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| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # Parameters | |
| d = 5 | |
| n = 5 | |
| maxP = 10 | |
| n_samples = 10000 | |
| def formula_p1(n, d): |
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| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # Parameters | |
| d = 10 | |
| maxP = 10 | |
| n_samples = 100 | |
| # Identity matrix | |
| ii = np.eye(d) |
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| import asyncio | |
| import asyncssh | |
| import re | |
| from nicegui import ui | |
| # SSH connection details | |
| SSH_HOST = 'remote_host' | |
| SSH_PORT = 22 | |
| SSH_USERNAME = 'username' | |
| SSH_PASSWORD = 'password' |
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| from manim import * | |
| import numpy as np | |
| class DualRingHeatTransferAnimation(Scene): | |
| def construct(self): | |
| # Configuration | |
| num_blocks = 20 | |
| num_around = 39 | |
| block_size = 0.4 | |
| outer_radius = 3.3 |
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| from manim import * | |
| import numpy as np | |
| class DualRingHeatTransferAnimation(Scene): | |
| def construct(self): | |
| # Configuration | |
| num_blocks = 20 | |
| block_size = 0.4 | |
| outer_radius = 3.3 | |
| inner_radius = 2.9 |
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| from manim import * | |
| import numpy as np | |
| class HeatTransferAnimation(Scene): | |
| def construct(self): | |
| # Configuration | |
| num_blocks = 10 | |
| block_size = 1 | |
| spacing = 0.1 |
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| import geopandas as gpd | |
| import matplotlib.pyplot as plt | |
| import pandas as pd | |
| import matplotlib.colors as mcolors | |
| from shapely.geometry import Polygon, MultiPolygon | |
| import shapely.ops | |
| import os.path | |
| def get_text_color(fill_color): |
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| import instructor | |
| from pydantic import BaseModel, Field | |
| from typing import overload, Union, Literal, Generator | |
| from tqdm.asyncio import tqdm | |
| import asyncio | |
| import numpy as np | |
| import json | |
| import os, sys | |
| import diskcache, inspect, functools | |
| import random |
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| import instructor | |
| from pydantic import BaseModel, Field | |
| from typing import overload, Union, Literal, Generator | |
| from tqdm.asyncio import tqdm | |
| import asyncio | |
| import numpy as np | |
| import json | |
| import os, sys | |
| import diskcache, inspect, functools | |
| import random |
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| import torch | |
| import math | |
| from torch import nn | |
| import torch.nn.functional as F | |
| import matplotlib.pyplot as plt | |
| import matplotlib.cm as cm | |
| import matplotlib.colors as mcolors | |
| import numpy as np | |
| import seaborn as sns |