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Finished documenting operators module
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‎docs/build/doctrees/environment.pickle

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‎docs/build/html/py-modindex.html

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<td><img src="_static/minus.png" class="toggler"
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id="toggle-1" style="display: none" alt="-" /></td>
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‎docs/build/html/searchindex.js

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‎examples/Example_1.py

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@@ -190,7 +190,7 @@ def GRAD_TEST_FUNC(t, x): # ∇φ_t(x)
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data = DGCG.operators.K_t_star_full(measure)
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# uncomment the next line to see the backprojected data
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable.data = -data
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# dual_variable._data = -data
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# ani_1 = dual_variable.animate(measure = measure, block = True)
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# uncomment to see the noisy backprojected data
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable.data = -data
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# dual_variable._data = -data
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# ani_2 = dual_variable.animate(measure = measure, block = True)
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# settings to speed up the convergence.

‎examples/Example_2.py

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@@ -261,7 +261,7 @@ def GRAD_TEST_FUNC(t, x): # ∇φ_t(x)
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data = DGCG.operators.K_t_star_full(measure)
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# uncomment the next line to see the backprojected data
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable.data = -data
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# dual_variable._data = -data
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# ani_1 = dual_variable.animate(measure = measure, block = True)
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# uncomment to see the noisy backprojected data
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable.data = -data
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# dual_variable._data = -data
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# ani_2 = dual_variable.animate(measure = measure, block = True)
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# settings to speed up the convergence.

‎examples/Example_2b.py

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@@ -261,7 +261,7 @@ def GRAD_TEST_FUNC(t, x): # ∇φ_t(x)
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data = DGCG.operators.K_t_star_full(measure)
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# uncomment the next line to see the backprojected data
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# ani_2 = dual_variable.animate(measure = measure, block = True)
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# settings to speed up the convergence.

‎examples/Example_2b_accelerated.py

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@@ -261,7 +261,7 @@ def GRAD_TEST_FUNC(t, x): # ∇φ_t(x)
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data = DGCG.operators.K_t_star_full(measure)
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# dual_variable = DGCG.classes.dual_variable(DGCG.classes.measure())
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# ani_2 = dual_variable.animate(measure = measure, block = True)
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# Input dual-gap tolerance

‎examples/Example_3.py

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data = DGCG.operators.K_t_star_full(measure)
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‎src/DGCG.py

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operators.K = rounded_H_dim
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operators.test_func = test_func
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operators.grad_test_func = grad_test_func
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operators.H_DIMENSIONS = rounded_H_dim
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operators.TEST_FUNC = test_func
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operators.GRAD_TEST_FUNC = grad_test_func
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def solve(data, **kwargs):

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