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\u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc \u0628\u0631\u0627\u06cc \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0628\u0631 \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u06a9 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0645\u062d\u0628\u0648\u0628 Matplotlib \u062a\u0645\u0631\u06a9\u0632 \u062f\u0627\u0631\u062f. \u0628\u0631\u0627\u06cc \u0622\u0634\u0646\u0627\u06cc\u06cc \u0628\u0627 \u0633\u0627\u06cc\u0631 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u062f\u0648\u0631\u0647 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\u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0645\u0641\u0627\u0647\u06cc\u0645 \u0627\u0635\u0644\u06cc Matplotlib<\/a> \u0631\u0627 \u062a\u0648\u0636\u06cc\u062d \u0645\u06cc \u062f\u0647\u062f \u062a\u0627 \u0641\u0631\u062f \u0628\u062a\u0648\u0627\u0646\u062f \u067e\u062a\u0627\u0646\u0633\u06cc\u0644 \u06a9\u0627\u0645\u0644 \u0622\u0646 \u0631\u0627 \u06a9\u0634\u0641 \u06a9\u0646\u062f.<\/p>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u0645\u0639\u0631\u0641\u06cc \u0628\u0647 pyplot<\/h3>\n\n\n\nmatplotlib.pyplot \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u06cc \u0627\u0632 \u062a\u0648\u0627\u0628\u0639 \u0633\u0628\u06a9 \u0641\u0631\u0645\u0627\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0628\u0627\u0639\u062b \u0645\u06cc \u0634\u0648\u062f Matplotlib \u0645\u0627\u0646\u0646\u062f MATLAB \u06a9\u0627\u0631 \u06a9\u0646\u062f. \u0647\u0631 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matplotlib.pyplot as plt\n\nplt.plot([1, 2, 3, 4])\n\nplt.ylabel('some numbers')\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0627\u06cc\u062c\u0627\u062f \u062a\u062c\u0633\u0645 \u062e\u0637\u06cc \u0628\u0627 Matplotlib<\/h3>\n\n\n\n\u0634\u0627\u06cc\u062f \u062a\u0639\u062c\u0628 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0686\u0631\u0627 \u0645\u062d\u0648\u0631 x \u0627\u0632 \u06f0-\u06f3 \u0648 \u0645\u062d\u0648\u0631 y \u0627\u0632 \u06f1-\u06f4 \u0645\u062a\u063a\u06cc\u0631 \u0627\u0633\u062a. \u0627\u06af\u0631 \u06cc\u06a9 \u0644\u06cc\u0633\u062a \u06cc\u0627 \u0622\u0631\u0627\u06cc\u0647 \u0648\u0627\u062d\u062f \u0628\u0647 \u0641\u0631\u0645\u0627\u0646 () \u062f\u0631 \u0637\u0631\u062d () \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f\u060c Matplotlib \u0641\u0631\u0636 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u062f\u0646\u0628\u0627\u0644\u0647 \u0627\u06cc \u0627\u0632 \u0645\u0642\u0627\u062f\u06cc\u0631 y \u0627\u0633\u062a\u060c \u0648 \u0628\u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0645\u0642\u0627\u062f\u06cc\u0631 x \u0631\u0627 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u062f. \u0627\u0632 \u0622\u0646\u062c\u0627 \u06a9\u0647 \u062f\u0627\u0645\u0646\u0647 \u0647\u0627\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06f0 \u0634\u0631\u0648\u0639 \u0645\u06cc \u0634\u0648\u062f\u060c \u0628\u0631\u062f\u0627\u0631 x \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u062f\u0627\u0631\u0627\u06cc \u0637\u0648\u0644 Y \u0627\u0633\u062a \u0627\u0645\u0627 \u0628\u0627 \u06f0 \u0634\u0631\u0648\u0639 \u0645\u06cc \u0634\u0648\u062f. \u0627\u0632 \u0627\u06cc\u0646 \u0631\u0648 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc x [0\u060c\u06f1\u060c\u06f2\u060c\u06f3] \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n() Plot \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0647\u0645\u0647 \u06a9\u0627\u0631\u0647 \u0627\u0633\u062a \u0648 \u062a\u0639\u062f\u0627\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u062f\u0644\u062e\u0648\u0627\u0647 \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u062e\u0648\u0627\u0647\u062f \u06af\u0631\u0641\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 x \u062f\u0631 \u0645\u0642\u0627\u0628\u0644 y\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0633\u062a\u0648\u0631 \u0631\u0627 \u0635\u0627\u062f\u0631 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16])<\/pre>\n\n\n\n\u0642\u0627\u0644\u0628 \u0628\u0646\u062f\u06cc \u0637\u0631\u062d \u062e\u0648\u062f<\/h3>\n\n\n\n\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0633\u0648\u0645 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0633\u062a \u06a9\u0647 \u0631\u0646\u06af \u0648 \u0646\u0648\u0639 \u062e\u0637 \u0646\u0642\u0634\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f. \u062d\u0631\u0648\u0641 \u0648 \u0646\u0645\u0627\u062f\u0647\u0627\u06cc \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0632 MATLAB \u0627\u0633\u062a\u060c \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0631\u0646\u06af \u0631\u0627 \u0628\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0628\u0647 \u0633\u0628\u06a9 \u062e\u0637 \u062c\u0645\u0639 \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u067e\u06cc\u0634 \u0641\u0631\u0636 “b-” \u0627\u0633\u062a\u060c \u06a9\u0647 \u06cc\u06a9 \u062e\u0637 \u0622\u0628\u06cc \u062c\u0627\u0645\u062f \u0627\u0633\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0645\u0648\u0627\u0631\u062f \u0641\u0648\u0642 \u0628\u0627 \u062f\u0627\u06cc\u0631\u0647 \u0647\u0627\u06cc \u0642\u0631\u0645\u0632 \u062f\u0631 Matplotlib\u060c \u0634\u0645\u0627 \u0635\u0627\u062f\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')\n\nplt.axis([0, 6, 0, 20])\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0642\u0637\u0647 \u0627\u06cc \u0628\u0627 matplotlib<\/h3>\n\n\n\n\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u067e\u0627\u06cc\u062a\u0648\u0646 \u062c\u0627\u0645\u0639 <\/a>\n\n \n \n \n \u06f2,\u06f5\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f2\u06f9\u06f9,\u06f5\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f5\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc 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numbers')\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0627\u06cc\u062c\u0627\u062f \u062a\u062c\u0633\u0645 \u062e\u0637\u06cc \u0628\u0627 Matplotlib<\/h3>\n\n\n\n\u0634\u0627\u06cc\u062f \u062a\u0639\u062c\u0628 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0686\u0631\u0627 \u0645\u062d\u0648\u0631 x \u0627\u0632 \u06f0-\u06f3 \u0648 \u0645\u062d\u0648\u0631 y \u0627\u0632 \u06f1-\u06f4 \u0645\u062a\u063a\u06cc\u0631 \u0627\u0633\u062a. \u0627\u06af\u0631 \u06cc\u06a9 \u0644\u06cc\u0633\u062a \u06cc\u0627 \u0622\u0631\u0627\u06cc\u0647 \u0648\u0627\u062d\u062f \u0628\u0647 \u0641\u0631\u0645\u0627\u0646 () \u062f\u0631 \u0637\u0631\u062d () \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f\u060c Matplotlib \u0641\u0631\u0636 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u062f\u0646\u0628\u0627\u0644\u0647 \u0627\u06cc \u0627\u0632 \u0645\u0642\u0627\u062f\u06cc\u0631 y \u0627\u0633\u062a\u060c \u0648 \u0628\u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 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\u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u062f\u0644\u062e\u0648\u0627\u0647 \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u062e\u0648\u0627\u0647\u062f \u06af\u0631\u0641\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 x \u062f\u0631 \u0645\u0642\u0627\u0628\u0644 y\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0633\u062a\u0648\u0631 \u0631\u0627 \u0635\u0627\u062f\u0631 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16])<\/pre>\n\n\n\n\u0642\u0627\u0644\u0628 \u0628\u0646\u062f\u06cc \u0637\u0631\u062d \u062e\u0648\u062f<\/h3>\n\n\n\n\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0633\u0648\u0645 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0633\u062a \u06a9\u0647 \u0631\u0646\u06af \u0648 \u0646\u0648\u0639 \u062e\u0637 \u0646\u0642\u0634\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f. \u062d\u0631\u0648\u0641 \u0648 \u0646\u0645\u0627\u062f\u0647\u0627\u06cc \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0632 MATLAB \u0627\u0633\u062a\u060c \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0631\u0646\u06af \u0631\u0627 \u0628\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0628\u0647 \u0633\u0628\u06a9 \u062e\u0637 \u062c\u0645\u0639 \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u067e\u06cc\u0634 \u0641\u0631\u0636 “b-” \u0627\u0633\u062a\u060c \u06a9\u0647 \u06cc\u06a9 \u062e\u0637 \u0622\u0628\u06cc \u062c\u0627\u0645\u062f \u0627\u0633\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0645\u0648\u0627\u0631\u062f \u0641\u0648\u0642 \u0628\u0627 \u062f\u0627\u06cc\u0631\u0647 \u0647\u0627\u06cc \u0642\u0631\u0645\u0632 \u062f\u0631 Matplotlib\u060c \u0634\u0645\u0627 \u0635\u0627\u062f\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')\n\nplt.axis([0, 6, 0, 20])\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0642\u0637\u0647 \u0627\u06cc \u0628\u0627 matplotlib<\/h3>\n\n\n\n\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u067e\u0627\u06cc\u062a\u0648\u0646 \u062c\u0627\u0645\u0639 <\/a>\n\n \n \n \n \u06f2,\u06f5\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f2\u06f9\u06f9,\u06f5\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f5\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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\u0627\u0633\u062a:<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.plot([1, 2, 3, 4])\n\nplt.ylabel('some numbers')\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0627\u06cc\u062c\u0627\u062f \u062a\u062c\u0633\u0645 \u062e\u0637\u06cc \u0628\u0627 Matplotlib<\/h3>\n\n\n\n\u0634\u0627\u06cc\u062f \u062a\u0639\u062c\u0628 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0686\u0631\u0627 \u0645\u062d\u0648\u0631 x \u0627\u0632 \u06f0-\u06f3 \u0648 \u0645\u062d\u0648\u0631 y \u0627\u0632 \u06f1-\u06f4 \u0645\u062a\u063a\u06cc\u0631 \u0627\u0633\u062a. \u0627\u06af\u0631 \u06cc\u06a9 \u0644\u06cc\u0633\u062a \u06cc\u0627 \u0622\u0631\u0627\u06cc\u0647 \u0648\u0627\u062d\u062f \u0628\u0647 \u0641\u0631\u0645\u0627\u0646 () \u062f\u0631 \u0637\u0631\u062d () \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f\u060c Matplotlib \u0641\u0631\u0636 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u062f\u0646\u0628\u0627\u0644\u0647 \u0627\u06cc \u0627\u0632 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\u062f\u0633\u062a\u0648\u0631 \u0647\u0645\u0647 \u06a9\u0627\u0631\u0647 \u0627\u0633\u062a \u0648 \u062a\u0639\u062f\u0627\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u062f\u0644\u062e\u0648\u0627\u0647 \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u062e\u0648\u0627\u0647\u062f \u06af\u0631\u0641\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 x \u062f\u0631 \u0645\u0642\u0627\u0628\u0644 y\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0633\u062a\u0648\u0631 \u0631\u0627 \u0635\u0627\u062f\u0631 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16])<\/pre>\n\n\n\n\u0642\u0627\u0644\u0628 \u0628\u0646\u062f\u06cc \u0637\u0631\u062d \u062e\u0648\u062f<\/h3>\n\n\n\n\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 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\u062c\u0627\u0645\u062f \u0627\u0633\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0645\u0648\u0627\u0631\u062f \u0641\u0648\u0642 \u0628\u0627 \u062f\u0627\u06cc\u0631\u0647 \u0647\u0627\u06cc \u0642\u0631\u0645\u0632 \u062f\u0631 Matplotlib\u060c \u0634\u0645\u0627 \u0635\u0627\u062f\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')\n\nplt.axis([0, 6, 0, 20])\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0642\u0637\u0647 \u0627\u06cc \u0628\u0627 matplotlib<\/h3>\n\n\n\n\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u067e\u0627\u06cc\u062a\u0648\u0646 \u062c\u0627\u0645\u0639 <\/a>\n\n \n \n \n \u06f2,\u06f5\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f2\u06f9\u06f9,\u06f5\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f5\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
APP pyplot \u0639\u0645\u0648\u0645\u0627 \u062f\u0631 Matplotlib \u0646\u0633\u0628\u062a \u0628\u0647 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0646\u0639\u0637\u0627\u0641 \u067e\u0630\u06cc\u0631 \u0627\u0633\u062a. \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062a\u0645\u0627\u0633\u0647\u0627\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f\u06cc \u06a9\u0647 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0645\u0634\u0627\u0647\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0645\u06cc \u062a\u0648\u0627\u0646\u0646\u062f \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0631\u0648\u0634\u0647\u0627\u06cc\u06cc \u0627\u0632 \u06cc\u06a9 \u0634\u06cc\u0621 Axes \u0646\u06cc\u0632 \u062e\u0648\u0627\u0646\u062f\u0647 \u0634\u0648\u0646\u062f. \u062a\u0648\u0635\u06cc\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0628\u0631\u0627\u06cc \u062f\u06cc\u062f\u0646 \u0686\u06af\u0648\u0646\u06af\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634\u0647\u0627 \u0648 \u0645\u062b\u0627\u0644\u0647\u0627 \u0631\u0627 \u0645\u0631\u0648\u0631 \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\n
\u0627\u06cc\u062c\u0627\u062f \u062a\u062c\u0633\u0645 \u0628\u0627 pyplot \u0628\u0633\u06cc\u0627\u0631 \u0633\u0631\u06cc\u0639 \u0627\u0633\u062a:<\/p>\n\n\n\n
import matplotlib.pyplot as plt\n\nplt.plot([1, 2, 3, 4])\n\nplt.ylabel('some numbers')\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0627\u06cc\u062c\u0627\u062f \u062a\u062c\u0633\u0645 \u062e\u0637\u06cc \u0628\u0627 Matplotlib<\/h3>\n\n\n\n\u0634\u0627\u06cc\u062f \u062a\u0639\u062c\u0628 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0686\u0631\u0627 \u0645\u062d\u0648\u0631 x \u0627\u0632 \u06f0-\u06f3 \u0648 \u0645\u062d\u0648\u0631 y \u0627\u0632 \u06f1-\u06f4 \u0645\u062a\u063a\u06cc\u0631 \u0627\u0633\u062a. \u0627\u06af\u0631 \u06cc\u06a9 \u0644\u06cc\u0633\u062a \u06cc\u0627 \u0622\u0631\u0627\u06cc\u0647 \u0648\u0627\u062d\u062f \u0628\u0647 \u0641\u0631\u0645\u0627\u0646 () \u062f\u0631 \u0637\u0631\u062d () \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f\u060c Matplotlib \u0641\u0631\u0636 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u062f\u0646\u0628\u0627\u0644\u0647 \u0627\u06cc \u0627\u0632 \u0645\u0642\u0627\u062f\u06cc\u0631 y \u0627\u0633\u062a\u060c \u0648 \u0628\u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0645\u0642\u0627\u062f\u06cc\u0631 x \u0631\u0627 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u062f. \u0627\u0632 \u0622\u0646\u062c\u0627 \u06a9\u0647 \u062f\u0627\u0645\u0646\u0647 \u0647\u0627\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06f0 \u0634\u0631\u0648\u0639 \u0645\u06cc \u0634\u0648\u062f\u060c \u0628\u0631\u062f\u0627\u0631 x \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u062f\u0627\u0631\u0627\u06cc \u0637\u0648\u0644 Y \u0627\u0633\u062a \u0627\u0645\u0627 \u0628\u0627 \u06f0 \u0634\u0631\u0648\u0639 \u0645\u06cc \u0634\u0648\u062f. \u0627\u0632 \u0627\u06cc\u0646 \u0631\u0648 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc x [0\u060c\u06f1\u060c\u06f2\u060c\u06f3] \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n() Plot \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0647\u0645\u0647 \u06a9\u0627\u0631\u0647 \u0627\u0633\u062a \u0648 \u062a\u0639\u062f\u0627\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u062f\u0644\u062e\u0648\u0627\u0647 \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u062e\u0648\u0627\u0647\u062f \u06af\u0631\u0641\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 x \u062f\u0631 \u0645\u0642\u0627\u0628\u0644 y\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0633\u062a\u0648\u0631 \u0631\u0627 \u0635\u0627\u062f\u0631 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16])<\/pre>\n\n\n\n\u0642\u0627\u0644\u0628 \u0628\u0646\u062f\u06cc \u0637\u0631\u062d \u062e\u0648\u062f<\/h3>\n\n\n\n\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0633\u0648\u0645 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0633\u062a \u06a9\u0647 \u0631\u0646\u06af \u0648 \u0646\u0648\u0639 \u062e\u0637 \u0646\u0642\u0634\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f. \u062d\u0631\u0648\u0641 \u0648 \u0646\u0645\u0627\u062f\u0647\u0627\u06cc \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0632 MATLAB \u0627\u0633\u062a\u060c \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0631\u0646\u06af \u0631\u0627 \u0628\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0628\u0647 \u0633\u0628\u06a9 \u062e\u0637 \u062c\u0645\u0639 \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u067e\u06cc\u0634 \u0641\u0631\u0636 “b-” \u0627\u0633\u062a\u060c \u06a9\u0647 \u06cc\u06a9 \u062e\u0637 \u0622\u0628\u06cc \u062c\u0627\u0645\u062f \u0627\u0633\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0645\u0648\u0627\u0631\u062f \u0641\u0648\u0642 \u0628\u0627 \u062f\u0627\u06cc\u0631\u0647 \u0647\u0627\u06cc \u0642\u0631\u0645\u0632 \u062f\u0631 Matplotlib\u060c \u0634\u0645\u0627 \u0635\u0627\u062f\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')\n\nplt.axis([0, 6, 0, 20])\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0642\u0637\u0647 \u0627\u06cc \u0628\u0627 matplotlib<\/h3>\n\n\n\n\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u067e\u0627\u06cc\u062a\u0648\u0646 \u062c\u0627\u0645\u0639 <\/a>\n\n \n \n \n \u06f2,\u06f5\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f2\u06f9\u06f9,\u06f5\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f5\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc 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[…]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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plt.plot([1, 2, 3, 4], [1, 4, 9, 16])<\/pre>\n\n\n\n\u0642\u0627\u0644\u0628 \u0628\u0646\u062f\u06cc \u0637\u0631\u062d \u062e\u0648\u062f<\/h3>\n\n\n\n\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0633\u0648\u0645 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0633\u062a \u06a9\u0647 \u0631\u0646\u06af \u0648 \u0646\u0648\u0639 \u062e\u0637 \u0646\u0642\u0634\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f. \u062d\u0631\u0648\u0641 \u0648 \u0646\u0645\u0627\u062f\u0647\u0627\u06cc \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0632 MATLAB \u0627\u0633\u062a\u060c \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0631\u0646\u06af \u0631\u0627 \u0628\u0627 \u06cc\u06a9 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\u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0622\u0631\u06af\u0648\u0645\u0627\u0646 x \u060c y \u060c \u06cc\u06a9 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0633\u0648\u0645 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0633\u062a \u06a9\u0647 \u0631\u0646\u06af \u0648 \u0646\u0648\u0639 \u062e\u0637 \u0646\u0642\u0634\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f. \u062d\u0631\u0648\u0641 \u0648 \u0646\u0645\u0627\u062f\u0647\u0627\u06cc \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u0627\u0632 MATLAB \u0627\u0633\u062a\u060c \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0631\u0646\u06af \u0631\u0627 \u0628\u0627 \u06cc\u06a9 \u0631\u0634\u062a\u0647 \u0628\u0647 \u0633\u0628\u06a9 \u062e\u0637 \u062c\u0645\u0639 \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0631\u0634\u062a\u0647 \u0641\u0631\u0645\u062a \u067e\u06cc\u0634 \u0641\u0631\u0636 “b-” \u0627\u0633\u062a\u060c \u06a9\u0647 \u06cc\u06a9 \u062e\u0637 \u0622\u0628\u06cc \u062c\u0627\u0645\u062f \u0627\u0633\u062a. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0645\u0648\u0627\u0631\u062f \u0641\u0648\u0642 \u0628\u0627 \u062f\u0627\u06cc\u0631\u0647 \u0647\u0627\u06cc \u0642\u0631\u0645\u0632 \u062f\u0631 Matplotlib\u060c \u0634\u0645\u0627 \u0635\u0627\u062f\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\n
plt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')\n\nplt.axis([0, 6, 0, 20])\n\nplt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0642\u0637\u0647 \u0627\u06cc \u0628\u0627 matplotlib<\/h3>\n\n\n\n\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u067e\u0627\u06cc\u062a\u0648\u0646 \u062c\u0627\u0645\u0639 <\/a>\n\n \n \n \n \u06f2,\u06f5\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f2\u06f9\u06f9,\u06f5\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f5\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\nimport numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u0645\u0633\u062a\u0646\u062f\u0627\u062a \u0637\u0631\u062d () \u0631\u0627 \u0628\u0631\u0627\u06cc \u0644\u06cc\u0633\u062a \u06a9\u0627\u0645\u0644\u06cc \u0627\u0632 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u062e\u0637 \u0648 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0642\u0627\u0644\u0628 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0633\u062a\u0648\u0631() ax \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 [xmin\u060c xmax\u060c ymin\u060c ymax] \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f \u0648 \u0646\u0645\u0627\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\n\n
\u0627\u06af\u0631 Matplotlib \u0628\u0647 \u06a9\u0627\u0631 \u0628\u0627 \u0644\u06cc\u0633\u062a \u0645\u062d\u062f\u0648\u062f \u0645\u06cc \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u06cc \u0641\u0627\u06cc\u062f\u0647 \u0628\u0648\u062f. \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc numpy \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u06a9\u0627\u0646\u0633 \u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u062e\u0644\u06cc \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0634\u0645\u0627\u0631\u0647 \u06af\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u062e\u0637 \u0628\u0627 \u0633\u0628\u06a9 \u0647\u0627\u06cc \u0641\u0631\u0645\u062a \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\n\n\n
import numpy as np# evenly sampled time at 200ms intervalst = np.arange(0., 5., 0.2)# red dashes, blue squares and green trianglesplt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')plt.show()<\/pre>\n\n\n\n<\/figure><\/h3>\n\n\n\n\u062a\u0631\u0633\u06cc\u0645 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc<\/h3>\n\n\n\n\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\nMatplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\ndata = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u0645\u0648\u0627\u0631\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0627\u0635 \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627 \u0631\u0627 \u0645\u06cc \u062f\u0647\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0628\u0627 numpy.recarray \u06cc\u0627 pandas.DataFrame.<\/p>\n\n\n\n
Matplotlib \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0634\u06cc\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0631\u0627\u0626\u0647\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0634\u06a9\u0627\u0644\u06cc \u0628\u0627 \u0631\u0634\u062a\u0647 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n\n
data = {'a': np.arange(50),\n\n'c': np.random.randint(0, 50, 50),\n\n'd': np.random.randn(50)}\n\ndata['b'] = data['a'] + 10 * np.random.randn(50)\n\ndata['d'] = np.abs(data['d']) * 100\n\nplt.scatter('a', 'b', c='c', s='d', data=data)\n\nplt.xlabel('entry a')\n\nplt.ylabel('entry b')\n\nplt.show()<\/pre>\n\n\n\n<\/figcaption><\/figure>\n\n\n\n\u062e\u0648\u0627\u0635 \u062e\u0637 \u06a9\u0646\u062a\u0631\u0644<\/h3>\n\n\n\n\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0646\u0648\u06cc\u0633\u06cc \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u067e\u06cc\u0634\u0631\u0641\u062a\u0647) <\/a>\n\n \n \n \n \u06f2,\u06f3\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f1,\u06f6\u06f7\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nplt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u062e\u0637\u0648\u0637 \u062f\u0627\u0631\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646\u0647\u0627 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f: \u067e\u0647\u0646\u0627\u06cc \u0628\u0627\u0646\u062f\u060c \u0633\u0628\u06a9 \u062e\u0637\u060c \u0631\u0646\u06af \u062e\u0637 \u0648 \u063a\u06cc\u0631\u0647. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062e\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n
\u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\n
plt.plot(x, y, linewidth=2.0)<\/pre>\n\n\n\n\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\nline, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u0627\u06af\u0631 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u0646\u062f\u0647 \u0646\u0645\u0648\u0646\u0647 Line2D \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0646\u0642\u0634\u0647 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 Line2D \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c .line1, line2 = plot(x1, y1, x2, y2) \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0641\u0631\u0636 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u06a9\u0647 \u0645\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u062e\u0637 \u062f\u0627\u0631\u06cc\u0645 \u0628\u0647 \u0637\u0648\u0631\u06cc \u06a9\u0647 \u0644\u06cc\u0633\u062a \u0628\u0631\u06af\u0634\u062a \u0634\u062f\u0647 \u0627\u0632 \u0637\u0648\u0644 \u06f1 \u0628\u0627\u0634\u062f. \u0645\u0627 \u0627\u0632 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc tuple \u0628\u0627 \u062e\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0648\u0644\u06cc\u0646 \u0639\u0646\u0635\u0631 \u0622\u0646 \u0644\u06cc\u0633\u062a \u0631\u0627 \u0628\u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645:<\/p>\n\n\n\n
line, = plt.plot(x, y, '-')line.set_antialiased(False) # turn off antialiasing<\/pre>\n\n\n\n\u0627\u0632 \u062f\u0633\u062a\u0648\u0631 setp () \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u062f\u0631 \u0645\u062b\u0627\u0644 \u0632\u06cc\u0631 \u0627\u0632 \u06cc\u06a9 \u062f\u0633\u062a\u0648\u0631 \u0628\u0647 \u0633\u0628\u06a9 Matplotlib \u0628\u0631\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0686\u0646\u062f\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0644\u06cc\u0633\u062a \u062e\u0637\u0648\u0637 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. setp \u0628\u0647 \u0637\u0648\u0631 \u0634\u0641\u0627\u0641 \u0628\u0627 \u0644\u06cc\u0633\u062a\u06cc \u0627\u0632 \u0627\u0634\u06cc\u0627\u0621 \u06cc\u0627 \u06cc\u06a9 \u0634\u06cc \u0648\u0627\u062d\u062f \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u06a9\u0644\u0645\u0647 \u06a9\u0644\u06cc\u062f\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u0627 \u062c\u0641\u062a \u0647\u0627\u06cc string\/value \u0628\u0647 \u0633\u0628\u06a9 MATLAB \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n\n\n\nlines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0628\u062e\u0634 \u0645\u0647\u0645 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0633\u0645 \u0627\u0633\u062a. \u062f\u0631 \u0637\u06cc \u0686\u0646\u062f \u0633\u0627\u0644 \u06af\u0630\u0634\u062a\u0647 \u0627\u0646\u0648\u0627\u0639 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u06af\u0631\u0627\u0641\u06cc\u06a9\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u06cc\u0627\u0641\u062a\u0647 \u0627\u0633\u062a. \u062f\u0631 \u0627\u062f\u0627\u0645\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u06cc \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0628\u0627 \u0645\u0627 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627\u0634\u06cc\u062f. \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u062d\u0628\u0648\u0628\u06cc\u062a Python \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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lines = plt.plot(x1, y1, x2, y2)\n\n# use keyword args\n\nplt.setp(lines, color='r', linewidth=2.0)\n\n# or MATLAB style string value pairs\n\nplt.setp(lines, 'color', 'r', 'linewidth', 2.0)<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631<\/h3>\n\n\n\nMATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\ndef f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u0646\u062f\u060c \u0646\u0627\u0627\u0645\u06cc\u062f \u0646\u0634\u0648\u06cc\u062f.<\/p>\n\n\n\n\n \n \n <\/div>\n\n \n \n \u0622\u0645\u0648\u0632\u0634 \u0632\u0628\u0627\u0646 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u062f\u0648\u0646 \u062f\u0627\u0646\u0634 \u0627\u0648\u0644\u06cc\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc <\/a>\n\n \n \n \n \u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc 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\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0632\u0628\u0627\u0646\u06cc […]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
MATLAB \u0648 pyplot \u0645\u0641\u0647\u0648\u0645 \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f. \u062a\u0645\u0627\u0645 \u062f\u0633\u062a\u0648\u0631\u0627\u062a \u062a\u0631\u0633\u06cc\u0645 \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f. \u062a\u0627\u0628\u0639 () gca \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc (Matplotlib.axes.Axes) \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f\u060c \u0648 () gcf \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627\u0632 \u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f (matplotlib.figure.Figure). \u0628\u0647 \u0637\u0648\u0631 \u0645\u0639\u0645\u0648\u0644\u060c \u0644\u0627\u0632\u0645 \u0646\u06cc\u0633\u062a \u0646\u06af\u0631\u0627\u0646 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0628\u0627\u0634\u06cc\u062f\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0645\u0631\u0627\u0642\u0628\u062a \u0645\u06cc \u0634\u0648\u0646\u062f. \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u062f\u0648 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.<\/p>\n\n\n\n
def f(t):\n\nreturn np.exp(-t) * np.cos(2*np.pi*t)\n\nt1 = np.arange(0.0, 5.0, 0.1)\n\nt2 = np.arange(0.0, 5.0, 0.02)\n\nplt.figure()\n\nplt.subplot(211)\n\nplt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')\n\nplt.subplot(212)\n\nplt.plot(t2, np.cos(2*np.pi*t2), 'r--')\n\nplt.show()<\/pre>\n\n\n\n\u06a9\u0627\u0631 \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 \u0645\u062d\u0648\u0631 \u062f\u0631 matplotlib<\/h3>\n\n\n\n\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\nimport matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 \u0646\u0628\u0627\u0634\u06cc\u062f \u0686\u0648\u0646 \u06a9\u0647 \u062d\u0627\u0644\u062a\u00ac\u0647\u0627 \u062f\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib (\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u062a\u0635\u0648\u06cc\u0631 \u0641\u0639\u0644\u06cc\u060c \u0634\u06a9\u0644 \u0648 \u0645\u062d\u0648\u0631\u0647\u0627) \u062f\u0631 \u067e\u0634\u062a \u0635\u062d\u0646\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u062d\u0641\u0638 \u0645\u06cc 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\u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Matplotlib \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0628\u0627\u0634\u06cc\u0645.<\/p>\n","protected":false},"excerpt":{"rendered":"\u0634\u0645\u0627 \u0631\u0648\u0632\u0627\u0646\u0647 \u062d\u062c\u0645 \u0639\u0638\u06cc\u0645\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc 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[…]<\/p>\n","protected":false},"author":78,"featured_media":2386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,9],"tags":[],"class_list":["post-2377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming-and-it-training","category-python-articles"],"_links":{"self":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/comments?post=2377"}],"version-history":[{"count":6,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions"}],"predecessor-version":[{"id":68686,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/posts\/2377\/revisions\/68686"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media\/2386"}],"wp:attachment":[{"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/media?parent=2377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/categories?post=2377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maktabkhooneh.org\/mag\/wp-json\/wp\/v2\/tags?post=2377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\u0641\u0631\u0645\u0627\u0646 () figure \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 figure(1) \u0628\u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f\u060c \u062f\u0642\u06cc\u0642\u0627\u064b \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u06cc\u0634 \u0641\u0631\u0636 (\u06f1\u06f1\u06f1) \u0627\u06af\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0647\u06cc\u0686 \u0645\u062d\u0648\u0631\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0646\u06a9\u0646\u06cc\u062f \u0628\u0647 \u0637\u0648\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f. command \u062f\u0631 \u0641\u0631\u0645\u0627\u0646 subplot \u0627\u06af\u0631 numrows * numcols<\/p>\n\n\n\n
\u0634\u0645\u0627 \u062f\u0631 Matplotlib \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u062f\u0644\u062e\u0648\u0627\u0647\u06cc \u0627\u0632 \u062e\u0631\u062f\u0647 \u0647\u0627\u06cc \u0641\u0631\u0639\u06cc \u0648 \u0645\u062d\u0648\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062d\u0648\u0631\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f\u060c \u0627\u0632 \u062f\u0633\u062a\u0648\u0631 () axes \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u06a9\u0647 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u06a9\u0627\u0646 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 ([\u0633\u0645\u062a \u0686\u067e \u060c \u067e\u0627\u06cc\u06cc\u0646 \u060c \u0639\u0631\u0636 \u060c \u0627\u0631\u062a\u0641\u0627\u0639]) \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0647 \u0634\u06a9\u0644 \u06a9\u0633\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. Axes Demo \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0646 \u0645\u062d\u0648\u0631\u0647\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u06cc \u0648 Basic Subplot Demo \u0646\u0645\u0648\u0646\u0647 \u0628\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0628\u0627 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\n\n\n
\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 figure() \u062a\u0639\u062f\u0627\u062f \u0628\u06cc\u0634\u062a\u0631\u06cc \u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631 \u0635\u0641\u062d\u0647 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f. \u0627\u0644\u0628\u062a\u0647\u060c \u0647\u0631 \u0634\u06a9\u0644 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062d\u0627\u0648\u06cc \u0645\u062d\u0648\u0631\u0647\u0627 \u0648 \u0632\u06cc\u0631\u0634\u0627\u062e\u0647 \u0647\u0627\u06cc\u06cc \u0628\u0627\u0634\u062f \u0647\u0631 \u0637\u0648\u0631 \u06a9\u0647 \u0634\u0645\u0627 \u0635\u0644\u0627\u062d \u0628\u062f\u0627\u0646\u06cc\u062f \u0630\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u067e\u0631\u062f\u0627\u0632\u06cc\u0645.<\/p>\n\n\n\n
import matplotlib.pyplot as plt\n\nplt.figure(1) # the first figure\n\nplt.subplot(211) # the first subplot in the first figure\n\nplt.plot([1, 2, 3])\n\nplt.subplot(212) # the second subplot in the first figure\n\nplt.plot([4, 5, 6])\n\n\n\n\nplt.figure(2) # a second figure\n\nplt.plot([4, 5, 6]) # creates a subplot(111) by default\n\n\n\n\nplt.figure(1) # figure 1 current; subplot(212) still current\n\nplt.subplot(211) # make subplot(211) in figure1 current\n\nplt.title('Easy as 1, 2, 3') # subplot 211 title<\/pre>\n\n\n\n\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0634\u06a9\u0644 \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 \u062a\u0627\u0628\u0639 () clf \u0648 \u0645\u062d\u0648\u0631\u0647\u0627\u06cc \u0641\u0639\u0644\u06cc \u0631\u0627 \u0628\u0627 () cla\u067e\u0627\u06a9 \u06a9\u0646\u06cc\u062f. \u0627\u06af\u0631 \u0627\u062d\u0633\u0627\u0633 \u0645\u0634\u06a9\u0644\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0646\u06af\u0631\u0627\u0646 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\u06f1,\u06f0\u06f9\u06f9,\u06f0\u06f0\u06f0 <\/span>\n\n \n \n \u06f7\u06f6\u06f9,\u06f3\u06f0\u06f0 <\/span>\n \u062a\u0648\u0645\u0627\u0646<\/span>\n <\/span>\n\n \n \u06f3\u06f0% <\/div>\n \n <\/div>\n \n \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062e\u0631\u06cc\u062f <\/button>\n <\/div>\n<\/div>\n<\/div><\/div><\/div>\n\n\n\u0627\u06cc\u0646 \u0641\u0642\u0637 \u06cc\u06a9 \u0631\u0648\u0634 \u062d\u0627\u0644\u062a\u06cc \u062e\u0627\u0635 \u062f\u0631 \u0627\u0637\u0631\u0627\u0641 \u06cc\u06a9 API \u0634\u06cc \u06af\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f. \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u0645\u0637\u0627\u0644\u0628 \u0645\u0647\u0645\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u0631\u0633\u0645 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 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