Merge branch 'develop' into enh/air-brakes

CHANGELOG.md

@@ -32,7 +32,6 @@ straightforward as possible.
 
 ### Added
 
-- DOC: Added this changelog file [#472](https://github.com/RocketPy-Team/RocketPy/pull/472)
 -
 
 ### Changed
@@ -43,6 +42,29 @@ straightforward as possible.
 
 -
 
+## [v1.1.2] - 2023-11-25
+
+You can install this version by running `pip install rocketpy==1.1.2`
+
+### Fixed
+
+- BUG: Function breaks if a header is present in the csv file [#485](https://github.com/RocketPy-Team/RocketPy/pull/485)
+
+## [v1.1.1] - 2023-11-23
+
+You can install this version by running `pip install rocketpy==1.1.1`
+
+### Added
+
+- DOC: Added this changelog file [#472](https://github.com/RocketPy-Team/RocketPy/pull/472)
+- ENH: Prevent out of bounds Tanks from Instantiation #484 [#484](https://github.com/RocketPy-Team/RocketPy/pull/484)
+
+### Fixed
+
+- HOTFIX: Negative Static Margin [#476](https://github.com/RocketPy-Team/RocketPy/pull/476)
+- HOTFIX: 2D .CSV Function and missing set_get_value_opt call [#478](https://github.com/RocketPy-Team/RocketPy/pull/478)
+- HOTFIX: Tanks Overfill not Being Detected [#479](https://github.com/RocketPy-Team/RocketPy/pull/479)
+
 ## [v1.1.0] - 2023-11-19
 
 You can install this version by running `pip install rocketpy==1.1.0`

docs/conf.py

@@ -24,7 +24,7 @@
 author = "RocketPy Team"
 
 # The full version, including alpha/beta/rc tags
-release = "1.1.0"
+release = "1.1.2"
 
 
 # -- General configuration ---------------------------------------------------

docs/user/installation.rst

@@ -19,7 +19,7 @@ If you want to choose a specific version to guarantee compatibility, you may ins
 
 .. code-block:: shell
 
-    pip install rocketpy==1.1.0
+    pip install rocketpy==1.1.2
 
 
 Optional Installation Method: ``conda``

docs/user/motors/liquidmotor.rst

@@ -40,15 +40,15 @@ Then we must first define the tanks:
   fuel_gas = Fluid(name="ethanol_g", density=1.59)
 
   # Define tanks geometry
-  tanks_shape = CylindricalTank(radius = 0.1, height = 1, spherical_caps = True)
+  tanks_shape = CylindricalTank(radius = 0.1, height = 1.2, spherical_caps = True)
 
   # Define tanks
   oxidizer_tank = MassFlowRateBasedTank(
       name="oxidizer tank",
       geometry=tanks_shape,
       flux_time=5,
       initial_liquid_mass=32,
-      initial_gas_mass=0.1,
+      initial_gas_mass=0.01,
       liquid_mass_flow_rate_in=0,
       liquid_mass_flow_rate_out=lambda t: 32 / 3 * exp(-0.25 * t),
       gas_mass_flow_rate_in=0,

rocketpy/mathutils/function.py

@@ -39,14 +39,26 @@ def __init__(
 
         Parameters
         ----------
-        source : function, scalar, ndarray, string
-            The actual function. If type is function, it will be called for
-            evaluation. If type is int or float, it will be treated as a
-            constant function. If ndarray, its points will be used for
-            interpolation. An ndarray should be as [(x0, y0, z0), (x1, y1, z1),
-            (x2, y2, z2), ...] where x0 and y0 are inputs and z0 is output. If
-            string, imports file named by the string and treats it as csv.
-            The file is converted into ndarray and should not have headers.
+        source : callable, scalar, ndarray, string, or Function
+            The data source to be used for the function:
+
+            - Callable: Called for evaluation with input values. Must have the
+              desired inputs as arguments and return a single output value.
+              Input order is important. Example: Python functions, classes, and
+              methods.
+
+            - int or float: Treated as a constant value function.
+
+            - ndarray: Used for interpolation. Format as [(x0, y0, z0),
+            (x1, y1, z1), ..., (xn, yn, zn)], where 'x' and 'y' are inputs,
+            and 'z' is the output.
+
+            - string: Path to a CSV file. The file is read and converted into an
+            ndarray. The file can optionally contain a single header line.
+
+            - Function: Copies the source of the provided Function object,
+            creating a new Function with adjusted inputs and outputs.
+
         inputs : string, sequence of strings, optional
             The name of the inputs of the function. Will be used for
             representation and graphing (axis names). 'Scalar' is default.
@@ -74,6 +86,13 @@ def __init__(
         Returns
         -------
         None
+
+        Notes
+        -----
+        (I) CSV files can optionally contain a single header line. If present,
+        the header is ignored during processing.
+        (II) Fields in CSV files may be enclosed in double quotes. If fields are
+        not quoted, double quotes should not appear inside them.
         """
         # Set input and output
         if inputs is None:
@@ -133,25 +152,42 @@ def set_outputs(self, outputs):
         return self
 
     def set_source(self, source):
-        """Set the source which defines the output of the function giving a
-        certain input.
+        """Sets the data source for the function, defining how the function
+        produces output from a given input.
 
         Parameters
         ----------
-        source : function, scalar, ndarray, string, Function
-            The actual function. If type is function, it will be called for
-            evaluation. If type is int or float, it will be treated as a
-            constant function. If ndarray, its points will be used for
-            interpolation. An ndarray should be as [(x0, y0, z0), (x1, y1, z1),
-            (x2, y2, z2), ...] where x0 and y0 are inputs and z0 is output. If
-            string, imports file named by the string and treats it as csv.
-            The file is converted into ndarray and should not have headers.
-            If the source is a Function, its source will be copied and another
-            Function will be created following the new inputs and outputs.
+        source : callable, scalar, ndarray, string, or Function
+            The data source to be used for the function:
+
+            - Callable: Called for evaluation with input values. Must have the
+              desired inputs as arguments and return a single output value.
+              Input order is important. Example: Python functions, classes, and
+              methods.
+
+            - int or float: Treated as a constant value function.
+
+            - ndarray: Used for interpolation. Format as [(x0, y0, z0),
+            (x1, y1, z1), ..., (xn, yn, zn)], where 'x' and 'y' are inputs,
+            and 'z' is the output.
+
+            - string: Path to a CSV file. The file is read and converted into an
+            ndarray. The file can optionally contain a single header line.
+
+            - Function: Copies the source of the provided Function object,
+            creating a new Function with adjusted inputs and outputs.
+
+        Notes
+        -----
+        (I) CSV files can optionally contain a single header line. If present,
+        the header is ignored during processing.
+        (II) Fields in CSV files may be enclosed in double quotes. If fields are
+        not quoted, double quotes should not appear inside them.
 
         Returns
         -------
         self : Function
+            Returns the Function instance.
         """
         _ = self._check_user_input(
             source,
@@ -164,21 +200,18 @@ def set_source(self, source):
         if isinstance(source, Function):
             source = source.get_source()
         # Import CSV if source is a string or Path and convert values to ndarray
-        elif isinstance(source, (str, Path)):
-            # Read file and check for headers
-            with open(source, mode="r") as f:
-                first_line = f.readline()
-            # If headers are found...
-            if first_line[0] in ['"', "'"]:
-                # Headers available
-                first_line = first_line.replace('"', " ").replace("'", " ")
-                first_line = first_line.split(" , ")
-                self.set_inputs(first_line[0])
-                self.set_outputs(first_line[1:])
-                source = np.loadtxt(source, delimiter=",", skiprows=1, dtype=float)
-            # if headers are not found
-            else:
-                source = np.loadtxt(source, delimiter=",", dtype=float)
+        if isinstance(source, (str, Path)):
+            with open(source, "r") as file:
+                try:
+                    source = np.loadtxt(file, delimiter=",", dtype=float)
+                except ValueError:
+                    # If an error occurs, headers are present
+                    source = np.loadtxt(source, delimiter=",", dtype=float, skiprows=1)
+                except Exception as e:
+                    raise ValueError(
+                        "The source file is not a valid csv or txt file."
+                    ) from e
+
         # Convert to ndarray if source is a list
         if isinstance(source, (list, tuple)):
             source = np.array(source, dtype=np.float64)
@@ -2715,7 +2748,7 @@ def compose(self, func, extrapolate=False):
         if isinstance(self.source, np.ndarray) and isinstance(func.source, np.ndarray):
             # Perform bounds check for composition
             if not extrapolate:
-                if func.min < self.x_initial and func.max > self.x_final:
+                if func.min < self.x_initial or func.max > self.x_final:
                     raise ValueError(
                         f"Input Function image {func.min, func.max} must be within "
                         f"the domain of the Function {self.x_initial, self.x_final}."
@@ -2785,7 +2818,8 @@ def _check_user_input(
             dimensions of inputs and outputs. If the outputs list has more than
             one element.
         TypeError
-            If the source is not a list, np.ndarray, or Function object.
+            If the source is not a list, np.ndarray, Function object, str or
+            Path.
         Warning
             If inputs or outputs do not match for a Function source, or if
             defaults are used for inputs, interpolation,and extrapolation for a
@@ -2829,11 +2863,20 @@ def _check_user_input(
             # Deal with csv or txt
             if isinstance(source, (str, Path)):
                 # Convert to numpy array
-                source = np.loadtxt(source, delimiter=",", dtype=float)
+                try:
+                    source = np.loadtxt(source, delimiter=",", dtype=float)
+                except ValueError:
+                    # Skip header
+                    source = np.loadtxt(source, delimiter=",", dtype=float, skiprows=1)
+                except Exception as e:
+                    raise ValueError(
+                        "The source file is not a valid csv or txt file."
+                    ) from e
 
-            # this will also trigger an error if the source is not a list of
-            # numbers or if the array is not homogeneous
-            source = np.array(source, dtype=np.float64)
+            else:
+                # this will also trigger an error if the source is not a list of
+                # numbers or if the array is not homogeneous
+                source = np.array(source, dtype=np.float64)
 
             # check dimensions
             source_dim = source.shape[1]