "
| 628 | \n", "0.377800 | \n", "
| 630 | \n", "1.086900 | \n", "
| 632 | \n", "0.739200 | \n", "
| 634 | \n", "1.911900 | \n", "
| 636 | \n", "1.063100 | \n", "
| 638 | \n", "1.085400 | \n", "
| 640 | \n", "1.567200 | \n", "
| 642 | \n", "1.142000 | \n", "
| 644 | \n", "1.227200 | \n", "
| 646 | \n", "0.634300 | \n", "
| 648 | \n", "1.114200 | \n", "
| 650 | \n", "1.720100 | \n", "
| 652 | \n", "1.164100 | \n", "
| 654 | \n", "0.539700 | \n", "
| 656 | \n", "1.046500 | \n", "
| 658 | \n", "0.855500 | \n", "
| 660 | \n", "1.609400 | \n", "
| 662 | \n", "0.975000 | \n", "
| 664 | \n", "0.827100 | \n", "
| 666 | \n", "1.404700 | \n", "
| 668 | \n", "0.275000 | \n", "
| 670 | \n", "0.941900 | \n", "
| 672 | \n", "0.534600 | \n", "
| 674 | \n", "1.141000 | \n", "
| 676 | \n", "1.010700 | \n", "
| 678 | \n", "1.769700 | \n", "
| 680 | \n", "0.846200 | \n", "
| 682 | \n", "1.648800 | \n", "
| 684 | \n", "1.081300 | \n", "
| 686 | \n", "1.243800 | \n", "
| 688 | \n", "1.015300 | \n", "
| 690 | \n", "1.333100 | \n", "
| 692 | \n", "0.807400 | \n", "
| 694 | \n", "0.225400 | \n", "
| 696 | \n", "1.229300 | \n", "
| 698 | \n", "0.488200 | \n", "
| 700 | \n", "0.733000 | \n", "
| 702 | \n", "1.070600 | \n", "
| 704 | \n", "0.525600 | \n", "
| 706 | \n", "1.657000 | \n", "
| 708 | \n", "0.769100 | \n", "
| 710 | \n", "0.720000 | \n", "
| 712 | \n", "1.482800 | \n", "
| 714 | \n", "1.360000 | \n", "
| 716 | \n", "0.549300 | \n", "
| 718 | \n", "1.019000 | \n", "
| 720 | \n", "1.033300 | \n", "
| 722 | \n", "0.404900 | \n", "
| 724 | \n", "0.849300 | \n", "
| 726 | \n", "1.675300 | \n", "
| 728 | \n", "0.361800 | \n", "
| 730 | \n", "1.944800 | \n", "
| 732 | \n", "0.613900 | \n", "
| 734 | \n", "0.491600 | \n", "
| 736 | \n", "0.873100 | \n", "
| 738 | \n", "2.040400 | \n", "
| 740 | \n", "1.131800 | \n", "
| 742 | \n", "1.560000 | \n", "
| 744 | \n", "1.292000 | \n", "
| 746 | \n", "0.867700 | \n", "
| 748 | \n", "0.900800 | \n", "
| 750 | \n", "1.283200 | \n", "
| 752 | \n", "0.488100 | \n", "
| 754 | \n", "0.679700 | \n", "
| 756 | \n", "1.033600 | \n", "
| 758 | \n", "0.608300 | \n", "
| 760 | \n", "1.508200 | \n", "
| 762 | \n", "1.478200 | \n", "
| 764 | \n", "1.449100 | \n", "
| 766 | \n", "1.334300 | \n", "
| 768 | \n", "0.939800 | \n", "
| 770 | \n", "0.816200 | \n", "
| 772 | \n", "0.588100 | \n", "
| 774 | \n", "1.268800 | \n", "
| 776 | \n", "1.428600 | \n", "
| 778 | \n", "1.148200 | \n", "
| 780 | \n", "1.187100 | \n", "
| 782 | \n", "0.722600 | \n", "
| 784 | \n", "0.367600 | \n", "
| 786 | \n", "0.766500 | \n", "
| 788 | \n", "1.198600 | \n", "
| 790 | \n", "1.007400 | \n", "
| 792 | \n", "1.128300 | \n", "
| 794 | \n", "0.942500 | \n", "
| 796 | \n", "1.235000 | \n", "
| 798 | \n", "0.573700 | \n", "
| 800 | \n", "0.656600 | \n", "
| 802 | \n", "1.156000 | \n", "
| 804 | \n", "0.961400 | \n", "
| 806 | \n", "1.102600 | \n", "
| 808 | \n", "0.923500 | \n", "
| 810 | \n", "0.524100 | \n", "
| 812 | \n", "0.914300 | \n", "
| 814 | \n", "0.617900 | \n", "
| 816 | \n", "0.387300 | \n", "
| 818 | \n", "2.696800 | \n", "
| 820 | \n", "0.939200 | \n", "
| 822 | \n", "1.621900 | \n", "
| 824 | \n", "0.812500 | \n", "
| 826 | \n", "1.280700 | \n", "
| 828 | \n", "0.644500 | \n", "
| 830 | \n", "0.642000 | \n", "
| 832 | \n", "1.736000 | \n", "
| 834 | \n", "0.147500 | \n", "
| 836 | \n", "0.714600 | \n", "
| 838 | \n", "0.518700 | \n", "
| 840 | \n", "1.370700 | \n", "
| 842 | \n", "0.963000 | \n", "
| 844 | \n", "1.289800 | \n", "
| 846 | \n", "0.824600 | \n", "
| 848 | \n", "1.433400 | \n", "
| 850 | \n", "1.063900 | \n", "
| 852 | \n", "0.626100 | \n", "
| 854 | \n", "1.321500 | \n", "
| 856 | \n", "2.149200 | \n", "
| 858 | \n", "0.699800 | \n", "
| 860 | \n", "1.678500 | \n", "
| 862 | \n", "0.754700 | \n", "
| 864 | \n", "0.397900 | \n", "
| 866 | \n", "1.741900 | \n", "
| 868 | \n", "0.794600 | \n", "
| 870 | \n", "0.809600 | \n", "
| 872 | \n", "0.440500 | \n", "
| 874 | \n", "0.927700 | \n", "
| 876 | \n", "0.499400 | \n", "
| 878 | \n", "0.912300 | \n", "
| 880 | \n", "1.399800 | \n", "
| 882 | \n", "1.283700 | \n", "
| 884 | \n", "1.860100 | \n", "
| 886 | \n", "1.633100 | \n", "
| 888 | \n", "0.613100 | \n", "
| 890 | \n", "1.448900 | \n", "
| 892 | \n", "1.376900 | \n", "
| 894 | \n", "0.503800 | \n", "
| 896 | \n", "1.799400 | \n", "
| 898 | \n", "1.260500 | \n", "
| 900 | \n", "0.666600 | \n", "
| 902 | \n", "1.256300 | \n", "
| 904 | \n", "1.117400 | \n", "
| 906 | \n", "1.220900 | \n", "
| 908 | \n", "1.324400 | \n", "
| 910 | \n", "0.376900 | \n", "
| 912 | \n", "1.635900 | \n", "
| 914 | \n", "1.270800 | \n", "
| 916 | \n", "0.677600 | \n", "
| 918 | \n", "0.646900 | \n", "
| 920 | \n", "0.359500 | \n", "
| 922 | \n", "1.314800 | \n", "
| 924 | \n", "0.867500 | \n", "
| 926 | \n", "1.249600 | \n", "
| 928 | \n", "0.607800 | \n", "
| 930 | \n", "0.774600 | \n", "
| 932 | \n", "0.235800 | \n", "
| 934 | \n", "1.265300 | \n", "
| 936 | \n", "1.376300 | \n", "
| 938 | \n", "1.157800 | \n", "
| 940 | \n", "1.090900 | \n", "
| 942 | \n", "0.216800 | \n", "
| 944 | \n", "0.932500 | \n", "
| 946 | \n", "0.933800 | \n", "
| 948 | \n", "1.067900 | \n", "
| 950 | \n", "0.782000 | \n", "
| 952 | \n", "1.514400 | \n", "
| 954 | \n", "0.644700 | \n", "
| 956 | \n", "1.415700 | \n", "
| 958 | \n", "1.024900 | \n", "
| 960 | \n", "0.266600 | \n", "
| 962 | \n", "0.544900 | \n", "
| 964 | \n", "1.135500 | \n", "
| 966 | \n", "0.605700 | \n", "
| 968 | \n", "0.776000 | \n", "
| 970 | \n", "0.812400 | \n", "
| 972 | \n", "0.561400 | \n", "
| 974 | \n", "0.999500 | \n", "
| 976 | \n", "1.409900 | \n", "
| 978 | \n", "1.350600 | \n", "
| 980 | \n", "1.201800 | \n", "
| 982 | \n", "1.833000 | \n", "
| 984 | \n", "0.834700 | \n", "
| 986 | \n", "1.230300 | \n", "
| 988 | \n", "0.967600 | \n", "
| 990 | \n", "0.351700 | \n", "
| 992 | \n", "0.678500 | \n", "
| 994 | \n", "1.263600 | \n", "
| 996 | \n", "0.808500 | \n", "
| 998 | \n", "0.641700 | \n", "
| 1000 | \n", "0.863300 | \n", "
| 1002 | \n", "0.296700 | \n", "
| 1004 | \n", "0.425500 | \n", "
| 1006 | \n", "1.358700 | \n", "
| 1008 | \n", "1.409800 | \n", "
| 1010 | \n", "0.657300 | \n", "
| 1012 | \n", "0.753000 | \n", "
| 1014 | \n", "1.504600 | \n", "
| 1016 | \n", "1.147500 | \n", "
| 1018 | \n", "0.525000 | \n", "
| 1020 | \n", "1.333100 | \n", "
| 1022 | \n", "0.588100 | \n", "
| 1024 | \n", "1.371200 | \n", "
| 1026 | \n", "0.779500 | \n", "
| 1028 | \n", "1.129600 | \n", "
| 1030 | \n", "1.941300 | \n", "
| 1032 | \n", "2.262500 | \n", "
| 1034 | \n", "1.051600 | \n", "
| 1036 | \n", "0.614900 | \n", "
| 1038 | \n", "1.729100 | \n", "
| 1040 | \n", "0.727500 | \n", "
| 1042 | \n", "0.373800 | \n", "
| 1044 | \n", "0.931300 | \n", "
| 1046 | \n", "0.641500 | \n", "
| 1048 | \n", "1.009900 | \n", "
| 1050 | \n", "0.639300 | \n", "
| 1052 | \n", "1.418700 | \n", "
| 1054 | \n", "1.643800 | \n", "
| 1056 | \n", "1.508700 | \n", "
| 1058 | \n", "0.657400 | \n", "
| 1060 | \n", "1.216400 | \n", "
| 1062 | \n", "1.118300 | \n", "
| 1064 | \n", "1.028600 | \n", "
| 1066 | \n", "0.589300 | \n", "
| 1068 | \n", "1.265900 | \n", "
| 1070 | \n", "0.677800 | \n", "
| 1072 | \n", "0.787200 | \n", "
| 1074 | \n", "1.469000 | \n", "
| 1076 | \n", "1.430700 | \n", "
| 1078 | \n", "1.567800 | \n", "
| 1080 | \n", "0.770500 | \n", "
| 1082 | \n", "0.930600 | \n", "
| 1084 | \n", "0.566400 | \n", "
| 1086 | \n", "1.250100 | \n", "
| 1088 | \n", "1.284000 | \n", "
| 1090 | \n", "0.786500 | \n", "
| 1092 | \n", "1.538700 | \n", "
| 1094 | \n", "1.792400 | \n", "
| 1096 | \n", "1.263500 | \n", "
| 1098 | \n", "0.792700 | \n", "
| 1100 | \n", "0.382800 | \n", "
| 1102 | \n", "1.591100 | \n", "
| 1104 | \n", "0.734200 | \n", "
| 1106 | \n", "0.376600 | \n", "
| 1108 | \n", "2.163300 | \n", "
| 1110 | \n", "0.120900 | \n", "
| 1112 | \n", "0.871700 | \n", "
| 1114 | \n", "0.894800 | \n", "
| 1116 | \n", "1.166700 | \n", "
| 1118 | \n", "1.548400 | \n", "
| 1120 | \n", "0.886200 | \n", "
| 1122 | \n", "0.681500 | \n", "
| 1124 | \n", "1.697400 | \n", "
| 1126 | \n", "0.845300 | \n", "
| 1128 | \n", "2.255700 | \n", "
| 1130 | \n", "2.191900 | \n", "
| 1132 | \n", "1.907300 | \n", "
| 1134 | \n", "1.758800 | \n", "
| 1136 | \n", "0.582800 | \n", "
| 1138 | \n", "1.448400 | \n", "
| 1140 | \n", "1.276700 | \n", "
| 1142 | \n", "0.459800 | \n", "
| 1144 | \n", "0.762700 | \n", "
| 1146 | \n", "0.476100 | \n", "
| 1148 | \n", "0.317100 | \n", "
| 1150 | \n", "0.317600 | \n", "
| 1152 | \n", "0.969100 | \n", "
| 1154 | \n", "1.236500 | \n", "
| 1156 | \n", "0.714600 | \n", "
| 1158 | \n", "0.278700 | \n", "
| 1160 | \n", "1.417700 | \n", "
| 1162 | \n", "1.511300 | \n", "
| 1164 | \n", "1.672900 | \n", "
| 1166 | \n", "1.228000 | \n", "
| 1168 | \n", "2.786400 | \n", "
| 1170 | \n", "1.227600 | \n", "
| 1172 | \n", "1.069600 | \n", "
| 1174 | \n", "0.329800 | \n", "
| 1176 | \n", "0.929300 | \n", "
| 1178 | \n", "1.217500 | \n", "
| 1180 | \n", "0.555100 | \n", "
| 1182 | \n", "0.465800 | \n", "
| 1184 | \n", "0.973800 | \n", "
| 1186 | \n", "0.647300 | \n", "
| 1188 | \n", "1.196400 | \n", "
| 1190 | \n", "1.854700 | \n", "
| 1192 | \n", "0.088300 | \n", "
| 1194 | \n", "0.980800 | \n", "
| 1196 | \n", "0.462900 | \n", "
| 1198 | \n", "2.079100 | \n", "
| 1200 | \n", "2.171900 | \n", "
| 1202 | \n", "0.418100 | \n", "
| 1204 | \n", "0.490600 | \n", "
| 1206 | \n", "2.112700 | \n", "
| 1208 | \n", "0.978700 | \n", "
| 1210 | \n", "1.110800 | \n", "
| 1212 | \n", "0.931700 | \n", "
| 1214 | \n", "0.422700 | \n", "
| 1216 | \n", "0.373300 | \n", "
| 1218 | \n", "0.633900 | \n", "
| 1220 | \n", "0.247900 | \n", "
| 1222 | \n", "0.193400 | \n", "
| 1224 | \n", "0.543400 | \n", "
| 1226 | \n", "0.792500 | \n", "
| 1228 | \n", "1.117500 | \n", "
| 1230 | \n", "0.892100 | \n", "
| 1232 | \n", "0.885900 | \n", "
| 1234 | \n", "2.497100 | \n", "
| 1236 | \n", "1.689600 | \n", "
| 1238 | \n", "2.464400 | \n", "
| 1240 | \n", "2.856400 | \n", "
| 1242 | \n", "1.363900 | \n", "
| 1244 | \n", "1.094800 | \n", "
| 1246 | \n", "1.188400 | \n", "
| 1248 | \n", "1.452300 | \n", "
| 1250 | \n", "2.223200 | \n", "
| 1252 | \n", "1.858600 | \n", "
| 1254 | \n", "0.522900 | \n", "
| 1256 | \n", "1.267500 | \n", "
| 1258 | \n", "0.950100 | \n", "
| 1260 | \n", "0.409000 | \n", "
| 1262 | \n", "1.098700 | \n", "
| 1264 | \n", "0.574100 | \n", "
| 1266 | \n", "0.971200 | \n", "
| 1268 | \n", "0.428200 | \n", "
| 1270 | \n", "0.163500 | \n", "
| 1272 | \n", "1.692000 | \n", "
| 1274 | \n", "1.237400 | \n", "
| 1276 | \n", "0.659300 | \n", "
| 1278 | \n", "0.652900 | \n", "
| 1280 | \n", "1.952700 | \n", "
| 1282 | \n", "0.512800 | \n", "
| 1284 | \n", "1.040800 | \n", "
| 1286 | \n", "0.261600 | \n", "
| 1288 | \n", "0.861800 | \n", "
| 1290 | \n", "0.683500 | \n", "
| 1292 | \n", "0.785600 | \n", "
| 1294 | \n", "0.301100 | \n", "
| 1296 | \n", "0.563300 | \n", "
| 1298 | \n", "1.034900 | \n", "
| 1300 | \n", "0.972700 | \n", "
| 1302 | \n", "1.326800 | \n", "
| 1304 | \n", "1.187100 | \n", "
| 1306 | \n", "0.513200 | \n", "
| 1308 | \n", "1.382200 | \n", "
| 1310 | \n", "1.775500 | \n", "
| 1312 | \n", "1.709400 | \n", "
| 1314 | \n", "0.675900 | \n", "
| 1316 | \n", "1.929300 | \n", "
| 1318 | \n", "1.699200 | \n", "
| 1320 | \n", "1.219300 | \n", "
| 1322 | \n", "1.067300 | \n", "
| 1324 | \n", "1.320300 | \n", "
| 1326 | \n", "0.770000 | \n", "
| 1328 | \n", "1.624900 | \n", "
| 1330 | \n", "0.670300 | \n", "
| 1332 | \n", "0.431400 | \n", "
| 1334 | \n", "0.463000 | \n", "
| 1336 | \n", "1.262900 | \n", "
| 1338 | \n", "0.291100 | \n", "
| 1340 | \n", "2.482800 | \n", "
| 1342 | \n", "0.734300 | \n", "
| 1344 | \n", "1.075200 | \n", "
| 1346 | \n", "0.473300 | \n", "
| 1348 | \n", "0.475500 | \n", "
| 1350 | \n", "0.817000 | \n", "
| 1352 | \n", "1.018300 | \n", "
| 1354 | \n", "0.339900 | \n", "
| 1356 | \n", "1.025900 | \n", "
| 1358 | \n", "0.880000 | \n", "
| 1360 | \n", "1.038100 | \n", "
| 1362 | \n", "0.390600 | \n", "
| 1364 | \n", "0.305000 | \n", "
| 1366 | \n", "1.357000 | \n", "
| 1368 | \n", "0.821100 | \n", "
| 1370 | \n", "0.858700 | \n", "
| 1372 | \n", "0.316200 | \n", "
| 1374 | \n", "0.991700 | \n", "
| 1376 | \n", "0.945200 | \n", "
| 1378 | \n", "1.407200 | \n", "
| 1380 | \n", "0.371100 | \n", "
| 1382 | \n", "1.043600 | \n", "
| 1384 | \n", "0.501900 | \n", "
| 1386 | \n", "1.181700 | \n", "
| 1388 | \n", "1.886900 | \n", "
| 1390 | \n", "1.609900 | \n", "
| 1392 | \n", "2.462400 | \n", "
| 1394 | \n", "2.102500 | \n", "
| 1396 | \n", "1.581800 | \n", "
| 1398 | \n", "0.399800 | \n", "
| 1400 | \n", "1.090900 | \n", "
| 1402 | \n", "0.322700 | \n", "
| 1404 | \n", "0.709400 | \n", "
| 1406 | \n", "0.198500 | \n", "
| 1408 | \n", "0.719700 | \n", "
| 1410 | \n", "0.603400 | \n", "
| 1412 | \n", "0.224800 | \n", "
| 1414 | \n", "1.489600 | \n", "
| 1416 | \n", "1.457400 | \n", "
| 1418 | \n", "1.478200 | \n", "
| 1420 | \n", "0.509100 | \n", "
| 1422 | \n", "1.019300 | \n", "
| 1424 | \n", "1.241900 | \n", "
| 1426 | \n", "0.735300 | \n", "
| 1428 | \n", "0.706300 | \n", "
| 1430 | \n", "0.870700 | \n", "
| 1432 | \n", "2.354000 | \n", "
| 1434 | \n", "0.639500 | \n", "
| 1436 | \n", "1.081100 | \n", "
| 1438 | \n", "1.160500 | \n", "
| 1440 | \n", "0.431400 | \n", "
| 1442 | \n", "0.802700 | \n", "
| 1444 | \n", "0.329900 | \n", "
| 1446 | \n", "0.979600 | \n", "
| 1448 | \n", "0.805900 | \n", "
| 1450 | \n", "0.517900 | \n", "
| 1452 | \n", "0.949500 | \n", "
| 1454 | \n", "0.584200 | \n", "
| 1456 | \n", "1.625800 | \n", "
| 1458 | \n", "1.694800 | \n", "
| 1460 | \n", "0.511300 | \n", "
| 1462 | \n", "1.065500 | \n", "
| 1464 | \n", "1.185600 | \n", "
| 1466 | \n", "0.952800 | \n", "
| 1468 | \n", "1.891900 | \n", "
| 1470 | \n", "0.148700 | \n", "
| 1472 | \n", "1.255400 | \n", "
| 1474 | \n", "0.751000 | \n", "
| 1476 | \n", "2.335800 | \n", "
| 1478 | \n", "0.812800 | \n", "
| 1480 | \n", "1.532600 | \n", "
| 1482 | \n", "0.592300 | \n", "
| 1484 | \n", "0.458700 | \n", "
| 1486 | \n", "1.326800 | \n", "
| 1488 | \n", "1.105100 | \n", "
| 1490 | \n", "0.496900 | \n", "
| 1492 | \n", "0.498500 | \n", "
| 1494 | \n", "0.666600 | \n", "
| 1496 | \n", "1.306300 | \n", "
| 1498 | \n", "1.264500 | \n", "
| 1500 | \n", "1.128100 | \n", "
| 1502 | \n", "0.927400 | \n", "
| 1504 | \n", "0.618500 | \n", "
| 1506 | \n", "1.048300 | \n", "
| 1508 | \n", "0.337600 | \n", "
| 1510 | \n", "0.162200 | \n", "
| 1512 | \n", "0.266900 | \n", "
| 1514 | \n", "0.575800 | \n", "
| 1516 | \n", "0.983800 | \n", "
| 1518 | \n", "1.882600 | \n", "
| 1520 | \n", "1.081000 | \n", "
| 1522 | \n", "1.032300 | \n", "
| 1524 | \n", "0.729200 | \n", "
| 1526 | \n", "1.256700 | \n", "
| 1528 | \n", "0.538600 | \n", "
| 1530 | \n", "0.549900 | \n", "
| 1532 | \n", "0.960100 | \n", "
| 1534 | \n", "1.032000 | \n", "
| 1536 | \n", "0.500900 | \n", "
| 1538 | \n", "0.438600 | \n", "
| 1540 | \n", "1.232800 | \n", "
| 1542 | \n", "0.365400 | \n", "
| 1544 | \n", "0.628800 | \n", "
| 1546 | \n", "1.568900 | \n", "
| 1548 | \n", "1.177200 | \n", "
| 1550 | \n", "1.202200 | \n", "
| 1552 | \n", "0.885400 | \n", "
| 1554 | \n", "0.739500 | \n", "
| 1556 | \n", "0.825900 | \n", "
| 1558 | \n", "1.148100 | \n", "
| 1560 | \n", "2.024200 | \n", "
| 1562 | \n", "0.244600 | \n", "
| 1564 | \n", "0.952000 | \n", "
| 1566 | \n", "1.624700 | \n", "
| 1568 | \n", "0.954500 | \n", "
| 1570 | \n", "1.053700 | \n", "
| 1572 | \n", "1.435500 | \n", "
| 1574 | \n", "0.951700 | \n", "
| 1576 | \n", "1.467900 | \n", "
| 1578 | \n", "0.950000 | \n", "
| 1580 | \n", "1.733800 | \n", "
| 1582 | \n", "0.849500 | \n", "
| 1584 | \n", "0.796100 | \n", "
| 1586 | \n", "1.460000 | \n", "
| 1588 | \n", "0.297900 | \n", "
| 1590 | \n", "0.937000 | \n", "
| 1592 | \n", "1.081400 | \n", "
| 1594 | \n", "1.289100 | \n", "
| 1596 | \n", "0.974600 | \n", "
| 1598 | \n", "0.639800 | \n", "
| 1600 | \n", "0.759700 | \n", "
| 1602 | \n", "0.813500 | \n", "
| 1604 | \n", "1.635800 | \n", "
| 1606 | \n", "1.082700 | \n", "
| 1608 | \n", "0.193200 | \n", "
| 1610 | \n", "0.808200 | \n", "
| 1612 | \n", "1.413700 | \n", "
| 1614 | \n", "1.019800 | \n", "
| 1616 | \n", "0.548000 | \n", "
| 1618 | \n", "0.244300 | \n", "
| 1620 | \n", "1.104800 | \n", "
| 1622 | \n", "0.763400 | \n", "
| 1624 | \n", "0.798400 | \n", "
| 1626 | \n", "1.579400 | \n", "
| 1628 | \n", "0.874500 | \n", "
| 1630 | \n", "2.651800 | \n", "
| 1632 | \n", "0.564000 | \n", "
| 1634 | \n", "1.649900 | \n", "
| 1636 | \n", "1.499400 | \n", "
| 1638 | \n", "0.272100 | \n", "
| 1640 | \n", "1.525800 | \n", "
| 1642 | \n", "0.987000 | \n", "
| 1644 | \n", "0.370000 | \n", "
| 1646 | \n", "1.041600 | \n", "
| 1648 | \n", "0.799900 | \n", "
| 1650 | \n", "1.696200 | \n", "
| 1652 | \n", "0.654000 | \n", "
| 1654 | \n", "1.238300 | \n", "
| 1656 | \n", "1.184500 | \n", "
| 1658 | \n", "1.834600 | \n", "
| 1660 | \n", "2.409100 | \n", "
| 1662 | \n", "0.735700 | \n", "
| 1664 | \n", "1.465700 | \n", "
| 1666 | \n", "0.500200 | \n", "
| 1668 | \n", "0.114000 | \n", "
| 1670 | \n", "1.024400 | \n", "
| 1672 | \n", "0.787100 | \n", "
| 1674 | \n", "0.909500 | \n", "
| 1676 | \n", "1.645800 | \n", "
| 1678 | \n", "0.956700 | \n", "
| 1680 | \n", "0.649900 | \n", "
| 1682 | \n", "0.624300 | \n", "
| 1684 | \n", "1.320200 | \n", "
| 1686 | \n", "0.712000 | \n", "
| 1688 | \n", "0.901700 | \n", "
| 1690 | \n", "0.332400 | \n", "
| 1692 | \n", "0.748300 | \n", "
| 1694 | \n", "0.667500 | \n", "
| 1696 | \n", "1.066200 | \n", "
| 1698 | \n", "0.860200 | \n", "
| 1700 | \n", "1.302400 | \n", "
| 1702 | \n", "0.702300 | \n", "
| 1704 | \n", "1.699300 | \n", "
| 1706 | \n", "0.194700 | \n", "
| 1708 | \n", "0.308800 | \n", "
| 1710 | \n", "0.689700 | \n", "
| 1712 | \n", "0.867900 | \n", "
| 1714 | \n", "1.266900 | \n", "
| 1716 | \n", "0.844100 | \n", "
| 1718 | \n", "0.725700 | \n", "
| 1720 | \n", "0.730600 | \n", "
| 1722 | \n", "0.876100 | \n", "
| 1724 | \n", "0.921500 | \n", "
| 1726 | \n", "2.011600 | \n", "
| 1728 | \n", "1.054100 | \n", "
| 1730 | \n", "0.914700 | \n", "
| 1732 | \n", "1.297300 | \n", "
| 1734 | \n", "1.062800 | \n", "
| 1736 | \n", "0.481900 | \n", "
| 1738 | \n", "0.333400 | \n", "
| 1740 | \n", "0.386400 | \n", "
| 1742 | \n", "1.190200 | \n", "
| 1744 | \n", "1.044600 | \n", "
| 1746 | \n", "1.026700 | \n", "
| 1748 | \n", "0.609600 | \n", "
| 1750 | \n", "0.659300 | \n", "
| 1752 | \n", "1.357200 | \n", "
| 1754 | \n", "1.142800 | \n", "
| 1756 | \n", "0.688600 | \n", "
| 1758 | \n", "1.761200 | \n", "
| 1760 | \n", "1.106700 | \n", "
| 1762 | \n", "0.877200 | \n", "
| 1764 | \n", "0.619100 | \n", "
| 1766 | \n", "1.776900 | \n", "
| 1768 | \n", "0.938900 | \n", "
| 1770 | \n", "0.627600 | \n", "
| 1772 | \n", "0.970500 | \n", "
| 1774 | \n", "0.869400 | \n", "
| 1776 | \n", "0.733700 | \n", "
| 1778 | \n", "1.624000 | \n", "
| 1780 | \n", "1.100300 | \n", "
| 1782 | \n", "0.247700 | \n", "
| 1784 | \n", "0.772800 | \n", "
| 1786 | \n", "0.618300 | \n", "
| 1788 | \n", "0.729900 | \n", "
| 1790 | \n", "0.610800 | \n", "
| 1792 | \n", "0.702100 | \n", "
| 1794 | \n", "1.101600 | \n", "
| 1796 | \n", "1.546300 | \n", "
| 1798 | \n", "0.866600 | \n", "
| 1800 | \n", "0.565700 | \n", "
| 1802 | \n", "1.346600 | \n", "
| 1804 | \n", "0.422300 | \n", "
| 1806 | \n", "1.428100 | \n", "
| 1808 | \n", "0.279000 | \n", "
| 1810 | \n", "0.221200 | \n", "
| 1812 | \n", "0.821600 | \n", "
| 1814 | \n", "0.760900 | \n", "
| 1816 | \n", "0.723000 | \n", "
| 1818 | \n", "0.938300 | \n", "
| 1820 | \n", "0.572400 | \n", "
| 1822 | \n", "0.531200 | \n", "
| 1824 | \n", "1.217900 | \n", "
| 1826 | \n", "0.441600 | \n", "
| 1828 | \n", "0.261500 | \n", "
| 1830 | \n", "0.278900 | \n", "
| 1832 | \n", "0.547100 | \n", "
| 1834 | \n", "0.858800 | \n", "
| 1836 | \n", "0.929700 | \n", "
| 1838 | \n", "1.071800 | \n", "
| 1840 | \n", "1.263600 | \n", "
| 1842 | \n", "1.095600 | \n", "
| 1844 | \n", "0.607500 | \n", "
| 1846 | \n", "0.624000 | \n", "
| 1848 | \n", "1.900100 | \n", "
| 1850 | \n", "1.031800 | \n", "
| 1852 | \n", "0.337800 | \n", "
| 1854 | \n", "1.342500 | \n", "
| 1856 | \n", "0.748000 | \n", "
| 1858 | \n", "1.165000 | \n", "
| 1860 | \n", "1.311900 | \n", "
| 1862 | \n", "0.223100 | \n", "
| 1864 | \n", "2.727000 | \n", "
| 1866 | \n", "0.645000 | \n", "
| 1868 | \n", "0.711900 | \n", "
| 1870 | \n", "0.664600 | \n", "
| 1872 | \n", "0.686800 | \n", "
| 1874 | \n", "0.199800 | \n", "
| 1876 | \n", "0.942800 | \n", "
| 1878 | \n", "1.017200 | \n", "
| 1880 | \n", "0.834200 | \n", "
| 1882 | \n", "1.084200 | \n", "
| 1884 | \n", "1.292800 | \n", "
| 1886 | \n", "2.371700 | \n", "
| 1888 | \n", "2.327300 | \n", "
| 1890 | \n", "0.662300 | \n", "
| 1892 | \n", "0.649100 | \n", "
| 1894 | \n", "0.617000 | \n", "
| 1896 | \n", "0.761000 | \n", "
| 1898 | \n", "1.497400 | \n", "
| 1900 | \n", "1.440900 | \n", "
| 1902 | \n", "0.118300 | \n", "
| 1904 | \n", "1.545700 | \n", "
| 1906 | \n", "0.989700 | \n", "
| 1908 | \n", "0.526900 | \n", "
| 1910 | \n", "0.937900 | \n", "
| 1912 | \n", "0.552700 | \n", "
| 1914 | \n", "1.252300 | \n", "
| 1916 | \n", "1.513500 | \n", "
| 1918 | \n", "1.402500 | \n", "
| 1920 | \n", "1.028500 | \n", "
| 1922 | \n", "1.189000 | \n", "
| 1924 | \n", "0.437100 | \n", "
| 1926 | \n", "0.439300 | \n", "
| 1928 | \n", "1.006700 | \n", "
| 1930 | \n", "1.133700 | \n", "
| 1932 | \n", "1.316800 | \n", "
| 1934 | \n", "0.326400 | \n", "
| 1936 | \n", "0.343200 | \n", "
| 1938 | \n", "1.728200 | \n", "
| 1940 | \n", "0.762800 | \n", "
| 1942 | \n", "0.410700 | \n", "
| 1944 | \n", "0.972300 | \n", "
| 1946 | \n", "1.461800 | \n", "
| 1948 | \n", "1.317000 | \n", "
| 1950 | \n", "1.300400 | \n", "
| 1952 | \n", "1.515500 | \n", "
| 1954 | \n", "0.542000 | \n", "
| 1956 | \n", "0.239200 | \n", "
| 1958 | \n", "0.786100 | \n", "
| 1960 | \n", "1.083500 | \n", "
| 1962 | \n", "0.404500 | \n", "
| 1964 | \n", "0.827100 | \n", "
| 1966 | \n", "1.571800 | \n", "
| 1968 | \n", "0.806100 | \n", "
| 1970 | \n", "0.904500 | \n", "
| 1972 | \n", "0.753400 | \n", "
| 1974 | \n", "0.437200 | \n", "
| 1976 | \n", "0.678600 | \n", "
| 1978 | \n", "1.135500 | \n", "
| 1980 | \n", "2.838200 | \n", "
| 1982 | \n", "1.254100 | \n", "
| 1984 | \n", "2.135700 | \n", "
| 1986 | \n", "0.698300 | \n", "
| 1988 | \n", "0.322200 | \n", "
| 1990 | \n", "0.626700 | \n", "
| 1992 | \n", "0.818200 | \n", "
| 1994 | \n", "0.458600 | \n", "
| 1996 | \n", "0.770500 | \n", "
| 1998 | \n", "0.650500 | \n", "
| 2000 | \n", "1.063500 | \n", "
| 2002 | \n", "1.997500 | \n", "
| 2004 | \n", "1.597500 | \n", "
| 2006 | \n", "1.045000 | \n", "
| 2008 | \n", "0.415100 | \n", "
| 2010 | \n", "0.444600 | \n", "
| 2012 | \n", "0.686700 | \n", "
| 2014 | \n", "0.758400 | \n", "
| 2016 | \n", "1.510300 | \n", "
| 2018 | \n", "0.989300 | \n", "
| 2020 | \n", "1.331600 | \n", "
| 2022 | \n", "0.566700 | \n", "
| 2024 | \n", "0.717600 | \n", "
| 2026 | \n", "0.927800 | \n", "
| 2028 | \n", "0.734700 | \n", "
| 2030 | \n", "0.484700 | \n", "
| 2032 | \n", "0.887900 | \n", "
| 2034 | \n", "1.406600 | \n", "
| 2036 | \n", "0.126900 | \n", "
| 2038 | \n", "0.749900 | \n", "
| 2040 | \n", "0.576400 | \n", "
| 2042 | \n", "0.683400 | \n", "
| 2044 | \n", "0.452500 | \n", "
| 2046 | \n", "1.421400 | \n", "
| 2048 | \n", "0.885100 | \n", "
| 2050 | \n", "1.575900 | \n", "
| 2052 | \n", "0.860000 | \n", "
| 2054 | \n", "0.708500 | \n", "
| 2056 | \n", "0.745700 | \n", "
| 2058 | \n", "0.864300 | \n", "
| 2060 | \n", "1.066900 | \n", "
| 2062 | \n", "0.699200 | \n", "
| 2064 | \n", "0.319200 | \n", "
| 2066 | \n", "0.771000 | \n", "
| 2068 | \n", "0.918500 | \n", "
| 2070 | \n", "1.223400 | \n", "
| 2072 | \n", "0.900400 | \n", "
| 2074 | \n", "1.237300 | \n", "
| 2076 | \n", "0.552900 | \n", "
| 2078 | \n", "0.164900 | \n", "
| 2080 | \n", "0.586600 | \n", "
| 2082 | \n", "0.362900 | \n", "
| 2084 | \n", "0.153600 | \n", "
| 2086 | \n", "1.041100 | \n", "
| 2088 | \n", "1.117100 | \n", "
| 2090 | \n", "0.353800 | \n", "
| 2092 | \n", "0.603000 | \n", "
| 2094 | \n", "1.253400 | \n", "
| 2096 | \n", "0.270400 | \n", "
| 2098 | \n", "0.616500 | \n", "
| 2100 | \n", "1.784900 | \n", "
| 2102 | \n", "0.908100 | \n", "
| 2104 | \n", "0.501100 | \n", "
| 2106 | \n", "0.709800 | \n", "
| 2108 | \n", "1.343700 | \n", "
| 2110 | \n", "0.186000 | \n", "
| 2112 | \n", "0.876600 | \n", "
| 2114 | \n", "1.980500 | \n", "
| 2116 | \n", "1.394700 | \n", "
| 2118 | \n", "0.924800 | \n", "
| 2120 | \n", "0.703900 | \n", "
| 2122 | \n", "0.950400 | \n", "
| 2124 | \n", "0.477700 | \n", "
| 2126 | \n", "0.804700 | \n", "
| 2128 | \n", "0.971800 | \n", "
| 2130 | \n", "0.481600 | \n", "
| 2132 | \n", "1.025600 | \n", "
| 2134 | \n", "0.161200 | \n", "
| 2136 | \n", "0.384100 | \n", "
| 2138 | \n", "0.622300 | \n", "
| 2140 | \n", "0.363100 | \n", "
| 2142 | \n", "0.786700 | \n", "
| 2144 | \n", "1.644700 | \n", "
| 2146 | \n", "0.742300 | \n", "
| 2148 | \n", "0.693800 | \n", "
| 2150 | \n", "0.397600 | \n", "
| 2152 | \n", "1.859100 | \n", "
| 2154 | \n", "0.250900 | \n", "
| 2156 | \n", "0.471700 | \n", "
| 2158 | \n", "0.491600 | \n", "
| 2160 | \n", "0.695100 | \n", "
| 2162 | \n", "1.109000 | \n", "
| 2164 | \n", "1.553600 | \n", "
| 2166 | \n", "1.030600 | \n", "
| 2168 | \n", "0.904000 | \n", "
| 2170 | \n", "0.462800 | \n", "
| 2172 | \n", "0.443600 | \n", "
| 2174 | \n", "1.283400 | \n", "
| 2176 | \n", "0.831900 | \n", "
| 2178 | \n", "0.993300 | \n", "
| 2180 | \n", "0.659500 | \n", "
| 2182 | \n", "0.959100 | \n", "
| 2184 | \n", "0.119500 | \n", "
| 2186 | \n", "0.521500 | \n", "
| 2188 | \n", "0.191300 | \n", "
| 2190 | \n", "0.837200 | \n", "
| 2192 | \n", "2.311000 | \n", "
| 2194 | \n", "1.820800 | \n", "
| 2196 | \n", "0.056800 | \n", "
| 2198 | \n", "0.960500 | \n", "
| 2200 | \n", "1.873900 | \n", "
| 2202 | \n", "1.446900 | \n", "
| 2204 | \n", "0.408900 | \n", "
| 2206 | \n", "1.273400 | \n", "
| 2208 | \n", "1.215700 | \n", "
| 2210 | \n", "0.513300 | \n", "
| 2212 | \n", "1.040100 | \n", "
| 2214 | \n", "1.301000 | \n", "
| 2216 | \n", "0.563400 | \n", "
| 2218 | \n", "1.417100 | \n", "
| 2220 | \n", "0.148100 | \n", "
| 2222 | \n", "0.961700 | \n", "
| 2224 | \n", "0.381100 | \n", "
| 2226 | \n", "0.577800 | \n", "
| 2228 | \n", "1.503400 | \n", "
| 2230 | \n", "0.849300 | \n", "
| 2232 | \n", "0.791200 | \n", "
| 2234 | \n", "1.708600 | \n", "
| 2236 | \n", "0.682500 | \n", "
| 2238 | \n", "0.502900 | \n", "
| 2240 | \n", "0.231200 | \n", "
| 2242 | \n", "0.885400 | \n", "
| 2244 | \n", "0.623500 | \n", "
| 2246 | \n", "0.931800 | \n", "
| 2248 | \n", "0.662300 | \n", "
| 2250 | \n", "2.789000 | \n", "
| 2252 | \n", "2.007700 | \n", "
| 2254 | \n", "0.147000 | \n", "
| 2256 | \n", "0.080500 | \n", "
| 2258 | \n", "0.712800 | \n", "
| 2260 | \n", "0.424400 | \n", "
| 2262 | \n", "0.526300 | \n", "
| 2264 | \n", "0.510600 | \n", "
| 2266 | \n", "1.296500 | \n", "
| 2268 | \n", "0.261100 | \n", "
| 2270 | \n", "1.292300 | \n", "
| 2272 | \n", "0.483400 | \n", "
| 2274 | \n", "0.888000 | \n", "
| 2276 | \n", "1.247000 | \n", "
| 2278 | \n", "0.421200 | \n", "
| 2280 | \n", "0.885000 | \n", "
| 2282 | \n", "0.869900 | \n", "
| 2284 | \n", "0.706100 | \n", "
| 2286 | \n", "1.218000 | \n", "
| 2288 | \n", "0.872800 | \n", "
| 2290 | \n", "0.241200 | \n", "
| 2292 | \n", "0.624800 | \n", "
| 2294 | \n", "1.388400 | \n", "
| 2296 | \n", "0.419100 | \n", "
| 2298 | \n", "0.759100 | \n", "
| 2300 | \n", "1.486100 | \n", "
| 2302 | \n", "0.949700 | \n", "
| 2304 | \n", "0.763800 | \n", "
| 2306 | \n", "0.917900 | \n", "
| 2308 | \n", "0.717800 | \n", "
| 2310 | \n", "1.390500 | \n", "
| 2312 | \n", "1.050800 | \n", "
| 2314 | \n", "0.673400 | \n", "
| 2316 | \n", "0.123100 | \n", "
| 2318 | \n", "0.528300 | \n", "
| 2320 | \n", "1.725800 | \n", "
| 2322 | \n", "1.989500 | \n", "
| 2324 | \n", "0.806200 | \n", "
| 2326 | \n", "0.354100 | \n", "
| 2328 | \n", "0.155700 | \n", "
| 2330 | \n", "1.634600 | \n", "
| 2332 | \n", "0.564200 | \n", "
| 2334 | \n", "0.550000 | \n", "
| 2336 | \n", "0.688300 | \n", "
| 2338 | \n", "1.315400 | \n", "
| 2340 | \n", "1.615500 | \n", "
| 2342 | \n", "0.792600 | \n", "
| 2344 | \n", "1.434800 | \n", "
| 2346 | \n", "0.857700 | \n", "
| 2348 | \n", "0.364600 | \n", "
| 2350 | \n", "0.984200 | \n", "
| 2352 | \n", "0.658000 | \n", "
| 2354 | \n", "0.532400 | \n", "
| 2356 | \n", "0.096000 | \n", "
| 2358 | \n", "0.283100 | \n", "
| 2360 | \n", "1.195700 | \n", "
| 2362 | \n", "1.407400 | \n", "
| 2364 | \n", "1.137200 | \n", "
| 2366 | \n", "2.147700 | \n", "
| 2368 | \n", "0.475900 | \n", "
| 2370 | \n", "1.002600 | \n", "
| 2372 | \n", "0.167700 | \n", "
| 2374 | \n", "0.678300 | \n", "
| 2376 | \n", "1.208000 | \n", "
| 2378 | \n", "0.279300 | \n", "
| 2380 | \n", "1.161000 | \n", "
| 2382 | \n", "0.593300 | \n", "
| 2384 | \n", "0.319900 | \n", "
| 2386 | \n", "0.423500 | \n", "
| 2388 | \n", "1.612500 | \n", "
| 2390 | \n", "1.135200 | \n", "
| 2392 | \n", "0.919800 | \n", "
| 2394 | \n", "1.148700 | \n", "
| 2396 | \n", "0.724700 | \n", "
| 2398 | \n", "1.231100 | \n", "
| 2400 | \n", "0.456200 | \n", "
| 2402 | \n", "1.661300 | \n", "
| 2404 | \n", "0.415300 | \n", "
| 2406 | \n", "1.362000 | \n", "
| 2408 | \n", "0.551900 | \n", "
| 2410 | \n", "1.176100 | \n", "
| 2412 | \n", "1.066300 | \n", "
| 2414 | \n", "0.902300 | \n", "
| 2416 | \n", "0.701100 | \n", "
| 2418 | \n", "0.518200 | \n", "
| 2420 | \n", "2.336900 | \n", "
| 2422 | \n", "0.679500 | \n", "
| 2424 | \n", "0.668300 | \n", "
| 2426 | \n", "0.177500 | \n", "
| 2428 | \n", "0.565000 | \n", "
| 2430 | \n", "0.348900 | \n", "
| 2432 | \n", "0.341100 | \n", "
| 2434 | \n", "1.493400 | \n", "
| 2436 | \n", "1.216800 | \n", "
| 2438 | \n", "0.582600 | \n", "
| 2440 | \n", "0.945500 | \n", "
| 2442 | \n", "0.492600 | \n", "
| 2444 | \n", "2.005200 | \n", "
| 2446 | \n", "0.880200 | \n", "
| 2448 | \n", "1.496700 | \n", "
| 2450 | \n", "1.140900 | \n", "
| 2452 | \n", "1.627600 | \n", "
| 2454 | \n", "0.362000 | \n", "
| 2456 | \n", "1.778300 | \n", "
| 2458 | \n", "0.132100 | \n", "
| 2460 | \n", "1.387500 | \n", "
| 2462 | \n", "1.741400 | \n", "
| 2464 | \n", "0.505700 | \n", "
| 2466 | \n", "0.584500 | \n", "
| 2468 | \n", "1.078900 | \n", "
| 2470 | \n", "0.926800 | \n", "
| 2472 | \n", "1.118100 | \n", "
| 2474 | \n", "0.424600 | \n", "
| 2476 | \n", "2.227600 | \n", "
| 2478 | \n", "0.877600 | \n", "
| 2480 | \n", "1.058100 | \n", "
| 2482 | \n", "1.070900 | \n", "
| 2484 | \n", "0.683400 | \n", "
| 2486 | \n", "0.536200 | \n", "
| 2488 | \n", "0.855700 | \n", "
| 2490 | \n", "0.800500 | \n", "
| 2492 | \n", "0.533100 | \n", "
| 2494 | \n", "1.061600 | \n", "
| 2496 | \n", "0.762200 | \n", "
| 2498 | \n", "1.547600 | \n", "
| 2500 | \n", "0.353400 | \n", "
| 2502 | \n", "1.060800 | \n", "
| 2504 | \n", "0.449800 | \n", "
| 2506 | \n", "0.719900 | \n", "
| 2508 | \n", "1.150200 | \n", "
| 2510 | \n", "0.624300 | \n", "
| 2512 | \n", "1.007600 | \n", "
| 2514 | \n", "1.550000 | \n", "
| 2516 | \n", "0.401200 | \n", "
| 2518 | \n", "2.170600 | \n", "
| 2520 | \n", "1.710500 | \n", "
| 2522 | \n", "1.826400 | \n", "
| 2524 | \n", "1.857300 | \n", "
| 2526 | \n", "0.403300 | \n", "
| 2528 | \n", "0.996200 | \n", "
| 2530 | \n", "1.129500 | \n", "
| 2532 | \n", "0.785600 | \n", "
| 2534 | \n", "0.866300 | \n", "
| 2536 | \n", "1.089400 | \n", "
| 2538 | \n", "2.868400 | \n", "
| 2540 | \n", "0.847200 | \n", "
| 2542 | \n", "0.357400 | \n", "
| 2544 | \n", "1.412600 | \n", "
| 2546 | \n", "0.897100 | \n", "
| 2548 | \n", "0.577100 | \n", "
| 2550 | \n", "0.892600 | \n", "
| 2552 | \n", "0.182300 | \n", "
| 2554 | \n", "0.536000 | \n", "
| 2556 | \n", "0.591700 | \n", "
| 2558 | \n", "0.285700 | \n", "
| 2560 | \n", "1.110600 | \n", "
| 2562 | \n", "0.475300 | \n", "
| 2564 | \n", "0.268500 | \n", "
| 2566 | \n", "1.692300 | \n", "
| 2568 | \n", "1.630000 | \n", "
| 2570 | \n", "0.803400 | \n", "
| 2572 | \n", "2.384500 | \n", "
| 2574 | \n", "0.661000 | \n", "
| 2576 | \n", "1.088000 | \n", "
| 2578 | \n", "0.281400 | \n", "
| 2580 | \n", "1.448900 | \n", "
| 2582 | \n", "1.055900 | \n", "
| 2584 | \n", "0.229000 | \n", "
| 2586 | \n", "1.747400 | \n", "
| 2588 | \n", "0.291000 | \n", "
| 2590 | \n", "1.139900 | \n", "
| 2592 | \n", "0.301500 | \n", "
| 2594 | \n", "1.283300 | \n", "
| 2596 | \n", "0.110400 | \n", "
| 2598 | \n", "1.742400 | \n", "
| 2600 | \n", "0.963700 | \n", "
| 2602 | \n", "0.927800 | \n", "
| 2604 | \n", "1.890700 | \n", "
| 2606 | \n", "1.477100 | \n", "
| 2608 | \n", "0.545200 | \n", "
| 2610 | \n", "1.007900 | \n", "
| 2612 | \n", "0.670200 | \n", "
| 2614 | \n", "0.767600 | \n", "
| 2616 | \n", "1.482200 | \n", "
| 2618 | \n", "1.203800 | \n", "
| 2620 | \n", "0.485100 | \n", "
| 2622 | \n", "0.628700 | \n", "
| 2624 | \n", "1.137200 | \n", "
| 2626 | \n", "1.029400 | \n", "
| 2628 | \n", "0.224000 | \n", "
| 2630 | \n", "0.680200 | \n", "
| 2632 | \n", "0.372700 | \n", "
| 2634 | \n", "0.698800 | \n", "
| 2636 | \n", "0.548800 | \n", "
| 2638 | \n", "0.294100 | \n", "
| 2640 | \n", "0.820200 | \n", "
| 2642 | \n", "1.043700 | \n", "
| 2644 | \n", "0.878100 | \n", "
| 2646 | \n", "0.648500 | \n", "
| 2648 | \n", "1.069600 | \n", "
| 2650 | \n", "2.247900 | \n", "
| 2652 | \n", "2.308500 | \n", "
| 2654 | \n", "0.255700 | \n", "
| 2656 | \n", "0.657800 | \n", "
| 2658 | \n", "0.717200 | \n", "
| 2660 | \n", "0.344900 | \n", "
| 2662 | \n", "0.624000 | \n", "
| 2664 | \n", "0.541400 | \n", "
| 2666 | \n", "0.876800 | \n", "
| 2668 | \n", "2.084600 | \n", "
| 2670 | \n", "1.203400 | \n", "
| 2672 | \n", "0.642100 | \n", "
| 2674 | \n", "1.448100 | \n", "
| 2676 | \n", "0.455300 | \n", "
| 2678 | \n", "0.475400 | \n", "
| 2680 | \n", "1.130400 | \n", "
| 2682 | \n", "0.385700 | \n", "
| 2684 | \n", "0.723800 | \n", "
| 2686 | \n", "0.843600 | \n", "
| 2688 | \n", "1.181700 | \n", "
| 2690 | \n", "0.935300 | \n", "
| 2692 | \n", "1.946500 | \n", "
| 2694 | \n", "0.730000 | \n", "
| 2696 | \n", "0.890800 | \n", "
| 2698 | \n", "0.711900 | \n", "
| 2700 | \n", "0.469300 | \n", "
| 2702 | \n", "0.605100 | \n", "
| 2704 | \n", "0.210600 | \n", "
| 2706 | \n", "0.257700 | \n", "
| 2708 | \n", "1.842000 | \n", "
| 2710 | \n", "0.772300 | \n", "
| 2712 | \n", "1.064400 | \n", "
| 2714 | \n", "0.647700 | \n", "
| 2716 | \n", "0.585700 | \n", "
| 2718 | \n", "0.407100 | \n", "
| 2720 | \n", "0.859600 | \n", "
| 2722 | \n", "0.652200 | \n", "
| 2724 | \n", "0.350000 | \n", "
| 2726 | \n", "0.408600 | \n", "
| 2728 | \n", "0.115900 | \n", "
| 2730 | \n", "0.764800 | \n", "
| 2732 | \n", "0.396500 | \n", "
| 2734 | \n", "0.246900 | \n", "
| 2736 | \n", "1.111400 | \n", "
| 2738 | \n", "0.923400 | \n", "
| 2740 | \n", "1.172100 | \n", "
| 2742 | \n", "0.171900 | \n", "
| 2744 | \n", "0.957400 | \n", "
| 2746 | \n", "1.094800 | \n", "
| 2748 | \n", "0.595200 | \n", "
| 2750 | \n", "0.534300 | \n", "
| 2752 | \n", "0.634200 | \n", "
| 2754 | \n", "1.523100 | \n", "
| 2756 | \n", "1.499200 | \n", "
| 2758 | \n", "0.468100 | \n", "
| 2760 | \n", "2.470900 | \n", "
| 2762 | \n", "1.291000 | \n", "
| 2764 | \n", "1.071000 | \n", "
| 2766 | \n", "0.606900 | \n", "
| 2768 | \n", "0.374000 | \n", "
| 2770 | \n", "1.293900 | \n", "
| 2772 | \n", "0.139300 | \n", "
| 2774 | \n", "1.950900 | \n", "
| 2776 | \n", "1.015200 | \n", "
| 2778 | \n", "1.277600 | \n", "
| 2780 | \n", "0.517400 | \n", "
| 2782 | \n", "2.518500 | \n", "
| 2784 | \n", "1.072600 | \n", "
| 2786 | \n", "0.783600 | \n", "
| 2788 | \n", "0.255400 | \n", "
| 2790 | \n", "1.250700 | \n", "
| 2792 | \n", "0.306100 | \n", "
| 2794 | \n", "1.154800 | \n", "
| 2796 | \n", "1.401100 | \n", "
| 2798 | \n", "0.544000 | \n", "
| 2800 | \n", "0.691400 | \n", "
| 2802 | \n", "1.439000 | \n", "
| 2804 | \n", "0.718600 | \n", "
| 2806 | \n", "1.979400 | \n", "
| 2808 | \n", "0.933800 | \n", "
| 2810 | \n", "0.516200 | \n", "
| 2812 | \n", "0.780900 | \n", "
| 2814 | \n", "1.444300 | \n", "
| 2816 | \n", "1.376000 | \n", "
| 2818 | \n", "0.346900 | \n", "
| 2820 | \n", "2.346200 | \n", "
| 2822 | \n", "0.439600 | \n", "
| 2824 | \n", "1.008200 | \n", "
| 2826 | \n", "0.495600 | \n", "
| 2828 | \n", "0.267600 | \n", "
| 2830 | \n", "0.285800 | \n", "
| 2832 | \n", "0.622600 | \n", "
| 2834 | \n", "1.128000 | \n", "
| 2836 | \n", "0.755600 | \n", "
| 2838 | \n", "0.580800 | \n", "
| 2840 | \n", "0.489100 | \n", "
| 2842 | \n", "0.914400 | \n", "
| 2844 | \n", "0.175200 | \n", "
| 2846 | \n", "1.392400 | \n", "
| 2848 | \n", "0.026700 | \n", "
| 2850 | \n", "1.062300 | \n", "
| 2852 | \n", "0.260300 | \n", "
| 2854 | \n", "1.597600 | \n", "
| 2856 | \n", "1.036000 | \n", "
| 2858 | \n", "0.764200 | \n", "
| 2860 | \n", "0.177700 | \n", "
| 2862 | \n", "1.346300 | \n", "
| 2864 | \n", "0.614700 | \n", "
| 2866 | \n", "0.781300 | \n", "
| 2868 | \n", "0.877900 | \n", "
| 2870 | \n", "1.926000 | \n", "
| 2872 | \n", "0.105700 | \n", "
| 2874 | \n", "0.717000 | \n", "
| 2876 | \n", "0.946000 | \n", "
| 2878 | \n", "0.589500 | \n", "
| 2880 | \n", "1.175100 | \n", "
| 2882 | \n", "0.435100 | \n", "
| 2884 | \n", "1.771800 | \n", "
| 2886 | \n", "2.040900 | \n", "
| 2888 | \n", "0.824200 | \n", "
| 2890 | \n", "1.677200 | \n", "
| 2892 | \n", "1.026900 | \n", "
| 2894 | \n", "1.108600 | \n", "
| 2896 | \n", "0.716800 | \n", "
| 2898 | \n", "0.801200 | \n", "
| 2900 | \n", "0.650100 | \n", "
| 2902 | \n", "1.033500 | \n", "
| 2904 | \n", "1.949300 | \n", "
| 2906 | \n", "1.968600 | \n", "
| 2908 | \n", "0.787000 | \n", "
| 2910 | \n", "1.442900 | \n", "
| 2912 | \n", "0.953800 | \n", "
| 2914 | \n", "0.300200 | \n", "
| 2916 | \n", "0.585900 | \n", "
| 2918 | \n", "1.515200 | \n", "
| 2920 | \n", "1.656500 | \n", "
| 2922 | \n", "1.892000 | \n", "
| 2924 | \n", "1.185600 | \n", "
| 2926 | \n", "0.791400 | \n", "
| 2928 | \n", "0.847200 | \n", "
| 2930 | \n", "1.036200 | \n", "
| 2932 | \n", "0.721700 | \n", "
| 2934 | \n", "1.284400 | \n", "
| 2936 | \n", "1.134300 | \n", "
| 2938 | \n", "1.775100 | \n", "
| 2940 | \n", "0.267700 | \n", "
| 2942 | \n", "1.619700 | \n", "
| 2944 | \n", "0.223700 | \n", "
| 2946 | \n", "0.887200 | \n", "
| 2948 | \n", "1.128100 | \n", "
| 2950 | \n", "0.337500 | \n", "
| 2952 | \n", "1.129100 | \n", "
| 2954 | \n", "0.905500 | \n", "
| 2956 | \n", "0.816900 | \n", "
| 2958 | \n", "1.634100 | \n", "
| 2960 | \n", "0.288100 | \n", "
| 2962 | \n", "0.837200 | \n", "
| 2964 | \n", "0.965600 | \n", "
| 2966 | \n", "1.236700 | \n", "
| 2968 | \n", "0.650000 | \n", "
| 2970 | \n", "0.529200 | \n", "
| 2972 | \n", "0.978600 | \n", "
| 2974 | \n", "0.732700 | \n", "
| 2976 | \n", "0.779100 | \n", "
| 2978 | \n", "1.017500 | \n", "
| 2980 | \n", "0.145800 | \n", "
| 2982 | \n", "0.527900 | \n", "
| 2984 | \n", "0.973500 | \n", "
| 2986 | \n", "0.805600 | \n", "
| 2988 | \n", "1.328400 | \n", "
| 2990 | \n", "1.554300 | \n", "
| 2992 | \n", "0.333600 | \n", "
| 2994 | \n", "0.647600 | \n", "
| 2996 | \n", "0.815100 | \n", "
| 2998 | \n", "0.948300 | \n", "
| 3000 | \n", "1.460800 | \n", "
| 3002 | \n", "0.651700 | \n", "
| 3004 | \n", "1.261600 | \n", "
| 3006 | \n", "1.301700 | \n", "
| 3008 | \n", "0.079800 | \n", "
| 3010 | \n", "0.337400 | \n", "
| 3012 | \n", "0.608800 | \n", "
| 3014 | \n", "0.764400 | \n", "
| 3016 | \n", "0.923400 | \n", "
| 3018 | \n", "0.185900 | \n", "
| 3020 | \n", "1.060900 | \n", "
| 3022 | \n", "1.199500 | \n", "
| 3024 | \n", "0.770300 | \n", "
| 3026 | \n", "1.008800 | \n", "
| 3028 | \n", "0.950900 | \n", "
| 3030 | \n", "1.025000 | \n", "
| 3032 | \n", "1.335200 | \n", "
| 3034 | \n", "0.623700 | \n", "
| 3036 | \n", "0.176200 | \n", "
| 3038 | \n", "0.944700 | \n", "
| 3040 | \n", "0.423900 | \n", "
| 3042 | \n", "0.466900 | \n", "
| 3044 | \n", "0.288000 | \n", "
| 3046 | \n", "0.247100 | \n", "
| 3048 | \n", "0.699600 | \n", "
| 3050 | \n", "0.948200 | \n", "
| 3052 | \n", "1.347800 | \n", "
| 3054 | \n", "0.639000 | \n", "
| 3056 | \n", "0.354400 | \n", "
| 3058 | \n", "0.576900 | \n", "
| 3060 | \n", "0.693000 | \n", "
| 3062 | \n", "0.273000 | \n", "
| 3064 | \n", "2.351800 | \n", "
| 3066 | \n", "0.509600 | \n", "
| 3068 | \n", "0.192600 | \n", "
| 3070 | \n", "0.791900 | \n", "
| 3072 | \n", "0.465300 | \n", "
| 3074 | \n", "0.720300 | \n", "
| 3076 | \n", "0.402100 | \n", "
| 3078 | \n", "1.884300 | \n", "
| 3080 | \n", "0.702900 | \n", "
| 3082 | \n", "1.381100 | \n", "
| 3084 | \n", "0.543600 | \n", "
| 3086 | \n", "2.079800 | \n", "
| 3088 | \n", "0.151100 | \n", "
| 3090 | \n", "0.551100 | \n", "
| 3092 | \n", "0.467700 | \n", "
| 3094 | \n", "0.943200 | \n", "
| 3096 | \n", "0.226000 | \n", "
| 3098 | \n", "2.306300 | \n", "
| 3100 | \n", "0.271700 | \n", "
| 3102 | \n", "0.787100 | \n", "
| 3104 | \n", "0.454500 | \n", "
| 3106 | \n", "1.344200 | \n", "
| 3108 | \n", "0.629500 | \n", "
| 3110 | \n", "1.551200 | \n", "
| 3112 | \n", "0.415000 | \n", "
| 3114 | \n", "1.276400 | \n", "
| 3116 | \n", "1.276300 | \n", "
| 3118 | \n", "1.107300 | \n", "
| 3120 | \n", "1.459500 | \n", "
| 3122 | \n", "1.939900 | \n", "
| 3124 | \n", "0.891400 | \n", "
| 3126 | \n", "0.957300 | \n", "
| 3128 | \n", "1.074300 | \n", "
| 3130 | \n", "0.515100 | \n", "
| 3132 | \n", "0.376800 | \n", "
| 3134 | \n", "0.200500 | \n", "
| 3136 | \n", "0.570300 | \n", "
| 3138 | \n", "0.979900 | \n", "
| 3140 | \n", "0.219800 | \n", "
| 3142 | \n", "1.095800 | \n", "
| 3144 | \n", "0.952800 | \n", "
| 3146 | \n", "0.216800 | \n", "
| 3148 | \n", "0.450200 | \n", "
| 3150 | \n", "0.193900 | \n", "
| 3152 | \n", "0.573300 | \n", "
| 3154 | \n", "0.400400 | \n", "
| 3156 | \n", "1.180400 | \n", "
| 3158 | \n", "0.871800 | \n", "
| 3160 | \n", "1.298000 | \n", "
| 3162 | \n", "1.329200 | \n", "
| 3164 | \n", "1.164800 | \n", "
| 3166 | \n", "1.260600 | \n", "
| 3168 | \n", "0.335300 | \n", "
| 3170 | \n", "0.821300 | \n", "
| 3172 | \n", "0.221300 | \n", "
| 3174 | \n", "0.494600 | \n", "
| 3176 | \n", "1.173800 | \n", "
| 3178 | \n", "1.591900 | \n", "
| 3180 | \n", "0.394600 | \n", "
| 3182 | \n", "0.966100 | \n", "
| 3184 | \n", "1.268900 | \n", "
| 3186 | \n", "0.288700 | \n", "
| 3188 | \n", "1.403500 | \n", "
| 3190 | \n", "0.474900 | \n", "
| 3192 | \n", "1.322300 | \n", "
| 3194 | \n", "1.444300 | \n", "
| 3196 | \n", "0.598500 | \n", "
| 3198 | \n", "1.285000 | \n", "
| 3200 | \n", "0.560100 | \n", "
| 3202 | \n", "1.277500 | \n", "
| 3204 | \n", "0.251000 | \n", "
| 3206 | \n", "0.214300 | \n", "
| 3208 | \n", "0.138200 | \n", "
| 3210 | \n", "0.397000 | \n", "
| 3212 | \n", "0.878300 | \n", "
| 3214 | \n", "0.838300 | \n", "
| 3216 | \n", "1.681300 | \n", "
| 3218 | \n", "0.159200 | \n", "
| 3220 | \n", "0.228400 | \n", "
| 3222 | \n", "1.341500 | \n", "
| 3224 | \n", "0.401600 | \n", "
| 3226 | \n", "0.232800 | \n", "
| 3228 | \n", "0.884100 | \n", "
| 3230 | \n", "1.347400 | \n", "
| 3232 | \n", "0.703000 | \n", "
| 3234 | \n", "0.710200 | \n", "
| 3236 | \n", "0.490500 | \n", "
| 3238 | \n", "0.232900 | \n", "
| 3240 | \n", "0.803500 | \n", "
| 3242 | \n", "1.021300 | \n", "
| 3244 | \n", "0.250100 | \n", "
| 3246 | \n", "2.120700 | \n", "
| 3248 | \n", "0.904700 | \n", "
| 3250 | \n", "0.357200 | \n", "
| 3252 | \n", "0.758500 | \n", "
| 3254 | \n", "0.331800 | \n", "
| 3256 | \n", "0.995500 | \n", "
| 3258 | \n", "0.799300 | \n", "
| 3260 | \n", "0.767400 | \n", "
| 3262 | \n", "0.418600 | \n", "
| 3264 | \n", "0.776700 | \n", "
| 3266 | \n", "0.447400 | \n", "
| 3268 | \n", "0.394800 | \n", "
| 3270 | \n", "1.249300 | \n", "
| 3272 | \n", "0.530400 | \n", "
| 3274 | \n", "0.905700 | \n", "
| 3276 | \n", "0.972700 | \n", "
| 3278 | \n", "1.102000 | \n", "
| 3280 | \n", "1.128500 | \n", "
| 3282 | \n", "0.679300 | \n", "
| 3284 | \n", "0.281800 | \n", "
| 3286 | \n", "1.127300 | \n", "
| 3288 | \n", "0.409200 | \n", "
| 3290 | \n", "1.294700 | \n", "
| 3292 | \n", "1.561400 | \n", "
| 3294 | \n", "0.795200 | \n", "
| 3296 | \n", "0.851700 | \n", "
| 3298 | \n", "0.979700 | \n", "
| 3300 | \n", "0.490100 | \n", "
| 3302 | \n", "0.823400 | \n", "
| 3304 | \n", "1.853500 | \n", "
| 3306 | \n", "0.142900 | \n", "
| 3308 | \n", "0.756900 | \n", "
| 3310 | \n", "0.745300 | \n", "
| 3312 | \n", "0.955400 | \n", "
| 3314 | \n", "0.707100 | \n", "
| 3316 | \n", "0.968700 | \n", "
| 3318 | \n", "0.760200 | \n", "
| 3320 | \n", "1.013900 | \n", "
| 3322 | \n", "0.735300 | \n", "
| 3324 | \n", "1.308600 | \n", "
| 3326 | \n", "1.524800 | \n", "
| 3328 | \n", "0.467000 | \n", "
| 3330 | \n", "0.487500 | \n", "
| 3332 | \n", "0.740300 | \n", "
| 3334 | \n", "0.773100 | \n", "
| 3336 | \n", "2.257300 | \n", "
| 3338 | \n", "1.065900 | \n", "
| 3340 | \n", "1.243200 | \n", "
| 3342 | \n", "0.767400 | \n", "
| 3344 | \n", "0.905200 | \n", "
| 3346 | \n", "0.457100 | \n", "
| 3348 | \n", "1.402100 | \n", "
| 3350 | \n", "0.172500 | \n", "
| 3352 | \n", "0.705400 | \n", "
| 3354 | \n", "0.230500 | \n", "
| 3356 | \n", "1.411500 | \n", "
| 3358 | \n", "0.928400 | \n", "
| 3360 | \n", "0.234000 | \n", "
| 3362 | \n", "0.507900 | \n", "
| 3364 | \n", "1.068700 | \n", "
| 3366 | \n", "0.763000 | \n", "
| 3368 | \n", "0.757700 | \n", "
| 3370 | \n", "0.349700 | \n", "
| 3372 | \n", "0.118300 | \n", "
| 3374 | \n", "0.085200 | \n", "
| 3376 | \n", "0.465300 | \n", "
| 3378 | \n", "1.634100 | \n", "
| 3380 | \n", "1.295000 | \n", "
| 3382 | \n", "1.255500 | \n", "
| 3384 | \n", "1.102100 | \n", "
| 3386 | \n", "1.186600 | \n", "
| 3388 | \n", "0.525600 | \n", "
| 3390 | \n", "0.152300 | \n", "
| 3392 | \n", "1.537100 | \n", "
| 3394 | \n", "0.666500 | \n", "
| 3396 | \n", "0.625100 | \n", "
| 3398 | \n", "1.162100 | \n", "
| 3400 | \n", "1.604700 | \n", "
| 3402 | \n", "0.548900 | \n", "
| 3404 | \n", "0.603300 | \n", "
| 3406 | \n", "1.438000 | \n", "
| 3408 | \n", "1.453800 | \n", "
| 3410 | \n", "0.479600 | \n", "
| 3412 | \n", "0.649300 | \n", "
| 3414 | \n", "1.286700 | \n", "
| 3416 | \n", "1.610900 | \n", "
| 3418 | \n", "0.847500 | \n", "
| 3420 | \n", "0.493700 | \n", "
| 3422 | \n", "0.564900 | \n", "
| 3424 | \n", "1.611900 | \n", "
| 3426 | \n", "1.520900 | \n", "
| 3428 | \n", "1.487800 | \n", "
| 3430 | \n", "1.179700 | \n", "
| 3432 | \n", "2.636700 | \n", "
| 3434 | \n", "0.625200 | \n", "
| 3436 | \n", "0.459700 | \n", "
| 3438 | \n", "0.431200 | \n", "
| 3440 | \n", "0.278700 | \n", "
| 3442 | \n", "0.524700 | \n", "
| 3444 | \n", "0.243500 | \n", "
| 3446 | \n", "0.193600 | \n", "
| 3448 | \n", "1.017400 | \n", "
| 3450 | \n", "1.203200 | \n", "
| 3452 | \n", "1.076300 | \n", "
| 3454 | \n", "1.091900 | \n", "
| 3456 | \n", "0.416000 | \n", "
| 3458 | \n", "1.096000 | \n", "
| 3460 | \n", "0.308100 | \n", "
| 3462 | \n", "0.518200 | \n", "
| 3464 | \n", "0.690000 | \n", "
| 3466 | \n", "0.697200 | \n", "
| 3468 | \n", "0.724600 | \n", "
| 3470 | \n", "1.237000 | \n", "
| 3472 | \n", "0.405300 | \n", "
| 3474 | \n", "0.265400 | \n", "
| 3476 | \n", "0.169000 | \n", "
| 3478 | \n", "0.293100 | \n", "
| 3480 | \n", "0.385700 | \n", "
| 3482 | \n", "0.456900 | \n", "
| 3484 | \n", "1.053600 | \n", "
| 3486 | \n", "0.304500 | \n", "
| 3488 | \n", "0.956700 | \n", "
| 3490 | \n", "0.147900 | \n", "
| 3492 | \n", "0.393600 | \n", "
| 3494 | \n", "1.206100 | \n", "
| 3496 | \n", "0.332300 | \n", "
| 3498 | \n", "0.729200 | \n", "
| 3500 | \n", "1.073200 | \n", "
| 3502 | \n", "0.666100 | \n", "
| 3504 | \n", "0.305900 | \n", "
| 3506 | \n", "0.460200 | \n", "
| 3508 | \n", "0.179700 | \n", "
| 3510 | \n", "0.427600 | \n", "
| 3512 | \n", "1.010600 | \n", "
| 3514 | \n", "0.840500 | \n", "
| 3516 | \n", "0.115500 | \n", "
| 3518 | \n", "2.116400 | \n", "
| 3520 | \n", "0.420100 | \n", "
| 3522 | \n", "1.361400 | \n", "
| 3524 | \n", "0.802200 | \n", "
| 3526 | \n", "1.435900 | \n", "
| 3528 | \n", "0.157000 | \n", "
| 3530 | \n", "0.502200 | \n", "
| 3532 | \n", "1.139700 | \n", "
| 3534 | \n", "0.746800 | \n", "
| 3536 | \n", "0.572200 | \n", "
| 3538 | \n", "0.835500 | \n", "
| 3540 | \n", "0.836900 | \n", "
| 3542 | \n", "0.713800 | \n", "
| 3544 | \n", "0.947500 | \n", "
| 3546 | \n", "1.178600 | \n", "
| 3548 | \n", "0.726900 | \n", "
| 3550 | \n", "0.961500 | \n", "
| 3552 | \n", "0.396600 | \n", "
| 3554 | \n", "1.235400 | \n", "
| 3556 | \n", "0.991200 | \n", "
| 3558 | \n", "1.284400 | \n", "
| 3560 | \n", "1.121200 | \n", "
| 3562 | \n", "0.779000 | \n", "
| 3564 | \n", "0.296400 | \n", "
| 3566 | \n", "0.742400 | \n", "
| 3568 | \n", "1.829100 | \n", "
| 3570 | \n", "0.654700 | \n", "
| 3572 | \n", "0.247800 | \n", "
| 3574 | \n", "0.607200 | \n", "
| 3576 | \n", "0.368900 | \n", "
| 3578 | \n", "0.365100 | \n", "
| 3580 | \n", "1.302800 | \n", "
| 3582 | \n", "0.441400 | \n", "
| 3584 | \n", "1.113500 | \n", "
| 3586 | \n", "1.817300 | \n", "
| 3588 | \n", "0.752100 | \n", "
| 3590 | \n", "0.376000 | \n", "
| 3592 | \n", "0.070200 | \n", "
| 3594 | \n", "0.186900 | \n", "
| 3596 | \n", "0.955900 | \n", "
| 3598 | \n", "0.348000 | \n", "
| 3600 | \n", "1.330700 | \n", "
| 3602 | \n", "0.178800 | \n", "
| 3604 | \n", "0.641000 | \n", "
| 3606 | \n", "1.142500 | \n", "
| 3608 | \n", "0.346900 | \n", "
| 3610 | \n", "0.935800 | \n", "
| 3612 | \n", "1.167100 | \n", "
| 3614 | \n", "0.540800 | \n", "
| 3616 | \n", "0.705500 | \n", "
| 3618 | \n", "0.619300 | \n", "
| 3620 | \n", "1.136300 | \n", "
| 3622 | \n", "0.930800 | \n", "
| 3624 | \n", "0.753700 | \n", "
| 3626 | \n", "0.654800 | \n", "
| 3628 | \n", "0.673600 | \n", "
| 3630 | \n", "0.664300 | \n", "
| 3632 | \n", "1.471300 | \n", "
| 3634 | \n", "1.173300 | \n", "
| 3636 | \n", "0.097700 | \n", "
| 3638 | \n", "1.135500 | \n", "
| 3640 | \n", "0.600100 | \n", "
| 3642 | \n", "0.455900 | \n", "
| 3644 | \n", "0.266600 | \n", "
| 3646 | \n", "0.694000 | \n", "
| 3648 | \n", "0.791400 | \n", "
| 3650 | \n", "0.113100 | \n", "
| 3652 | \n", "0.592500 | \n", "
| 3654 | \n", "1.313300 | \n", "
| 3656 | \n", "1.388700 | \n", "
| 3658 | \n", "2.309300 | \n", "
| 3660 | \n", "1.218100 | \n", "
| 3662 | \n", "0.393200 | \n", "
| 3664 | \n", "0.260300 | \n", "
| 3666 | \n", "0.377400 | \n", "
| 3668 | \n", "0.858600 | \n", "
| 3670 | \n", "0.556100 | \n", "
| 3672 | \n", "0.871700 | \n", "
| 3674 | \n", "1.773600 | \n", "
| 3676 | \n", "0.979400 | \n", "
| 3678 | \n", "1.092500 | \n", "
| 3680 | \n", "0.530600 | \n", "
| 3682 | \n", "0.260400 | \n", "
| 3684 | \n", "1.226900 | \n", "
| 3686 | \n", "0.531800 | \n", "
| 3688 | \n", "0.905400 | \n", "
| 3690 | \n", "0.079600 | \n", "
| 3692 | \n", "0.773200 | \n", "
| 3694 | \n", "0.114800 | \n", "
| 3696 | \n", "0.911900 | \n", "
| 3698 | \n", "0.929200 | \n", "
| 3700 | \n", "1.221400 | \n", "
| 3702 | \n", "0.408300 | \n", "
| 3704 | \n", "1.011300 | \n", "
| 3706 | \n", "0.903200 | \n", "
| 3708 | \n", "0.309800 | \n", "
| 3710 | \n", "0.522700 | \n", "
| 3712 | \n", "1.858200 | \n", "
| 3714 | \n", "1.547400 | \n", "
| 3716 | \n", "2.452600 | \n", "
| 3718 | \n", "0.319600 | \n", "
| 3720 | \n", "0.993300 | \n", "
| 3722 | \n", "0.201700 | \n", "
| 3724 | \n", "0.184100 | \n", "
| 3726 | \n", "0.350300 | \n", "
| 3728 | \n", "1.248800 | \n", "
| 3730 | \n", "0.760900 | \n", "
| 3732 | \n", "0.811700 | \n", "
| 3734 | \n", "1.122100 | \n", "
| 3736 | \n", "1.268100 | \n", "
| 3738 | \n", "1.137500 | \n", "
| 3740 | \n", "0.070000 | \n", "
| 3742 | \n", "0.726800 | \n", "
| 3744 | \n", "1.214200 | \n", "
| 3746 | \n", "0.752200 | \n", "
| 3748 | \n", "1.681400 | \n", "
| 3750 | \n", "0.693000 | \n", "
| 3752 | \n", "1.275600 | \n", "
| 3754 | \n", "0.548900 | \n", "
| 3756 | \n", "1.211600 | \n", "
| 3758 | \n", "0.525300 | \n", "
| 3760 | \n", "0.498600 | \n", "
| 3762 | \n", "0.609600 | \n", "
| 3764 | \n", "1.063200 | \n", "
| 3766 | \n", "1.360800 | \n", "
| 3768 | \n", "0.289500 | \n", "
| 3770 | \n", "0.829400 | \n", "
| 3772 | \n", "0.107500 | \n", "
| 3774 | \n", "1.129800 | \n", "
| 3776 | \n", "0.803300 | \n", "
| 3778 | \n", "0.758600 | \n", "
| 3780 | \n", "0.445200 | \n", "
| 3782 | \n", "0.975500 | \n", "
| 3784 | \n", "0.682900 | \n", "
| 3786 | \n", "0.827300 | \n", "
| 3788 | \n", "0.671900 | \n", "
| 3790 | \n", "0.162100 | \n", "
| 3792 | \n", "1.288600 | \n", "
| 3794 | \n", "0.958200 | \n", "
| 3796 | \n", "0.201100 | \n", "
| 3798 | \n", "0.891200 | \n", "
| 3800 | \n", "1.049700 | \n", "
| 3802 | \n", "1.657600 | \n", "
| 3804 | \n", "0.330800 | \n", "
| 3806 | \n", "0.654300 | \n", "
| 3808 | \n", "1.606900 | \n", "
| 3810 | \n", "0.060600 | \n", "
| 3812 | \n", "0.421700 | \n", "
| 3814 | \n", "0.682400 | \n", "
| 3816 | \n", "1.136900 | \n", "
| 3818 | \n", "0.800500 | \n", "
| 3820 | \n", "0.476200 | \n", "
| 3822 | \n", "0.762900 | \n", "
| 3824 | \n", "0.055200 | \n", "
| 3826 | \n", "1.200000 | \n", "
| 3828 | \n", "1.270300 | \n", "
| 3830 | \n", "0.989600 | \n", "
| 3832 | \n", "1.691400 | \n", "
| 3834 | \n", "0.472100 | \n", "
| 3836 | \n", "0.989100 | \n", "
| 3838 | \n", "0.301700 | \n", "
| 3840 | \n", "1.155200 | \n", "
| 3842 | \n", "1.163300 | \n", "
| 3844 | \n", "1.419100 | \n", "
| 3846 | \n", "0.559200 | \n", "
| 3848 | \n", "2.868000 | \n", "
| 3850 | \n", "0.146400 | \n", "
| 3852 | \n", "0.200900 | \n", "
| 3854 | \n", "0.096200 | \n", "
| 3856 | \n", "1.411000 | \n", "
| 3858 | \n", "0.940400 | \n", "
| 3860 | \n", "1.850400 | \n", "
| 3862 | \n", "0.476800 | \n", "
| 3864 | \n", "0.450100 | \n", "
| 3866 | \n", "0.520200 | \n", "
| 3868 | \n", "0.599900 | \n", "
| 3870 | \n", "1.884100 | \n", "
| 3872 | \n", "0.479100 | \n", "
| 3874 | \n", "0.201200 | \n", "
| 3876 | \n", "0.730400 | \n", "
| 3878 | \n", "0.922200 | \n", "
| 3880 | \n", "0.554900 | \n", "
| 3882 | \n", "2.535200 | \n", "
| 3884 | \n", "1.594400 | \n", "
| 3886 | \n", "0.931000 | \n", "
| 3888 | \n", "2.036900 | \n", "
| 3890 | \n", "1.238300 | \n", "
| 3892 | \n", "0.995200 | \n", "
| 3894 | \n", "1.321700 | \n", "
| 3896 | \n", "0.133000 | \n", "
| 3898 | \n", "2.398300 | \n", "
| 3900 | \n", "1.214800 | \n", "
| 3902 | \n", "0.739900 | \n", "
| 3904 | \n", "0.597000 | \n", "
| 3906 | \n", "1.505000 | \n", "
| 3908 | \n", "1.680900 | \n", "
| 3910 | \n", "1.502900 | \n", "
| 3912 | \n", "1.543600 | \n", "
| 3914 | \n", "0.496100 | \n", "
| 3916 | \n", "1.186200 | \n", "
| 3918 | \n", "0.249100 | \n", "
| 3920 | \n", "0.688600 | \n", "
| 3922 | \n", "0.246300 | \n", "
| 3924 | \n", "0.845900 | \n", "
| 3926 | \n", "1.447400 | \n", "
| 3928 | \n", "0.610500 | \n", "
| 3930 | \n", "0.410500 | \n", "
| 3932 | \n", "0.598000 | \n", "
| 3934 | \n", "0.615700 | \n", "
| 3936 | \n", "1.561200 | \n", "
| 3938 | \n", "0.260700 | \n", "
| 3940 | \n", "0.141800 | \n", "
| 3942 | \n", "0.384600 | \n", "
| 3944 | \n", "1.218500 | \n", "
| 3946 | \n", "0.183200 | \n", "
| 3948 | \n", "0.468900 | \n", "
| 3950 | \n", "0.285700 | \n", "
| 3952 | \n", "0.958800 | \n", "
| 3954 | \n", "0.186000 | \n", "
| 3956 | \n", "2.172300 | \n", "
| 3958 | \n", "1.269600 | \n", "
| 3960 | \n", "1.001700 | \n", "
| 3962 | \n", "0.756000 | \n", "
| 3964 | \n", "0.996100 | \n", "
| 3966 | \n", "0.647700 | \n", "
| 3968 | \n", "0.129700 | \n", "
| 3970 | \n", "1.577600 | \n", "
| 3972 | \n", "0.813900 | \n", "
| 3974 | \n", "1.130600 | \n", "
| 3976 | \n", "1.285400 | \n", "
| 3978 | \n", "0.155300 | \n", "
| 3980 | \n", "0.526000 | \n", "
| 3982 | \n", "0.202700 | \n", "
| 3984 | \n", "0.356000 | \n", "
| 3986 | \n", "0.824300 | \n", "
| 3988 | \n", "1.574700 | \n", "
| 3990 | \n", "1.877100 | \n", "
| 3992 | \n", "0.617000 | \n", "
| 3994 | \n", "0.769900 | \n", "
| 3996 | \n", "1.115300 | \n", "
| 3998 | \n", "0.742200 | \n", "
| 4000 | \n", "1.054700 | \n", "
| 4002 | \n", "0.881700 | \n", "
| 4004 | \n", "1.786300 | \n", "
| 4006 | \n", "1.348300 | \n", "
| 4008 | \n", "0.053900 | \n", "
| 4010 | \n", "0.843400 | \n", "
| 4012 | \n", "0.240100 | \n", "
| 4014 | \n", "0.821900 | \n", "
| 4016 | \n", "0.474100 | \n", "
| 4018 | \n", "1.025500 | \n", "
| 4020 | \n", "0.505100 | \n", "
| 4022 | \n", "0.279000 | \n", "
| 4024 | \n", "2.394600 | \n", "
| 4026 | \n", "1.673200 | \n", "
| 4028 | \n", "1.242600 | \n", "
| 4030 | \n", "0.598100 | \n", "
| 4032 | \n", "0.729500 | \n", "
| 4034 | \n", "0.967000 | \n", "
| 4036 | \n", "0.770000 | \n", "
| 4038 | \n", "0.969800 | \n", "
| 4040 | \n", "1.687100 | \n", "
| 4042 | \n", "0.952200 | \n", "
| 4044 | \n", "1.001400 | \n", "
| 4046 | \n", "0.291600 | \n", "
| 4048 | \n", "0.499700 | \n", "
| 4050 | \n", "1.502200 | \n", "
| 4052 | \n", "1.153700 | \n", "
| 4054 | \n", "1.894900 | \n", "
| 4056 | \n", "0.509400 | \n", "
| 4058 | \n", "2.145400 | \n", "
| 4060 | \n", "0.055000 | \n", "
| 4062 | \n", "0.346700 | \n", "
| 4064 | \n", "0.730900 | \n", "
| 4066 | \n", "0.804800 | \n", "
| 4068 | \n", "0.635100 | \n", "
| 4070 | \n", "1.658500 | \n", "
| 4072 | \n", "0.121700 | \n", "
| 4074 | \n", "1.178600 | \n", "
| 4076 | \n", "2.197700 | \n", "
| 4078 | \n", "0.404700 | \n", "
| 4080 | \n", "0.728000 | \n", "
| 4082 | \n", "0.234200 | \n", "
| 4084 | \n", "0.178500 | \n", "
| 4086 | \n", "1.347100 | \n", "
| 4088 | \n", "0.450700 | \n", "
| 4090 | \n", "0.160800 | \n", "
| 4092 | \n", "1.519900 | \n", "
| 4094 | \n", "1.543100 | \n", "
| 4096 | \n", "0.819900 | \n", "
| 4098 | \n", "0.477400 | \n", "
| 4100 | \n", "0.296400 | \n", "
| 4102 | \n", "0.584800 | \n", "
| 4104 | \n", "0.797900 | \n", "
| 4106 | \n", "0.916000 | \n", "
| 4108 | \n", "0.491100 | \n", "
| 4110 | \n", "1.201900 | \n", "
| 4112 | \n", "0.539500 | \n", "
| 4114 | \n", "0.277200 | \n", "
| 4116 | \n", "0.351100 | \n", "
| 4118 | \n", "0.011800 | \n", "
| 4120 | \n", "0.974700 | \n", "
| 4122 | \n", "0.130500 | \n", "
| 4124 | \n", "2.027100 | \n", "
| 4126 | \n", "0.186000 | \n", "
| 4128 | \n", "0.187400 | \n", "
| 4130 | \n", "0.822500 | \n", "
| 4132 | \n", "0.197900 | \n", "
| 4134 | \n", "0.222800 | \n", "
| 4136 | \n", "1.495500 | \n", "
| 4138 | \n", "1.747400 | \n", "
| 4140 | \n", "1.325700 | \n", "
| 4142 | \n", "0.579400 | \n", "
| 4144 | \n", "1.661000 | \n", "
| 4146 | \n", "0.494000 | \n", "
| 4148 | \n", "1.054800 | \n", "
| 4150 | \n", "0.971600 | \n", "
| 4152 | \n", "1.554200 | \n", "
| 4154 | \n", "0.027700 | \n", "
| 4156 | \n", "1.305800 | \n", "
| 4158 | \n", "0.681400 | \n", "
| 4160 | \n", "0.039400 | \n", "
| 4162 | \n", "1.437100 | \n", "
| 4164 | \n", "2.048500 | \n", "
| 4166 | \n", "0.624700 | \n", "
| 4168 | \n", "1.088000 | \n", "
| 4170 | \n", "0.311200 | \n", "
| 4172 | \n", "0.284200 | \n", "
| 4174 | \n", "0.772600 | \n", "
| 4176 | \n", "0.167300 | \n", "
| 4178 | \n", "0.579100 | \n", "
| 4180 | \n", "0.648900 | \n", "
| 4182 | \n", "1.183400 | \n", "
| 4184 | \n", "0.103000 | \n", "
| 4186 | \n", "0.415500 | \n", "
| 4188 | \n", "0.506200 | \n", "
| 4190 | \n", "0.807800 | \n", "
| 4192 | \n", "0.472100 | \n", "
| 4194 | \n", "1.469200 | \n", "
| 4196 | \n", "0.326300 | \n", "
| 4198 | \n", "0.482500 | \n", "
| 4200 | \n", "0.519100 | \n", "
| 4202 | \n", "1.132500 | \n", "
| 4204 | \n", "1.024100 | \n", "
| 4206 | \n", "0.593500 | \n", "
| 4208 | \n", "0.500900 | \n", "
| 4210 | \n", "0.221900 | \n", "
| 4212 | \n", "1.760200 | \n", "
| 4214 | \n", "1.100100 | \n", "
| 4216 | \n", "0.760100 | \n", "
| 4218 | \n", "0.442800 | \n", "
| 4220 | \n", "1.613600 | \n", "
| 4222 | \n", "0.917300 | \n", "
| 4224 | \n", "0.919700 | \n", "
| 4226 | \n", "0.781100 | \n", "
| 4228 | \n", "2.538900 | \n", "
| 4230 | \n", "0.095100 | \n", "
| 4232 | \n", "0.332800 | \n", "
| 4234 | \n", "0.752200 | \n", "
| 4236 | \n", "0.827400 | \n", "
| 4238 | \n", "0.581300 | \n", "
| 4240 | \n", "1.032700 | \n", "
| 4242 | \n", "0.799600 | \n", "
| 4244 | \n", "0.456600 | \n", "
| 4246 | \n", "0.657000 | \n", "
| 4248 | \n", "0.857300 | \n", "
| 4250 | \n", "0.818500 | \n", "
| 4252 | \n", "0.781900 | \n", "
| 4254 | \n", "1.428000 | \n", "
| 4256 | \n", "0.823200 | \n", "
| 4258 | \n", "0.679100 | \n", "
| 4260 | \n", "0.305900 | \n", "
| 4262 | \n", "0.144800 | \n", "
| 4264 | \n", "0.273000 | \n", "
| 4266 | \n", "0.083900 | \n", "
| 4268 | \n", "0.620900 | \n", "
| 4270 | \n", "1.536300 | \n", "
| 4272 | \n", "1.624600 | \n", "
| 4274 | \n", "1.556400 | \n", "
| 4276 | \n", "0.357000 | \n", "
| 4278 | \n", "0.934700 | \n", "
| 4280 | \n", "1.472900 | \n", "
| 4282 | \n", "1.146600 | \n", "
| 4284 | \n", "0.859100 | \n", "
| 4286 | \n", "2.764100 | \n", "
| 4288 | \n", "0.749200 | \n", "
| 4290 | \n", "0.778700 | \n", "
| 4292 | \n", "1.495700 | \n", "
| 4294 | \n", "0.315900 | \n", "
| 4296 | \n", "1.218500 | \n", "
| 4298 | \n", "0.513400 | \n", "
| 4300 | \n", "2.274200 | \n", "
| 4302 | \n", "0.309600 | \n", "
| 4304 | \n", "1.879900 | \n", "
| 4306 | \n", "1.370100 | \n", "
| 4308 | \n", "0.106500 | \n", "
| 4310 | \n", "0.237500 | \n", "
| 4312 | \n", "0.685600 | \n", "
| 4314 | \n", "1.215100 | \n", "
| 4316 | \n", "1.811700 | \n", "
| 4318 | \n", "0.443500 | \n", "
| 4320 | \n", "1.462700 | \n", "
| 4322 | \n", "2.466000 | \n", "
| 4324 | \n", "0.112200 | \n", "
| 4326 | \n", "0.934500 | \n", "
| 4328 | \n", "1.060200 | \n", "
| 4330 | \n", "1.204200 | \n", "
| 4332 | \n", "1.320400 | \n", "
| 4334 | \n", "0.730700 | \n", "
| 4336 | \n", "1.705400 | \n", "
| 4338 | \n", "0.270700 | \n", "
| 4340 | \n", "0.885100 | \n", "
| 4342 | \n", "1.814100 | \n", "
| 4344 | \n", "0.948100 | \n", "
| 4346 | \n", "0.223300 | \n", "
| 4348 | \n", "2.090200 | \n", "
| 4350 | \n", "0.294300 | \n", "
| 4352 | \n", "0.507800 | \n", "
| 4354 | \n", "1.077100 | \n", "
| 4356 | \n", "0.116500 | \n", "
| 4358 | \n", "0.819500 | \n", "
| 4360 | \n", "1.938200 | \n", "
| 4362 | \n", "0.508900 | \n", "
| 4364 | \n", "1.557000 | \n", "
| 4366 | \n", "0.548900 | \n", "
| 4368 | \n", "0.323900 | \n", "
| 4370 | \n", "0.217200 | \n", "
| 4372 | \n", "0.477900 | \n", "
| 4374 | \n", "0.786800 | \n", "
| 4376 | \n", "1.609000 | \n", "
| 4378 | \n", "0.307900 | \n", "
| 4380 | \n", "0.902000 | \n", "
| 4382 | \n", "0.510600 | \n", "
| 4384 | \n", "2.558900 | \n", "
| 4386 | \n", "0.319000 | \n", "
| 4388 | \n", "0.398500 | \n", "
| 4390 | \n", "0.169000 | \n", "
| 4392 | \n", "0.785400 | \n", "
| 4394 | \n", "2.811200 | \n", "
| 4396 | \n", "1.999100 | \n", "
| 4398 | \n", "0.801300 | \n", "
| 4400 | \n", "0.920500 | \n", "
| 4402 | \n", "0.505500 | \n", "
| 4404 | \n", "0.403500 | \n", "
| 4406 | \n", "0.288200 | \n", "
| 4408 | \n", "0.909500 | \n", "
| 4410 | \n", "1.561800 | \n", "
| 4412 | \n", "0.107600 | \n", "
| 4414 | \n", "0.247200 | \n", "
| 4416 | \n", "0.256200 | \n", "
| 4418 | \n", "0.211100 | \n", "
| 4420 | \n", "0.667200 | \n", "
| 4422 | \n", "0.752600 | \n", "
| 4424 | \n", "0.311900 | \n", "
| 4426 | \n", "0.457300 | \n", "
| 4428 | \n", "0.352500 | \n", "
| 4430 | \n", "1.172800 | \n", "
| 4432 | \n", "0.767700 | \n", "
| 4434 | \n", "0.282300 | \n", "
| 4436 | \n", "0.423800 | \n", "
| 4438 | \n", "0.418200 | \n", "
| 4440 | \n", "0.196400 | \n", "
| 4442 | \n", "0.447600 | \n", "
| 4444 | \n", "1.221900 | \n", "
| 4446 | \n", "0.249400 | \n", "
| 4448 | \n", "0.925800 | \n", "
| 4450 | \n", "0.134600 | \n", "
| 4452 | \n", "0.700500 | \n", "
| 4454 | \n", "0.181000 | \n", "
| 4456 | \n", "0.383500 | \n", "
| 4458 | \n", "1.843900 | \n", "
| 4460 | \n", "0.566400 | \n", "
| 4462 | \n", "0.165000 | \n", "
| 4464 | \n", "0.916700 | \n", "
| 4466 | \n", "1.327900 | \n", "
| 4468 | \n", "0.992200 | \n", "
| 4470 | \n", "0.378800 | \n", "
| 4472 | \n", "0.223100 | \n", "
| 4474 | \n", "0.017500 | \n", "
| 4476 | \n", "0.348200 | \n", "
| 4478 | \n", "0.464800 | \n", "
| 4480 | \n", "0.336600 | \n", "
| 4482 | \n", "0.452600 | \n", "
| 4484 | \n", "0.499800 | \n", "
| 4486 | \n", "1.681200 | \n", "
| 4488 | \n", "0.089100 | \n", "
| 4490 | \n", "0.720400 | \n", "
| 4492 | \n", "0.218200 | \n", "
| 4494 | \n", "0.134200 | \n", "
| 4496 | \n", "0.438500 | \n", "
| 4498 | \n", "0.128700 | \n", "
| 4500 | \n", "0.990300 | \n", "
| 4502 | \n", "1.808300 | \n", "
| 4504 | \n", "0.238300 | \n", "
| 4506 | \n", "2.768400 | \n", "
| 4508 | \n", "0.993500 | \n", "
| 4510 | \n", "1.286300 | \n", "
| 4512 | \n", "0.744700 | \n", "
| 4514 | \n", "1.741800 | \n", "
| 4516 | \n", "0.292900 | \n", "
| 4518 | \n", "1.422800 | \n", "
| 4520 | \n", "2.184800 | \n", "
| 4522 | \n", "0.891100 | \n", "
| 4524 | \n", "0.447100 | \n", "
| 4526 | \n", "1.035000 | \n", "
| 4528 | \n", "0.260500 | \n", "
| 4530 | \n", "0.184500 | \n", "
| 4532 | \n", "1.743800 | \n", "
| 4534 | \n", "1.924300 | \n", "
| 4536 | \n", "1.428300 | \n", "
| 4538 | \n", "0.299100 | \n", "
| 4540 | \n", "0.587000 | \n", "
| 4542 | \n", "0.860700 | \n", "
| 4544 | \n", "0.805500 | \n", "
| 4546 | \n", "0.493500 | \n", "
| 4548 | \n", "0.738400 | \n", "
| 4550 | \n", "0.419100 | \n", "
| 4552 | \n", "2.008500 | \n", "
| 4554 | \n", "0.137000 | \n", "
| 4556 | \n", "0.936700 | \n", "
| 4558 | \n", "0.872300 | \n", "
| 4560 | \n", "0.041300 | \n", "
| 4562 | \n", "0.691500 | \n", "
| 4564 | \n", "0.277100 | \n", "
| 4566 | \n", "0.577600 | \n", "
| 4568 | \n", "0.730700 | \n", "
| 4570 | \n", "0.135200 | \n", "
| 4572 | \n", "0.028600 | \n", "
| 4574 | \n", "1.193200 | \n", "
| 4576 | \n", "1.014100 | \n", "
| 4578 | \n", "0.460200 | \n", "
| 4580 | \n", "2.397300 | \n", "
| 4582 | \n", "1.251500 | \n", "
| 4584 | \n", "1.870000 | \n", "
| 4586 | \n", "0.436600 | \n", "
| 4588 | \n", "0.891600 | \n", "
| 4590 | \n", "0.139800 | \n", "
| 4592 | \n", "0.743300 | \n", "
| 4594 | \n", "0.502500 | \n", "
| 4596 | \n", "0.888300 | \n", "
| 4598 | \n", "0.937700 | \n", "
| 4600 | \n", "1.129200 | \n", "
| 4602 | \n", "2.221700 | \n", "
| 4604 | \n", "1.277500 | \n", "
| 4606 | \n", "1.990300 | \n", "
| 4608 | \n", "1.274600 | \n", "
| 4610 | \n", "1.234700 | \n", "
| 4612 | \n", "1.294100 | \n", "
| 4614 | \n", "1.803000 | \n", "
| 4616 | \n", "0.085000 | \n", "
| 4618 | \n", "0.186300 | \n", "
| 4620 | \n", "0.846600 | \n", "
| 4622 | \n", "0.149200 | \n", "
| 4624 | \n", "2.590000 | \n", "
| 4626 | \n", "0.368900 | \n", "
| 4628 | \n", "0.771600 | \n", "
| 4630 | \n", "0.320000 | \n", "
| 4632 | \n", "0.975600 | \n", "
| 4634 | \n", "0.657100 | \n", "
| 4636 | \n", "0.151700 | \n", "
| 4638 | \n", "2.204500 | \n", "
| 4640 | \n", "0.560900 | \n", "
| 4642 | \n", "0.879100 | \n", "
| 4644 | \n", "0.927300 | \n", "
| 4646 | \n", "0.341700 | \n", "
| 4648 | \n", "0.716900 | \n", "
| 4650 | \n", "0.469800 | \n", "
| 4652 | \n", "0.204300 | \n", "
| 4654 | \n", "0.314500 | \n", "
| 4656 | \n", "0.984800 | \n", "
| 4658 | \n", "0.484100 | \n", "
| 4660 | \n", "1.758600 | \n", "
| 4662 | \n", "0.419400 | \n", "
| 4664 | \n", "0.314100 | \n", "
| 4666 | \n", "0.240200 | \n", "
| 4668 | \n", "0.958600 | \n", "
| 4670 | \n", "0.915000 | \n", "
| 4672 | \n", "0.362100 | \n", "
| 4674 | \n", "0.840500 | \n", "
| 4676 | \n", "0.169200 | \n", "
| 4678 | \n", "0.267200 | \n", "
| 4680 | \n", "0.252200 | \n", "
| 4682 | \n", "0.672900 | \n", "
| 4684 | \n", "0.233900 | \n", "
| 4686 | \n", "1.105900 | \n", "
| 4688 | \n", "1.188600 | \n", "
| 4690 | \n", "1.877300 | \n", "
| 4692 | \n", "1.045400 | \n", "
| 4694 | \n", "0.979500 | \n", "
| 4696 | \n", "0.530800 | \n", "
| 4698 | \n", "1.584700 | \n", "
| 4700 | \n", "0.129400 | \n", "
| 4702 | \n", "0.072700 | \n", "
| 4704 | \n", "0.861500 | \n", "
| 4706 | \n", "1.088200 | \n", "
| 4708 | \n", "1.254200 | \n", "
| 4710 | \n", "1.946300 | \n", "
| 4712 | \n", "2.351200 | \n", "
| 4714 | \n", "2.187600 | \n", "
| 4716 | \n", "0.632900 | \n", "
| 4718 | \n", "0.739200 | \n", "
| 4720 | \n", "1.475200 | \n", "
| 4722 | \n", "0.938900 | \n", "
| 4724 | \n", "0.834000 | \n", "
| 4726 | \n", "2.086600 | \n", "
| 4728 | \n", "1.896800 | \n", "
| 4730 | \n", "0.852600 | \n", "
| 4732 | \n", "0.295400 | \n", "
| 4734 | \n", "0.745200 | \n", "
| 4736 | \n", "0.507500 | \n", "
| 4738 | \n", "0.472900 | \n", "
| 4740 | \n", "0.037600 | \n", "
| 4742 | \n", "1.075900 | \n", "
| 4744 | \n", "0.112500 | \n", "
| 4746 | \n", "1.221900 | \n", "
| 4748 | \n", "0.664600 | \n", "
| 4750 | \n", "0.368200 | \n", "
| 4752 | \n", "0.069700 | \n", "
| 4754 | \n", "1.524000 | \n", "
| 4756 | \n", "1.806700 | \n", "
| 4758 | \n", "1.395900 | \n", "
| 4760 | \n", "1.115700 | \n", "
| 4762 | \n", "1.329000 | \n", "
| 4764 | \n", "0.875500 | \n", "
| 4766 | \n", "1.280400 | \n", "
| 4768 | \n", "0.765000 | \n", "
| 4770 | \n", "1.167700 | \n", "
| 4772 | \n", "0.671600 | \n", "
| 4774 | \n", "0.485900 | \n", "
| 4776 | \n", "1.632600 | \n", "
| 4778 | \n", "0.322800 | \n", "
| 4780 | \n", "0.363000 | \n", "
| 4782 | \n", "0.140100 | \n", "
| 4784 | \n", "0.905100 | \n", "
| 4786 | \n", "0.964400 | \n", "
| 4788 | \n", "0.738000 | \n", "
| 4790 | \n", "0.921100 | \n", "
| 4792 | \n", "0.798300 | \n", "
| 4794 | \n", "0.355100 | \n", "
| 4796 | \n", "0.061800 | \n", "
| 4798 | \n", "0.097400 | \n", "
| 4800 | \n", "0.751500 | \n", "
| 4802 | \n", "1.543300 | \n", "
| 4804 | \n", "0.720900 | \n", "
| 4806 | \n", "0.996300 | \n", "
| 4808 | \n", "0.648700 | \n", "
| 4810 | \n", "2.104300 | \n", "
| 4812 | \n", "1.341200 | \n", "
| 4814 | \n", "2.951800 | \n", "
| 4816 | \n", "2.047500 | \n", "
| 4818 | \n", "0.066800 | \n", "
| 4820 | \n", "0.063400 | \n", "
| 4822 | \n", "0.251100 | \n", "
| 4824 | \n", "1.455200 | \n", "
| 4826 | \n", "1.833600 | \n", "
| 4828 | \n", "0.319800 | \n", "
| 4830 | \n", "0.961700 | \n", "
| 4832 | \n", "0.264900 | \n", "
| 4834 | \n", "3.011600 | \n", "
| 4836 | \n", "1.103200 | \n", "
| 4838 | \n", "1.395400 | \n", "
| 4840 | \n", "0.470100 | \n", "
| 4842 | \n", "0.562000 | \n", "
| 4844 | \n", "1.021300 | \n", "
| 4846 | \n", "0.668700 | \n", "
| 4848 | \n", "0.197700 | \n", "
| 4850 | \n", "0.583900 | \n", "
| 4852 | \n", "1.323900 | \n", "
| 4854 | \n", "0.564900 | \n", "
| 4856 | \n", "0.076100 | \n", "
| 4858 | \n", "0.474400 | \n", "
| 4860 | \n", "0.871800 | \n", "
| 4862 | \n", "1.870100 | \n", "
| 4864 | \n", "1.737900 | \n", "
| 4866 | \n", "1.317500 | \n", "
| 4868 | \n", "0.581700 | \n", "
| 4870 | \n", "0.974400 | \n", "
| 4872 | \n", "0.961300 | \n", "
| 4874 | \n", "0.110000 | \n", "
| 4876 | \n", "0.781200 | \n", "
| 4878 | \n", "0.940300 | \n", "
| 4880 | \n", "1.186700 | \n", "
| 4882 | \n", "1.396900 | \n", "
| 4884 | \n", "1.685200 | \n", "
| 4886 | \n", "0.428600 | \n", "
| 4888 | \n", "0.466400 | \n", "
| 4890 | \n", "1.438300 | \n", "
| 4892 | \n", "0.414400 | \n", "
| 4894 | \n", "0.353000 | \n", "
| 4896 | \n", "0.272500 | \n", "
| 4898 | \n", "0.863100 | \n", "
| 4900 | \n", "0.591900 | \n", "
| 4902 | \n", "0.383000 | \n", "
| 4904 | \n", "1.179800 | \n", "
| 4906 | \n", "1.410700 | \n", "
| 4908 | \n", "1.536000 | \n", "
| 4910 | \n", "1.930900 | \n", "
| 4912 | \n", "0.458400 | \n", "
| 4914 | \n", "1.828400 | \n", "
| 4916 | \n", "1.157100 | \n", "
| 4918 | \n", "0.171400 | \n", "
| 4920 | \n", "0.090000 | \n", "
| 4922 | \n", "0.220500 | \n", "
| 4924 | \n", "1.172500 | \n", "
| 4926 | \n", "1.106700 | \n", "
| 4928 | \n", "0.279100 | \n", "
| 4930 | \n", "0.759800 | \n", "
| 4932 | \n", "1.068100 | \n", "
| 4934 | \n", "0.689300 | \n", "
| 4936 | \n", "0.817600 | \n", "
| 4938 | \n", "0.380900 | \n", "
| 4940 | \n", "1.178700 | \n", "
| 4942 | \n", "0.963200 | \n", "
| 4944 | \n", "0.228200 | \n", "
| 4946 | \n", "0.296100 | \n", "
| 4948 | \n", "0.801800 | \n", "
| 4950 | \n", "1.440700 | \n", "
| 4952 | \n", "0.113500 | \n", "
| 4954 | \n", "0.349100 | \n", "
| 4956 | \n", "0.261700 | \n", "
| 4958 | \n", "0.511500 | \n", "
| 4960 | \n", "2.246400 | \n", "
| 4962 | \n", "0.999700 | \n", "
| 4964 | \n", "1.388600 | \n", "
| 4966 | \n", "1.226500 | \n", "
| 4968 | \n", "1.098000 | \n", "
| 4970 | \n", "0.396100 | \n", "
| 4972 | \n", "0.420800 | \n", "
| 4974 | \n", "0.345100 | \n", "
| 4976 | \n", "0.666300 | \n", "
| 4978 | \n", "2.183600 | \n", "
| 4980 | \n", "1.067400 | \n", "
| 4982 | \n", "2.100500 | \n", "
| 4984 | \n", "0.769100 | \n", "
| 4986 | \n", "0.105000 | \n", "
| 4988 | \n", "1.273500 | \n", "
| 4990 | \n", "0.790400 | \n", "
| 4992 | \n", "1.570600 | \n", "
| 4994 | \n", "0.969200 | \n", "
| 4996 | \n", "0.170900 | \n", "
| 4998 | \n", "1.205500 | \n", "
| 5000 | \n", "0.780000 | \n", "
| 5002 | \n", "1.377600 | \n", "
| 5004 | \n", "0.727700 | \n", "
| 5006 | \n", "1.210000 | \n", "
| 5008 | \n", "1.419200 | \n", "
| 5010 | \n", "1.142300 | \n", "
| 5012 | \n", "0.662000 | \n", "
| 5014 | \n", "1.063100 | \n", "
| 5016 | \n", "2.092000 | \n", "
| 5018 | \n", "1.628900 | \n", "
| 5020 | \n", "0.061700 | \n", "
| 5022 | \n", "0.603100 | \n", "
| 5024 | \n", "1.186100 | \n", "
| 5026 | \n", "1.192600 | \n", "
| 5028 | \n", "0.990000 | \n", "
| 5030 | \n", "0.711800 | \n", "
| 5032 | \n", "1.370200 | \n", "
| 5034 | \n", "0.421900 | \n", "
| 5036 | \n", "1.273200 | \n", "
| 5038 | \n", "1.211200 | \n", "
| 5040 | \n", "0.335100 | \n", "
| 5042 | \n", "0.938400 | \n", "
| 5044 | \n", "1.002400 | \n", "
| 5046 | \n", "0.777000 | \n", "
| 5048 | \n", "0.113600 | \n", "
| 5050 | \n", "1.099200 | \n", "
| 5052 | \n", "1.872800 | \n", "
| 5054 | \n", "0.332400 | \n", "
| 5056 | \n", "0.238900 | \n", "
| 5058 | \n", "0.787600 | \n", "
| 5060 | \n", "0.391400 | \n", "
| 5062 | \n", "0.545000 | \n", "
| 5064 | \n", "0.892600 | \n", "
| 5066 | \n", "0.239700 | \n", "
| 5068 | \n", "0.755900 | \n", "
| 5070 | \n", "1.211300 | \n", "
| 5072 | \n", "0.437500 | \n", "
| 5074 | \n", "1.957000 | \n", "
| 5076 | \n", "0.110000 | \n", "
| 5078 | \n", "2.058200 | \n", "
| 5080 | \n", "0.709800 | \n", "
| 5082 | \n", "1.277600 | \n", "
| 5084 | \n", "0.731000 | \n", "
| 5086 | \n", "0.796800 | \n", "
| 5088 | \n", "0.740900 | \n", "
| 5090 | \n", "0.835700 | \n", "
| 5092 | \n", "0.371500 | \n", "
| 5094 | \n", "0.599500 | \n", "
| 5096 | \n", "0.051700 | \n", "
| 5098 | \n", "0.869500 | \n", "
| 5100 | \n", "2.953600 | \n", "
| 5102 | \n", "1.096000 | \n", "
| 5104 | \n", "0.561600 | \n", "
| 5106 | \n", "0.209500 | \n", "
| 5108 | \n", "1.034600 | \n", "
| 5110 | \n", "0.428400 | \n", "
| 5112 | \n", "1.470100 | \n", "
| 5114 | \n", "0.769700 | \n", "
| 5116 | \n", "0.172300 | \n", "
| 5118 | \n", "0.433100 | \n", "
| 5120 | \n", "0.446400 | \n", "
| 5122 | \n", "0.194200 | \n", "
| 5124 | \n", "1.374800 | \n", "
| 5126 | \n", "2.130900 | \n", "
| 5128 | \n", "0.814000 | \n", "
| 5130 | \n", "0.094000 | \n", "
| 5132 | \n", "0.974000 | \n", "
| 5134 | \n", "1.123800 | \n", "
| 5136 | \n", "1.810000 | \n", "
| 5138 | \n", "1.954000 | \n", "
| 5140 | \n", "0.874100 | \n", "
| 5142 | \n", "0.391900 | \n", "
| 5144 | \n", "1.399500 | \n", "
| 5146 | \n", "0.792900 | \n", "
| 5148 | \n", "0.690600 | \n", "
| 5150 | \n", "0.924000 | \n", "
| 5152 | \n", "1.479800 | \n", "
| 5154 | \n", "0.967900 | \n", "
| 5156 | \n", "1.349300 | \n", "
| 5158 | \n", "0.090400 | \n", "
| 5160 | \n", "0.286400 | \n", "
| 5162 | \n", "0.166400 | \n", "
| 5164 | \n", "1.080700 | \n", "
| 5166 | \n", "0.262500 | \n", "
| 5168 | \n", "1.376900 | \n", "
| 5170 | \n", "1.075200 | \n", "
| 5172 | \n", "0.715600 | \n", "
| 5174 | \n", "0.323800 | \n", "
| 5176 | \n", "1.176800 | \n", "
| 5178 | \n", "1.176800 | \n", "
| 5180 | \n", "0.723700 | \n", "
| 5182 | \n", "0.424700 | \n", "
| 5184 | \n", "0.930500 | \n", "
| 5186 | \n", "1.607600 | \n", "
| 5188 | \n", "0.160100 | \n", "
| 5190 | \n", "0.151200 | \n", "
| 5192 | \n", "1.436400 | \n", "
| 5194 | \n", "0.108800 | \n", "
| 5196 | \n", "1.118300 | \n", "
| 5198 | \n", "0.533700 | \n", "
| 5200 | \n", "0.864700 | \n", "
| 5202 | \n", "0.855900 | \n", "
| 5204 | \n", "0.604900 | \n", "
| 5206 | \n", "0.929400 | \n", "
| 5208 | \n", "0.582200 | \n", "
| 5210 | \n", "0.714100 | \n", "
| 5212 | \n", "1.098600 | \n", "
| 5214 | \n", "0.791200 | \n", "
| 5216 | \n", "0.239900 | \n", "
| 5218 | \n", "1.343000 | \n", "
| 5220 | \n", "0.108800 | \n", "
| 5222 | \n", "1.034500 | \n", "
| 5224 | \n", "0.277800 | \n", "
| 5226 | \n", "1.407500 | \n", "
| 5228 | \n", "1.204400 | \n", "
| 5230 | \n", "0.646500 | \n", "
| 5232 | \n", "0.438200 | \n", "
| 5234 | \n", "0.066000 | \n", "
| 5236 | \n", "0.433300 | \n", "
| 5238 | \n", "1.398700 | \n", "
| 5240 | \n", "0.130400 | \n", "
| 5242 | \n", "0.287500 | \n", "
| 5244 | \n", "0.333100 | \n", "
| 5246 | \n", "1.096900 | \n", "
| 5248 | \n", "0.379500 | \n", "
| 5250 | \n", "1.085800 | \n", "
| 5252 | \n", "0.046600 | \n", "
| 5254 | \n", "0.173100 | \n", "
| 5256 | \n", "0.199500 | \n", "
| 5258 | \n", "0.565100 | \n", "
| 5260 | \n", "0.734800 | \n", "
| 5262 | \n", "0.876400 | \n", "
| 5264 | \n", "0.171400 | \n", "
| 5266 | \n", "0.749900 | \n", "
| 5268 | \n", "1.813500 | \n", "
| 5270 | \n", "0.794900 | \n", "
| 5272 | \n", "1.008000 | \n", "
| 5274 | \n", "0.675000 | \n", "
| 5276 | \n", "0.601400 | \n", "
| 5278 | \n", "0.614100 | \n", "
| 5280 | \n", "0.408600 | \n", "
| 5282 | \n", "0.524300 | \n", "
| 5284 | \n", "0.975900 | \n", "
| 5286 | \n", "0.898900 | \n", "
| 5288 | \n", "0.823100 | \n", "
| 5290 | \n", "0.530100 | \n", "
| 5292 | \n", "1.187600 | \n", "
| 5294 | \n", "0.193400 | \n", "
| 5296 | \n", "1.953600 | \n", "
| 5298 | \n", "1.523600 | \n", "
| 5300 | \n", "0.462300 | \n", "
| 5302 | \n", "0.045300 | \n", "
| 5304 | \n", "1.219300 | \n", "
| 5306 | \n", "1.105500 | \n", "
| 5308 | \n", "1.993600 | \n", "
| 5310 | \n", "0.178400 | \n", "
| 5312 | \n", "0.860300 | \n", "
| 5314 | \n", "2.178300 | \n", "
| 5316 | \n", "1.722000 | \n", "
| 5318 | \n", "0.404600 | \n", "
| 5320 | \n", "0.098700 | \n", "
| 5322 | \n", "0.336100 | \n", "
| 5324 | \n", "0.291500 | \n", "
| 5326 | \n", "0.167500 | \n", "
| 5328 | \n", "1.245400 | \n", "
| 5330 | \n", "0.424000 | \n", "
| 5332 | \n", "1.237400 | \n", "
| 5334 | \n", "0.153000 | \n", "
| 5336 | \n", "0.630700 | \n", "
| 5338 | \n", "0.248200 | \n", "
"
],
"text/plain": [
" "
]
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"=== EMID Music ↔ Image Emotion Alignment ===\n",
"Model | Same Acc | Joint Acc | Emotion Acc\n",
"--------------------------------------------------\n",
"Base | 49.0% | 46.5% | 0.0%\n",
"LoRA | 79.0% | 76.5% | 75.5%\n",
"\n",
"Δ same accuracy: +30.0% | Δ joint accuracy: +30.0% | Δ emotion accuracy: +75.5%\n"
]
}
],
"source": [
"import inspect\n",
"import os\n",
"import shutil\n",
"\n",
"# Make reruns deterministic and avoid output-dir conflicts on older transformers builds\n",
"if os.path.exists(OUTPUT_DIR):\n",
" shutil.rmtree(OUTPUT_DIR)\n",
"\n",
"lora_cfg = LoraConfig(\n",
" r=16,\n",
" lora_alpha=32,\n",
" lora_dropout=0.05,\n",
" target_modules=[\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"],\n",
" task_type=\"CAUSAL_LM\",\n",
")\n",
"\n",
"thinker = get_peft_model(thinker, lora_cfg)\n",
"\n",
"supported = inspect.signature(TrainingArguments.__init__).parameters\n",
"\n",
"ta_kwargs = {\n",
" \"output_dir\": OUTPUT_DIR,\n",
" \"per_device_train_batch_size\": 1,\n",
" \"gradient_accumulation_steps\": 4,\n",
" \"num_train_epochs\": 1,\n",
" \"learning_rate\": 1e-5,\n",
" \"logging_steps\": 2,\n",
" \"remove_unused_columns\": False,\n",
"}\n",
"\n",
"optional_kwargs = {\n",
" \"save_total_limit\": 1,\n",
" \"data_seed\": SEED,\n",
" \"report_to\": \"none\",\n",
" \"overwrite_output_dir\": True,\n",
" \"bf16\": bool(torch.cuda.is_available() and getattr(torch.cuda, \"is_bf16_supported\", lambda: False)()),\n",
" \"fp16\": bool(torch.cuda.is_available() and not getattr(torch.cuda, \"is_bf16_supported\", lambda: False)()),\n",
"}\n",
"\n",
"for k, v in optional_kwargs.items():\n",
" if k in supported:\n",
" ta_kwargs[k] = v\n",
"\n",
"trainer = Trainer(\n",
" model=thinker,\n",
" args=TrainingArguments(**ta_kwargs),\n",
" train_dataset=train_dataset,\n",
" data_collator=build_collator(processor),\n",
")\n",
"\n",
"trainer.train()\n",
"tuned = evaluate(trainer.model, processor, eval_dataset)\n",
"\n",
"print(\"\\n=== EMID Music ↔ Image Emotion Alignment ===\")\n",
"print(f\"{'Model':<12} | {'Same Acc':>8} | {'Joint Acc':>9} | {'Emotion Acc':>11}\")\n",
"print(\"-\" * 50)\n",
"for name, scores in ((\"Base\", baseline), (\"LoRA\", tuned)):\n",
" print(f\"{name:<12} | {scores[0]*100:8.1f}% | {scores[2]*100:9.1f}% | {scores[1]*100:11.1f}%\")\n",
"print(\n",
" f\"\\nΔ same accuracy: {(tuned[0] - baseline[0])*100:+.1f}% | \"\n",
" f\"Δ joint accuracy: {(tuned[2] - baseline[2])*100:+.1f}% | \"\n",
" f\"Δ emotion accuracy: {(tuned[1] - baseline[1])*100:+.1f}%\"\n",
")"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "A100",
"provenance": [],
"machine_shape": "hm"
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
\n",
" \n",
"
\n",
" \n",
" \n",
" \n",
" Step \n",
" Training Loss \n",
" \n",
" \n",
" 2 \n",
" 11.120700 \n",
" \n",
" \n",
" 4 \n",
" 12.752000 \n",
" \n",
" \n",
" 6 \n",
" 12.770500 \n",
" \n",
" \n",
" 8 \n",
" 9.409800 \n",
" \n",
" \n",
" 10 \n",
" 8.352200 \n",
" \n",
" \n",
" 12 \n",
" 7.326300 \n",
" \n",
" \n",
" 14 \n",
" 5.519600 \n",
" \n",
" \n",
" 16 \n",
" 4.076400 \n",
" \n",
" \n",
" 18 \n",
" 3.979900 \n",
" \n",
" \n",
" 20 \n",
" 3.921200 \n",
" \n",
" \n",
" 22 \n",
" 3.146400 \n",
" \n",
" \n",
" 24 \n",
" 2.703000 \n",
" \n",
" \n",
" 26 \n",
" 2.341300 \n",
" \n",
" \n",
" 28 \n",
" 2.402500 \n",
" \n",
" \n",
" 30 \n",
" 3.587200 \n",
" \n",
" \n",
" 32 \n",
" 3.418400 \n",
" \n",
" \n",
" 34 \n",
" 3.016600 \n",
" \n",
" \n",
" 36 \n",
" 4.271700 \n",
" \n",
" \n",
" 38 \n",
" 4.183500 \n",
" \n",
" \n",
" 40 \n",
" 2.487100 \n",
" \n",
" \n",
" 42 \n",
" 1.097400 \n",
" \n",
" \n",
" 44 \n",
" 1.437600 \n",
" \n",
" \n",
" 46 \n",
" 3.918300 \n",
" \n",
" \n",
" 48 \n",
" 3.086200 \n",
" \n",
" \n",
" 50 \n",
" 1.670800 \n",
" \n",
" \n",
" 52 \n",
" 1.581400 \n",
" \n",
" \n",
" 54 \n",
" 2.796000 \n",
" \n",
" \n",
" 56 \n",
" 2.437700 \n",
" \n",
" \n",
" 58 \n",
" 1.653400 \n",
" \n",
" \n",
" 60 \n",
" 2.771800 \n",
" \n",
" \n",
" 62 \n",
" 2.438400 \n",
" \n",
" \n",
" 64 \n",
" 3.086200 \n",
" \n",
" \n",
" 66 \n",
" 1.426800 \n",
" \n",
" \n",
" 68 \n",
" 1.242500 \n",
" \n",
" \n",
" 70 \n",
" 1.128600 \n",
" \n",
" \n",
" 72 \n",
" 0.873500 \n",
" \n",
" \n",
" 74 \n",
" 2.578600 \n",
" \n",
" \n",
" 76 \n",
" 1.075300 \n",
" \n",
" \n",
" 78 \n",
" 2.393000 \n",
" \n",
" \n",
" 80 \n",
" 1.035200 \n",
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" \n",
" 82 \n",
" 1.096900 \n",
" \n",
" \n",
" 84 \n",
" 1.065600 \n",
" \n",
" \n",
" 86 \n",
" 0.786100 \n",
" \n",
" \n",
" 88 \n",
" 1.359100 \n",
" \n",
" \n",
" 90 \n",
" 0.904300 \n",
" \n",
" \n",
" 92 \n",
" 2.244100 \n",
" \n",
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" 94 \n",
" 2.556300 \n",
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" 96 \n",
" 1.950200 \n",
" \n",
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" 98 \n",
" 2.228000 \n",
" \n",
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" 100 \n",
" 2.259800 \n",
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" 102 \n",
" 0.838400 \n",
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" 104 \n",
" 0.762100 \n",
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" 106 \n",
" 1.795600 \n",
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" 108 \n",
" 1.362700 \n",
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" 110 \n",
" 1.852800 \n",
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" 112 \n",
" 1.579700 \n",
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" 0.857700 \n",
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" 1.279900 \n",
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" 118 \n",
" 1.558000 \n",
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" 120 \n",
" 2.141400 \n",
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" 122 \n",
" 2.241900 \n",
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" 124 \n",
" 2.734300 \n",
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" 126 \n",
" 1.248000 \n",
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" 128 \n",
" 2.037600 \n",
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" 130 \n",
" 1.368600 \n",
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" 132 \n",
" 0.953100 \n",
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" 134 \n",
" 1.323600 \n",
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" 136 \n",
" 1.227000 \n",
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" 1.342800 \n",
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" 1.600900 \n",
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" 1.108200 \n",
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" 168 \n",
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" 2.572800 \n",
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" 174 \n",
" 1.363500 \n",
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" 176 \n",
" 1.340800 \n",
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" 1.081900 \n",
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" 182 \n",
" 0.546600 \n",
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" 184 \n",
" 0.901900 \n",
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" 186 \n",
" 0.630600 \n",
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" 188 \n",
" 0.931300 \n",
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" 190 \n",
" 1.405000 \n",
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" 192 \n",
" 1.526200 \n",
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" 194 \n",
" 2.008500 \n",
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" 196 \n",
" 1.442600 \n",
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" 198 \n",
" 0.549100 \n",
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" 200 \n",
" 1.914800 \n",
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" 1.910200 \n",
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" 204 \n",
" 0.990300 \n",
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" 1.081400 \n",
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" 1.289100 \n",
" \n",
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" 0.639800 \n",
" \n",
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" 0.759700 \n",
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" 0.813500 \n",
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" 1604 \n",
" 1.635800 \n",
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" 1.082700 \n",
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" 0.193200 \n",
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" 0.808200 \n",
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" 1.413700 \n",
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" 1.019800 \n",
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" 0.548000 \n",
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" 0.244300 \n",
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" 1.104800 \n",
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" 0.763400 \n",
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" 0.798400 \n",
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" 1.579400 \n",
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" 0.874500 \n",
" \n",
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" 1630 \n",
" 2.651800 \n",
" \n",
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" 1632 \n",
" 0.564000 \n",
" \n",
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" 1634 \n",
" 1.649900 \n",
" \n",
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" 1636 \n",
" 1.499400 \n",
" \n",
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" 1638 \n",
" 0.272100 \n",
" \n",
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" 1640 \n",
" 1.525800 \n",
" \n",
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" 1642 \n",
" 0.987000 \n",
" \n",
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" 1644 \n",
" 0.370000 \n",
" \n",
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" 1646 \n",
" 1.041600 \n",
" \n",
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" 1648 \n",
" 0.799900 \n",
" \n",
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" 1650 \n",
" 1.696200 \n",
" \n",
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" 1652 \n",
" 0.654000 \n",
" \n",
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" 1654 \n",
" 1.238300 \n",
" \n",
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" 1656 \n",
" 1.184500 \n",
" \n",
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" 1658 \n",
" 1.834600 \n",
" \n",
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" 1660 \n",
" 2.409100 \n",
" \n",
" \n",
" 1662 \n",
" 0.735700 \n",
" \n",
" \n",
" 1664 \n",
" 1.465700 \n",
" \n",
" \n",
" 1666 \n",
" 0.500200 \n",
" \n",
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" 1668 \n",
" 0.114000 \n",
" \n",
" \n",
" 1670 \n",
" 1.024400 \n",
" \n",
" \n",
" 1672 \n",
" 0.787100 \n",
" \n",
" \n",
" 1674 \n",
" 0.909500 \n",
" \n",
" \n",
" 1676 \n",
" 1.645800 \n",
" \n",
" \n",
" 1678 \n",
" 0.956700 \n",
" \n",
" \n",
" 1680 \n",
" 0.649900 \n",
" \n",
" \n",
" 1682 \n",
" 0.624300 \n",
" \n",
" \n",
" 1684 \n",
" 1.320200 \n",
" \n",
" \n",
" 1686 \n",
" 0.712000 \n",
" \n",
" \n",
" 1688 \n",
" 0.901700 \n",
" \n",
" \n",
" 1690 \n",
" 0.332400 \n",
" \n",
" \n",
" 1692 \n",
" 0.748300 \n",
" \n",
" \n",
" 1694 \n",
" 0.667500 \n",
" \n",
" \n",
" 1696 \n",
" 1.066200 \n",
" \n",
" \n",
" 1698 \n",
" 0.860200 \n",
" \n",
" \n",
" 1700 \n",
" 1.302400 \n",
" \n",
" \n",
" 1702 \n",
" 0.702300 \n",
" \n",
" \n",
" 1704 \n",
" 1.699300 \n",
" \n",
" \n",
" 1706 \n",
" 0.194700 \n",
" \n",
" \n",
" 1708 \n",
" 0.308800 \n",
" \n",
" \n",
" 1710 \n",
" 0.689700 \n",
" \n",
" \n",
" 1712 \n",
" 0.867900 \n",
" \n",
" \n",
" 1714 \n",
" 1.266900 \n",
" \n",
" \n",
" 1716 \n",
" 0.844100 \n",
" \n",
" \n",
" 1718 \n",
" 0.725700 \n",
" \n",
" \n",
" 1720 \n",
" 0.730600 \n",
" \n",
" \n",
" 1722 \n",
" 0.876100 \n",
" \n",
" \n",
" 1724 \n",
" 0.921500 \n",
" \n",
" \n",
" 1726 \n",
" 2.011600 \n",
" \n",
" \n",
" 1728 \n",
" 1.054100 \n",
" \n",
" \n",
" 1730 \n",
" 0.914700 \n",
" \n",
" \n",
" 1732 \n",
" 1.297300 \n",
" \n",
" \n",
" 1734 \n",
" 1.062800 \n",
" \n",
" \n",
" 1736 \n",
" 0.481900 \n",
" \n",
" \n",
" 1738 \n",
" 0.333400 \n",
" \n",
" \n",
" 1740 \n",
" 0.386400 \n",
" \n",
" \n",
" 1742 \n",
" 1.190200 \n",
" \n",
" \n",
" 1744 \n",
" 1.044600 \n",
" \n",
" \n",
" 1746 \n",
" 1.026700 \n",
" \n",
" \n",
" 1748 \n",
" 0.609600 \n",
" \n",
" \n",
" 1750 \n",
" 0.659300 \n",
" \n",
" \n",
" 1752 \n",
" 1.357200 \n",
" \n",
" \n",
" 1754 \n",
" 1.142800 \n",
" \n",
" \n",
" 1756 \n",
" 0.688600 \n",
" \n",
" \n",
" 1758 \n",
" 1.761200 \n",
" \n",
" \n",
" 1760 \n",
" 1.106700 \n",
" \n",
" \n",
" 1762 \n",
" 0.877200 \n",
" \n",
" \n",
" 1764 \n",
" 0.619100 \n",
" \n",
" \n",
" 1766 \n",
" 1.776900 \n",
" \n",
" \n",
" 1768 \n",
" 0.938900 \n",
" \n",
" \n",
" 1770 \n",
" 0.627600 \n",
" \n",
" \n",
" 1772 \n",
" 0.970500 \n",
" \n",
" \n",
" 1774 \n",
" 0.869400 \n",
" \n",
" \n",
" 1776 \n",
" 0.733700 \n",
" \n",
" \n",
" 1778 \n",
" 1.624000 \n",
" \n",
" \n",
" 1780 \n",
" 1.100300 \n",
" \n",
" \n",
" 1782 \n",
" 0.247700 \n",
" \n",
" \n",
" 1784 \n",
" 0.772800 \n",
" \n",
" \n",
" 1786 \n",
" 0.618300 \n",
" \n",
" \n",
" 1788 \n",
" 0.729900 \n",
" \n",
" \n",
" 1790 \n",
" 0.610800 \n",
" \n",
" \n",
" 1792 \n",
" 0.702100 \n",
" \n",
" \n",
" 1794 \n",
" 1.101600 \n",
" \n",
" \n",
" 1796 \n",
" 1.546300 \n",
" \n",
" \n",
" 1798 \n",
" 0.866600 \n",
" \n",
" \n",
" 1800 \n",
" 0.565700 \n",
" \n",
" \n",
" 1802 \n",
" 1.346600 \n",
" \n",
" \n",
" 1804 \n",
" 0.422300 \n",
" \n",
" \n",
" 1806 \n",
" 1.428100 \n",
" \n",
" \n",
" 1808 \n",
" 0.279000 \n",
" \n",
" \n",
" 1810 \n",
" 0.221200 \n",
" \n",
" \n",
" 1812 \n",
" 0.821600 \n",
" \n",
" \n",
" 1814 \n",
" 0.760900 \n",
" \n",
" \n",
" 1816 \n",
" 0.723000 \n",
" \n",
" \n",
" 1818 \n",
" 0.938300 \n",
" \n",
" \n",
" 1820 \n",
" 0.572400 \n",
" \n",
" \n",
" 1822 \n",
" 0.531200 \n",
" \n",
" \n",
" 1824 \n",
" 1.217900 \n",
" \n",
" \n",
" 1826 \n",
" 0.441600 \n",
" \n",
" \n",
" 1828 \n",
" 0.261500 \n",
" \n",
" \n",
" 1830 \n",
" 0.278900 \n",
" \n",
" \n",
" 1832 \n",
" 0.547100 \n",
" \n",
" \n",
" 1834 \n",
" 0.858800 \n",
" \n",
" \n",
" 1836 \n",
" 0.929700 \n",
" \n",
" \n",
" 1838 \n",
" 1.071800 \n",
" \n",
" \n",
" 1840 \n",
" 1.263600 \n",
" \n",
" \n",
" 1842 \n",
" 1.095600 \n",
" \n",
" \n",
" 1844 \n",
" 0.607500 \n",
" \n",
" \n",
" 1846 \n",
" 0.624000 \n",
" \n",
" \n",
" 1848 \n",
" 1.900100 \n",
" \n",
" \n",
" 1850 \n",
" 1.031800 \n",
" \n",
" \n",
" 1852 \n",
" 0.337800 \n",
" \n",
" \n",
" 1854 \n",
" 1.342500 \n",
" \n",
" \n",
" 1856 \n",
" 0.748000 \n",
" \n",
" \n",
" 1858 \n",
" 1.165000 \n",
" \n",
" \n",
" 1860 \n",
" 1.311900 \n",
" \n",
" \n",
" 1862 \n",
" 0.223100 \n",
" \n",
" \n",
" 1864 \n",
" 2.727000 \n",
" \n",
" \n",
" 1866 \n",
" 0.645000 \n",
" \n",
" \n",
" 1868 \n",
" 0.711900 \n",
" \n",
" \n",
" 1870 \n",
" 0.664600 \n",
" \n",
" \n",
" 1872 \n",
" 0.686800 \n",
" \n",
" \n",
" 1874 \n",
" 0.199800 \n",
" \n",
" \n",
" 1876 \n",
" 0.942800 \n",
" \n",
" \n",
" 1878 \n",
" 1.017200 \n",
" \n",
" \n",
" 1880 \n",
" 0.834200 \n",
" \n",
" \n",
" 1882 \n",
" 1.084200 \n",
" \n",
" \n",
" 1884 \n",
" 1.292800 \n",
" \n",
" \n",
" 1886 \n",
" 2.371700 \n",
" \n",
" \n",
" 1888 \n",
" 2.327300 \n",
" \n",
" \n",
" 1890 \n",
" 0.662300 \n",
" \n",
" \n",
" 1892 \n",
" 0.649100 \n",
" \n",
" \n",
" 1894 \n",
" 0.617000 \n",
" \n",
" \n",
" 1896 \n",
" 0.761000 \n",
" \n",
" \n",
" 1898 \n",
" 1.497400 \n",
" \n",
" \n",
" 1900 \n",
" 1.440900 \n",
" \n",
" \n",
" 1902 \n",
" 0.118300 \n",
" \n",
" \n",
" 1904 \n",
" 1.545700 \n",
" \n",
" \n",
" 1906 \n",
" 0.989700 \n",
" \n",
" \n",
" 1908 \n",
" 0.526900 \n",
" \n",
" \n",
" 1910 \n",
" 0.937900 \n",
" \n",
" \n",
" 1912 \n",
" 0.552700 \n",
" \n",
" \n",
" 1914 \n",
" 1.252300 \n",
" \n",
" \n",
" 1916 \n",
" 1.513500 \n",
" \n",
" \n",
" 1918 \n",
" 1.402500 \n",
" \n",
" \n",
" 1920 \n",
" 1.028500 \n",
" \n",
" \n",
" 1922 \n",
" 1.189000 \n",
" \n",
" \n",
" 1924 \n",
" 0.437100 \n",
" \n",
" \n",
" 1926 \n",
" 0.439300 \n",
" \n",
" \n",
" 1928 \n",
" 1.006700 \n",
" \n",
" \n",
" 1930 \n",
" 1.133700 \n",
" \n",
" \n",
" 1932 \n",
" 1.316800 \n",
" \n",
" \n",
" 1934 \n",
" 0.326400 \n",
" \n",
" \n",
" 1936 \n",
" 0.343200 \n",
" \n",
" \n",
" 1938 \n",
" 1.728200 \n",
" \n",
" \n",
" 1940 \n",
" 0.762800 \n",
" \n",
" \n",
" 1942 \n",
" 0.410700 \n",
" \n",
" \n",
" 1944 \n",
" 0.972300 \n",
" \n",
" \n",
" 1946 \n",
" 1.461800 \n",
" \n",
" \n",
" 1948 \n",
" 1.317000 \n",
" \n",
" \n",
" 1950 \n",
" 1.300400 \n",
" \n",
" \n",
" 1952 \n",
" 1.515500 \n",
" \n",
" \n",
" 1954 \n",
" 0.542000 \n",
" \n",
" \n",
" 1956 \n",
" 0.239200 \n",
" \n",
" \n",
" 1958 \n",
" 0.786100 \n",
" \n",
" \n",
" 1960 \n",
" 1.083500 \n",
" \n",
" \n",
" 1962 \n",
" 0.404500 \n",
" \n",
" \n",
" 1964 \n",
" 0.827100 \n",
" \n",
" \n",
" 1966 \n",
" 1.571800 \n",
" \n",
" \n",
" 1968 \n",
" 0.806100 \n",
" \n",
" \n",
" 1970 \n",
" 0.904500 \n",
" \n",
" \n",
" 1972 \n",
" 0.753400 \n",
" \n",
" \n",
" 1974 \n",
" 0.437200 \n",
" \n",
" \n",
" 1976 \n",
" 0.678600 \n",
" \n",
" \n",
" 1978 \n",
" 1.135500 \n",
" \n",
" \n",
" 1980 \n",
" 2.838200 \n",
" \n",
" \n",
" 1982 \n",
" 1.254100 \n",
" \n",
" \n",
" 1984 \n",
" 2.135700 \n",
" \n",
" \n",
" 1986 \n",
" 0.698300 \n",
" \n",
" \n",
" 1988 \n",
" 0.322200 \n",
" \n",
" \n",
" 1990 \n",
" 0.626700 \n",
" \n",
" \n",
" 1992 \n",
" 0.818200 \n",
" \n",
" \n",
" 1994 \n",
" 0.458600 \n",
" \n",
" \n",
" 1996 \n",
" 0.770500 \n",
" \n",
" \n",
" 1998 \n",
" 0.650500 \n",
" \n",
" \n",
" 2000 \n",
" 1.063500 \n",
" \n",
" \n",
" 2002 \n",
" 1.997500 \n",
" \n",
" \n",
" 2004 \n",
" 1.597500 \n",
" \n",
" \n",
" 2006 \n",
" 1.045000 \n",
" \n",
" \n",
" 2008 \n",
" 0.415100 \n",
" \n",
" \n",
" 2010 \n",
" 0.444600 \n",
" \n",
" \n",
" 2012 \n",
" 0.686700 \n",
" \n",
" \n",
" 2014 \n",
" 0.758400 \n",
" \n",
" \n",
" 2016 \n",
" 1.510300 \n",
" \n",
" \n",
" 2018 \n",
" 0.989300 \n",
" \n",
" \n",
" 2020 \n",
" 1.331600 \n",
" \n",
" \n",
" 2022 \n",
" 0.566700 \n",
" \n",
" \n",
" 2024 \n",
" 0.717600 \n",
" \n",
" \n",
" 2026 \n",
" 0.927800 \n",
" \n",
" \n",
" 2028 \n",
" 0.734700 \n",
" \n",
" \n",
" 2030 \n",
" 0.484700 \n",
" \n",
" \n",
" 2032 \n",
" 0.887900 \n",
" \n",
" \n",
" 2034 \n",
" 1.406600 \n",
" \n",
" \n",
" 2036 \n",
" 0.126900 \n",
" \n",
" \n",
" 2038 \n",
" 0.749900 \n",
" \n",
" \n",
" 2040 \n",
" 0.576400 \n",
" \n",
" \n",
" 2042 \n",
" 0.683400 \n",
" \n",
" \n",
" 2044 \n",
" 0.452500 \n",
" \n",
" \n",
" 2046 \n",
" 1.421400 \n",
" \n",
" \n",
" 2048 \n",
" 0.885100 \n",
" \n",
" \n",
" 2050 \n",
" 1.575900 \n",
" \n",
" \n",
" 2052 \n",
" 0.860000 \n",
" \n",
" \n",
" 2054 \n",
" 0.708500 \n",
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" 2.055100 \n",
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" 5810 \n",
" 0.422800 \n",
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" 0.802600 \n",
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" 1.603200 \n",
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" 0.212900 \n",
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" 2.204900 \n",
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" 0.100200 \n",
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" 0.466100 \n",
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" 5824 \n",
" 0.989100 \n",
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" 0.870500 \n",
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" 5828 \n",
" 0.661900 \n",
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" 0.149600 \n",
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" 0.114200 \n",
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" 5834 \n",
" 1.333100 \n",
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" 1.075300 \n",
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" 0.118200 \n",
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" 5840 \n",
" 0.165200 \n",
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" 5842 \n",
" 0.086800 \n",
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" 5844 \n",
" 1.444600 \n",
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" 5846 \n",
" 2.244600 \n",
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" 5848 \n",
" 0.027200 \n",
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" 5850 \n",
" 1.621500 \n",
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" 5852 \n",
" 0.376800 \n",
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" 5854 \n",
" 0.652200 \n",
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" 5856 \n",
" 0.709200 \n",
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" 5858 \n",
" 1.651100 \n",
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" 5860 \n",
" 0.709700 \n",
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" 5862 \n",
" 0.991700 \n",
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" 5864 \n",
" 1.146600 \n",
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" 5866 \n",
" 0.819900 \n",
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" 5868 \n",
" 0.121300 \n",
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" 5870 \n",
" 1.040400 \n",
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" 5872 \n",
" 1.668100 \n",
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" 5874 \n",
" 0.532000 \n",
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" 5876 \n",
" 0.270200 \n",
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" 5878 \n",
" 2.117500 \n",
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" 5880 \n",
" 0.889500 \n",
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" 5882 \n",
" 0.931900 \n",
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" 5884 \n",
" 0.022300 \n",
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" 5886 \n",
" 0.456700 \n",
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" 5888 \n",
" 2.385800 \n",
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" 5890 \n",
" 0.103300 \n",
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" 5892 \n",
" 0.922100 \n",
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" 5894 \n",
" 0.306900 \n",
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" 0.132900 \n",
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" 5898 \n",
" 0.169700 \n",
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" 5900 \n",
" 0.093400 \n",
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" 5902 \n",
" 2.197600 \n",
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" 5904 \n",
" 1.283500 \n",
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" 5906 \n",
" 0.836000 \n",
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" 5908 \n",
" 0.656400 \n",
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" 5910 \n",
" 0.781500 \n",
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" 5912 \n",
" 0.922200 \n",
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" 5914 \n",
" 1.422900 \n",
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" 0.998500 \n",
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" 0.809500 \n",
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" 5920 \n",
" 0.511200 \n",
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" 5922 \n",
" 1.247300 \n",
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" 5924 \n",
" 0.206000 \n",
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" 5926 \n",
" 0.051000 \n",
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" 5928 \n",
" 2.358100 \n",
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" 5930 \n",
" 1.567800 \n",
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" 5932 \n",
" 0.831700 \n",
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" 5934 \n",
" 1.660600 \n",
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" 5936 \n",
" 0.340400 \n",
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" 0.668500 \n",
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" 5940 \n",
" 0.485600 \n",
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" 5942 \n",
" 1.180500 \n",
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" 5944 \n",
" 0.051000 \n",
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" 5946 \n",
" 0.345600 \n",
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" 5948 \n",
" 0.282100 \n",
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" 5950 \n",
" 0.076100 \n",
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" 5952 \n",
" 0.139000 \n",
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" 1.402700 \n",
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" 0.261200 \n",
" \n",
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" 5958 \n",
" 0.425500 \n",
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" 5960 \n",
" 0.173400 \n",
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" 0.805700 \n",
" \n",
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" 5964 \n",
" 1.785900 \n",
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" 5966 \n",
" 1.362800 \n",
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" 5968 \n",
" 1.197800 \n",
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" 5970 \n",
" 0.183900 \n",
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" 0.504800 \n",
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" 0.806300 \n",
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" 0.104500 \n",
" \n",
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" 5978 \n",
" 3.084400 \n",
" \n",
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" 5980 \n",
" 0.413600 \n",
" \n",
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" 5982 \n",
" 0.976400 \n",
" \n",
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" 5984 \n",
" 0.617700 \n",
" \n",
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" 5986 \n",
" 1.003600 \n",
" \n",
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" 5988 \n",
" 0.818200 \n",
" \n",
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" 5990 \n",
" 2.232500 \n",
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" 5992 \n",
" 0.847600 \n",
" \n",
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" 5994 \n",
" 1.089500 \n",
" \n",
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" 5996 \n",
" 0.324500 \n",
" \n",
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" 5998 \n",
" 0.195200 \n",
" \n",
" \n",
" \n",
"6000 \n",
" 0.480500 \n",
"