From e92c84ba37bd991b5a7f093fbc411280568ea380 Mon Sep 17 00:00:00 2001 From: nishanpoojary Date: Tue, 26 May 2020 12:34:24 +0530 Subject: Upload scalar-functions Folder --- .../scalar-functions/Scalar_Function_Quiz.pdf | Bin 0 -> 87455 bytes .../scalar-functions/file1_domain_range.py | 132 +++++++++++++++ .../file2_scalar_function_application.py | 129 +++++++++++++++ .../scalar-functions/file3_parabola_example.py | 35 ++++ .../scalar-functions/file4_neural_nets.py | 177 +++++++++++++++++++++ .../scalar-functions/gifs/file1_domain_range.gif | Bin 0 -> 74879 bytes .../gifs/file2_scalar_function_application.gif | Bin 0 -> 225144 bytes .../gifs/file3_parabola_example.gif | Bin 0 -> 905534 bytes .../scalar-functions/gifs/file4_neural_nets.gif | Bin 0 -> 95828 bytes 9 files changed, 473 insertions(+) create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/Scalar_Function_Quiz.pdf create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file1_domain_range.py create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file2_scalar_function_application.py create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file3_parabola_example.py create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file4_neural_nets.py create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file1_domain_range.gif create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file2_scalar_function_application.gif create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file3_parabola_example.gif create mode 100644 FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file4_neural_nets.gif (limited to 'FSF-2020') diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/Scalar_Function_Quiz.pdf b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/Scalar_Function_Quiz.pdf new file mode 100644 index 0000000..6d94a2c Binary files /dev/null and b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/Scalar_Function_Quiz.pdf differ diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file1_domain_range.py b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file1_domain_range.py new file mode 100644 index 0000000..9b1ca7b --- /dev/null +++ b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file1_domain_range.py @@ -0,0 +1,132 @@ +# Plotting Graphs +from manimlib.imports import * + +class PlotGraphs(GraphScene): + CONFIG = { + "x_min": -5, + "x_max": 5, + "y_min": 0, + "y_max": 4, + "graph_origin": ORIGIN + 2.5* DOWN, + "x_labeled_nums": list(range(-5, 6)), + "y_labeled_nums": list(range(0, 5)), + } + def construct(self): + + topic = TextMobject("Domain and Range") + topic.scale(2) + topic.set_color(YELLOW) + self.play(Write(topic)) + self.play(FadeOut(topic)) + self.wait(1) + + + XTD = self.x_axis_width/(self.x_max- self.x_min) + YTD = self.y_axis_height/(self.y_max- self.y_min) + + self.setup_axes(animate = True) + + graphobj = self.get_graph(lambda x : np.sqrt(x + 4), x_min = -4, x_max = 5) + graph_lab = self.get_graph_label(graphobj, label = r"\sqrt{x + 4}") + + + rangeline1 = Arrow(self.graph_origin+2.2*YTD*UP+5*XTD*LEFT, self.graph_origin+4.1*YTD*UP+5*XTD*LEFT) + rangeline2 = Arrow(self.graph_origin+1.7*YTD*UP+5*XTD*LEFT, self.graph_origin+5*XTD*LEFT) + rangeline1.set_color(RED) + rangeline2.set_color(RED) + + rangeMsg = TextMobject(r"Range: $y \geq 0$") + rangeMsg.move_to(self.graph_origin+2*YTD*UP+5*XTD*LEFT) + rangeMsg.scale(0.5) + rangeMsg.set_color(YELLOW) + + domainline1 = Line(self.graph_origin+0.6*YTD*DOWN+1.2*XTD*LEFT, self.graph_origin+0.6*YTD*DOWN + 4*XTD*LEFT) + domainline2 = Arrow(self.graph_origin+0.6*YTD*DOWN+1.1*XTD*RIGHT, self.graph_origin+0.6*YTD*DOWN + 5.3*XTD*RIGHT) + domainline1.set_color(PINK) + domainline2.set_color(PINK) + + domainMsg = TextMobject(r"Domain: $x \geq -4$") + domainMsg.move_to(self.graph_origin+0.6*YTD*DOWN) + domainMsg.scale(0.5) + domainMsg.set_color(GREEN) + + + + + self.play(ShowCreation(graphobj)) + self.play(ShowCreation(graph_lab)) + self.wait(1) + self.play(GrowArrow(rangeline1)) + self.play(GrowArrow(rangeline2)) + self.play(Write(rangeMsg)) + self.wait(1) + self.play(GrowArrow(domainline1)) + self.play(GrowArrow(domainline2)) + self.play(Write(domainMsg)) + self.wait(3) + + self.wait(2) + + + + +class PlotSineGraphs(GraphScene): + CONFIG = { + "x_min": -8, + "x_max": 8, + "y_min": -1, + "y_max": 1, + "graph_origin": ORIGIN, + "x_labeled_nums": list(range(-8, 9)), + "y_labeled_nums": list(range(-1, 2)), + } + def construct(self): + + + + XTD = self.x_axis_width/(self.x_max- self.x_min) + YTD = self.y_axis_height/(self.y_max- self.y_min) + + self.setup_axes(animate = True) + + sineobj = self.get_graph(lambda x : np.sin(x), x_min = -7, x_max = 8) + sine_lab = self.get_graph_label(sineobj, label = "\\sin(x)") + + + rangeline1 = Line(8*XTD*LEFT,1*YTD*UP+8*XTD*LEFT) + rangeline2 = Line(8*XTD*LEFT,1*YTD*DOWN+8*XTD*LEFT) + rangeline1.set_color(RED) + rangeline2.set_color(RED) + + rangeMsg = TextMobject(r"Range: $-1 \leq y \leq 1$") + rangeMsg.move_to(1.1*YTD*UP+8.5*XTD*LEFT) + rangeMsg.scale(0.5) + rangeMsg.set_color(YELLOW) + + + domainline1 = Arrow(1.1*YTD*DOWN+2*XTD*LEFT, 1.1*YTD*DOWN + 8.5*XTD*LEFT) + domainline2 = Arrow(1.1*YTD*DOWN+2*XTD*RIGHT, 1.1*YTD*DOWN + 8.5*XTD*RIGHT) + domainline1.set_color(PINK) + domainline2.set_color(PINK) + + domainMsg = TextMobject(r"Domain: $[-\infty, \infty]$") + domainMsg.move_to(1.1*YTD*DOWN) + domainMsg.scale(0.5) + domainMsg.set_color(GREEN) + + + + self.play(ShowCreation(sineobj)) + self.play(ShowCreation(sine_lab)) + self.wait(1) + self.play(GrowArrow(rangeline1)) + self.play(GrowArrow(rangeline2)) + self.play(Write(rangeMsg)) + self.wait(1) + self.play(GrowArrow(domainline1)) + self.play(GrowArrow(domainline2)) + self.play(Write(domainMsg)) + self.wait(3) + + + \ No newline at end of file diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file2_scalar_function_application.py b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file2_scalar_function_application.py new file mode 100644 index 0000000..56b3e53 --- /dev/null +++ b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file2_scalar_function_application.py @@ -0,0 +1,129 @@ +from manimlib.imports import * + +class ScalarApplication(ThreeDScene): + def construct(self): + axes = ThreeDAxes() # creates a 3D Axis + + cube = Cube() + cube.set_fill(YELLOW_E, opacity = 0.1) + cube.scale(2) + self.set_camera_orientation(phi=0 * DEGREES,theta=270*DEGREES) + self.play(ShowCreation(cube),ShowCreation(axes)) + + dot = Sphere() + dot.scale(0.1) + dot.move_to(np.array([1,0.5,1])) + dot.set_fill(RED) + + #dot = Dot(np.array([1,0.5,1]), color = RED) + temp_func = TextMobject("T(x,y,z)") + temp_func.next_to(dot,RIGHT) + temp_func.set_color(RED) + temp_func_trans = TextMobject("T(1,0.5,1)") + temp_func_trans.next_to(dot,RIGHT) + temp_func_trans.set_color(RED) + temp = TextMobject(r"$36 ^\circ$") + temp.next_to(dot,RIGHT) + temp.set_color(RED_E) + + + self.play(ShowCreation(dot)) + self.play(ShowCreation(temp_func)) + self.play(Transform(temp_func, temp_func_trans)) + self.wait(1) + self.play(Transform(temp_func, temp)) + + + + + dot1 = Sphere() + dot1.scale(0.1) + dot1.move_to(np.array([-1,-0.8,-1.5])) + dot1.set_fill(BLUE_E) + #dot1 = Dot(np.array([-1,-0.8,-1.5]), color = BLUE) + temp_func1 = TextMobject("T(x,y,z)") + temp_func1.next_to(dot1,LEFT) + temp_func1.set_color(BLUE) + temp_func_trans1 = TextMobject("T(-1,-0.8,-1.5)") + temp_func_trans1.next_to(dot1,LEFT) + temp_func_trans1.set_color(BLUE) + temp1 = TextMobject(r"$24 ^\circ$") + temp1.next_to(dot1,LEFT) + temp1.set_color(BLUE) + + self.play(ShowCreation(dot1)) + self.play(ShowCreation(temp_func1)) + self.play(Transform(temp_func1, temp_func_trans1)) + self.wait(1) + self.play(Transform(temp_func1, temp1)) + + self.play(FadeOut(temp_func)) + self.play(FadeOut(temp_func1)) + + + self.move_camera(phi=80* DEGREES,theta=45*DEGREES,run_time=3) + + self.begin_ambient_camera_rotation(rate=0.2) + self.wait(4) + self.stop_ambient_camera_rotation() + self.wait(2) + + + + +class AddTempScale(Scene): + def construct(self): + temp_scale = ImageMobject("tempscale.png") + temp_scale.scale(4) + temp_scale.move_to(2*RIGHT) + self.play(ShowCreation(temp_scale)) + + + temp_func = TextMobject("T(x,y,z)") + temp_func.move_to(3*UP +2*LEFT) + temp_func.set_color(RED) + temp_func_trans = TextMobject("T(1,0.5,1)") + temp_func_trans.move_to(3*UP +2*LEFT) + temp_func_trans.set_color(RED) + temp = TextMobject(r"$36 ^\circ$") + temp.set_color(RED) + temp.move_to(3*UP +2*LEFT) + temp.scale(0.7) + + self.play(ShowCreation(temp_func)) + self.play(Transform(temp_func, temp_func_trans)) + self.wait(1) + self.play(Transform(temp_func, temp)) + self.play(ApplyMethod(temp_func.move_to, 1.8*UP +1.8*RIGHT)) + + + temp_func1 = TextMobject("T(x,y,z)") + temp_func1.move_to(2*UP +2*LEFT) + temp_func1.set_color(BLUE) + temp_func_trans1 = TextMobject("T(-1,-0.8,-1.5)") + temp_func_trans1.move_to(2*UP +2*LEFT) + temp_func_trans1.set_color(BLUE) + temp1 = TextMobject(r"$24 ^\circ$") + temp1.set_color(BLUE) + temp1.move_to(2*UP +2*LEFT) + temp1.scale(0.7) + + self.play(ShowCreation(temp_func1)) + self.play(Transform(temp_func1, temp_func_trans1)) + self.wait(1) + self.play(Transform(temp_func1, temp1)) + self.play(ApplyMethod(temp_func1.move_to, 0.6*UP +1.8*RIGHT)) + + + + transtext = TextMobject("Scalar Function Transform:") + transtext.set_color(GREEN) + transtext1 = TextMobject(r"$\mathbb{R}^3 \rightarrow \mathbb{R}$") + transtext1.set_color(YELLOW_E) + transtext.move_to(3*UP +3*LEFT) + transtext1.next_to(transtext,DOWN) + self.play(Write(transtext)) + self.play(Write(transtext1)) + self.wait(2) + + diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file3_parabola_example.py b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file3_parabola_example.py new file mode 100644 index 0000000..74dc063 --- /dev/null +++ b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file3_parabola_example.py @@ -0,0 +1,35 @@ +from manimlib.imports import * + +class Parabola(ThreeDScene): + def construct(self): + axes = ThreeDAxes() # creates a 3D Axis + + paraboloid = ParametricSurface( + lambda u, v: np.array([ + 2*np.cosh(u)*np.cos(v), + 2*np.cosh(u)*np.sin(v), + 2*np.sinh(u) + ]),v_min=0,v_max=TAU,u_min=0,u_max=2,checkerboard_colors=[YELLOW_D, YELLOW_E], + resolution=(15, 32)) + + text3d = TextMobject(r"Plot of $f: \mathbb{R}^2 \rightarrow \mathbb{R}$", "z = f(x,y)") + self.add_fixed_in_frame_mobjects(text3d) + text3d[0].move_to(4*LEFT+2*DOWN) + text3d[1].next_to(text3d[0], DOWN) + text3d[0].set_color_by_gradient(RED, ORANGE, YELLOW, GREEN, BLUE, PURPLE) + text3d[1].set_color_by_gradient(RED, ORANGE, YELLOW, GREEN, BLUE) + + #self.set_camera_orientation(phi=0 * DEGREES,theta=270*DEGREES) + self.move_camera(phi=110* DEGREES,theta=45*DEGREES) + self.add(axes) + self.play(ShowCreation(paraboloid)) + self.play(Write(text3d[0])) + self.play(Write(text3d[1])) + self.begin_ambient_camera_rotation(rate=0.2) + self.wait(3) + self.move_camera(phi=0 * DEGREES,theta=180*DEGREES,run_time=3) + self.wait(3) + self.move_camera(phi=110* DEGREES,theta=90*DEGREES,run_time=3) + self.wait(3) + + \ No newline at end of file diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file4_neural_nets.py b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file4_neural_nets.py new file mode 100644 index 0000000..eb6bf45 --- /dev/null +++ b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/file4_neural_nets.py @@ -0,0 +1,177 @@ +from manimlib.imports import * + +class SigmoidFunc(GraphScene): + CONFIG = { + "x_min": -4, + "x_max": 4, + "y_min": -1, + "y_max": 1, + "graph_origin": ORIGIN + 0.8*DOWN, + "x_labeled_nums": list(range(-4, 5)), + "y_labeled_nums": list(range(-1, 2)), + "y_axis_height": 4.5, + } + def construct(self): + XTD = self.x_axis_width/(self.x_max- self.x_min) + YTD = self.y_axis_height/(self.y_max- self.y_min) + + topic = TextMobject("Sigmoid Function") + topic.move_to(3.2*UP) + topic.set_color_by_gradient(RED, ORANGE, YELLOW, GREEN, BLUE, PURPLE) + + self.setup_axes(animate = True) + sigmoid_func = self.get_graph(lambda x : (1/(1 + np.exp(-x))), x_min = -4, x_max = 4) + sigmoid_lab = self.get_graph_label(sigmoid_func, label = r"\frac{1}{1 + e^{-z}}") + + + + + self.play(ShowCreation(sigmoid_func),Write(sigmoid_lab)) + self.play(Write(topic)) + self.wait(2) + self.play(FadeOut(sigmoid_func), FadeOut(sigmoid_lab)) + self.wait(1) + + + +class NeuralNet(GraphScene): + def construct(self): + + sigmoid_exp = TextMobject(r"g(z) = g($\theta^T$ X) = $\frac{1}{1 + e^{-z}}$") + sigmoid_exp.move_to(3*UP + 4*LEFT) + sigmoid_exp.scale(0.8) + sigmoid_exp.set_color(BLUE) + sigmoid_exp1 = TextMobject(r"Predict: 'y = 1'",r"When g(z) $\geq$ 0.5, z $\geq$ 0, $\theta^T$ X $\geq$ 0") + sigmoid_exp2 = TextMobject(r"Predict: 'y = 0'", r"When g(z) $\leq$ 0.5, z $\leq$ 0, $\theta^T$ X $\leq$ 0") + sigmoid_exp1.scale(0.5) + sigmoid_exp2.scale(0.5) + sigmoid_exp1.set_color(PURPLE) + sigmoid_exp2.set_color(PURPLE) + + sigmoid_exp1[0].next_to(sigmoid_exp, 1.5*DOWN) + sigmoid_exp1[1].next_to(sigmoid_exp1[0], DOWN) + sigmoid_exp2[0].next_to(sigmoid_exp1[1], 1.5*DOWN) + sigmoid_exp2[1].next_to(sigmoid_exp2[0], DOWN) + + + self.play(Write(sigmoid_exp)) + self.play(Write(sigmoid_exp1[0]), Write(sigmoid_exp1[1])) + self.play(Write(sigmoid_exp2[0]), Write(sigmoid_exp2[1])) + self.wait(2) + + + neuron1 = Circle() + neuron1.set_fill(YELLOW_A, opacity = 0.5) + + neuron2 = Circle() + neuron2.set_fill(ORANGE, opacity = 0.5) + + neuron3 = Circle() + neuron3.set_fill(GREEN_E, opacity = 0.5) + + neuron1.move_to(2*UP+RIGHT) + neuron2.move_to(2*DOWN+RIGHT) + neuron3.move_to(4*RIGHT) + + arrow1 = Arrow(neuron1.get_right(),neuron3.get_left(),buff=0.1) + arrow1.set_color(RED) + arrow2 = Arrow(neuron2.get_right(),neuron3.get_left(),buff=0.1) + arrow2.set_color(RED) + + arrow3 = Arrow(neuron3.get_right(),7*RIGHT,buff=0.1) + arrow3.set_color(RED) + + + sign1 = TextMobject("+1") + sign1.move_to(2*UP+RIGHT) + sign1.scale(2) + sign2 = TextMobject(r"$x_1$") + sign2.move_to(2*DOWN+RIGHT) + sign2.scale(2) + sign3 = TextMobject(r"$h_{\theta}(x)$") + sign3.move_to(6*RIGHT+0.4*DOWN) + sign3.scale(0.7) + sign4 = TextMobject(r"$= g(10 - 20x_1)$") + sign4.next_to(sign3,DOWN) + sign4.scale(0.5) + sign5 = TextMobject(r"$= g(10 - 20x_1)$") + sign5.next_to(sign3,DOWN) + sign5.scale(0.5) + sign6 = TextMobject(r"$= g(10 - 20x_1)$") + sign6.next_to(sign3,DOWN) + sign6.scale(0.5) + + + weight1 = TextMobject("10") + weight1.next_to(arrow1,UP) + weight2 = TextMobject("-20") + weight2.next_to(arrow2,DOWN) + + gate = TextMobject("NOT GATE") + gate.set_color_by_gradient(RED, ORANGE, YELLOW, GREEN, BLUE, PURPLE) + gate.scale(1.5) + gate.move_to(3*RIGHT+3.5*UP) + + + + truth_table = TextMobject(r"\begin{displaymath}\begin{array}{|c|c|} x & y\\ \hline 1 & 0 \\0 & 1 \\\end{array}\end{displaymath}") + truth_table.next_to(sigmoid_exp2[1], 3*DOWN) + + values = TextMobject("1", "0") + values.scale(2) + + sign4_trans1 = TextMobject(r"$= g(10 - 20(1))$") + sign4_trans2 = TextMobject(r"$= g(10 - 20(0))$") + sign4_trans1.next_to(sign3,DOWN) + sign4_trans2.next_to(sign3,DOWN) + sign4_trans1.scale(0.5) + sign4_trans2.scale(0.5) + + + + output1 = TextMobject("y = 0") + output2 = TextMobject("y = 1") + output1.next_to(sign4,DOWN) + output2.next_to(sign4,DOWN) + output1.scale(1.5) + output2.scale(1.5) + + + + self.play(ShowCreation(neuron1),ShowCreation(neuron2)) + self.play(ShowCreation(neuron3)) + self.play(ShowCreation(sign1),ShowCreation(sign2)) + self.wait(1) + + self.play(GrowArrow(arrow1)) + self.play(GrowArrow(arrow2)) + self.play(ShowCreation(weight1),ShowCreation(weight2)) + + + + self.play(GrowArrow(arrow3)) + self.play(Write(sign3),Write(sign4)) + + self.play(Write(gate)) + self.play(ShowCreation(truth_table)) + + self.play(ApplyMethod(values[0].move_to, 2*DOWN+RIGHT)) + self.play(FadeOut(values[0])) + self.play(Transform(sign4,sign4_trans1)) + self.play(Write(output1)) + self.wait(1) + self.play(FadeOut(output1)) + self.play(Transform(sign4, sign5)) + + + self.play(ApplyMethod(values[1].move_to, 2*DOWN+RIGHT)) + self.play(FadeOut(values[1])) + self.play(Transform(sign4,sign4_trans2)) + self.play(Write(output2)) + self.wait(1) + self.play(FadeOut(output2)) + self.play(Transform(sign4, sign6)) + + self.wait(2) + + diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file1_domain_range.gif b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file1_domain_range.gif new file mode 100644 index 0000000..d0351e5 Binary files /dev/null and b/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file1_domain_range.gif differ diff --git a/FSF-2020/calculus-of-several-variables/multivariable-functions-and-paritial-derivatives/scalar-functions/gifs/file2_scalar_function_application.gif 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