[a84a0ca] | 1 | r""" |
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| 2 | This model calculates intensity using simple linear function |
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| 3 | |
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| 4 | Definition |
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| 5 | ---------- |
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| 6 | |
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| 7 | The scattering intensity $I(q)$ is calculated as |
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| 8 | |
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| 9 | .. math:: |
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| 10 | |
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[416609b] | 11 | I(q) = \text{scale} (A + B \cdot q) + \text{background} |
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[a84a0ca] | 12 | |
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| 13 | .. note:: |
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| 14 | For 2D plots intensity has different definition than other shape independent models |
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| 15 | |
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| 16 | .. math:: |
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[416609b] | 17 | I(q) = \text{scale} (I(qx) \cdot I(qy)) + \text{background} |
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[a84a0ca] | 18 | |
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| 19 | References |
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| 20 | ---------- |
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| 21 | |
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| 22 | None. |
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| 23 | |
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| 24 | """ |
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| 25 | from numpy import inf |
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| 26 | |
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| 27 | name = "line" |
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| 28 | title = "Line model" |
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| 29 | description = """\ |
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| 30 | I(q) = A + B*q |
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| 31 | |
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| 32 | List of default parameters: |
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| 33 | A = intercept |
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| 34 | B = slope |
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| 35 | """ |
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| 36 | category = "shape-independent" |
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| 37 | |
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| 38 | # pylint: disable=bad-whitespace, line-too-long |
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| 39 | # ["name", "units", default, [lower, upper], "type", "description"], |
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| 40 | parameters = [["intercept", "1/cm", 1.0, [-inf, inf], "", "intercept in linear model"], |
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| 41 | ["slope", "Ang/cm", 1.0, [-inf, inf], "", "slope in linear model"], |
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| 42 | ] |
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| 43 | # pylint: enable=bad-whitespace, line-too-long |
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| 44 | |
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| 45 | def Iq(q, intercept, slope): |
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| 46 | """ |
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| 47 | :param q: Input q-value |
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| 48 | :param intercept: Intrecept in linear model |
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| 49 | :param slope: Slope in linear model |
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| 50 | :return: Calculated Intensity |
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| 51 | """ |
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| 52 | inten = intercept + slope*q |
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| 53 | return inten |
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| 54 | |
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| 55 | Iq.vectorized = True # Iq accepts an array of q values |
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| 56 | |
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| 57 | def Iqxy(qx, qy, *args): |
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| 58 | """ |
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| 59 | :param qx: Input q_x-value |
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| 60 | :param qy: Input q_y-value |
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| 61 | :param args: Remaining arguments |
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| 62 | :return: 2D-Intensity |
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| 63 | """ |
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[416609b] | 64 | # TODO: SasView documents 2D intensity as Iq(qx)*Iq(qy), but returns Iq(qy) |
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| 65 | # Note: SasView.run([r, theta]) does return Iq(qx)*Iq(qy) |
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[a84a0ca] | 66 | return Iq(qx, *args)*Iq(qy, *args) |
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| 67 | |
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[2c74c11] | 68 | Iqxy.vectorized = True # Iqxy accepts an array of qx qy values |
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| 69 | |
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[a84a0ca] | 70 | |
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| 71 | tests = [ |
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[416609b] | 72 | [{'intercept': 1.0, 'slope': 1.0, }, 1.0, 2.001], |
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| 73 | [{'intercept': 1.0, 'slope': 1.0, }, 0.0, 1.001], |
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| 74 | [{'intercept': 1.0, 'slope': 1.0, }, 0.4, 1.401], |
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| 75 | [{'intercept': 1.0, 'slope': 1.0, }, 1.3, 2.301], |
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| 76 | [{'intercept': 1.0, 'slope': 1.0, }, 0.5, 1.501], |
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| 77 | [{'intercept': 1.0, 'slope': 1.0, }, [0.4, 0.5], [1.401, 1.501]], |
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| 78 | [{'intercept': 1.0, 'slope': 1.0, 'background': 0.0, }, (1.3, 1.57), 5.911], |
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[a84a0ca] | 79 | ] |
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