process(None) return pd.Series of units

physicslab/experiment/curie_temperature.py

@@ -21,18 +21,25 @@ def process(data):
     Parameter :attr:`data` must include temperature and magnetization.
     See :class:`Columns` for details and column names.
 
-    :param data: Measured data
+    :param data: Measured data. If None, return units instead
     :type data: pandas.DataFrame
-    :return: Derived quantities listed in :meth:`Columns.output`.
+    :return: Derived quantities listed in :meth:`Columns.output` or units
     :rtype: pandas.Series
     """
-    measurement = Measurement(data)
+    if data is None:
+        from physicslab.experiment import UNITS
+        name = UNITS
+        curie_temperature = 'K'
 
-    curie_temperature = measurement.analyze()
+    else:
+        name = get_name(data)
+        measurement = Measurement(data)
+
+        curie_temperature = measurement.analyze()
 
     return pd.Series(
         data=(curie_temperature,),
-        index=Columns.output(), name=get_name(data))
+        index=Columns.output(), name=name)
 
 
 class Columns(_ColumnsBase):

physicslab/experiment/hall.py

@@ -10,7 +10,7 @@
 
 from scipy.constants import e as elementary_charge
 
-from physicslab.electricity import carrier_concentration, Mobility, Resistance
+from physicslab.electricity import Carrier_concentration, Mobility, Resistance
 from physicslab.ui import plot_grid
 from physicslab.utility import _ColumnsBase, squarificate, get_name
 
@@ -24,29 +24,42 @@ def process(data, thickness=None, sheet_resistance=None):
     The optional parameters allows to calculate additional quantities:
     `concentration` and `mobility`.
 
-    :param data: Measured data
-    :type data: pandas.DataFrame
+    :param data: Measured data. If None, return units instead
+    :type data: pandas.DataFrame or None
     :param thickness: Sample dimension perpendicular to the plane marked
         by the electrical contacts, defaults to None
     :type thickness: float, optional
     :param sheet_resistance: Defaults to None
     :type sheet_resistance: float, optional
-    :return: Derived quantities listed in :meth:`Columns.output`.
+    :return: Derived quantities listed in :meth:`Columns.output` or units
     :rtype: pandas.Series
     """
-    measurement = Measurement(data)
-    (concentration, mobility) = [np.nan] * 2
-
-    sheet_density, conductivity_type, residual = measurement.analyze()
-    if thickness is not None:
-        concentration = carrier_concentration(sheet_density, thickness)
-    if sheet_resistance is not None:
-        mobility = Mobility.from_sheets(sheet_density, sheet_resistance)
+    if data is None:
+        from physicslab.experiment import UNITS
+        import physicslab.electricity as el
+        name = UNITS
+        sheet_density = el.Carrier_sheet_concentration.UNIT
+        conductivity_type = '<str>'
+        residual = 'T^2'  # Squared y-axis while fitting.
+        concentration = el.Carrier_concentration.UNIT
+        mobility = el.Mobility.UNIT
+
+    else:
+        name = get_name(data)
+        measurement = Measurement(data)
+        (concentration, mobility) = [np.nan] * 2
+
+        sheet_density, conductivity_type, residual = measurement.analyze()
+        if thickness is not None:
+            concentration = Carrier_concentration.from_sheet_density(
+                sheet_density, thickness)
+        if sheet_resistance is not None:
+            mobility = Mobility.from_sheets(sheet_density, sheet_resistance)
 
     return pd.Series(
         data=(sheet_density, conductivity_type, residual,
               concentration, mobility),
-        index=Columns.output(), name=get_name(data))
+        index=Columns.output(), name=name)
 
 
 class Columns(_ColumnsBase):
@@ -57,7 +70,7 @@ class Columns(_ColumnsBase):
     MAGNETICFIELD = 'B'
     HALLVOLTAGE = 'VH'
     CURRENT = 'I'
-    SHEET_DENSITY = 'sheet_density'
+    SHEET_DENSITY = 'sheet_density'  # Carrier.
     CONDUCTIVITY_TYPE = 'conductivity_type'
     RESIDUAL = 'residual'
     CONCENTRATION = 'concentration'

physicslab/experiment/magnetism_type.py

@@ -24,33 +24,48 @@ def process(data, diamagnetism=True, ferromagnetism=True):
     Output :attr:`ratio_DM_FM` compares max values - probably for the
     strongest magnetic field.
 
-    :param pandas.DataFrame data: Measured data
+    :param data: Measured data. If None, return units instead
+    :type data: pandas.DataFrame or None
     :param diamagnetism: Look for diamagnetism contribution, defaults to True
     :type diamagnetism: bool, optional
     :param ferromagnetism: Look for ferromagnetism contribution,
         defaults to True
     :type ferromagnetism: bool, optional
-    :return: Derived quantities listed in :meth:`Columns.output`.
+    :return: Derived quantities listed in :meth:`Columns.output` or units
     :rtype: pandas.Series
     """
-    measurement = Measurement(data)
-    (magnetic_susceptibility, offset, saturation, remanence,
-     coercivity, ratio_DM_FM) = [np.nan] * 6
-
-    if diamagnetism:
-        magnetic_susceptibility, offset = measurement.diamagnetism(
-            from_residual=True)
-    if ferromagnetism:
-        saturation, remanence, coercivity = measurement.ferromagnetism(
-            from_residual=True)
-    if diamagnetism and ferromagnetism:
-        ratio_DM_FM = abs(measurement.data[Columns.DIAMAGNETISM].iloc[-1]
-                          / measurement.data[Columns.FERROMAGNETISM].iloc[-1])
+    if data is None:
+        from physicslab.experiment import UNITS
+        name = UNITS
+        # [B] = Oe; [M] = emu
+        magnetic_susceptibility = 'emu/Oe'
+        offset = 'emu'
+        saturation = 'emu'
+        remanence = 'emu'
+        coercivity = 'Oe'
+        ratio_DM_FM = '1'
+
+    else:
+        name = get_name(data)
+        measurement = Measurement(data)
+        (magnetic_susceptibility, offset, saturation, remanence,
+         coercivity, ratio_DM_FM) = [np.nan] * 6
+
+        if diamagnetism:
+            magnetic_susceptibility, offset = measurement.diamagnetism(
+                from_residual=True)
+        if ferromagnetism:
+            saturation, remanence, coercivity = measurement.ferromagnetism(
+                from_residual=True)
+        if diamagnetism and ferromagnetism:
+            ratio_DM_FM = abs(
+                measurement.data[Columns.DIAMAGNETISM].iloc[-1]
+                / measurement.data[Columns.FERROMAGNETISM].iloc[-1])
 
     return pd.Series(
         data=(magnetic_susceptibility, offset, saturation, remanence,
               coercivity, ratio_DM_FM),
-        index=Columns.output(), name=get_name(data))
+        index=Columns.output(), name=name)
 
 
 class Columns(_ColumnsBase):

physicslab/experiment/profilometer.py

@@ -22,22 +22,40 @@ def process(data, **kwargs):
     Output `histogram` column (type :class:`~Measurement.Histogram`) stores
     histogram data and fit data.
 
-    :param data: Measured data
+    :param data: Measured data. If None, return units instead
     :type data: pandas.DataFrame
     :param kwargs: All additional keyword arguments are passed to the
         :meth:`Measurement.analyze` call.
-    :return: Derived quantities listed in :meth:`Columns.output`.
+    :return: Derived quantities listed in :meth:`Columns.output` or units
     :rtype: pandas.Series
     """
-    measurement = Measurement(data)
-    # () = [np.nan] * 0
+    if data is None:
+        from physicslab.experiment import UNITS
+        name = UNITS
+        length_unit = 'nm'
+        if 'nanometer' in kwargs and not kwargs['nanometer']:  # Default True.
+            length_unit = 'm'
+        m_m = '({m}, {m})'.format(m=length_unit)
+
+        expected_values = m_m
+        variances = m_m
+        amplitudes = m_m
+        FWHMs = m_m
+        thickness = length_unit
+        histogram = '<class>'
+
+    else:
+        name = get_name(data)
+        measurement = Measurement(data)
+        # () = [np.nan] * 0
+
+        (expected_values, variances, amplitudes, FWHMs, thickness, histogram
+         ) = measurement.analyze(**kwargs)
 
-    (expected_values, variances, amplitudes, FWHMs, thickness, histogram
-     ) = measurement.analyze(**kwargs)
     return pd.Series(
         data=(expected_values, variances, amplitudes, FWHMs, thickness,
               histogram),
-        index=Columns.output(), name=get_name(data))
+        index=Columns.output(), name=name)
 
 
 class Columns(_ColumnsBase):

physicslab/experiment/van_der_pauw.py

@@ -31,29 +31,41 @@ def process(data, thickness=None):
     The optional parameter allows to calculate additional quantities:
     `resistivity` and `conductivity`.
 
-    :param data: Measured data
-    :type data: pandas.DataFrame
+    :param data: Measured data. If None, return units instead
+    :type data: pandas.DataFrame or None
     :param thickness: Sample dimension perpendicular to the plane marked
         by the electrical contacts, defaults to None
     :type thickness: float, optional
-    :return: Derived quantities listed in :meth:`Columns.output`.
+    :return: Derived quantities listed in :meth:`Columns.output` or units
     :rtype: pandas.Series
     """
-    measurement = Measurement(data)
-    (resistivity, conductivity) = [np.nan] * 2
-
-    Rh, Rv = measurement.analyze()
-    sheet_resistance, ratio_resistance = Solve.analyze(Rh, Rv)
-    sheet_conductance = 1 / sheet_resistance
-    if thickness is not None:
-        resistivity = Resistivity.from_sheet_resistance(sheet_resistance,
-                                                        thickness)
-        conductivity = 1 / resistivity
+    if data is None:
+        from physicslab.experiment import UNITS
+        import physicslab.electricity as el
+        name = UNITS
+        sheet_resistance = el.Sheet_Resistance.UNIT
+        ratio_resistance = '1'
+        sheet_conductance = el.Sheet_Conductance.UNIT
+        resistivity = el.Resistivity.UNIT
+        conductivity = el.Conductivity.UNIT
+
+    else:
+        name = get_name(data)
+        measurement = Measurement(data)
+        (resistivity, conductivity) = [np.nan] * 2
+
+        Rh, Rv = measurement.analyze()
+        sheet_resistance, ratio_resistance = Solve.analyze(Rh, Rv)
+        sheet_conductance = 1 / sheet_resistance
+        if thickness is not None:
+            resistivity = Resistivity.from_sheet_resistance(sheet_resistance,
+                                                            thickness)
+            conductivity = 1 / resistivity
 
     return pd.Series(
         data=(sheet_resistance, ratio_resistance, sheet_conductance,
               resistivity, conductivity),
-        index=Columns.output(), name=get_name(data))
+        index=Columns.output(), name=name)
 
 
 class Solve: